Cot-side electro-encephalography and interstitial glucose monitoring during insulin-induced hypoglycaemia in newborn lambs.

PubMed

Harris, Deborah L; Battin, Malcolm R; Williams, Chris E; Weston, Philip J; Harding, Jane E

2009-01-01

The optimal approach to detection and management of neonatal hypoglycaemia remains unclear. We sought to demonstrate whether electro-encephalography (EEG) changes could be detected on the amplitude-integrated EEG monitor during induced hypoglycaemia in newborn lambs, and also to determine the accuracy of continuously measured interstitial glucose in this situation. Needle electrodes were placed in the P3-P4, O1-O2 montages. The interstitial glucose sensor was placed subcutaneously. After 30 min baseline recordings, hypoglycaemia was induced by insulin infusion and blood glucose levels were monitored every 5 min. The infusion was adjusted to reduce blood glucose levels by 0.5 mmol/l every 15 min and then maintain a blood glucose level <1.0 mmol/l for 4 h. EEG parameters analysed included amplitude, continuity and spectral edge frequency. The interstitial and blood glucose levels were compared. All lambs (n = 15, aged 3-11 days) became hypoglycaemic, with median blood glucose levels falling from 6.5 to 1.0 mmol/l, p < 0.0001. There were no detectable changes in any of the measured EEG parameters related to hypoglycaemia, although seizures occurred in 2 lambs. There was moderate agreement between the intermittent blood glucose and continuous interstitial glucose measurements in the baseline, decline, and hypoglycaemia periods (mean difference -0.7 mmol/l, 95% confidence interval, CI, -2.8 to 1.4 mmol/l). However, agreement was poor during reversal of hypoglycaemia (mean difference 4.5 mmol/l, 95% CI -1.1 to 10.7 mmol/l). The cot-side EEG may not be a useful clinical tool in the detection of neurological changes induced by hypoglycaemia. However, continuous interstitial glucose monitoring may be useful in the management of babies at risk of hypoglycaemia. (c) 2008 S. Karger AG, Basel.

EEG and Coma.

PubMed

Ardeshna, Nikesh I

2016-03-01

Coma is defined as a state of extreme unresponsiveness, in which a person exhibits no voluntary movement or behavior even to painful stimuli. The utilization of EEG for patients in coma has increased dramatically over the last few years. In fact, many institutions have set protocols for continuous EEG (cEEG) monitoring for patients in coma due to potential causes such as subarachnoid hemorrhage or cardiac arrest. Consequently, EEG plays an important role in diagnosis, managenent, and in some cases even prognosis of coma patients.

The probability of seizures during EEG monitoring in critically ill adults.

PubMed

Westover, M Brandon; Shafi, Mouhsin M; Bianchi, Matt T; Moura, Lidia M V R; O'Rourke, Deirdre; Rosenthal, Eric S; Chu, Catherine J; Donovan, Samantha; Hoch, Daniel B; Kilbride, Ronan D; Cole, Andrew J; Cash, Sydney S

2015-03-01

To characterize the risk for seizures over time in relation to EEG findings in hospitalized adults undergoing continuous EEG monitoring (cEEG). Retrospective analysis of cEEG data and medical records from 625 consecutive adult inpatients monitored at a tertiary medical center. Using survival analysis methods, we estimated the time-dependent probability that a seizure will occur within the next 72-h, if no seizure has occurred yet, as a function of EEG abnormalities detected so far. Seizures occurred in 27% (168/625). The first seizure occurred early (<30min of monitoring) in 58% (98/168). In 527 patients without early seizures, 159 (30%) had early epileptiform abnormalities, versus 368 (70%) without. Seizures were eventually detected in 25% of patients with early epileptiform discharges, versus 8% without early discharges. The 72-h risk of seizures declined below 5% if no epileptiform abnormalities were present in the first two hours, whereas 16h of monitoring were required when epileptiform discharges were present. 20% (74/388) of patients without early epileptiform abnormalities later developed them; 23% (17/74) of these ultimately had seizures. Only 4% (12/294) experienced a seizure without preceding epileptiform abnormalities. Seizure risk in acute neurological illness decays rapidly, at a rate dependent on abnormalities detected early during monitoring. This study demonstrates that substantial risk stratification is possible based on early EEG abnormalities. These findings have implications for patient-specific determination of the required duration of cEEG monitoring in hospitalized patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Acute confusional state of unknown cause in the elderly: a study with continuous EEG monitoring.

PubMed

Naeije, Gilles; Gaspard, Nicolas; Depondt, Chantal; Pepersack, Thierry; Legros, Benjamin

2012-03-01

Acute confusional state (ACS) is a frequent cause of emergency consultation in the elderly. Many causes of ACS are also risk factors for seizures. Both non-convulsive seizures and status epilepticus can cause acute confusion. The yield of routine EEG may not be optimal in case of prolonged post-ictal confusion. We thus, sought to evaluate the yield of CEEG in identifying seizures in elderly patients with ACS of unknown origin. We reviewed our CEEG database for patients over 75 years with ACS and collected EEG, CEEG and clinical information. Thirty-one percent (15/48) of the CEEG performed in elderly patients were done for ACS. Routine EEG did not reveal any epileptic anomalies in 7/15 patients. Among those, CEEG identified interictal epileptiform discharges (IED) in 2 and NCSE in 1. In 8/15 patients, routine EEG revealed epileptiform abnormalities: 3 with IED (including 1 with periodic lateralized discharges), 3 with non-convulsive seizures (NCSz) and 2 with non-convulsive status epilepticus (NCSE). Among patients with only IED, CEEG revealed NCSz in 1 and NCSE in 2. This retrospective study suggests that NCSz and NCSE may account for more cases of ACS than what was previously thought. A single negative routine EEG does not exclude this diagnosis. Continuous EEG (CEEG) monitoring is more revealing than routine EEG for the detection of NCSE and NCSz in confused elderly. The presence of IED in the first routine EEG strongly suggests concomitant NCSz or NCSE. Prospective studies are required to further determine the role of CEEG monitoring in the assessment of ACS in the elderly and to establish the incidence of NCSz and NCSE in this setting. Copyright © 2012 Elsevier Inc. All rights reserved.

Mouse EEG spike detection based on the adapted continuous wavelet transform

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.

2016-04-01

Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.

The utility of conductive plastic electrodes in prolonged ICU EEG monitoring.

PubMed

Das, Rohit R; Lucey, Brendan P; Chou, Sherry H-Y; Espinosa, Patricio S; Zamani, Amir A; Dworetzky, Barbara A; Bromfield, Edward B; Lee, Jong Woo

2009-01-01

We investigated the feasibility and utilization of conductive plastic electrodes (CPEs) in patients undergoing continuous video-electroencephalographic (EEG) monitoring in the intensive care unit (ICU), and assessed the quality of brain magnetic resonance imaging (MRI) and computed tomography (CT) images obtained during this period. A total of 54 patients were monitored. Seizures were recorded in 16 patients. Twenty-five patients had neuroimaging performed with electrodes in place; 15 MRI and 23 CT scans were performed. All patients had excellent quality anatomical images without clinically significant artifacts, and without any signs or symptoms that raised safety concerns. Recording quality of the EEG was indistinguishable to that achieved with standard gold electrodes. The use of CPEs allowed for uninterrupted EEG recording of patients who required urgent neuroimaging, and decreased the amount of time spent by the technologists required to remove and reattach leads.

Neurometric assessment of intraoperative anesthetic

DOEpatents

Kangas, Lars J.; Keller, Paul E.

1998-01-01

The present invention is a method and apparatus for collecting EEG data, reducing the EEG data into coefficients, and correlating those coefficients with a depth of unconsciousness or anesthetic depth, and which obtains a bounded first derivative of anesthetic depth to indicate trends. The present invention provides a developed artificial neural network based method capable of continuously analyzing EEG data to discriminate between awake and anesthetized states in an individual and continuously monitoring anesthetic depth trends in real-time. The present invention enables an anesthesiologist to respond immediately to changes in anesthetic depth of the patient during surgery and to administer the correct amount of anesthetic.

Electrographic status epilepticus in children with critical illness: Epidemiology and outcome.

PubMed

Abend, Nicholas S

2015-08-01

Electrographic seizures and electrographic status epilepticus are common in children with critical illness with acute encephalopathy, leading to increasing use of continuous EEG monitoring. Many children with electrographic status epilepticus have no associated clinical signs, so EEG monitoring is required for seizure identification. Further, there is increasing evidence that high seizure burdens, often classified as electrographic status epilepticus, are associated with worse outcomes. This review discusses the incidence of electrographic status epilepticus, risk factors for electrographic status epilepticus, and associations between electrographic status epilepticus and outcomes, and it summarizes recent guidelines and consensus statements addressing EEG monitoring in children with critical illness. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015 Elsevier Inc. All rights reserved.

Postictal apnea as an important mechanism for SUDEP: A near-SUDEP with continuous EEG-ECG-EMG recording.

PubMed

Jin, Lang; Zhang, Ying; Wang, Xiao-Li; Zhang, Wen-Juan; Liu, Yong-Hong; Jiang, Zhao

2017-09-01

Sudden unexpected death in epilepsy (SUDEP) is one of the most frequent causes of death among patients with epilepsy. Most SUDEP or near-SUDEP are unwitnessed and not observed or recorded during video-EEG recording in epilepsy monitoring units. This report describes a young woman with post ictal apnea and generalized EEG suppression (PGES) after a secondary generalized tonic-clonic seizure (sGTCS). This was accompanied by bradycardia and then ventricular tachycardia (VT). But at the end of VT, the patient's breath recovered without any intervention, such as cardio-respiratory resuscitation. This case report with continuous EEG, EKG, EMG during near SUDEP may provide insights into the mechanism of action. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neurometric assessment of intraoperative anesthetic

DOEpatents

Kangas, L.J.; Keller, P.E.

1998-07-07

The present invention is a method and apparatus for collecting EEG data, reducing the EEG data into coefficients, and correlating those coefficients with a depth of unconsciousness or anesthetic depth, and which obtains a bounded first derivative of anesthetic depth to indicate trends. The present invention provides a developed artificial neural network based method capable of continuously analyzing EEG data to discriminate between awake and anesthetized states in an individual and continuously monitoring anesthetic depth trends in real-time. The present invention enables an anesthesiologist to respond immediately to changes in anesthetic depth of the patient during surgery and to administer the correct amount of anesthetic. 7 figs.

Neurometric assessment of intraoperative anesthetic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kangas, L.J.; Keller, P.E.

1998-07-07

The present invention is a method and apparatus for collecting EEG data, reducing the EEG data into coefficients, and correlating those coefficients with a depth of unconsciousness or anesthetic depth, and which obtains a bounded first derivative of anesthetic depth to indicate trends. The present invention provides a developed artificial neural network based method capable of continuously analyzing EEG data to discriminate between awake and anesthetized states in an individual and continuously monitoring anesthetic depth trends in real-time. The present invention enables an anesthesiologist to respond immediately to changes in anesthetic depth of the patient during surgery and to administermore » the correct amount of anesthetic. 7 figs.« less

Early Oxygen-Utilization and Brain Activity in Preterm Infants

PubMed Central

de Vries, Linda S.; Groenendaal, Floris; Toet, Mona C.; Lemmers, Petra M. A.; Vosse van de, Renè E.; van Bel, Frank; Benders, Manon J. N. L.

2015-01-01

The combined monitoring of oxygen supply and delivery using Near-InfraRed spectroscopy (NIRS) and cerebral activity using amplitude-integrated EEG (aEEG) could yield new insights into brain metabolism and detect potentially vulnerable conditions soon after birth. The relationship between NIRS and quantitative aEEG/EEG parameters has not yet been investigated. Our aim was to study the association between oxygen utilization during the first 6 h after birth and simultaneously continuously monitored brain activity measured by aEEG/EEG. Forty-four hemodynamically stable babies with a GA < 28 weeks, with good quality NIRS and aEEG/EEG data available and who did not receive morphine were included in the study. aEEG and NIRS monitoring started at NICU admission. The relation between regional cerebral oxygen saturation (rScO2) and cerebral fractional tissue oxygen extraction (cFTOE), and quantitative measurements of brain activity such as number of spontaneous activity transients (SAT) per minute (SAT rate), the interval in seconds (i.e. time) between SATs (ISI) and the minimum amplitude of the EEG in μV (min aEEG) were evaluated. rScO2 was negatively associated with SAT rate (β=-3.45 [CI=-5.76- -1.15], p=0.004) and positively associated with ISI (β=1.45 [CI=0.44-2.45], p=0.006). cFTOE was positively associated with SAT rate (β=0.034 [CI=0.009-0.059], p=0.008) and negatively associated with ISI (β=-0.015 [CI=-0.026- -0.004], p=0.007). Oxygen delivery and utilization, as indicated by rScO2 and cFTOE, are directly related to functional brain activity, expressed by SAT rate and ISI during the first hours after birth, showing an increase in oxygen extraction in preterm infants with increased early electro-cerebral activity. NIRS monitored oxygenation may be a useful biomarker of brain vulnerability in high-risk infants. PMID:25965343

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms 1D wavelet.

Can arousing feedback rectify lapses in driving? Prediction from EEG power spectra.

PubMed

Lin, Chin-Teng; Huang, Kuan-Chih; Chuang, Chun-Hsiang; Ko, Li-Wei; Jung, Tzyy-Ping

2013-10-01

This study explores the neurophysiological changes, measured using an electroencephalogram (EEG), in response to an arousing warning signal delivered to drowsy drivers, and predicts the efficacy of the feedback based on changes in the EEG. Eleven healthy subjects participated in sustained-attention driving experiments. The driving task required participants to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel, while their EEG and driving performance were continuously monitored. The arousing warning signal was delivered to participants who experienced momentary behavioral lapses, failing to respond rapidly to lane-departure events (specifically the reaction time exceeded three times the alert reaction time). The results of our previous studies revealed that arousing feedback immediately reversed deteriorating driving performance, which was accompanied by concurrent EEG theta- and alpha-power suppression in the bilateral occipital areas. This study further proposes a feedback efficacy assessment system to accurately estimate the efficacy of arousing warning signals delivered to drowsy participants by monitoring the changes in their EEG power spectra immediately thereafter. The classification accuracy was up 77.8% for determining the need for triggering additional warning signals. The findings of this study, in conjunction with previous studies on EEG correlates of behavioral lapses, might lead to a practical closed-loop system to predict, monitor and rectify behavioral lapses of human operators in attention-critical settings.

Subclinical Early Post-Traumatic Seizures Detected by Continuous EEG Monitoring in a Consecutive Pediatric Cohort

PubMed Central

Arndt, Daniel H; Lerner, Jason T; Matsumoto, Joyce H; Madikians, Andranik; Yudovin, Sue; Valino, Heather; McArthur, David L; Wu, Joyce Y; Leung, Michelle; Buxley, Farzad; Szeliga, Conrad; Van Hirtum-Das, Michele; Sankar, Raman; Brooks-Kayal, Amy; Giza, Christopher C

2015-01-01

Summary Purpose Traumatic brain injury (TBI) is an important cause of morbidity and mortality in children and early post-traumatic seizures (EPTS) are a contributing factor to ongoing acute damage. Continuous video EEG monitoring (cEEG) was utilized to assess the burden of clinical and electrographic EPTS. Methods Eighty-seven consecutive, unselected (mild – severe), acute TBI patients requiring pediatric intensive care unit (PICU) admission at 2 academic centers were prospectively monitored with cEEG per established clinical TBI protocols. Clinical and subclinical seizures and status epilepticus (SE, clinical and subclinical) were assessed for their relation to clinical risk factors and short-term outcome measures. Key findings Of all patients, 42.5% (37/87) had seizures. Younger age (p=0.002) and mechanism (abusive head trauma - AHT, p<0.001) were significant risk factors. Subclinical seizures occurred in 16.1% (14/87), 6 of whom had only subclinical seizures. Risk factors for subclinical seizures included: younger age (p<0.001), AHT (p<0.001) and intraaxial bleed (p<0.001). Status Epilepticus (SE) occurred in 18.4% (16/87) with risk factors including: younger age (p<0.001), AHT (p<0.001), and intraaxial bleed (p=0.002). Subclinical SE was detected in 13.8% (12/87) with significant risk factors including: younger age (p<0.001), AHT (p=0.001), and intraaxial bleed (p=0.004). Subclinical seizures were associated with lower discharge KOSCHI score (p=0.002). SE and subclinical SE were associated with increased hospital length of stay (p=0.017 and p=0.041 respectively) and lower hospital discharge KOSCHI (p=0.007 and p=0.040 respectively). Significance cEEG monitoring significantly improves detection of seizures/SE and is the only way to detect subclinical seizures/SE. cEEG may be indicated after pediatric TBI, particularly in younger children, AHT cases, and those with intraaxial blood on CT. PMID:24032982

EEG in connection with coma.

PubMed

Wilson, John A; Nordal, Helge J

2013-01-08

Coma is a dynamic condition that may have various causes. Important changes may take place rapidly, often with consequences for treatment. The purpose of this article is to provide a brief overview of EEG patterns in comas with various causes, and indicate how EEG contributes in an assessment of the prognosis for coma patients. The article is based on many years of clinical and research-based experience of EEG used for patients in coma. A self-built reference database was supplemented by searches for relevant articles in PubMed. EEG reveals immediate changes in coma, and can provide early information on cause and prognosis. It is the only diagnostic tool for detecting a non-convulsive epileptic status. Locked-in- syndrome may be overseen without EEG. Repeated EEG scans increase diagnostic certainty and make it possible to monitor the development of coma. EEG reflects brain function continuously and therefore holds a key place in the assessment and treatment of coma.

Development and Feasibility Testing of a Critical Care EEG Monitoring Database for Standardized Clinical Reporting and Multicenter Collaborative Research.

PubMed

Lee, Jong Woo; LaRoche, Suzette; Choi, Hyunmi; Rodriguez Ruiz, Andres A; Fertig, Evan; Politsky, Jeffrey M; Herman, Susan T; Loddenkemper, Tobias; Sansevere, Arnold J; Korb, Pearce J; Abend, Nicholas S; Goldstein, Joshua L; Sinha, Saurabh R; Dombrowski, Keith E; Ritzl, Eva K; Westover, Michael B; Gavvala, Jay R; Gerard, Elizabeth E; Schmitt, Sarah E; Szaflarski, Jerzy P; Ding, Kan; Haas, Kevin F; Buchsbaum, Richard; Hirsch, Lawrence J; Wusthoff, Courtney J; Hopp, Jennifer L; Hahn, Cecil D

2016-04-01

The rapid expansion of the use of continuous critical care electroencephalogram (cEEG) monitoring and resulting multicenter research studies through the Critical Care EEG Monitoring Research Consortium has created the need for a collaborative data sharing mechanism and repository. The authors describe the development of a research database incorporating the American Clinical Neurophysiology Society standardized terminology for critical care EEG monitoring. The database includes flexible report generation tools that allow for daily clinical use. Key clinical and research variables were incorporated into a Microsoft Access database. To assess its utility for multicenter research data collection, the authors performed a 21-center feasibility study in which each center entered data from 12 consecutive intensive care unit monitoring patients. To assess its utility as a clinical report generating tool, three large volume centers used it to generate daily clinical critical care EEG reports. A total of 280 subjects were enrolled in the multicenter feasibility study. The duration of recording (median, 25.5 hours) varied significantly between the centers. The incidence of seizure (17.6%), periodic/rhythmic discharges (35.7%), and interictal epileptiform discharges (11.8%) was similar to previous studies. The database was used as a clinical reporting tool by 3 centers that entered a total of 3,144 unique patients covering 6,665 recording days. The Critical Care EEG Monitoring Research Consortium database has been successfully developed and implemented with a dual role as a collaborative research platform and a clinical reporting tool. It is now available for public download to be used as a clinical data repository and report generating tool.

Hyperglycemia is associated with simultaneous alterations in electrical brain activity in youths with type 1 diabetes mellitus.

PubMed

Rachmiel, M; Cohen, M; Heymen, E; Lezinger, M; Inbar, D; Gilat, S; Bistritzer, T; Leshem, G; Kan-Dror, E; Lahat, E; Ekstein, D

2016-02-01

To assess the association between hyperglycemia and electrical brain activity in type 1 diabetes mellitus (T1DM). Nine youths with T1DM were monitored simultaneously and continuously by EEG and continuous glucose monitor system, for 40 h. EEG powers of 0.5-80 Hz frequency bands in all the different brain regions were analyzed according to interstitial glucose concentration (IGC) ranges of 4-11 mmol/l, 11-15.5 mmol/l and >15.5 mmol/l. Analysis of variance was used to examine the differences in EEG power of each frequency band between the subgroups of IGC. Analysis was performed separately during wakefulness and sleep, controlling for age, gender and HbA1c. Mean IGC was 11.49 ± 5.26 mmol/l in 1253 combined measurements. IGC>15.5 mmol/l compared to 4-11 mmol/l was associated during wakefulness with increased EEG power of low frequencies and with decreased EEG power of high frequencies. During sleep, it was associated with increased EEG power of low frequencies in all brain areas and of high frequencies in frontal and central areas. Asymptomatic transient hyperglycemia in youth with T1DM is associated with simultaneous alterations in electrical brain activity during wakefulness and sleep. The clinical implications of immediate electrical brain alterations under hyperglycemia need to be studied and may lead to adaptations of management. Copyright © 2015. Published by Elsevier Ireland Ltd.

Functional neurotoxicity evaluation of noribogaine using video-EEG in cynomolgus monkeys.

PubMed

Authier, Simon; Accardi, Michael V; Paquette, Dominique; Pouliot, Mylène; Arezzo, Joseph; Stubbs, R John; Gerson, Ronald J; Friedhoff, Lawrence T; Weis, Holger

2016-01-01

Continuous video-electroencephalographic (EEG) monitoring remains the gold standard for seizure liability assessments in preclinical drug safety assessments. EEG monitored by telemetry was used to assess the behavioral and EEG effects of noribogaine hydrochloride (noribogaine) in cynomolgus monkeys. Noribogaine is an iboga alkaloid being studied for the treatment of opioid dependence. Six cynomolgus monkeys (3 per gender) were instrumented with EEG telemetry transmitters. Noribogaine was administered to each monkey at both doses (i.e., 160 and 320mg/kg, PO) with an interval between dosing of at least 6days, and the resulting behavioral and EEG effects were evaluated. IV pentylenetetrazol (PTZ), served as a positive control for induced seizures. The administration of noribogaine at either of the doses evaluated was not associated with EEG evidence of seizure or with EEG signals known to be premonitory signs of increased seizure risk (e.g., sharp waves, unusual synchrony, shifts to high-frequency patterns). Noribogaine was associated with a mild reduction in activity levels, increased scratching, licking and chewing, and some degree of poor coordination and related clinical signs. A single monkey exhibited brief myoclonic movements that increased in frequency at the high dose, but which did not appear to generalize, cluster or to be linked with EEG abnormalities. Noribogaine was also associated with emesis and partial anorexia. In contrast, PTZ was associated with substantial pre-ictal EEG patterns including large amplitude, repetitive sharp waves leading to generalized seizures and to typical post-ictal EEG frequency attenuation. EEG patterns were within normal limits following administration of noribogaine at doses up to 320mg/kg with concurrent clinical signs that correlated with plasma exposures and resolved by the end of the monitoring period. PTZ was invariably associated with EEG paroxysmal activity leading to ictal EEG. In the current study, a noribogaine dose of 320mg/kg was considered to be the EEG no observed adverse effect level (NOAEL) in conscious freely moving cynomolgus monkeys. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

EEG indices correlate with sustained attention performance in patients affected by diffuse axonal injury.

PubMed

Coelli, Stefania; Barbieri, Riccardo; Reni, Gianluigi; Zucca, Claudio; Bianchi, Anna Maria

2018-06-01

The aim of this study is to assess the ability of EEG-based indices in providing relevant information about cognitive engagement level during the execution of a clinical sustained attention (SA) test in healthy volunteers and DAI (diffused axonal injury)-affected patients. We computed three continuous power-based engagement indices (P β /P α , 1/P α , and P β / (P α + P θ )) from EEG recordings in a control group (n = 7) and seven DAI-affected patients executing a 10-min Conners' "not-X" continuous performance test (CPT). A correlation analysis was performed in order to investigate the existence of relations between the EEG metrics and behavioral parameters in both the populations. P β /P α and 1/P α indices were found to be correlated with reaction times in both groups while P β / (P α + P θ ) and P β /P α also correlated with the errors rate for DAI patients. In line with previous studies, time course fluctuations revealed a first strong decrease of attention after 2 min from the beginning of the test and a final fading at the end. Our results provide evidence that EEG-derived indices extraction and evaluation during SA tasks are helpful in the assessment of attention level in healthy subjects and DAI patients, offering motivations for including EEG monitoring in cognitive rehabilitation practice. Graphical abstract Three EEG-derived indices were computed from four electrodes montages in a population of seven healthy volunteers and a group of seven DAI-affected patients. Results show a significant correlation between the time course of the indices and behavioral parameters, thus demonstrating their usefulness in monitoring mental engagement level during a sustained attention task.

Validation of a Wireless, Self-Application, Ambulatory Electroencephalographic Sleep Monitoring Device in Healthy Volunteers.

PubMed

Finan, Patrick H; Richards, Jessica M; Gamaldo, Charlene E; Han, Dingfen; Leoutsakos, Jeannie Marie; Salas, Rachel; Irwin, Michael R; Smith, Michael T

2016-11-15

To evaluate the validity of an ambulatory electroencephalographic (EEG) monitor for the estimation of sleep continuity and architecture in healthy adults. Healthy, good sleeping participants (n = 14) were fit with both an ambulatory EEG monitor (Sleep Profiler) and a full polysomnography (PSG) montage. EEG recordings were gathered from both devices on the same night, during which sleep was permitted uninterrupted for eight hours. The study was set in an inpatient clinical research suite. PSG and Sleep Profiler records were scored by a neurologist board certified in sleep medicine, blinded to record identification. Agreement between the scored PSG record, the physician-scored Sleep Profiler record, and the Sleep Profiler record scored by an automatic algorithm was evaluated for each sleep stage, with the PSG record serving as the reference. Results indicated strong percent agreement across stages. Kappa was strongest for Stage N3 and REM. Specificity was high for all stages; sensitivity was low for Wake and Stage N1, and high for Stage N2, Stage N3, and REM. Agreement indices improved for the manually scored Sleep Profiler record relative to the autoscore record. Overall, the Sleep Profiler yields an EEG record with comparable sleep architecture estimates to PSG. Future studies should evaluate agreement between devices with a clinical sample that has greater periods of wake in order to better understand utility of this device for estimating sleep continuity indices, such as sleep onset latency and wake after sleep onset. © 2016 American Academy of Sleep Medicine

Stability of Early EEG Background Patterns After Pediatric Cardiac Arrest.

PubMed

Abend, Nicholas S; Xiao, Rui; Kessler, Sudha Kilaru; Topjian, Alexis A

2018-05-01

We aimed to determine whether EEG background characteristics remain stable across discrete time periods during the acute period after resuscitation from pediatric cardiac arrest. Children resuscitated from cardiac arrest underwent continuous conventional EEG monitoring. The EEG was scored in 12-hour epochs for up to 72 hours after return of circulation by an electroencephalographer using a Background Category with 4 levels (normal, slow-disorganized, discontinuous/burst-suppression, or attenuated-featureless) or 2 levels (normal/slow-disorganized or discontinuous/burst-suppression/attenuated-featureless). Survival analyses and mixed-effects ordinal logistic regression models evaluated whether the EEG remained stable across epochs. EEG monitoring was performed in 89 consecutive children. When EEG was assessed as the 4-level Background Category, 30% of subjects changed category over time. Based on initial Background Category, one quarter of the subjects changed EEG category by 24 hours if the initial EEG was attenuated-featureless, by 36 hours if the initial EEG was discontinuous or burst-suppression, by 48 hours if the initial EEG was slow-disorganized, and never if the initial EEG was normal. However, regression modeling for the 4-level Background Category indicated that the EEG did not change over time (odds ratio = 1.06, 95% confidence interval = 0.96-1.17, P = 0.26). Similarly, when EEG was assessed as the 2-level Background Category, 8% of subjects changed EEG category over time. However, regression modeling for the 2-level category indicated that the EEG did not change over time (odds ratio = 1.02, 95% confidence interval = 0.91-1.13, P = 0.75). The EEG Background Category changes over time whether analyzed as 4 levels (30% of subjects) or 2 levels (8% of subjects), although regression analyses indicated that no significant changes occurred over time for the full cohort. These data indicate that the Background Category is often stable during the acute 72 hours after pediatric cardiac arrest and thus may be a useful EEG assessment metric in future studies, but that some subjects do have EEG changes over time and therefore serial EEG assessments may be informative.

Prognostic value of amplitude-integrated electroencephalography in neonates with hypernatremic dehydration.

PubMed

Tekgunduz, Kadir Şerafettin; Caner, Ibrahim; Eras, Zeynep; Taştekin, Ayhan; Tan, Huseyin; Dinlen, Nurdan

2014-05-01

Hypernatremic dehydration in neonates is a condition that develops due to inadequate fluid intake and it may lead to cerebral damage. We aimed to determine whether there was an association between serum sodium levels on admission and aEEG patterns and prognosis, as well as any association between aEEG findings and survival rates and long-term prognosis. The present study included all term infants hospitalized for hypernatremic dehydration in between January 2010 and May 2011. Infants were monitored by aEEG. At 2 years of age, we performed a detailed evaluation to assess the impact of hypernatremic dehydration on the neurodevelopmental outcome. Twenty-one infants were admitted to the neonatal intensive care unit for hypernatremic dehydration. A correlation was found between increased serum sodium levels and aEEG abnormalities. Neurodevelopmental assessment was available for 17 of the 21 infants. The results revealed that hypernatremic dehydration did not adversely affect the long-term outcomes. The follow-up of newborns after discharge is key to determine the risks associated with hypernatremic dehydration. Our results suggest that hypernatremic dehydration had no impact on the long-term outcome. In addition, continuous aEEG monitoring could provide information regarding early prognosis and mortality.

Infraslow status epilepticus: A new form of subclinical status epilepticus recorded in a child with Sturge-Weber syndrome.

PubMed

Bello-Espinosa, Luis E

2015-08-01

Analysis of infraslow EEG activity (ISA) has shown potential in the evaluation of patients with epilepsy and in the differentiation between focal and generalized epilepsies. Infraslow EEG activity analysis may also provide insights into the pathophysiology of refractory clinical and subclinical status epilepticus. The purpose of this report is to describe a girl with Sturge-Weber syndrome (SWS) who presented with a 96-h refractory encephalopathy and nonischemic hemiparesis and who was identified to have infraslow status epilepticus (ISSE), which successfully resolved after midazolam administration. The continuous EEG recording of a 5-year-old girl with known structural epilepsy due to Sturge-Weber syndrome is presented. The patient presented to the ED with acute confusion, eye deviation, and right hemiparesis similar to two previous admissions. Despite administration of lorazepam, fosphenytoin, phenobarbital, and valproic loads, the patient showed no improvement in the clinical condition after 48 h. The continuous video-EEG monitoring (VEM) showed continuous severe diffuse nonrhythmic asymmetric slowing but no apparent ictal activity on continuous conventional EEG recording settings. As brain CT, CTA, CTV, and complete MRI scans including DWI obtained within 72 h of presentation failed to demonstrate any ischemic changes, analysis of the EEG infraslow (ISA) activity was undertaken using LFF: 0.01 Hz and HFF: of 0.1 Hz, respectively. Continuous subclinical unilateral rhythmic ictal ISA was identified. This was only evident on the left hemisphere which correlated with the structural changes due to SWS. A trial of continuous 120 to 240 μg/kg/h of IV midazolam resulted in immediate resolution of the contralateral hemiparesis and encephalopathy. Continuous prolonged rhythmic ictal infraslow activity (ISA) can cause super-refractory subclinical focal status epilepticus. This has not been previously reported, and we propose that this be called infraslow status epilepticus (ISSE). Infraslow EEG activity analysis should be performed in all patients with unexplained subclinical status epilepticus. This article is part of a Special Issue entitled "Status Epilepticus". Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

The changes of cerebral hemodynamics during ketamine induced anesthesia in a rat model.

PubMed

Bae, Jayyoung; Shin, Teo J; Kim, Seonghyun; Choi, Dong-Hyuk; Cho, Dongrae; Ham, Jinsil; Manca, Marco; Jeong, Seongwook; Lee, Boreom; Kim, Jae G

2018-05-25

Current electroencephalogram (EEG) based-consciousness monitoring technique is vulnerable to specific clinical conditions (eg, epilepsy and dementia). However, hemodynamics is the most fundamental and well-preserved parameter to evaluate, even under severe clinical situations. In this study, we applied near-infrared spectroscopy (NIRS) system to monitor hemodynamic change during ketamine-induced anesthesia to find its correlation with the level of consciousness. Oxy-hemoglobin (OHb) and deoxy-hemoglobin concentration levels were continuously acquired throughout the experiment, and the reflectance ratio between 730 and 850 nm was calculated to quantify the hemodynamic changes. The results showed double peaks of OHb concentration change during ketamine anesthesia, which seems to be closely related to the consciousness state of the rat. This finding suggests the possibility of NIRS based-hemodynamic monitoring as a supplementary parameter for consciousness monitoring, compensating drawbacks of EEG signal based monitoring. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Monitoring the Depth of Anesthesia Using a New Adaptive Neurofuzzy System.

PubMed

Shalbaf, Ahmad; Saffar, Mohsen; Sleigh, Jamie W; Shalbaf, Reza

2018-05-01

Accurate and noninvasive monitoring of the depth of anesthesia (DoA) is highly desirable. Since the anesthetic drugs act mainly on the central nervous system, the analysis of brain activity using electroencephalogram (EEG) is very useful. This paper proposes a novel automated method for assessing the DoA using EEG. First, 11 features including spectral, fractal, and entropy are extracted from EEG signal and then, by applying an algorithm according to exhaustive search of all subsets of features, a combination of the best features (Beta-index, sample entropy, shannon permutation entropy, and detrended fluctuation analysis) is selected. Accordingly, we feed these extracted features to a new neurofuzzy classification algorithm, adaptive neurofuzzy inference system with linguistic hedges (ANFIS-LH). This structure can successfully model systems with nonlinear relationships between input and output, and also classify overlapped classes accurately. ANFIS-LH, which is based on modified classical fuzzy rules, reduces the effects of the insignificant features in input space, which causes overlapping and modifies the output layer structure. The presented method classifies EEG data into awake, light, general, and deep states during anesthesia with sevoflurane in 17 patients. Its accuracy is 92% compared to a commercial monitoring system (response entropy index) successfully. Moreover, this method reaches the classification accuracy of 93% to categorize EEG signal to awake and general anesthesia states by another database of propofol and volatile anesthesia in 50 patients. To sum up, this method is potentially applicable to a new real-time monitoring system to help the anesthesiologist with continuous assessment of DoA quickly and accurately.

Pediatric ICU EEG Monitoring: Current Resources and Practice in the United States and Canada

PubMed Central

Sanchez, Sarah M.; Carpenter, Jessica; Chapman, Kevin E.; Dlugos, Dennis J.; Gallentine, William; Giza, Christopher C.; Goldstein, Joshua L.; Hahn, Cecil D.; Kessler, Sudha Kilaru; Loddenkemper, Tobias; Riviello, James J.; Abend, Nicholas S.

2013-01-01

PURPOSE To describe current continuous EEG (cEEG) utilization in critically ill children. METHODS An online survey of pediatric neurologists from 50 United States (U.S.) and 11 Canadian institutions was conducted in August 2011. RESULTS Responses were received from 58 of 61 (95%) surveyed institutions. Common cEEG indications are altered mental status after a seizure or status epilepticus (97%), altered mental status of unknown etiology (88%), or altered mental status with an acute primary neurological condition (88%). The median number of patients undergoing cEEG per month per center increased from August 2010 to August 2011 (6 to 10 per month in U.S., 2 to 3 per month in Canada). Few institutions have clinical pathways addressing cEEG use (31%). Physicians most commonly review cEEG twice per day (37%). There is variability regarding which services can order cEEG, the degree of neurology involvement, technologist availability, and whether technologists perform cEEG screening. CONCLUSIONS Among the surveyed institutions, which included primarily large academic centers, cEEG use in pediatric intensive care units is increasing and is often considered indicated for children with altered mental status at risk for non-convulsive seizures. However, there remains substantial variability in cEEG access and utilization among institutions. PMID:23545766

Integration of EEG lead placement templates into traditional technologist-based staffing models reduces costs in continuous video-EEG monitoring service.

PubMed

Kolls, Brad J; Lai, Amy H; Srinivas, Anang A; Reid, Robert R

2014-06-01

The purpose of this study was to determine the relative cost reductions within different staffing models for continuous video-electroencephalography (cvEEG) service by introducing a template system for 10/20 lead application. We compared six staffing models using decision tree modeling based on historical service line utilization data from the cvEEG service at our center. Templates were integrated into technologist-based service lines in six different ways. The six models studied were templates for all studies, templates for intensive care unit (ICU) studies, templates for on-call studies, templates for studies of ≤ 24-hour duration, technologists for on-call studies, and technologists for all studies. Cost was linearly related to the study volume for all models with the "templates for all" model incurring the lowest cost. The "technologists for all" model carried the greatest cost. Direct cost comparison shows that any introduction of templates results in cost savings, with the templates being used for patients located in the ICU being the second most cost efficient and the most practical of the combined models to implement. Cost difference between the highest and lowest cost models under the base case produced an annual estimated savings of $267,574. Implementation of the ICU template model at our institution under base case conditions would result in a $205,230 savings over our current "technologist for all" model. Any implementation of templates into a technologist-based cvEEG service line results in cost savings, with the most significant annual savings coming from using the templates for all studies, but the most practical implementation approach with the second highest cost reduction being the template used in the ICU. The lowered costs determined in this work suggest that a template-based cvEEG service could be supported at smaller centers with significantly reduced costs and could allow for broader use of cvEEG patient monitoring.

Cot-side electroencephalography monitoring is not clinically useful in the detection of mild neonatal hypoglycemia.

PubMed

Harris, Deborah L; Weston, Philip J; Williams, Christopher E; Pleasants, Anthony B; Battin, Malcolm R; Spooner, Claire G; Harding, Jane E

2011-11-01

To determine whether there is a relationship between electroencephalography patterns and hypoglycemia, by using simultaneous cot-side amplitude integrated electroencephalography (aEEG) and continuous interstitial glucose monitoring, and whether non-glucose cerebral fuels modified these patterns. Eligible babies were ≥ 32 weeks gestation, at risk for hypoglycemia, and admitted to the neonatal intensive care unit. Electrodes were placed in C3-P3, C4-P4 O1-O2 montages. A continuous interstitial glucose sensor was placed subcutaneously, and blood glucose was measured by using the glucose oxidase method. Non-glucose cerebral fuels were measured at study entry, exit, and during recognized hypoglycemia. A total of 101 babies were enrolled, with a median weight of 2179 g and gestation of 35 weeks. Twenty-four of the babies had aEEG recordings, and glucose concentrations were low (< 2.6 mM). There were 103 episodes of low glucose concentrations lasting 5 to 475 minutes, but no observable changes in aEEG variables. Plasma concentrations of lactate, beta-hydroxybutyrate, and glycerol were low and did not alter during hypoglycemia. Cot-side aEEG was not useful for the detection of neurological changes during mild hypoglycemia. Plasma concentrations of non-glucose cerebral fuels were low and unlikely to provide substantial neuroprotection. Copyright © 2011 Mosby, Inc. All rights reserved.

Long-term Continuous EEG Monitoring in Small Rodent Models of Human Disease Using the Epoch Wireless Transmitter System

PubMed Central

Zayachkivsky, Andrew; Lehmkuhle, Mark J.; Dudek, F. Edward

2015-01-01

Many progressive neurologic diseases in humans, such as epilepsy, require pre-clinical animal models that slowly develop the disease in order to test interventions at various stages of the disease process. These animal models are particularly difficult to implement in immature rodents, a classic model organism for laboratory study of these disorders. Recording continuous EEG in young animal models of seizures and other neurological disorders presents a technical challenge due to the small physical size of young rodents and their dependence on the dam prior to weaning. Therefore, there is not only a clear need for improving pre-clinical research that will better identify those therapies suitable for translation to the clinic but also a need for new devices capable of recording continuous EEG in immature rodents. Here, we describe the technology behind and demonstrate the use of a novel miniature telemetry system, specifically engineered for use in immature rats or mice, which is also effective for use in adult animals. PMID:26274779

High density scalp EEG in frontal lobe epilepsy.

PubMed

Feyissa, Anteneh M; Britton, Jeffrey W; Van Gompel, Jamie; Lagerlund, Terrance L; So, Elson; Wong-Kisiel, Lilly C; Cascino, Gregory C; Brinkman, Benjamin H; Nelson, Cindy L; Watson, Robert; Worrell, Gregory A

2017-01-01

Localization of seizures in frontal lobe epilepsy using the 10-20 system scalp EEG is often challenging because neocortical seizure can spread rapidly, significant muscle artifact, and the suboptimal spatial resolution for seizure generators involving mesial frontal lobe cortex. Our aim in this study was to determine the value of visual interpretation of 76 channel high density EEG (hdEEG) monitoring (10-10 system) in patients with suspected frontal lobe epilepsy, and to evaluate concordance with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional EEG, and intracranial EEG (iEEG). We performed a retrospective cohort study of 14 consecutive patients who underwent hdEEG monitoring for suspected frontal lobe seizures. The gold standard for localization was considered to be iEEG. Concordance of hdEEG findings with MRI, subtraction ictal SPECT co-registered to MRI (SISCOM), conventional 10-20 EEG, and iEEG as well as correlation of hdEEG localization with surgical outcome were examined. hdEEG localization was concordant with iEEG in 12/14 and was superior to conventional EEG 3/14 (p<0.01) and SISCOM 3/12 (p<0.01). hdEEG correctly lateralized seizure onset in 14/14 cases, compared to 9/14 (p=0.04) cases with conventional EEG. Seven patients underwent surgical resection, of whom five were seizure free. hdEEG monitoring should be considered in patients with suspected frontal epilepsy requiring localization of epileptogenic brain. hdEEG may assist in developing a hypothesis for iEEG monitoring and could potentially augment EEG source localization. Published by Elsevier B.V.

Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy.

PubMed

Rosenthal, Eric S; Biswal, Siddharth; Zafar, Sahar F; O'Connor, Kathryn L; Bechek, Sophia; Shenoy, Apeksha V; Boyle, Emily J; Shafi, Mouhsin M; Gilmore, Emily J; Foreman, Brandon P; Gaspard, Nicolas; Leslie-Mazwi, Thabele M; Rosand, Jonathan; Hoch, Daniel B; Ayata, Cenk; Cash, Sydney S; Cole, Andrew J; Patel, Aman B; Westover, M Brandon

2018-04-16

Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018. © 2018 American Neurological Association.

A capacitive, biocompatible and adhesive electrode for long-term and cap-free monitoring of EEG signals.

PubMed

Lee, Seung Min; Kim, Jeong Hun; Byeon, Hang Jin; Choi, Yoon Young; Park, Kwang Suk; Lee, Sang-Hoon

2013-06-01

Long-term electroencephalogram (EEG) monitoring broadens EEG applications to various areas, but it requires cap-free recording of EEG signals. Our objective here is to develop a capacitive, small-sized, adhesive and biocompatible electrode for the cap-free and long-term EEG monitoring. We have developed an electrode made of polydimethylsiloxane (PDMS) and adhesive PDMS for EEG monitoring. This electrode can be attached to a hairy scalp and be completely hidden by the hair. We tested its electrical and mechanical (adhesive) properties by measuring voltage gain to frequency and adhesive force using 30 repeat cycles of the attachment and detachment test. Electrode performance on EEG was evaluated by alpha rhythm detection and measuring steady state visually evoked potential and N100 auditory evoked potential. We observed the successful recording of alpha rhythm and evoked signals to diverse stimuli with high signal quality. The biocompatibility of the electrode was verified and a survey found that the electrode was comfortable and convenient to wear. These results indicate that the proposed EEG electrode is suitable and convenient for long term EEG monitoring.

Real-time segmentation of burst suppression patterns in critical care EEG monitoring

PubMed Central

Westover, M. Brandon; Shafi, Mouhsin M.; Ching, ShiNung; Chemali, Jessica J.; Purdon, Patrick L.; Cash, Sydney S.; Brown, Emery N.

2014-01-01

Objective Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. Methods A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced human electroencephalographers. We compare inter-rater agreement between manual EEG segmentations by experts with inter-rater agreement between human vs automatic segmentations, and investigate the robustness of segmentation quality to variations in algorithm parameter settings. We further compare the results of using these segmentations as input for calculating the burst suppression probability (BSP), a continuous measure of depth-of-suppression. Results Automated segmentation was comparable to manual segmentation, i.e. algorithm-vs-human agreement was comparable to human-vs-human agreement, as judged by comparing raw EEG segmentations or the derived BSP signals. Results were robust to modest variations in algorithm parameter settings. Conclusions Our automated method satisfactorily segments burst suppression data across a wide range adult ICU EEG patterns. Performance is comparable to or exceeds that of manual segmentation by human electroencephalographers. Significance Automated segmentation of burst suppression EEG patterns is an essential component of quantitative brain activity monitoring in critically ill and anesthetized adults. The segmentations produced by our algorithm provide a basis for accurate tracking of suppression depth. PMID:23891828

Real-time segmentation of burst suppression patterns in critical care EEG monitoring.

PubMed

Brandon Westover, M; Shafi, Mouhsin M; Ching, Shinung; Chemali, Jessica J; Purdon, Patrick L; Cash, Sydney S; Brown, Emery N

2013-09-30

Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced human electroencephalographers. We compare inter-rater agreement between manual EEG segmentations by experts with inter-rater agreement between human vs automatic segmentations, and investigate the robustness of segmentation quality to variations in algorithm parameter settings. We further compare the results of using these segmentations as input for calculating the burst suppression probability (BSP), a continuous measure of depth-of-suppression. Automated segmentation was comparable to manual segmentation, i.e. algorithm-vs-human agreement was comparable to human-vs-human agreement, as judged by comparing raw EEG segmentations or the derived BSP signals. Results were robust to modest variations in algorithm parameter settings. Our automated method satisfactorily segments burst suppression data across a wide range adult ICU EEG patterns. Performance is comparable to or exceeds that of manual segmentation by human electroencephalographers. Automated segmentation of burst suppression EEG patterns is an essential component of quantitative brain activity monitoring in critically ill and anesthetized adults. The segmentations produced by our algorithm provide a basis for accurate tracking of suppression depth. Copyright © 2013 Elsevier B.V. All rights reserved.

Time course of EEG background activity level before spontaneous awakening in infants.

PubMed

Zampi, Chiara; Fagioli, Igino; Salzarulo, Piero

2002-12-01

This research aimed to investigate the time course of the cortical activity level preceding spontaneous awakening as a function of age and state. Two groups of infants (1-4 and 9-14 weeks of age) were continuously monitored by polygraphic recording and behavioural observation during the night. The electroencephalographic (EEG) activity recorded by the C3-O1 lead was analysed through an automatic analysis method which provides, for each 30-s epoch, a single measure, time domain based, of the EEG synchronization. The EEG parameter values were computed in the 6 min preceding each awakening out of non-rapid eye movement (NREM) sleep and out of rapid eye movement (REM) sleep. The EEG background activity level did not change in the minutes preceding awakening out of REM sleep. Awakening out of NREM sleep was preceded by a change of EEG activity level in the direction of higher activation with different time course according to the age. Both REM and NREM sleep results suggest that a high level of EEG activity is a prerequisite for the occurrence of a spontaneous awakening.

EEG Monitoring and Antiepileptic Drugs in Children with Severe TBI.

PubMed

Ruzas, Christopher M; DeWitt, Peter E; Bennett, Kimberly S; Chapman, Kevin E; Harlaar, Nicole; Bennett, Tellen D

2017-04-01

Traumatic brain injury (TBI) causes substantial morbidity and mortality in US children. Post-traumatic seizures (PTS) occur in 11-42% of children with severe TBI and are associated with unfavorable outcome. Electroencephalographic (EEG) monitoring may be used to detect PTS and antiepileptic drugs (AEDs) may be used to treat PTS, but national rates of EEG and AED use are not known. The purpose of this study was to describe the frequency and timing of EEG and AED use in children hospitalized after severe TBI. Retrospective cohort study of 2165 children at 30 hospitals in a probabilistically linked dataset from the National Trauma Data Bank (NTDB) and the Pediatric Health Information Systems (PHIS) database, 2007-2010. We included children (age <18 years old at admission) with linked NTDB and PHIS records, severe (Emergency Department [ED] Glasgow Coma Scale [GCS] <8) TBI, hospital length of stay >24 h, and non-missing disposition. The primary outcomes were EEG and AED use. Overall, 31.8% of the cohort had EEG monitoring. Of those, 21.8% were monitored on the first hospital day. The median duration of EEG monitoring was 2.0 (IQR 1.0, 4.0) days. AEDs were prescribed to 52.0% of the cohort, of whom 61.8% received an AED on the first hospital day. The median duration of AED use was 8.0 (IQR 4.0, 17.0) days. EEG monitoring and AED use were more frequent in children with known risk factors for PTS. EEG monitoring and AED use were not related to hospital TBI volume. EEG use is relatively uncommon in children with severe TBI, but AEDs are frequently prescribed. EEG monitoring and AED use are more common in children with known risk factors for PTS.

Holistic approach for automated background EEG assessment in asphyxiated full-term infants

NASA Astrophysics Data System (ADS)

Matic, Vladimir; Cherian, Perumpillichira J.; Koolen, Ninah; Naulaers, Gunnar; Swarte, Renate M.; Govaert, Paul; Van Huffel, Sabine; De Vos, Maarten

2014-12-01

Objective. To develop an automated algorithm to quantify background EEG abnormalities in full-term neonates with hypoxic ischemic encephalopathy. Approach. The algorithm classifies 1 h of continuous neonatal EEG (cEEG) into a mild, moderate or severe background abnormality grade. These classes are well established in the literature and a clinical neurophysiologist labeled 272 1 h cEEG epochs selected from 34 neonates. The algorithm is based on adaptive EEG segmentation and mapping of the segments into the so-called segments’ feature space. Three features are suggested and further processing is obtained using a discretized three-dimensional distribution of the segments’ features represented as a 3-way data tensor. Further classification has been achieved using recently developed tensor decomposition/classification methods that reduce the size of the model and extract a significant and discriminative set of features. Main results. Effective parameterization of cEEG data has been achieved resulting in high classification accuracy (89%) to grade background EEG abnormalities. Significance. For the first time, the algorithm for the background EEG assessment has been validated on an extensive dataset which contained major artifacts and epileptic seizures. The demonstrated high robustness, while processing real-case EEGs, suggests that the algorithm can be used as an assistive tool to monitor the severity of hypoxic insults in newborns.

Permanency analysis on human electroencephalogram signals for pervasive Brain-Computer Interface systems.

PubMed

Sadeghi, Koosha; Junghyo Lee; Banerjee, Ayan; Sohankar, Javad; Gupta, Sandeep K S

2017-07-01

Brain-Computer Interface (BCI) systems use some permanent features of brain signals to recognize their corresponding cognitive states with high accuracy. However, these features are not perfectly permanent, and BCI system should be continuously trained over time, which is tedious and time consuming. Thus, analyzing the permanency of signal features is essential in determining how often to repeat training. In this paper, we monitor electroencephalogram (EEG) signals, and analyze their behavior through continuous and relatively long period of time. In our experiment, we record EEG signals corresponding to rest state (eyes open and closed) from one subject everyday, for three and a half months. The results show that signal features such as auto-regression coefficients remain permanent through time, while others such as power spectral density specifically in 5-7 Hz frequency band are not permanent. In addition, eyes open EEG data shows more permanency than eyes closed data.

Non-invasive monitoring of spreading depression.

PubMed

Bastany, Zoya J R; Askari, Shahbaz; Dumont, Guy A; Speckmann, Erwin-Josef; Gorji, Ali

2016-10-01

Spreading depression (SD), a slow propagating depolarization wave, plays an important role in pathophysiology of different neurological disorders. Yet, research into SD-related disorders has been hampered by the lack of non-invasive recording techniques of SD. Here we compared the manifestations of SD in continuous non-invasive electroencephalogram (EEG) recordings to invasive electrocorticographic (ECoG) recordings in order to obtain further insights into generator structures and electrogenic mechanisms of surface recording of SD. SD was induced by KCl application and simultaneous SD recordings were performed by scalp EEG as well as ECoG electrodes of somatosensory neocortex of rats using a novel homemade EEG amplifier, AgCl recording electrodes, and high chloride conductive gel. Different methods were used to analyze the data; including the spectrogram, bi-spectrogram, pattern distribution, relative spectrum power, and multivariable Gaussian fit analysis. The negative direct current (DC) shifts recorded by scalp electrodes exhibited a high homogeneity to those recorded by ECoG electrodes. Furthermore, this novel method of recording and analysis was able to separate SD recorded by scalp electrodes from non-neuronal DC shifts induced by other potential generators, such as the skin, muscles, arteries, dura, etc. These data suggest a novel application for continuous non-invasive monitoring of DC potential changes, such as SD. Non-invasive monitoring of SD would allow early intervention and improve outcome in SD-related neurological disorders. Copyright © 2016 IBRO. All rights reserved.

Xenon depresses aEEG background voltage activity whilst maintaining cardiovascular stability in sedated healthy newborn pigs.

PubMed

Sabir, Hemmen; Wood, Thomas; Gill, Hannah; Liu, Xun; Dingley, John; Thoresen, Marianne

2016-04-15

Changes in electroencephalography (EEG) voltage range are used to monitor the depth of anaesthesia, as well as predict outcome after hypoxia-ischaemia in neonates. Xenon is being investigated as a potential neuroprotectant after hypoxic-ischaemic brain injury, but the effect of Xenon on EEG parameters in children or neonates is not known. This study aimed to examine the effect of 50% inhaled Xenon on background amplitude-integrated EEG (aEEG) activity in sedated healthy newborn pigs. Five healthy newborn pigs, receiving intravenous fentanyl sedation, were ventilated for 24 h with 50%Xenon, 30%O2 and 20%N2 at normothermia. The upper and lower voltage-range of the aEEG was continuously monitored together with cardiovascular parameters throughout a 1 h baseline period with fentanyl sedation only, followed by 24 h of Xenon administration. The median (IQR) upper and lower aEEG voltage during 1 h baseline was 48.0 μV (46.0-50.0) and 25.0 μV (23.0-26.0), respectively. The median (IQR) aEEG upper and lower voltage ranges were significantly depressed to 21.5 μV (20.0-26.5) and 12.0 μV (12.0-16.5) from 10 min after the onset of 50% Xenon administration (p=0.002). After the initial Xenon induced depression in background aEEG voltage, no further aEEG changes were seen over the following 24h of ventilation with 50% xenon under fentanyl sedation. Mean arterial blood pressure and heart rate remained stable. Mean arterial blood pressure and heart rate were not significantly influenced by 24h Xenon ventilation. 50% Xenon rapidly depresses background aEEG voltage to a steady ~50% lower level in sedated healthy newborn pigs. Therefore, care must be taken when interpreting the background voltage in neonates also receiving Xenon. Copyright © 2016 Elsevier B.V. All rights reserved.

Wearable electroencephalography. What is it, why is it needed, and what does it entail?

PubMed

Casson, Alexander; Yates, David; Smith, Shelagh; Duncan, John; Rodriguez-Villegas, Esther

2010-01-01

The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brain waves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsy and the medical applications of wearable EEG, as this is the historical background of the EEG, our area of expertise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.

Nonconvulsive status epilepticus: the encephalopathic pediatric patient.

PubMed

Greiner, Hansel M; Holland, Katherine; Leach, James L; Horn, Paul S; Hershey, Andrew D; Rose, Douglas F

2012-03-01

A high prevalence of nonconvulsive status epilepticus (NCSE) has been reported in critically ill adults and neonates. Recent prospective pediatric studies focus on critically ill children and show wide variability in the frequency of NCSE. This study examines prevalence of pediatric NCSE regardless of inpatient setting and retrospectively identifies risk factors indicating a need for urgent continuous EEG. Medical records from patients aged 3 months to 21 years were identified either by (1) searching a clinical EEG database (n = 18) or (2) consecutive inpatient EEG referrals for NCSE over an 8-month period (n = 57). Seventy-five children, mean age of 7.8 years, were studied. NCSE was identified in 26 patients (35%) and in 8 of 57 (14%) patients referred for possible NCSE. More than half of the patients referred were outside of the ICU. A witnessed clinical seizure was observed in 24 of 26 (92%) patients with NCSE. Acute cortical neuroimaging abnormalities were significantly more frequent in patients with NCSE. The presence of clinical seizures and acute neuroimaging abnormality was associated with an 82% probability of NCSE. All but 1 patient with NCSE had electrographic or electroclinical seizures within the first hour of monitoring. A high prevalence of NCSE was observed, comparable to adult studies, but within a wider range of inpatient settings. Children with acute encephalopathy should undergo continuous EEG. This evaluation is more urgent if certain clinical risk factors are present. Optimal duration of monitoring and the effect of NCSE on prognosis should be studied.

Intracranial EEG fluctuates over months after implanting electrodes in human brain

NASA Astrophysics Data System (ADS)

Ung, Hoameng; Baldassano, Steven N.; Bink, Hank; Krieger, Abba M.; Williams, Shawniqua; Vitale, Flavia; Wu, Chengyuan; Freestone, Dean; Nurse, Ewan; Leyde, Kent; Davis, Kathryn A.; Cook, Mark; Litt, Brian

2017-10-01

Objective. Implanting subdural and penetrating electrodes in the brain causes acute trauma and inflammation that affect intracranial electroencephalographic (iEEG) recordings. This behavior and its potential impact on clinical decision-making and algorithms for implanted devices have not been assessed in detail. In this study we aim to characterize the temporal and spatial variability of continuous, prolonged human iEEG recordings. Approach. Intracranial electroencephalography from 15 patients with drug-refractory epilepsy, each implanted with 16 subdural electrodes and continuously monitored for an average of 18 months, was included in this study. Time and spectral domain features were computed each day for each channel for the duration of each patient’s recording. Metrics to capture post-implantation feature changes and inflexion points were computed on group and individual levels. A linear mixed model was used to characterize transient group-level changes in feature values post-implantation and independent linear models were used to describe individual variability. Main results. A significant decline in features important to seizure detection and prediction algorithms (mean line length, energy, and half-wave), as well as mean power in the Berger and high gamma bands, was observed in many patients over 100 d following implantation. In addition, spatial variability across electrodes declines post-implantation following a similar timeframe. All selected features decreased by 14-50% in the initial 75 d of recording on the group level, and at least one feature demonstrated this pattern in 13 of the 15 patients. Our findings indicate that iEEG signal features demonstrate increased variability following implantation, most notably in the weeks immediately post-implant. Significance. These findings suggest that conclusions drawn from iEEG, both clinically and for research, should account for spatiotemporal signal variability and that properly assessing the iEEG in patients, depending upon the application, may require extended monitoring.

Wireless multichannel electroencephalography in the newborn.

PubMed

Ibrahim, Z H; Chari, G; Abdel Baki, S; Bronshtein, V; Kim, M R; Weedon, J; Cracco, J; Aranda, J V

2016-01-01

First, to determine the feasibility of an ultra-compact wireless device (microEEG) to obtain multichannel electroencephalographic (EEG) recording in the Neonatal Intensive Care Unit (NICU). Second, to identify problem areas in order to improve wireless EEG performance. 28 subjects (gestational age 24-30 weeks, postnatal age <30 days) were recruited at 2 sites as part of an ongoing study of neonatal apnea and wireless EEG. Infants underwent 8-9 hour EEG recordings every 2-4 weeks using an electrode cap (ANT-Neuro) connected to the wireless EEG device (Bio-Signal Group). A 23 electrode configuration was used incorporating the International 10-20 System. The device transmitted recordings wirelessly to a laptop computer for bedside assessment. The recordings were assessed by a pediatric neurophysiologist for interpretability. A total of 84 EEGs were recorded from 28 neonates. 61 EEG studies were obtained in infants prior to 35 weeks corrected gestational age (CGA). NICU staff placed all electrode caps and initiated all recordings. Of these recordings 6 (10%) were uninterpretable due to artifacts and one study could not be accessed. The remaining 54 (89%) EEG recordings were acceptable for clinical review and interpretation by a pediatric neurophysiologist. Of the recordings obtained at 35 weeks corrected gestational age or later only 11 out of 23 (48%) were interpretable. Wireless EEG devices can provide practical, continuous, multichannel EEG monitoring in preterm neonates. Their small size and ease of use could overcome obstacles associated with EEG recording and interpretation in the NICU.

Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy

PubMed Central

Gu, Ying; Cleeren, Evy; Dan, Jonathan; Claes, Kasper; Hunyadi, Borbála

2017-01-01

A wearable electroencephalogram (EEG) device for continuous monitoring of patients suffering from epilepsy would provide valuable information for the management of the disease. Currently no EEG setup is small and unobtrusive enough to be used in daily life. Recording behind the ear could prove to be a solution to a wearable EEG setup. This article examines the feasibility of recording epileptic EEG from behind the ear. It is achieved by comparison with scalp EEG recordings. Traditional scalp EEG and behind-the-ear EEG were simultaneously acquired from 12 patients with temporal, parietal, or occipital lobe epilepsy. Behind-the-ear EEG consisted of cross-head channels and unilateral channels. The analysis on Electrooculography (EOG) artifacts resulting from eye blinking showed that EOG artifacts were absent on cross-head channels and had significantly small amplitudes on unilateral channels. Temporal waveform and frequency content during seizures from behind-the-ear EEG visually resembled that from scalp EEG. Further, coherence analysis confirmed that behind-the-ear EEG acquired meaningful epileptic discharges similarly to scalp EEG. Moreover, automatic seizure detection based on support vector machine (SVM) showed that comparable seizure detection performance can be achieved using these two recordings. With scalp EEG, detection had a median sensitivity of 100% and a false detection rate of 1.14 per hour, while, with behind-the-ear EEG, it had a median sensitivity of 94.5% and a false detection rate of 0.52 per hour. These findings demonstrate the feasibility of detecting seizures from EEG recordings behind the ear for patients with focal epilepsy. PMID:29295522

EEG-based "serious" games and monitoring tools for pain management.

PubMed

Sourina, Olga; Wang, Qiang; Nguyen, Minh Khoa

2011-01-01

EEG-based "serious games" for medical applications attracted recently more attention from the research community and industry as wireless EEG reading devices became easily available on the market. EEG-based technology has been applied in anesthesiology, psychology, etc. In this paper, we proposed and developed EEG-based "serious" games and doctor's monitoring tools that could be used for pain management. As EEG signal is considered to have a fractal nature, we proposed and develop a novel spatio-temporal fractal based algorithm for brain state quantification. The algorithm is implemented with blobby visualization tools for patient monitoring and in EEG-based "serious" games. Such games could be used by patient even at home convenience for pain management as an alternative to traditional drug treatment.

Simultaneous recording of EEG and electromyographic polygraphy increases the diagnostic yield of video-EEG monitoring.

PubMed

Hill, Aron T; Briggs, Belinda A; Seneviratne, Udaya

2014-06-01

To investigate the usefulness of adjunctive electromyographic (EMG) polygraphy in the diagnosis of clinical events captured during long-term video-EEG monitoring. A total of 40 patients (21 women, 19 men) aged between 19 and 72 years (mean 43) investigated using video-EEG monitoring were studied. Electromyographic activity was simultaneously recorded with EEG in four patients selected on clinical grounds. In these patients, surface EMG electrodes were placed over muscles suspected to be activated during a typical clinical event. Of the 40 patients investigated, 24 (60%) were given a diagnosis, whereas 16 (40%) remained undiagnosed. All four patients receiving adjunctive EMG polygraphy obtained a diagnosis, with three of these diagnoses being exclusively reliant on the EMG recordings. Specifically, one patient was diagnosed with propriospinal myoclonus, another patient was diagnosed with facio-mandibular myoclonus, and a third patient was found to have bruxism and periodic leg movements of sleep. The information obtained from surface EMG recordings aided the diagnosis of clinical events captured during video-EEG monitoring in 7.5% of the total cohort. This study suggests that EEG-EMG polygraphy may be used as a technique of improving the diagnostic yield of video-EEG monitoring in selected cases.

Video electroencephalogram telemetry in temporal lobe epilepsy

PubMed Central

Mani, Jayanti

2014-01-01

Temporal lobe epilepsy (TLE) is the most commonly encountered medically refractory epilepsy. It is also the substrate of refractory epilepsy that gives the most gratifying results in any epilepsy surgery program, with a minimum use of resources. Correlation of clinical behavior and the ictal patterns during ictal behavior is mandatory for success at epilepsy surgery. Video electroencephalogram (EEG) telemetry achieves this goal and hence plays a pivotal role in pre-surgical assessment. The role of telemetry is continuously evolving with the advent of digital EEG technology, of high-resolution volumetric magnetic resonance imaging and other functional imaging techniques. Most of surgical selection in patients with TLE can be done with a scalp video EEG monitoring. However, the limitations of the scalp EEG technique demand invasive recordings in a selected group of TLE patients. This subset of the patients can be a challenge to the epileptologist. PMID:24791089

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

PubMed

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks.

PubMed

Berka, Chris; Levendowski, Daniel J; Lumicao, Michelle N; Yau, Alan; Davis, Gene; Zivkovic, Vladimir T; Olmstead, Richard E; Tremoulet, Patrice D; Craven, Patrick L

2007-05-01

The ability to continuously and unobtrusively monitor levels of task engagement and mental workload in an operational environment could be useful in identifying more accurate and efficient methods for humans to interact with technology. This information could also be used to optimize the design of safer, more efficient work environments that increase motivation and productivity. The present study explored the feasibility of monitoring electroencephalo-graphic (EEG) indices of engagement and workload acquired unobtrusively and quantified during performance of cognitive tests. EEG was acquired from 80 healthy participants with a wireless sensor headset (F3-F4,C3-C4,Cz-POz,F3-Cz,Fz-C3,Fz-POz) during tasks including: multi-level forward/backward-digit-span, grid-recall, trails, mental-addition, 20-min 3-Choice Vigilance, and image-learning and memory tests. EEG metrics for engagement and workload were calculated for each 1 -s of EEG. Across participants, engagement but not workload decreased over the 20-min vigilance test. Engagement and workload were significantly increased during the encoding period of verbal and image-learning and memory tests when compared with the recognition/ recall period. Workload but not engagement increased linearly as level of difficulty increased in forward and backward-digit-span, grid-recall, and mental-addition tests. EEG measures correlated with both subjective and objective performance metrics. These data in combination with previous studies suggest that EEG engagement reflects information-gathering, visual processing, and allocation of attention. EEG workload increases with increasing working memory load and during problem solving, integration of information, analytical reasoning, and may be more reflective of executive functions. Inspection of EEG on a second-by-second timescale revealed associations between workload and engagement levels when aligned with specific task events providing preliminary evidence that second-by-second classifications reflect parameters of task performance.

A random forest model based classification scheme for neonatal amplitude-integrated EEG.

PubMed

Chen, Weiting; Wang, Yu; Cao, Guitao; Chen, Guoqiang; Gu, Qiufang

2014-01-01

Modern medical advances have greatly increased the survival rate of infants, while they remain in the higher risk group for neurological problems later in life. For the infants with encephalopathy or seizures, identification of the extent of brain injury is clinically challenging. Continuous amplitude-integrated electroencephalography (aEEG) monitoring offers a possibility to directly monitor the brain functional state of the newborns over hours, and has seen an increasing application in neonatal intensive care units (NICUs). This paper presents a novel combined feature set of aEEG and applies random forest (RF) method to classify aEEG tracings. To that end, a series of experiments were conducted on 282 aEEG tracing cases (209 normal and 73 abnormal ones). Basic features, statistic features and segmentation features were extracted from both the tracing as a whole and the segmented recordings, and then form a combined feature set. All the features were sent to a classifier afterwards. The significance of feature, the data segmentation, the optimization of RF parameters, and the problem of imbalanced datasets were examined through experiments. Experiments were also done to evaluate the performance of RF on aEEG signal classifying, compared with several other widely used classifiers including SVM-Linear, SVM-RBF, ANN, Decision Tree (DT), Logistic Regression(LR), ML, and LDA. The combined feature set can better characterize aEEG signals, compared with basic features, statistic features and segmentation features respectively. With the combined feature set, the proposed RF-based aEEG classification system achieved a correct rate of 92.52% and a high F1-score of 95.26%. Among all of the seven classifiers examined in our work, the RF method got the highest correct rate, sensitivity, specificity, and F1-score, which means that RF outperforms all of the other classifiers considered here. The results show that the proposed RF-based aEEG classification system with the combined feature set is efficient and helpful to better detect the brain disorders in newborns.

Real-time monitoring of human blood-brain barrier disruption

PubMed Central

Kiviniemi, Vesa; Korhonen, Vesa; Kortelainen, Jukka; Rytky, Seppo; Keinänen, Tuija; Tuovinen, Timo; Isokangas, Matti; Sonkajärvi, Eila; Siniluoto, Topi; Nikkinen, Juha; Alahuhta, Seppo; Tervonen, Osmo; Turpeenniemi-Hujanen, Taina; Myllylä, Teemu; Kuittinen, Outi; Voipio, Juha

2017-01-01

Chemotherapy aided by opening of the blood-brain barrier with intra-arterial infusion of hyperosmolar mannitol improves the outcome in primary central nervous system lymphoma. Proper opening of the blood-brain barrier is crucial for the treatment, yet there are no means available for its real-time monitoring. The intact blood-brain barrier maintains a mV-level electrical potential difference between blood and brain tissue, giving rise to a measurable electrical signal at the scalp. Therefore, we used direct-current electroencephalography (DC-EEG) to characterize the spatiotemporal behavior of scalp-recorded slow electrical signals during blood-brain barrier opening. Nine anesthetized patients receiving chemotherapy were monitored continuously during 47 blood-brain barrier openings induced by carotid or vertebral artery mannitol infusion. Left or right carotid artery mannitol infusion generated a strongly lateralized DC-EEG response that began with a 2 min negative shift of up to 2000 μV followed by a positive shift lasting up to 20 min above the infused carotid artery territory, whereas contralateral responses were of opposite polarity. Vertebral artery mannitol infusion gave rise to a minimally lateralized and more uniformly distributed slow negative response with a posterior-frontal gradient. Simultaneously performed near-infrared spectroscopy detected a multiphasic response beginning with mannitol-bolus induced dilution of blood and ending in a prolonged increase in the oxy/deoxyhemoglobin ratio. The pronounced DC-EEG shifts are readily accounted for by opening and sealing of the blood-brain barrier. These data show that DC-EEG is a promising real-time monitoring tool for blood-brain barrier disruption augmented drug delivery. PMID:28319185

Wireless multichannel electroencephalography in the newborn

PubMed Central

Ibrahim, Z.H.; Chari, G.; Abdel Baki, S.; Bronshtein, V.; Kim, M.R.; Weedon, J.; Cracco, J.; Aranda, J.V.

2016-01-01

OBJECTIVES: First, to determine the feasibility of an ultra-compact wireless device (microEEG) to obtain multichannel electroencephalographic (EEG) recording in the Neonatal Intensive Care Unit (NICU). Second, to identify problem areas in order to improve wireless EEG performance. STUDY DESIGN: 28 subjects (gestational age 24–30 weeks, postnatal age <30 days) were recruited at 2 sites as part of an ongoing study of neonatal apnea and wireless EEG. Infants underwent 8-9 hour EEG recordings every 2–4 weeks using an electrode cap (ANT-Neuro) connected to the wireless EEG device (Bio-Signal Group). A 23 electrode configuration was used incorporating the International 10–20 System. The device transmitted recordings wirelessly to a laptop computer for bedside assessment. The recordings were assessed by a pediatric neurophysiologist for interpretability. RESULTS: A total of 84 EEGs were recorded from 28 neonates. 61 EEG studies were obtained in infants prior to 35 weeks corrected gestational age (CGA). NICU staff placed all electrode caps and initiated all recordings. Of these recordings 6 (10%) were uninterpretable due to artifacts and one study could not be accessed. The remaining 54 (89%) EEG recordings were acceptable for clinical review and interpretation by a pediatric neurophysiologist. Of the recordings obtained at 35 weeks corrected gestational age or later only 11 out of 23 (48%) were interpretable. CONCLUSIONS: Wireless EEG devices can provide practical, continuous, multichannel EEG monitoring in preterm neonates. Their small size and ease of use could overcome obstacles associated with EEG recording and interpretation in the NICU. PMID:28009337

A Procedural Electroencephalogram Simulator for Evaluation of Anesthesia Monitors.

PubMed

Petersen, Christian Leth; Görges, Matthias; Massey, Roslyn; Dumont, Guy Albert; Ansermino, J Mark

2016-11-01

Recent research and advances in the automation of anesthesia are driving the need to better understand electroencephalogram (EEG)-based anesthesia end points and to test the performance of anesthesia monitors. This effort is currently limited by the need to collect raw EEG data directly from patients. A procedural method to synthesize EEG signals was implemented in a mobile software application. The application is capable of sending the simulated signal to an anesthesia depth of hypnosis monitor. Systematic sweeps of the simulator generate functional monitor response profiles reminiscent of how network analyzers are used to test electronic components. Three commercial anesthesia monitors (Entropy, NeuroSENSE, and BIS) were compared with this new technology, and significant response and feature variations between the monitor models were observed; this includes reproducible, nonmonotonic apparent multistate behavior and significant hysteresis at light levels of anesthesia. Anesthesia monitor response to a procedural simulator can reveal significant differences in internal signal processing algorithms. The ability to synthesize EEG signals at different anesthetic depths potentially provides a new method for systematically testing EEG-based monitors and automated anesthesia systems with all sensor hardware fully operational before human trials.

Long-term EEG in children.

PubMed

Montavont, A; Kaminska, A; Soufflet, C; Taussig, D

2015-03-01

Long-term video-EEG corresponds to a recording ranging from 1 to 24 h or even longer. It is indicated in the following situations: diagnosis of epileptic syndromes or unclassified epilepsy, pre-surgical evaluation for drug-resistant epilepsy, follow-up of epilepsy or in cases of paroxysmal symptoms whose etiology remains uncertain. There are some specificities related to paediatric care: a dedicated pediatric unit; continuous monitoring covering at least a full 24-hour period, especially in the context of pre-surgical evaluation; the requirement of presence by the parents, technician or nurse; and stronger attachment of electrodes (cup electrodes), the number of which is adapted to the age of the child. The chosen duration of the monitoring also depends on the frequency of seizures or paroxysmal events. The polygraphy must be adapted to the type and topography of movements. It is essential to have at least an electrocardiography (ECG) channel, respiratory sensor and electromyography (EMG) on both deltoids. There is no age limit for performing long-term video-EEG even in newborns and infants; nevertheless because of scalp fragility, strict surveillance of the baby's skin condition is required. In the specific context of pre-surgical evaluation, long-term video-EEG must record all types of seizures observed in the child. This monitoring is essential in order to develop hypotheses regarding the seizure onset zone, based on electroclinical correlations, which should be adapted to the child's age and the psychomotor development. Copyright © 2015. Published by Elsevier SAS.

Difficulty in clinical identification of neonatal seizures: an EEG monitor study.

PubMed Central

Fenichel, G. M.

1987-01-01

Seventeen newborns were monitored for 24 hours using a three-channel ambulatory EEG (A/EEG). All newborns were thought to be having subtle seizures by the nursery staff. Fifteen of the 17 newborns were recorded as having 1-30 clinical seizures during the time of monitoring. Only one newborn had clinically identified seizures associated with A/EEG discharges. The seizures were characterized by eye rolling. Fifty-two episodes (thought to be seizures) of lip smacking, bicycling, jerking, fisting, staring, stiffening, or any combination of the above occurred in eight newborns without an associated discharge on A/EEG. However, two of the eight had seizure discharges at other times, not associated with any clinical manifestation. Seventy-four apnea spells, thought to be possible seizures, occurred in seven newborns. None was associated with discharges on A/EEG, but one of these newborns had 50 A/EEG discharges unrelated to apnea or other clinical manifestations. PMID:3577211

EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach.

PubMed

Bosl, William J; Tager-Flusberg, Helen; Nelson, Charles A

2018-05-01

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.

Outcome following postanoxic status epilepticus in patients with targeted temperature management after cardiac arrest.

PubMed

Dragancea, Irina; Backman, Sofia; Westhall, Erik; Rundgren, Malin; Friberg, Hans; Cronberg, Tobias

2015-08-01

Postanoxic electrographic status epilepticus (ESE) is considered a predictor of poor outcome in resuscitated patients after cardiac arrest (CA). Observational data suggest that a subgroup of patients may have a good outcome. This study aimed to describe the prevalence of ESE and potential clinical and electrographic prognostic markers. In this retrospective single study, we analyzed consecutive patients who suffered from CA, and who received temperature management and were monitored with simplified continuous EEG (cEEG) during a five-year period. The patients' charts and cEEG data were initially screened to identify patients with clinical seizures or ESE. The cEEG diagnosis of ESE was retrospectively reanalyzed according to strict criteria by a neurophysiologist blinded to patient outcome. The EEG background patterns prior to the onset of ESE, duration of ESE, presence of clinical seizures, and use of antiepileptic drugs were analyzed. The results of somatosensory-evoked potentials (SSEPs) and neuron-specific enolase (NSE) at 48 h after CA were described in all patients with ESE. Antiepileptic treatment strategies were not protocolized. Outcome was evaluated using the Cerebral Performance Category (CPC) scale at 6 months, and good outcome was defined as CPC 1-2. Of 127 patients, 41 (32%) developed ESE. Twenty-five patients had a discontinuous EEG background prior to ESE, and all died without regaining consciousness. Sixteen patients developed a continuous EEG background prior to the start of ESE, four of whom survived, three with CPC 1-2 and one with CPC 3 at 6 months. Among survivors, ESE developed at a median of 46 h after CA. All had preserved N20 peaks on SSEP and NSE values of 18-37 μg/l. Electrographic status epilepticus is common among comatose patients after cardiac arrest, with few survivors. A combination of a continuous EEG background prior to ESE, preserved N20 peaks on SSEPs, and low or moderately elevated NSE levels may indicate a good outcome. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015 Elsevier Inc. All rights reserved.

Decoding human swallowing via electroencephalography: a state-of-the-art review

PubMed Central

Jestrović, Iva; Coyle, James L.

2015-01-01

Swallowing and swallowing disorders have garnered continuing interest over the past several decades. Electroencephalography (EEG) is an inexpensive and non-invasive procedure with very high temporal resolution which enables analysis of short and fast swallowing events, as well as an analysis of the organizational and behavioral aspects of cortical motor preparation, swallowing execution and swallowing regulation. EEG is a powerful technique which can be used alone or in combination with other techniques for monitoring swallowing, detection of swallowing motor imagery for diagnostic or biofeedback purposes, or to modulate and measure the effects of swallowing rehabilitation. This paper provides a review of the existing literature which has deployed EEG in the investigation of oropharyngeal swallowing, smell, taste and texture related to swallowing, cortical pre-motor activation in swallowing, and swallowing motor imagery detection. Furthermore, this paper provides a brief review of the different modalities of brain imaging techniques used to study swallowing brain activities, as well as the EEG components of interest for studies on swallowing and on swallowing motor imagery. Lastly, this paper provides directions for future swallowing investigations using EEG. PMID:26372528

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy - A comparison with scalp EEG monitoring.

PubMed

Zibrandtsen, I C; Kidmose, P; Christensen, C B; Kjaer, T W

2017-12-01

Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Three-dimensional intracranial EEG monitoring in presurgical assessment of MRI-negative frontal lobe epilepsy

PubMed Central

Yang, Peng-Fan; Shang, Ming-Chao; Lin, Qiao; Xiao, Hui; Mei, Zhen; Jia, Yan-Zeng; Liu, Wei; Zhong, Zhong-Hui

2016-01-01

Abstract Magnetic resonance imaging (MRI)-negative epilepsy is associated with poor clinical outcomes prognosis. The present study was aimed to assess whether intracranial 3D interictal and ictal electroencephalography (EEG) findings, a combination of EEG at a different depth, in addition to clinical, scalp EEG, and positron emission tomography–computed tomography (PETCT) data help to predict outcome in a series of patients with MRI-negative frontal lobe epilepsy (FLE) after surgery. Patients with MRI-negative FLE who were presurgically evaluated by 3D-intracranial EEG (3D-iEEG) recording were included. Outcome predictors were compared in patients with seizure freedom (group 1) and those with recurrent seizures (group 2) at least 24 months after surgery. Forty-seven patients (15 female) were included in this study. MRI was found normal in 38 patients, whereas a focal or regional hypometabolism was observed in 33 cases. Twenty-three patients (48.9%) were seizure-free (Engel class I), and 24 patients (51.1%) continued to have seizures (12 were class II, 7 were class III, and 5 were class IV). Detailed analysis of intracranial EEG revealed widespread (>2 cm) (17.4%:75%; P = 0.01) in contrast to focal seizure onset as well as shorter latency to onset of seizure spread (5.9 ± 7.1 s; 1.4 ± 2.9 s; P = 0.016) and to ictal involvement of brain structures beyond the frontal lobe (21.8 ± 20.3 s; 4.9 ± 5.1 s; P = 0.025) in patients without seizure freedom. The results suggest that presurgical evaluation using 3D-iEEG monitoring lead to a better surgical outcome as seizure free in MRI-negative FLE patients. PMID:27977572

Daytime outpatient versus inpatient video-EEG monitoring for presurgical evaluation in temporal lobe epilepsy.

PubMed

Guerreiro, Carlos A M; Montenegro, Maria Augusta; Kobayashi, Eliane; Noronha, Ana Lúcia A; Guerreiro, Marilisa M; Cendes, Fernando

2002-06-01

Video-EEG monitoring documentation of seizure localization is one of the most important aspects of a presurgical investigation in refractory temporal lobe epilepsy (TLE) patients. The objective of this study was to evaluate the efficacy of inpatient versus daytime outpatient telemetry. The authors evaluated prospectively 73 patients with medically intractable TLE. Ninety-one telemetry sessions were performed: 35 as inpatients and 56 as outpatients. Outpatient monitoring was performed in the EEG laboratory. They used 18-channel digital EEG. Medications were not changed in the outpatient group. For analysis of the data, time was counted in periods (12 hours = 1 period). Statistical analyses were performed using Student's t-test and the chi2 test. There were no differences between the two groups (outpatient versus inpatient) with respect to age and mean seizure frequency before monitoring, mean time to record the first seizure (1.1 versus 1.4 periods), mean number of seizures per period (0.6 for both groups), lateralization by interictal spiking (46% versus 57%), and lateralization by ictal EEG (59% versus 77%). Daytime outpatient video-EEG monitoring for presurgical evaluation is efficient and comparable with inpatient monitoring. Therefore, the improved cost benefit of outpatient monitoring may increase the access to surgery for individuals with intractable TLE.

Comparison of Amplitude-Integrated EEG and Conventional EEG in a Cohort of Premature Infants.

PubMed

Meledin, Irina; Abu Tailakh, Muhammad; Gilat, Shlomo; Yogev, Hagai; Golan, Agneta; Novack, Victor; Shany, Eilon

2017-03-01

To compare amplitude-integrated EEG (aEEG) and conventional EEG (EEG) activity in premature neonates. Biweekly aEEG and EEG were simultaneously recorded in a cohort of infants born less than 34 weeks gestation. aEEG recordings were visually assessed for lower and upper border amplitude and bandwidth. EEG recordings were compressed for visual evaluation of continuity and assessed using a signal processing software for interburst intervals (IBI) and frequencies' amplitude. Ten-minute segments of aEEG and EEG indices were compared using regression analysis. A total of 189 recordings from 67 infants were made, from which 1697 aEEG/EEG pairs of 10-minute segments were assessed. Good concordance was found for visual assessment of continuity between the 2 methods. EEG IBI, alpha and theta frequencies' amplitudes were negatively correlated to the aEEG lower border while conceptional age (CA) was positively correlated to aEEG lower border ( P < .001). IBI and all frequencies' amplitude were positively correlated to the upper aEEG border ( P ≤ .001). CA was negatively correlated to aEEG span while IBI, alpha, beta, and theta frequencies' amplitude were positively correlated to the aEEG span. Important information is retained and integrated in the transformation of premature neonatal EEG to aEEG. aEEG recordings in high-risk premature neonates reflect reliably EEG background information related to continuity and amplitude.

Brain Monitoring with Electroencephalography and the Electroencephalogram-Derived Bispectral Index During Cardiac Surgery

PubMed Central

Kertai, Miklos D.; Whitlock, Elizabeth L.; Avidan, Michael S.

2011-01-01

Cardiac surgery presents particular challenges for the anesthesiologist. In addition to standard and advanced monitors typically used during cardiac surgery, anesthesiologists may consider monitoring the brain with raw or processed electroencephalography (EEG). There is strong evidence that a protocol incorporating the processed EEG Bispectral Index (BIS) decreases the incidence intraoperative awareness compared with standard practice. However there is conflicting evidence that incorporating the BIS into cardiac anesthesia practice improves “fast-tracking,” decreases anesthetic drug use, or detects cerebral ischemia. Recent research, including many cardiac surgical patients, shows that a protocol based on BIS monitoring is not superior to a protocol based on end tidal anesthetic concentration monitoring in preventing awareness. There has been a resurgence of interest in the anesthesia literature in limited montage EEG monitoring, including nonproprietary processed indices. This has been accompanied by research showing that with structured training, anesthesiologists can glean useful information from the raw EEG trace. In this review, we discuss both the hypothesized benefits and limitations of BIS and frontal channel EEG monitoring in the cardiac surgical population. PMID:22253267

Use of EEG workload indices for diagnostic monitoring of vigilance decrement.

PubMed

Kamzanova, Altyngul T; Kustubayeva, Almira M; Matthews, Gerald

2014-09-01

A study was run to test which of five electroencephalographic (EEG) indices was most diagnostic of loss of vigilance at two levels of workload. EEG indices of alertness include conventional spectral power measures as well as indices combining measures from multiple frequency bands, such as the Task Load Index (TLI) and the Engagement Index (El). However, it is unclear which indices are optimal for early detection of loss of vigilance. Ninety-two participants were assigned to one of two experimental conditions, cued (lower workload) and uncued (higher workload), and then performed a 40-min visual vigilance task. Performance on this task is believed to be limited by attentional resource availability. EEG was recorded continuously. Performance, subjective state, and workload were also assessed. The task showed a vigilance decrement in performance; cuing improved performance and reduced subjective workload. Lower-frequency alpha (8 to 10.9 Hz) and TLI were most sensitive to the task parameters. The magnitude of temporal change was larger for lower-frequency alpha. Surprisingly, higher TLI was associated with superior performance. Frontal theta and El were influenced by task workload only in the final period of work. Correlational data also suggested that the indices are distinct from one another. Lower-frequency alpha appears to be the optimal index for monitoring vigilance on the task used here, but further work is needed to test how diagnosticity of EEG indices varies with task demands. Lower-frequency alpha may be used to diagnose loss of operator alertness on tasks requiring vigilance.

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection.

PubMed

Bogaarts, J G; Hilkman, D M W; Gommer, E D; van Kranen-Mastenbroek, V H J M; Reulen, J P H

2016-12-01

Continuous electroencephalographic monitoring of critically ill patients is an established procedure in intensive care units. Seizure detection algorithms, such as support vector machines (SVM), play a prominent role in this procedure. To correct for inter-human differences in EEG characteristics, as well as for intra-human EEG variability over time, dynamic EEG feature normalization is essential. Recently, the median decaying memory (MDM) approach was determined to be the best method of normalization. MDM uses a sliding baseline buffer of EEG epochs to calculate feature normalization constants. However, while this method does include non-seizure EEG epochs, it also includes EEG activity that can have a detrimental effect on the normalization and subsequent seizure detection performance. In this study, EEG data that is to be incorporated into the baseline buffer are automatically selected based on a novelty detection algorithm (Novelty-MDM). Performance of an SVM-based seizure detection framework is evaluated in 17 long-term ICU registrations using the area under the sensitivity-specificity ROC curve. This evaluation compares three different EEG normalization methods, namely a fixed baseline buffer (FB), the median decaying memory (MDM) approach, and our novelty median decaying memory (Novelty-MDM) method. It is demonstrated that MDM did not improve overall performance compared to FB (p < 0.27), partly because seizure like episodes were included in the baseline. More importantly, Novelty-MDM significantly outperforms both FB (p = 0.015) and MDM (p = 0.0065).

Phenobarbitone, neonatal seizures, and video-EEG

PubMed Central

Boylan, G; Rennie, J; Pressler, R; Wilson, G; Morton, M; Binnie, C

2002-01-01

Aims: To evaluate the effectiveness of phenobarbitone as an anticonvulsant in neonates. Methods: An observational study using video-EEG telemetry. Video-EEG was obtained before treatment was started, for an hour after treatment was given, two hours after treatment was given, and again between 12 and 24 hours after treatment was given. Patients were recruited from all babies who required phenobarbitone (20–40 mg/kg intravenously over 20 minutes) for suspected clinical seizures and had EEG monitoring one hour before and up to 24 hours after the initial dose. An EEG seizure discharge was defined as a sudden repetitive stereotyped discharge lasting for at least 10 seconds. Neonatal status epilepticus was defined as continuous seizure activity for at least 30 minutes. Seizures were categorised as EEG seizure discharges only (electrographic), or as EEG seizure discharges with accompanying clinical manifestations (electroclinical). Surviving babies were assessed at one year using the Griffiths neurodevelopmental score. Results: Fourteen babies were studied. Four responded to phenobarbitone; these had normal or moderately abnormal EEG background abnormalities and outcome was good. In the other 10 babies electrographic seizures increased after treatment, whereas electroclinical seizures reduced. Three babies were treated with second line anticonvulsants, of whom two responded. One of these had a normal neurodevelopmental score at one year, but the outcome for the remainder of the whole group was poor. Conclusion: Phenobarbitone is often ineffective as a first line anticonvulsant in neonates with seizures in whom the background EEG is significantly abnormal. PMID:11978746

A wavelet transform based method to determine depth of anesthesia to prevent awareness during general anesthesia.

PubMed

Mousavi, Seyed Mortaza; Adamoğlu, Ahmet; Demiralp, Tamer; Shayesteh, Mahrokh G

2014-01-01

Awareness during general anesthesia for its serious psychological effects on patients and some juristically problems for anesthetists has been an important challenge during past decades. Monitoring depth of anesthesia is a fundamental solution to this problem. The induction of anesthesia alters frequency and mean of amplitudes of the electroencephalogram (EEG), and its phase couplings. We analyzed EEG changes for phase coupling between delta and alpha subbands using a new algorithm for depth of general anesthesia measurement based on complex wavelet transform (CWT) in patients anesthetized by Propofol. Entropy and histogram of modulated signals were calculated by taking bispectral index (BIS) values as reference. Entropies corresponding to different BIS intervals using Mann-Whitney U test showed that they had different continuous distributions. The results demonstrated that there is a phase coupling between 3 and 4 Hz in delta and 8-9 Hz in alpha subbands and these changes are shown better at the channel T 7 of EEG. Moreover, when BIS values increase, the entropy value of modulated signal also increases and vice versa. In addition, measuring phase coupling between delta and alpha subbands of EEG signals through continuous CWT analysis reveals the depth of anesthesia level. As a result, awareness during anesthesia can be prevented.

Miniaturized, on-head, invasive electrode connector integrated EEG data acquisition system.

PubMed

Ives, John R; Mirsattari, Seyed M; Jones, D

2007-07-01

Intracranial electroencephalogram (EEG) monitoring involves recording multi-contact electrodes. The current systems require separate wires from each recording contact to the data acquisition unit resulting in many connectors and cables. To overcome limitations of such systems such as noise, restrictions in patient mobility and compliance, we developed a miniaturized EEG monitoring system with the amplifiers and multiplexers integrated into the electrode connectors and mounted on the head. Small, surface-mounted instrumentation amplifiers, coupled with 8:1 analog multiplexers, were assembled into 8-channel modular units to connect to 16:1 analog multiplexer manifold to create a small (55 cm(3)) head-mounted 128-channel system. A 6-conductor, 30 m long cable was used to transmit the EEG signals from the patient to the remote data acquisition system. Miniaturized EEG amplifiers and analog multiplexers were integrated directly into the electrode connectors. Up to 128-channels of EEG were amplified and analog multiplexed directly on the patient's head. The amplified EEG data were obtained over one long wire. A miniaturized system of invasive EEG recording has the potential to reduce artefact, simplify trouble-shooting, lower nursing care and increase patient compliance. Miniaturization technology improves intracranial EEG monitoring and leads to >128-channel capacity.

Wireless system for long-term EEG monitoring of absence epilepsy

NASA Astrophysics Data System (ADS)

Whitchurch, Ashwin K.; Ashok, B. H.; Kumaar, R. V.; Saurkesi, K.; Varadan, Vijay K.

2002-11-01

Absence epilepsy is a form of epilepsy common mostly in children. The most common manifestations of Absence epilepsy are staring and transient loss of responsiveness. Also, subtle motor activities may occur. Due to the subtle nature of these symptoms, episodes of absence epilepsy may often go unrecognized for long periods of time or be mistakenly attributed to attention deficit disorder or daydreaming. Spells of absence epilepsy may last about 10 seconds and occur hundreds of times each day. Patients have no recollections of the events that occurred during those seizures and will resume normal activity without any postictal symptoms. The EEG during such episodes of Absence epilepsy shows intermittent activity of 3 Hz generalized spike and wave complexes. As EEG is the only way of detecting such symptoms, it is required to monitor the EEG of the patient for a long time and thus remain only in bed. So, effectively the EEG is being monitored only when the patient is stationary. The wireless monitoring sys tem described in this paper aims at eliminating this constraint and enables the physicial to monitor the EEG when the patient resumes his normal activities. This approach could even help the doctor identify possible triggers of absence epilepsy.

Seizure clusters and adverse events during pre-surgical video-EEG monitoring with a slow anti-epileptic drug (AED) taper.

PubMed

Di Gennaro, Giancarlo; Picardi, Angelo; Sparano, Antonio; Mascia, Addolorata; Meldolesi, Giulio N; Grammaldo, Liliana G; Esposito, Vincenzo; Quarato, Pier P

2012-03-01

To evaluate the efficiency and safety of pre-surgical video-EEG monitoring with a slow anti-epileptic drug (AED) taper and a rescue benzodiazepine protocol. Fifty-four consecutive patients with refractory focal epilepsy who underwent pre-surgical video-electroencephalography (EEG) monitoring during the year 2010 were included in the study. Time to first seizure, duration of monitoring, incidence of 4-h and 24-h seizure clustering, secondarily generalised tonic-clonic seizures (sGTCS), status epilepticus, falls and cardiac asystole were evaluated. A total of 190 seizures were recorded. Six (11%) patients had 4-h clusters and 21 (39%) patients had 24-h clusters. While 15 sGTCS were recorded in 14 patients (26%), status epilepticus did not occur and no seizure was complicated with cardiac asystole. Epileptic falls with no significant injuries occurred in three patients. The mean time to first seizure was 3.3days and the time to conclude video-EEG monitoring averaged 6days. Seizure clustering was common during pre-surgical video-EEG monitoring, although serious adverse events were rare with a slow AED tapering and a rescue benzodiazepine protocol. Slow AED taper pre-surgical video-EEG monitoring is fairly safe when performed in a highly specialised and supervised hospital setting. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Assessing the depth of hypnosis of xenon anaesthesia with the EEG.

PubMed

Stuttmann, Ralph; Schultz, Arthur; Kneif, Thomas; Krauss, Terence; Schultz, Barbara

2010-04-01

Xenon was approved as an inhaled anaesthetic in Germany in 2005 and in other countries of the European Union in 2007. Owing to its low blood/gas partition coefficient, xenons effects on the central nervous system show a fast onset and offset and, even after long xenon anaesthetics, the wake-up times are very short. The aim of this study was to examine which electroencephalogram (EEG) stages are reached during xenon application and whether these stages can be identified by an automatic EEG classification. Therefore, EEG recordings were performed during xenon anaesthetics (EEG monitor: Narcotrend®). A total of 300 EEG epochs were assessed visually with regard to the EEG stages. These epochs were also classified automatically by the EEG monitor Narcotrend® using multivariate algorithms. There was a high correlation between visual and automatic classification (Spearman's rank correlation coefficient r=0.957, prediction probability Pk=0.949). Furthermore, it was observed that very deep stages of hypnosis were reached which are characterised by EEG activity in the low frequency range (delta waves). The burst suppression pattern was not seen. In deep hypnosis, in contrast to the xenon EEG, the propofol EEG was characterised by a marked superimposed higher frequency activity. To ensure an optimised dosage for the single patient, anaesthetic machines for xenon should be combined with EEG monitoring. To date, only a few anaesthetic machines for xenon are available. Because of the high price of xenon, new and further developments of machines focus on optimizing xenon consumption.

Electroencephalographic profiles for differentiation of disorders of consciousness

PubMed Central

2013-01-01

Background Electroencephalography (EEG) is best suited for long-term monitoring of brain functions in patients with disorders of consciousness (DOC). Mathematical tools are needed to facilitate efficient interpretation of long-duration sleep-wake EEG recordings. Methods Starting with matching pursuit (MP) decomposition, we automatically detect and parametrize sleep spindles, slow wave activity, K-complexes and alpha, beta and theta waves present in EEG recordings, and automatically construct profiles of their time evolution, relevant to the assessment of residual brain function in patients with DOC. Results Above proposed EEG profiles were computed for 32 patients diagnosed as minimally conscious state (MCS, 20 patients), vegetative state/unresponsive wakefulness syndrome (VS/UWS, 11 patients) and Locked-in Syndrome (LiS, 1 patient). Their interpretation revealed significant correlations between patients’ behavioral diagnosis and: (a) occurrence of sleep EEG patterns including sleep spindles, slow wave activity and light/deep sleep cycles, (b) appearance and variability across time of alpha, beta, and theta rhythms. Discrimination between MCS and VS/UWS based upon prominent features of these profiles classified correctly 87% of cases. Conclusions Proposed EEG profiles offer user-independent, repeatable, comprehensive and continuous representation of relevant EEG characteristics, intended as an aid in differentiation between VS/UWS and MCS states and diagnostic prognosis. To enable further development of this methodology into clinically usable tests, we share user-friendly software for MP decomposition of EEG (http://braintech.pl/svarog) and scripts used for creation of the presented profiles (attached to this article). PMID:24143892

Diagnostic and therapeutic yield of a patient-controlled portable EEG device with dry electrodes for home-monitoring neurological outpatients-rationale and protocol of the HOMEONE pilot study.

PubMed

Neumann, Thomas; Baum, Anne Katrin; Baum, Ulrike; Deike, Renate; Feistner, Helmut; Hinrichs, Hermann; Stokes, Joseph; Robra, Bernt-Peter

2018-01-01

The HOME ONE study is part of the larger HOME project, which aims to provide evidence of diagnostic and therapeutic yield ("change of management") of a patient-controlled portable EEG device with dry electrodes for the purposes of EEG home-monitoring neurological outpatients. The HOME ONE study is the first step in the process of investigating whether outpatient EEG home-monitoring changes the diagnosis and treatment of patients in comparison to conventional EEG ("change of management"). Both EEG devices (conventional and portable) will be systematically compared via a two-phase intra-individual assessment.In the first phase (pilot study phase), both EEG devices will be used within neurologist practices (all other things being equal). This pilot study (involving 130 patients) will evaluate the technical usability and efficacy of the new portable dry electrode EEG recorder in comparison to conventional EEG devices. Judgements will be based on technical assessments and EEG record examinations of private practitioners and two experienced neurologists (percent of concordant readings and kappa values).The second phase (feasibility study phase) aims to assess patients' acceptability and feasibility of the EEG home-monitoring and will provide insights into the extent diagnostic and therapeutic yields can be expected.For this purpose, a conventional EEG will be recorded in neurologist practices. Thereafter, the practice staff will instruct the patients on how the portable EEG device functions. The patients will subsequently use the devices in their home environment.The evaluation will compare the before and after documented diagnostic findings and the therapeutic consequences of the private practitioners with those of two experienced neurologists. To the best of our knowledge, this will be the first study of its kind to examine new approaches to diagnosing unclear consciousness disorders or other disorders of the CNS or the cardiovascular system through the use of a patient-controlled portable EEG device with dry electrodes for the purpose of home-monitoring neurological outpatients. If the two phases of the HOME ONE study provide sufficient evidence of diagnostic and therapeutic yields, this would justify (indication-specific) full-scale randomized controlled trials or observational studies. DRKS DRKS00012685. Registered 9 August 2017, retrospectively registered.

Variation in anticonvulsant selection and EEG monitoring following severe traumatic brain injury in children – Understanding resource availability in sites participating in a comparative effectiveness study

PubMed Central

Kurz, Jonathan E.; Poloyac, Samuel M.; Abend, Nicholas S.; Fabio, Anthony; Bell, Michael J.; Wainwright, Mark S.

2016-01-01

Objective Early post-traumatic seizures (PTS) may contribute to worsened outcomes after traumatic brain injury (TBI). Evidence to guide the evaluation and management of early PTS in children is limited. We undertook a survey of current practices of continuous electroencephalographic monitoring (cEEG), seizure prophylaxis and the management of early PTS to provide essential information for trial design and the development of PTS management pathways. Design Surveys were sent to site principal investigators at all 43 sites participating in the ADAPT (Approaches and Decisions in Acute Pediatric TBI) trial at the time of the survey. Surveys consisted of 12 questions addressing strategies to (i) implement cEEG monitoring, (ii) PTS prophylaxis, (iii) treat acute PTS, (iv) treat status epilepticus (SE) and refractory status epilepticus (RSE) and (v) monitor anti-seizure drug levels. Setting Institutions comprised a mixture of free-standing children’s hospitals and university medical centers across the United States and Europe. Measurements and Main Results cEEG monitoring was available in the pediatric intensive care unit in the overwhelming majority of clinical sites (98%); however, the plans to operationalize such monitoring for children varied considerably. A similar majority of sites report that administration of prophylactic anti-seizure medications is anticipated in children (93%), yet a minority reports that a specified protocol for treatment of PTS is in place (43%). Reported medication choices varied substantially between sites, but the majority of sites reported pentobarbital for RSE (81%). Presence of an treatment protocols for seizure prophylaxis, early PTS, post-traumatic SE and RSE was associated with decreased reported medications (all p < 0.05). Conclusions This study reports the current management practices for early PTS in select academic centers after pediatric severe TBI. The substantial variation in cEEG implementation, choice of seizure prophylaxis medications, and management of early PTS across institutions was reported, signifying areas of clinical uncertainty that will help provide for focused design of clinical trials. While sites with treatment protocols reported decreased number of medications for the scenarios described, completion of the ADAPT Trial will be able to determine if these protocols lead to decreased variability in medication administration in children at the clinical sites. PMID:27243415

Separation and reconstruction of BCG and EEG signals during continuous EEG and fMRI recordings

PubMed Central

Xia, Hongjing; Ruan, Dan; Cohen, Mark S.

2014-01-01

Despite considerable effort to remove it, the ballistocardiogram (BCG) remains a major artifact in electroencephalographic data (EEG) acquired inside magnetic resonance imaging (MRI) scanners, particularly in continuous (as opposed to event-related) recordings. In this study, we have developed a new Direct Recording Prior Encoding (DRPE) method to extract and separate the BCG and EEG components from contaminated signals, and have demonstrated its performance by comparing it quantitatively to the popular Optimal Basis Set (OBS) method. Our modified recording configuration allows us to obtain representative bases of the BCG- and EEG-only signals. Further, we have developed an optimization-based reconstruction approach to maximally incorporate prior knowledge of the BCG/EEG subspaces, and of the signal characteristics within them. Both OBS and DRPE methods were tested with experimental data, and compared quantitatively using cross-validation. In the challenging continuous EEG studies, DRPE outperforms the OBS method by nearly sevenfold in separating the continuous BCG and EEG signals. PMID:25002836

Levetiracetam versus phenytoin for seizure prophylaxis in severe traumatic brain injury

PubMed Central

Jones, Kristen E.; Puccio, Ava M.; Harshman, Kathy J.; Falcione, Bonnie; Benedict, Neal; Jankowitz, Brian T.; Stippler, Martina; Fischer, Michael; Sauber-Schatz, Erin K.; Fabio, Anthony; Darby, Joseph M.; Okonkwo, David O.

2013-01-01

Object Current standard of care for patients with severe traumatic brain injury (TBI) is prophylactic treatment with phenytoin for 7 days to decrease the risk of early posttraumatic seizures. Phenytoin alters drug metabolism, induces fever, and requires therapeutic-level monitoring. Alternatively, levetiracetam (Keppra) does not require serum monitoring or have significant pharmacokinetic interactions. In the current study, the authors compare the EEG findings in patients receiving phenytoin with those receiving levetiracetam monotherapy for seizure prophylaxis following severe TBI. Methods Data were prospectively collected in 32 cases in which patients received levetiracetam for the first 7 days after severe TBI and compared with data from a historical cohort of 41 cases in which patients received phenytoin monotherapy. Patients underwent 1-hour electroencephalographic (EEG) monitoring if they displayed persistent coma, decreased mental status, or clinical signs of seizures. The EEG results were grouped into normal and abnormal findings, with abnormal EEG findings further categorized as seizure activity or seizure tendency. Results Fifteen of 32 patients in the levetiracetam group warranted EEG monitoring. In 7 of these 15 cases the results were normal and in 8 abnormal; 1 patient had seizure activity, whereas 7 had seizure tendency. Twelve of 41 patients in the phenytoin group received EEG monitoring, with all results being normal. Patients treated with levetiracetam and phenytoin had equivalent incidence of seizure activity (p = 0.556). Patients receiving levetiracetam had a higher incidence of abnormal EEG findings (p = 0.003). Conclusions Levetiracetam is as effective as phenytoin in preventing early posttraumatic seizures but is associated with an increased seizure tendency on EEG analysis. PMID:18828701

Smart Helmet: Wearable Multichannel ECG and EEG

PubMed Central

Chanwimalueang, Theerasak; Goverdovsky, Valentin; Looney, David; Sharp, David; Mandic, Danilo P.

2016-01-01

Modern wearable technologies have enabled continuous recording of vital signs, however, for activities such as cycling, motor-racing, or military engagement, a helmet with embedded sensors would provide maximum convenience and the opportunity to monitor simultaneously both the vital signs and the electroencephalogram (EEG). To this end, we investigate the feasibility of recording the electrocardiogram (ECG), respiration, and EEG from face-lead locations, by embedding multiple electrodes within a standard helmet. The electrode positions are at the lower jaw, mastoids, and forehead, while for validation purposes a respiration belt around the thorax and a reference ECG from the chest serve as ground truth to assess the performance. The within-helmet EEG is verified by exposing the subjects to periodic visual and auditory stimuli and screening the recordings for the steady-state evoked potentials in response to these stimuli. Cycling and walking are chosen as real-world activities to illustrate how to deal with the so-induced irregular motion artifacts, which contaminate the recordings. We also propose a multivariate R-peak detection algorithm suitable for such noisy environments. Recordings in real-world scenarios support a proof of concept of the feasibility of recording vital signs and EEG from the proposed smart helmet. PMID:27957405

Clustering of spontaneous recurrent seizures separated by long seizure-free periods: An extended video-EEG monitoring study of a pilocarpine mouse model.

PubMed

Lim, Jung-Ah; Moon, Jangsup; Kim, Tae-Joon; Jun, Jin-Sun; Park, Byeongsu; Byun, Jung-Ick; Sunwoo, Jun-Sang; Park, Kyung-Il; Lee, Soon-Tae; Jung, Keun-Hwa; Jung, Ki-Young; Kim, Manho; Jeon, Daejong; Chu, Kon; Lee, Sang Kun

2018-01-01

Seizure clustering is a common and significant phenomenon in patients with epilepsy. The clustering of spontaneous recurrent seizures (SRSs) in animal models of epilepsy, including mouse pilocarpine models, has been reported. However, most studies have analyzed seizures for a short duration after the induction of status epilepticus (SE). In this study, we investigated the detailed characteristics of seizure clustering in the chronic stage of a mouse pilocarpine-induced epilepsy model for an extended duration by continuous 24/7 video-EEG monitoring. A seizure cluster was defined as the occurrence of one or more seizures per day for at least three consecutive days and at least five seizures during the cluster period. We analyzed the cluster duration, seizure-free period, cluster interval, and numbers of seizures within and outside the seizure clusters. The video-EEG monitoring began 84.5±33.7 days after the induction of SE and continued for 53.7±20.4 days. Every mouse displayed seizure clusters, and 97.0% of the seizures occurred within a cluster period. The seizure clusters were followed by long seizure-free periods of 16.3±6.8 days, showing a cyclic pattern. The SRSs also occurred in a grouped pattern within a day. We demonstrate that almost all seizures occur in clusters with a cyclic pattern in the chronic stage of a mouse pilocarpine-induced epilepsy model. The seizure-free periods between clusters were long. These findings should be considered when performing in vivo studies using this animal model. Furthermore, this model might be appropriate for studying the unrevealed mechanism of ictogenesis.

Biosensor Technologies for Augmented Brain-Computer Interfaces in the Next Decades

DTIC Science & Technology

2012-05-13

Research Triangle Park, NC 27709-2211 Augmented brain–computer interface (ABCI);biosensor; cognitive-state monitoring; electroencephalogram( EEG ); human...biosensor; cognitive-state monitoring; electroencephalogram ( EEG ); human brain imaging Manuscript received November 28, 2011; accepted December 20...magnetic reso- nance imaging (fMRI) [1], positron emission tomography (PET) [2], electroencephalograms ( EEGs ) and optical brain imaging techniques (i.e

Dual Frequency Head Maps: A New Method for Indexing Mental Workload Continuously during Execution of Cognitive Tasks

PubMed Central

Radüntz, Thea

2017-01-01

One goal of advanced information and communication technology is to simplify work. However, there is growing consensus regarding the negative consequences of inappropriate workload on employee's health and the safety of persons. In order to develop a method for continuous mental workload monitoring, we implemented a task battery consisting of cognitive tasks with diverse levels of complexity and difficulty. We conducted experiments and registered the electroencephalogram (EEG), performance data, and the NASA-TLX questionnaire from 54 people. Analysis of the EEG spectra demonstrates an increase of the frontal theta band power and a decrease of the parietal alpha band power, both under increasing task difficulty level. Based on these findings we implemented a new method for monitoring mental workload, the so-called Dual Frequency Head Maps (DFHM) that are classified by support vectors machines (SVMs) in three different workload levels. The results are in accordance with the expected difficulty levels arising from the requirements of the tasks on the executive functions. Furthermore, this article includes an empirical validation of the new method on a secondary subset with new subjects and one additional new task without any adjustment of the classifiers. Hence, the main advantage of the proposed method compared with the existing solutions is that it provides an automatic, continuous classification of the mental workload state without any need for retraining the classifier—neither for new subjects nor for new tasks. The continuous workload monitoring can help ensure good working conditions, maintain a good level of performance, and simultaneously preserve a good state of health. PMID:29276490

Neurodiagnostic techniques in neonatal critical care.

PubMed

Chang, Taeun; du Plessis, Adre

2012-04-01

This article reviews recent advances in the neurodiagnostic tools available to clinicians practicing in neonatal critical care. The advent of induced mild hypothermia for acute neonatal hypoxic-ischemic encephalopathy in 2005 has been responsible for renewed urgency in the development of precise and reliable neonatal neurodiagnostic techniques. Traditional evaluations of bedside head ultrasounds, head computed tomography scans, and routine electroencephalograms (EEGs) have been upgraded in most tertiary pediatric centers to incorporate protocols for MRI, continuous EEG monitoring with remote bedside access, amplitude-integrated EEG, and near-infrared spectroscopy. Meanwhile, recent studies supporting the association between placental pathology and neonatal brain injury highlight the need for closer examination of the placenta in the neurodiagnostic evaluation of the acutely ill newborn. As the pursuit of more effective neuroprotection moves into the "hypothermia plus" era, the identification, evaluation, and treatment of the neurologically affected newborn in the neonatal intensive care unit has increasing significance.

Nanosensor system for monitoring brain activity and drowsiness

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.; Harbaugh, Robert

2015-04-01

Detection of drowsiness in drivers to avoid on-road collisions and accidents is one of the most important applications that can be implemented to avert loss of life and property caused by accidents. A statistical report indicates that drowsy driving is equally harmful as driving under influence of alcohol. This report also indicates that drowsy driving is the third most influencing factor for accidents and 30% of the commercial vehicle accidents are caused because of drowsy driving. With a motivation to avoid accidents caused by drowsy driving, this paper proposes a technique of correlating EEG and EOG signals to detect drowsiness. Feature extracts of EEG and blink variability from EOG is correlated to detect the sleepiness/drowsiness of a driver. Moreover, to implement a more pragmatic approach towards continuous monitoring, a wireless real time monitoring approach has been incorporated using textile based nanosensors. Thereby, acquired bio potential signals are transmitted through GSM communication module to the receiver continuously. In addition to this, all the incorporated electronics are equipped in a flexible headband which can be worn by the driver. With this flexible headband approach, any intrusiveness that may be experienced by other cumbersome hardware is effectively mitigated. With the continuous transmission of data from the head band, the signals are processed on the receiver side to determine the condition of the driver. Early warning of driver's drowsiness will be displayed in the dashboard of the vehicle as well as alertness voice and sound alarm will be sent via the vehicle radio.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.

PubMed

Min, Jianliang; Wang, Ping; Hu, Jianfeng

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1-2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver.

Automated diagnosis of epilepsy using CWT, HOS and texture parameters.

PubMed

Acharya, U Rajendra; Yanti, Ratna; Zheng, Jia Wei; Krishnan, M Muthu Rama; Tan, Jen Hong; Martis, Roshan Joy; Lim, Choo Min

2013-06-01

Epilepsy is a chronic brain disorder which manifests as recurrent seizures. Electroencephalogram (EEG) signals are generally analyzed to study the characteristics of epileptic seizures. In this work, we propose a method for the automated classification of EEG signals into normal, interictal and ictal classes using Continuous Wavelet Transform (CWT), Higher Order Spectra (HOS) and textures. First the CWT plot was obtained for the EEG signals and then the HOS and texture features were extracted from these plots. Then the statistically significant features were fed to four classifiers namely Decision Tree (DT), K-Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) to select the best classifier. We observed that the SVM classifier with Radial Basis Function (RBF) kernel function yielded the best results with an average accuracy of 96%, average sensitivity of 96.9% and average specificity of 97% for 23.6 s duration of EEG data. Our proposed technique can be used as an automatic seizure monitoring software. It can also assist the doctors to cross check the efficacy of their prescribed drugs.

Wireless recording systems: from noninvasive EEG-NIRS to invasive EEG devices.

PubMed

Sawan, Mohamad; Salam, Muhammad T; Le Lan, Jérôme; Kassab, Amal; Gelinas, Sébastien; Vannasing, Phetsamone; Lesage, Frédéric; Lassonde, Maryse; Nguyen, Dang K

2013-04-01

In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 μ VRMS and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than 10(-10) post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.

Behavioural Inhibition System (BIS) sensitivity differentiates EEG theta responses during goal conflict in a continuous monitoring task.

PubMed

Moore, Roger A; Mills, Matthew; Marshman, Paul; Corr, Philip J

2012-08-01

Previous research has revealed that EEG theta oscillations are affected during goal conflict processing. This is consistent with the behavioural inhibition system (BIS) theory of anxiety (Gray & McNaughton, 2000). However, studies have not attempted to relate these BIS-related theta effects to BIS personality measures. Confirmation of such an association would provide further support for BIS theory, especially as it relates to trait differences. EEG was measured (32 electrodes) from extreme groups (low/high trait BIS) engaged in a target detection task. Goal conflicts were introduced throughout the task. Results show that the two groups did not differ in behavioural performance. The major EEG result was that a stepwise discriminant analysis indicated discrimination by 6 variables derived from coherence and power, with 5 of the 6 in the theta range as predicted by BIS theory and one in the beta range. Also, across the whole sample, EEG theta coherence increased at a variety of regions during primary goal conflict and showed a general increase during response execution; EEG theta power, in contrast, was primarily reactive to response execution. This is the first study to reveal a three-way relationship between the induction of goal conflict, the induction of theta power and coherence, and differentiation by psychometrically-defined low/high BIS status. Copyright © 2012 Elsevier B.V. All rights reserved.

Developing an Adaptability Training Strategy and Policy for the DoD

DTIC Science & Technology

2008-10-01

might include monitoring of trainees using electroencephalogram ( EEG ) technology to gain neurofeedback during scenario performance. In order to...group & adequate sample; pre and post iii. Possibly including EEG monitoring (and even neurofeedback ) 4. Should seek to determine general...Dr. John Cowan has developed a system called the Peak Achievement Trainer (PAT) EEG , which traces electrical activity in the brain and provides

Computerized EEG analysis for studying the effect of drugs on the central nervous system.

PubMed

Rosadini, G; Cavazza, B; Rodriguez, G; Sannita, W G; Siccardi, A

1977-11-01

Samples of our experience in quantitative pharmaco-EEG are reviewed to discuss and define its applicability and limits. Simple processing systems, such as the computation of Hjorth's descriptors, are useful for on-line monitoring of drug-induced EEG modifications which are evident also at the visual visual analysis. Power spectral analysis is suitable to identify and quantify EEG effects not evident at the visual inspection. It demonstrated how the EEG effects of compounds in a long-acting formulation vary according to the sampling time and the explored cerebral area. EEG modifications not detected by power spectral analysis can be defined by comparing statistically (F test) the spectral values of the EEG from a single lead at the different samples (longitudinal comparison), or the spectral values from different leads at any sample (intrahemispheric comparison). The presently available procedures of quantitative pharmaco-EEG are effective when applied to the study of mutltilead EEG recordings in a statistically significant sample of population. They do not seem reliable in the monitoring of directing of neuropyschiatric therapies in single patients, due to individual variability of drug effects.

Guidelines for intraoperative neuromonitoring using raw (analog or digital waveforms) and quantitative electroencephalography: a position statement by the American Society of Neurophysiological Monitoring.

PubMed

Isley, Michael R; Edmonds, Harvey L; Stecker, Mark

2009-12-01

Electroencephalography (EEG) is one of the oldest and most commonly utilized modalities for intraoperative neuromonitoring. Historically, interest in the EEG patterns associated with anesthesia is as old as the discovery of the EEG itself. The evolution of its intraoperative use was also expanded to include monitoring for assessing cortical perfusion and oxygenation during a variety of vascular, cardiac, and neurosurgical procedures. Furthermore, a number of quantitative or computer-processed algorithms have also been developed to aid in its visual representation and interpretation. The primary clinical outcomes for which modern EEG technology has made significant intraoperative contributions include: (1) recognizing and/or preventing perioperative ischemic insults, and (2) monitoring of brain function for anesthetic drug administration in order to determine depth of anesthesia (and level of consciousness), including the tailoring of drug levels to achieve a predefined neural effect (e.g., burst suppression). While the accelerated development of microprocessor technologies has fostered an extraordinarily rapid growth in the use of intraoperative EEG, there is still no universal adoption of a monitoring technique(s) or of criteria for its neural end-point(s) by anesthesiologists, surgeons, neurologists, and neurophysiologists. One of the most important limitations to routine intraoperative use of EEG may be the lack of standardization of methods, alarm criteria, and recommendations related to its application. Lastly, refinements in technology and signal processing can be expected to advance the usefulness of the intraoperative EEG for both anesthetic and surgical management of patients. This paper is the position statement of the American Society of Neurophysiological Monitoring. It is the practice guidelines for the intraoperative use of raw (analog and digital) and quantitative EEG. The following recommendations are based on trends in the current scientific and clinical literature and meetings, guidelines published by other organizations, expert opinion, and public review by the members of the American Society of Neurophysiological Monitoring. This document may not include all possible methodologies and interpretative criteria, nor do the authors and their sponsor intentionally exclude any new alternatives. The use of the techniques reviewed in these guidelines may reduce perioperative neurological morbidity and mortality. This position paper summarizes commonly used protocols for recording and interpreting the intraoperative use of EEG. Furthermore, the American Society of Neurophysiological Monitoring recognizes this as primarily an educational service.

Ring and peg electrodes for minimally-Invasive and long-term sub-scalp EEG recordings.

PubMed

Benovitski, Y B; Lai, A; McGowan, C C; Burns, O; Maxim, V; Nayagam, D A X; Millard, R; Rathbone, G D; le Chevoir, M A; Williams, R A; Grayden, D B; May, C N; Murphy, M; D'Souza, W J; Cook, M J; Williams, C E

2017-09-01

Minimally-invasive approaches are needed for long-term reliable Electroencephalography (EEG) recordings to assist with epilepsy diagnosis, investigation and more naturalistic monitoring. This study compared three methods for long-term implantation of sub-scalp EEG electrodes. Three types of electrodes (disk, ring, and peg) were fabricated from biocompatible materials and implanted under the scalp in five ambulatory ewes for 3months. Disk electrodes were inserted into sub-pericranial pockets. Ring electrodes were tunneled under the scalp. Peg electrodes were inserted into the skull, close to the dura. EEG was continuously monitored wirelessly. High resolution CT imaging, histopathology, and impedance measurements were used to assess the status of the electrodes at the end of the study. EEG amplitude was larger in the peg compared with the disk and ring electrodes (p<0.05). Similarly, chewing artifacts were lower in the peg electrodes (p<0.05). Electrode impedance increased after long-term implantation particularly for those within the bone (p<0.01). Micro-CT scans indicated that all electrodes stayed within the sub-scalp layers. All pegs remained within the burr holes as implanted with no evidence of extrusion. Eight of 10 disks partially eroded into the bone by 1.0mm from the surface of the skull. The ring arrays remained within the sub-scalp layers close to implantation site. Histology revealed that the electrodes were encapsulated in a thin fibrous tissue adjacent to the pericranium. Overlying this was a loose connective layer and scalp. Erosion into the bone occurred under the rim of the sub-pericranial disk electrodes. The results indicate that the peg electrodes provided high quality EEG, mechanical stability, and lower chewing artifact. Whereas, ring electrode arrays tunneled under the scalp enable minimal surgical techniques to be used for implantation and removal. Copyright © 2017 Elsevier B.V. All rights reserved.

Electroencephalogram (EEG) (For Parents)

MedlinePlus

... Most EEGs are done to diagnose and monitor seizure disorders. EEGs also can identify causes of other problems, ... are very safe. If your child has a seizure disorder, your doctor might want to stimulate and record ...

Microsensors and wireless system for monitoring epilepsy

NASA Astrophysics Data System (ADS)

Whitchurch, Ashwin K.; Ashok, B. H.; Kumaar, Raman V.; Sarukesi, K.; Jose, K. A.; Varadan, Vijay K.

2003-07-01

Epilepsy is a form of brain disorder caused by abnormal discharges of neurons. The most common manifestations of epilepsy are seizures which could affect visual, aural and motor abilities of a person. Absence epilepsy is a form of epilepsy common mostly in children. The most common manifestations of absence epilepsy are staring and transient loss of responsiveness. Also, subtle motor activities may occur. Due to the subtle nature of these symptoms, episodes of absence epilepsy may often go unrecognized for long periods of time or be mistakenly attributed to attention deficit disorder or daydreaming. Spells of absence epilepsy may last about 10 seconds and occur hundreds of times each day. Patients have no recollections of the events occurred during those seizures and will resume normal activity without any postictal symptoms. The EEG during such episodes of Absence epilepsy shows intermittent activity of 3 Hz generalized spike and wave complexes. As EEG is the only way of detecting such symptoms, it is required to monitor the EEG of the patient for a long time, usually the whole day. This requires that the patient be connected to the EEG recorder all the time and thus remain only in the bed. So, effectively the EEG is being monitored only when the patient is stationary. The wireless monitoring system described in this paper aims at eliminating this constraint and enables the physician to monitor the EEG when the patient resumes his normal activities. This approach could even help the doctor identify possible triggers of absence epilepsy.

Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral Responses-An Application in Ischemic Stroke.

PubMed

Guhathakurta, Debarpan; Dutta, Anirban

2016-01-01

Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about -15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.

Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral Responses—An Application in Ischemic Stroke

PubMed Central

Guhathakurta, Debarpan; Dutta, Anirban

2016-01-01

Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about −15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization. PMID:27378836

Forecasting seizures in dogs with naturally occurring epilepsy.

PubMed

Howbert, J Jeffry; Patterson, Edward E; Stead, S Matt; Brinkmann, Ben; Vasoli, Vincent; Crepeau, Daniel; Vite, Charles H; Sturges, Beverly; Ruedebusch, Vanessa; Mavoori, Jaideep; Leyde, Kent; Sheffield, W Douglas; Litt, Brian; Worrell, Gregory A

2014-01-01

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low-gamma (30-70 Hz), and high-gamma (70-180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.

Forecasting Seizures in Dogs with Naturally Occurring Epilepsy

PubMed Central

Stead, S. Matt; Brinkmann, Ben; Vasoli, Vincent; Crepeau, Daniel; Vite, Charles H.; Sturges, Beverly; Ruedebusch, Vanessa; Mavoori, Jaideep; Leyde, Kent; Sheffield, W. Douglas; Litt, Brian; Worrell, Gregory A.

2014-01-01

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low-gamma (30–70 Hz), and high-gamma (70–180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring. PMID:24416133

Wireless sleep monitoring headband to identify sleep and track fatigue

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Oh, Sechang; Varadan, Vijay K.

2014-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Commonly, the rudimentary bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper proposes the design of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the dry gold wire nano-sensors fabricated on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through WCDMA/GSM communication. This module is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the experienced fatigue level. The novel approach of using a wireless, real time, dry sensor on a flexible substrate reduces the obtrusiveness, and techniques adopted in the electronics and software facilitates and substantial increase in efficiency, accuracy and precision.

Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

NASA Astrophysics Data System (ADS)

Zapata, J. F.; Garzón, J.

2011-01-01

This study provides a new method for the detection of interhemispheric asymmetries in patients with continuous video-electroencephalography (EEG) monitoring at Intensive Care Unit (ICU), using wavelet energy. We obtained the registration of EEG signals in 42 patients with different pathologies, and then we proceeded to perform signal processing using the Matlab program, we compared the abnormalities recorded in the report by the neurophysiologist, the images of each patient and the result of signals analysis with the Discrete Wavelet Transform (DWT). Conclusions: there exists correspondence between the abnormalities found in the processing of the signal with the clinical reports of findings in patients; according to previous conclusion, the methodology used can be a useful tool for diagnosis and early quantitative detection of interhemispheric asymmetries.

Sustained Attention in Real Classroom Settings: An EEG Study.

PubMed

Ko, Li-Wei; Komarov, Oleksii; Hairston, W David; Jung, Tzyy-Ping; Lin, Chin-Teng

2017-01-01

Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra.

Sustained Attention in Real Classroom Settings: An EEG Study

PubMed Central

Ko, Li-Wei; Komarov, Oleksii; Hairston, W. David; Jung, Tzyy-Ping; Lin, Chin-Teng

2017-01-01

Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra. PMID:28824396

Incidence and localizing value of vertigo and dizziness in patients with epilepsy: Video-EEG monitoring study.

PubMed

Kim, Dong Wook; Sunwoo, Jun-Sang; Lee, Sang Kun

2016-10-01

Vertigo and dizziness are common neurological complaints that have long been associated with epilepsy. However, studies of patients with epileptic vertigo or dizziness with concurrent EEG monitoring are scarce. We performed the present study to investigate the incidence and localizing value of vertigo and dizziness in patients with epilepsy who had confirmation of EEG changes via video-EEG monitoring. Data of aura and clinical seizure episodes of 831 consecutive patients who underwent video-EEG monitoring were analyzed retrospectively. Out of 831 patients, 40 patients (4.8%) experienced vertigo or dizziness as aura (mean age, 32.8±11.8years), all of whom had partial seizures. Eight had mesial temporal, 20 had lateral temporal, four had frontal, one had parietal, and seven had occipital lobe onset seizures. An intracranial EEG with cortical stimulation study was performed in seven patients, and the area of stimulation-induced vertigo or dizziness coincided with the ictal onset area in only one patient. Our study showed that vertigo or dizziness is a common aura in patients with epilepsy, and that the temporal lobe is the most frequent ictal onset area in these patients. However, it can be suggested that the symptomatogenic area in patients with epileptic vertigo and dizziness may not coincide with the ictal onset area. Copyright © 2016 Elsevier B.V. All rights reserved.

Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system

PubMed Central

Min, Jianliang; Wang, Ping

2017-01-01

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) modeling by four classifiers. Second, we captured four significant channel regions according to weight-based electrodes via a simplified channel selection method. Finally, the evaluation model for detecting driver fatigue was established with four classifiers based on the EEG data from four channel regions. Twelve healthy subjects performed continuous simulated driving for 1–2 hours with EEG monitoring on a static simulator. The leave-one-out cross-validation approach obtained an accuracy of 98.3%, a sensitivity of 98.3% and a specificity of 98.2%. The experimental results verified the effectiveness of the proposed method, indicating that the multiple entropy fusion features are significant factors for inferring the fatigue state of a driver. PMID:29220351

Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction

NASA Technical Reports Server (NTRS)

Smith, M. E.; Gevins, A.; Brown, H.; Karnik, A.; Du, R.

2001-01-01

Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.

Monitoring in traumatic brain injury.

PubMed

Matz, P G; Pitts, L

1997-01-01

In the past several years, improvements in technology have advanced the monitoring capabilities for patients with TBI. The primary goal of monitoring the patient with TBI is to prevent secondary insults to the brain, primarily cerebral ischemia. Cerebral ischemia may occur early and without clinical correlation and portends a poor outcome. Measurement of ICP is the cornerstone of monitoring in the patient with TBI. Monitoring of ICP provides a measurement of CPP and a rough estimation of CBF. However, with alterations in pressure autoregulation, measurement of CPP does not always allow for determination of CBF. To circumvent this problem, direct measurements of CBF can be performed using clearance techniques (133Xe, N2O, Xe-CT) or invasive monitoring techniques (LDF, TDF, NIRS). Although direct and quantitative, clearance techniques do not allow for continuous monitoring. Invasive CBF monitoring techniques are new, and artifactual results can be problematic. The techniques of jugular venous saturation monitoring and TCD are well established and are powerful adjuncts to ICP monitoring. They allow the clinician to monitor cerebral oxygen extraction and blood flow velocity, respectively, for any given CPP. Use of TCD may predict posttraumatic vasospasm before clinical sequelae. Jugular venous saturation monitoring may detect clinically occult episodes of cerebral ischemia and increased oxygen extraction. Jugular venous saturation monitoring optimizes the use of hyperventilation in the treatment of intracranial hypertension. Although PET and SPECT scanning allow direct measurement of CMRO2, these techniques have limited application currently. Similarly, microdialysis is in its infancy but has demonstrated great promise for metabolic monitoring. EEG and SEP are excellent adjuncts to the monitoring arsenal and provide immediate information on current brain function. With improvements in electronic telemetry, functional monitoring by EEG or SEP may become an important part of routine monitoring in TBI.

Practical use of the raw electroencephalogram waveform during general anesthesia: the art and science.

PubMed

Bennett, Cambell; Voss, Logan J; Barnard, John P M; Sleigh, James W

2009-08-01

Quantitative electroencephalogram (qEEG) monitors are often used to estimate depth of anesthesia and intraoperative recall during general anesthesia. As with any monitor, the processed numerical output is often misleading and has to be interpreted within a clinical context. For the safe clinical use of these monitors, a clear mental picture of the expected raw electroencephalogram (EEG) patterns, as well as a knowledge of the common EEG artifacts, is absolutely necessary. This has provided the motivation to write this tutorial. We describe, and give examples of, the typical EEG features of adequate general anesthesia, effects of noxious stimulation, and adjunctive drugs. Artifacts are commonly encountered and may be classified as arising from outside the head, from the head but outside the brain (commonly frontal electromyogram), or from within the brain (atypical or pathologic). We include real examples of clinical problem-solving processes. In particular, it is important to realize that an artifactually high qEEG index is relatively common and may result in dangerous anesthetic drug overdose. The anesthesiologist must be certain that the qEEG number is consistent with the apparent state of the patient, the doses of various anesthetic drugs, and the degree of surgical stimulation, and that the qEEG number is consistent with the appearance of the raw EEG signal. Any discrepancy must be a stimulus for the immediate critical examination of the patient's state using all the available information rather than reactive therapy to "treat" a number.

A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness.

PubMed

Kim, Kyungsoo; Punte, Andrea Kleine; Mertens, Griet; Van de Heyning, Paul; Park, Kyung-Joon; Choi, Hongsoo; Choi, Ji-Woong; Song, Jae-Jin

2015-11-30

Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed CI artifacts. The proposed method selectively removes CI artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. CI artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with CIs. Copyright © 2015 Elsevier B.V. All rights reserved.

Removal of eye blink artifacts in wireless EEG sensor networks using reduced-bandwidth canonical correlation analysis.

PubMed

Somers, Ben; Bertrand, Alexander

2016-12-01

Chronic, 24/7 EEG monitoring requires the use of highly miniaturized EEG modules, which only measure a few EEG channels over a small area. For improved spatial coverage, a wireless EEG sensor network (WESN) can be deployed, consisting of multiple EEG modules, which interact through short-distance wireless communication. In this paper, we aim to remove eye blink artifacts in each EEG channel of a WESN by optimally exploiting the correlation between EEG signals from different modules, under stringent communication bandwidth constraints. We apply a distributed canonical correlation analysis (CCA-)based algorithm, in which each module only transmits an optimal linear combination of its local EEG channels to the other modules. The method is validated on both synthetic and real EEG data sets, with emulated wireless transmissions. While strongly reducing the amount of data that is shared between nodes, we demonstrate that the algorithm achieves the same eye blink artifact removal performance as the equivalent centralized CCA algorithm, which is at least as good as other state-of-the-art multi-channel algorithms that require a transmission of all channels. Due to their potential for extreme miniaturization, WESNs are viewed as an enabling technology for chronic EEG monitoring. However, multi-channel analysis is hampered in WESNs due to the high energy cost for wireless communication. This paper shows that multi-channel eye blink artifact removal is possible with a significantly reduced wireless communication between EEG modules.

Removal of eye blink artifacts in wireless EEG sensor networks using reduced-bandwidth canonical correlation analysis

NASA Astrophysics Data System (ADS)

Somers, Ben; Bertrand, Alexander

2016-12-01

Objective. Chronic, 24/7 EEG monitoring requires the use of highly miniaturized EEG modules, which only measure a few EEG channels over a small area. For improved spatial coverage, a wireless EEG sensor network (WESN) can be deployed, consisting of multiple EEG modules, which interact through short-distance wireless communication. In this paper, we aim to remove eye blink artifacts in each EEG channel of a WESN by optimally exploiting the correlation between EEG signals from different modules, under stringent communication bandwidth constraints. Approach. We apply a distributed canonical correlation analysis (CCA-)based algorithm, in which each module only transmits an optimal linear combination of its local EEG channels to the other modules. The method is validated on both synthetic and real EEG data sets, with emulated wireless transmissions. Main results. While strongly reducing the amount of data that is shared between nodes, we demonstrate that the algorithm achieves the same eye blink artifact removal performance as the equivalent centralized CCA algorithm, which is at least as good as other state-of-the-art multi-channel algorithms that require a transmission of all channels. Significance. Due to their potential for extreme miniaturization, WESNs are viewed as an enabling technology for chronic EEG monitoring. However, multi-channel analysis is hampered in WESNs due to the high energy cost for wireless communication. This paper shows that multi-channel eye blink artifact removal is possible with a significantly reduced wireless communication between EEG modules.

Electroencephalographic monitoring of complex mental tasks

NASA Technical Reports Server (NTRS)

Guisado, Raul; Montgomery, Richard; Montgomery, Leslie; Hickey, Chris

1992-01-01

Outlined here is the development of neurophysiological procedures to monitor operators during the performance of cognitive tasks. Our approach included the use of electroencepalographic (EEG) and rheoencephalographic (REG) techniques to determine changes in cortical function associated with cognition in the operator's state. A two channel tetrapolar REG, a single channel forearm impedance plethysmograph, a Lead I electrocardiogram (ECG) and a 21 channel EEG were used to measure subject responses to various visual-motor cognitive tasks. Testing, analytical, and display procedures for EEG and REG monitoring were developed that extend the state of the art and provide a valuable tool for the study of cerebral circulatory and neural activity during cognition.

Far-red to near infrared emission and scattering spectroscopy for biomedical applications

NASA Astrophysics Data System (ADS)

Zhang, Gang

2001-06-01

The thesis investigates the far-red and near infrared (NIR) spectral region from biomedical tissue samples for monitoring the state of tissues. The NIR emission wing intensity is weak in comparison to the emission in the visible spectral region. The wing emission from biomedical samples has revealed meaningful information about the state of the tissues. A model is presented to explain the shape of the spectral wing based on a continuum of energy levels. The wing can be used to classify different kinds of tissues; especially it can be used to differentiate cancer part from normal human breast tissues. The research work of the far-red emission from thermal damaged tissue samples shows that the emission intensity in this spectral region is proportional to the extent of the thermal damage of the tissue. Near infrared spectral absorption method is used to investigate blood hemodynamics (perfusion and oxygenation) in brain during sleep-wake transition. The result of the research demonstrates that the continuous wave (CW) type near infrared spectroscopy (NIRS) device can be used to investigate brain blood perfusion and oxygenation with a similar precision with frequency domain (FD) type device. The human subject sleep and wake transition, has been monitored by CW type NIRS instrument with traditional electroencephalograph (EEG) method. Parallel change in oxy-Hb and deoxy-Hb is a discrete event that occurs in the transition from both sleep to wakefulness and wakefulness to sleep. These hemodynamic switches are generally about few seconds delayed from the human decided transition point between sleep and wake on the polygraph EEG recording paper. The combination of NIRS and EEG methods monitor the brain activity, gives more information about the brain activity. The sleep apnea investigation was associated with recurrent apneas, insufficient nasal continuous positive airway pressure (CPAP) and the different response of the peripheral and central compartments to breathing events. The different results with finger pulse oximetry and NIRS suggest that optical monitoring of the brain may have advantages that may help clarify the morbidity of obstructive sleep apnea (OSA) Syndrome.

Teaching neuroimages: infant with glutaric aciduria type 1 presenting with infantile spasms and hypsarrhythmia.

PubMed

Young-Lin, Nichole; Shalev, Sarah; Glenn, Orit A; Gardner, Marisa; Lee, Chung; Wynshaw-Boris, Anthony; Gelfand, Amy A

2013-12-10

A 7-month-old boy with glutaric aciduria type 1 (GA1) presented with 1 week of clustered flexor spasms. Examination revealed mild axial hypotonia without encephalopathy. Video-EEG monitoring revealed hypsarrhythmia and infantile spasms (figure, A). MRI showed acute basal ganglia injury (figure, B). After 3 weeks of prednisolone treatment, 5-month follow-up showed continued resolution of hypsarrhythmia and spasms.

Rheoencephalographic and electroencephalographic measures of cognitive workload: analytical procedures.

PubMed

Montgomery, L D; Montgomery, R W; Guisado, R

1995-05-01

This investigation demonstrates the feasibility of mental workload assessment by rheoencephalographic (REG) and multichannel electroencephalographic (EEG) monitoring. During the performance of this research, unique testing, analytical and display procedures were developed for REG and EEG monitoring that extend the current state of the art and provide valuable tools for the study of cerebral circulatory and neural activity during cognition. REG records are analyzed to provide indices of the right and left hemisphere hemodynamic changes that take place during each test sequence. The EEG data are modeled using regression techniques and mathematically transformed to provide energy-density distributions of the scalp electrostatic field. These procedures permit concurrent REG/EEG cognitive testing not possible with current techniques. The introduction of a system for recording and analysis of cognitive REG/EEG test sequences facilitates the study of learning and memory disorders, dementia and other encephalopathies.

Rheoencephalographic and electroencephalographic measures of cognitive workload: analytical procedures

NASA Technical Reports Server (NTRS)

Montgomery, L. D.; Montgomery, R. W.; Guisado, R.

1995-01-01

This investigation demonstrates the feasibility of mental workload assessment by rheoencephalographic (REG) and multichannel electroencephalographic (EEG) monitoring. During the performance of this research, unique testing, analytical and display procedures were developed for REG and EEG monitoring that extend the current state of the art and provide valuable tools for the study of cerebral circulatory and neural activity during cognition. REG records are analyzed to provide indices of the right and left hemisphere hemodynamic changes that take place during each test sequence. The EEG data are modeled using regression techniques and mathematically transformed to provide energy-density distributions of the scalp electrostatic field. These procedures permit concurrent REG/EEG cognitive testing not possible with current techniques. The introduction of a system for recording and analysis of cognitive REG/EEG test sequences facilitates the study of learning and memory disorders, dementia and other encephalopathies.

NIRS-EEG joint imaging during transcranial direct current stimulation: Online parameter estimation with an autoregressive model.

PubMed

Sood, Mehak; Besson, Pierre; Muthalib, Makii; Jindal, Utkarsh; Perrey, Stephane; Dutta, Anirban; Hayashibe, Mitsuhiro

2016-12-01

Transcranial direct current stimulation (tDCS) has been shown to perturb both cortical neural activity and hemodynamics during (online) and after the stimulation, however mechanisms of these tDCS-induced online and after-effects are not known. Here, online resting-state spontaneous brain activation may be relevant to monitor tDCS neuromodulatory effects that can be measured using electroencephalography (EEG) in conjunction with near-infrared spectroscopy (NIRS). We present a Kalman Filter based online parameter estimation of an autoregressive (ARX) model to track the transient coupling relation between the changes in EEG power spectrum and NIRS signals during anodal tDCS (2mA, 10min) using a 4×1 ring high-definition montage. Our online ARX parameter estimation technique using the cross-correlation between log (base-10) transformed EEG band-power (0.5-11.25Hz) and NIRS oxy-hemoglobin signal in the low frequency (≤0.1Hz) range was shown in 5 healthy subjects to be sensitive to detect transient EEG-NIRS coupling changes in resting-state spontaneous brain activation during anodal tDCS. Conventional sliding window cross-correlation calculations suffer a fundamental problem in computing the phase relationship as the signal in the window is considered time-invariant and the choice of the window length and step size are subjective. Here, Kalman Filter based method allowed online ARX parameter estimation using time-varying signals that could capture transients in the coupling relationship between EEG and NIRS signals. Our new online ARX model based tracking method allows continuous assessment of the transient coupling between the electrophysiological (EEG) and the hemodynamic (NIRS) signals representing resting-state spontaneous brain activation during anodal tDCS. Published by Elsevier B.V.

Monitoring driver fatigue using a single-channel electroencephalographic device: A validation study by gaze-based, driving performance, and subjective data.

PubMed

Morales, José M; Díaz-Piedra, Carolina; Rieiro, Héctor; Roca-González, Joaquín; Romero, Samuel; Catena, Andrés; Fuentes, Luis J; Di Stasi, Leandro L

2017-12-01

Driver fatigue can impair performance as much as alcohol does. It is the most important road safety concern, causing thousands of accidents and fatalities every year. Thanks to technological developments, wearable, single-channel EEG devices are now getting considerable attention as fatigue monitors, as they could help drivers to assess their own levels of fatigue and, therefore, prevent the deterioration of performance. However, the few studies that have used single-channel EEG devices to investigate the physiological effects of driver fatigue have had inconsistent results, and the question of whether we can monitor driver fatigue reliably with these EEG devices remains open. Here, we assessed the validity of a single-channel EEG device (TGAM-based chip) to monitor changes in mental state (from alertness to fatigue). Fifteen drivers performed a 2-h simulated driving task while we recorded, simultaneously, their prefrontal brain activity and saccadic velocity. We used saccadic velocity as the reference index of fatigue. We also collected subjective ratings of alertness and fatigue, as well as driving performance. We found that the power spectra of the delta EEG band showed an inverted U-shaped quadratic trend (EEG power spectra increased for the first hour and half, and decreased during the last thirty minutes), while the power spectra of the beta band linearly increased as the driving session progressed. Coherently, saccadic velocity linearly decreased and speeding time increased, suggesting a clear effect of fatigue. Subjective data corroborated these conclusions. Overall, our results suggest that the TGAM-based chip EEG device is able to detect changes in mental state while performing a complex and dynamic everyday task as driving. Copyright © 2017 Elsevier Ltd. All rights reserved.

Changes in the electroencephalogram during anaesthesia and their physiological basis.

PubMed

Hagihira, S

2015-07-01

The use of EEG monitors to assess the level of hypnosis during anaesthesia has become widespread. Anaesthetists, however, do not usually observe the raw EEG data: they generally pay attention only to the Bispectral Index (BIS™) and other indices calculated by EEG monitors. This abstracted information only partially characterizes EEG features. To properly appreciate the availability and reliability of EEG-derived indices, it is necessary to understand how raw EEG changes during anaesthesia. With hemi-frontal lead EEGs obtained under volatile anaesthesia or propofol anaesthesia, the dominant EEG frequency decreases and the amplitude increases with increasing concentrations of anaesthetic. Looking more closely, the EEG changes are more complicated. At surgical concentrations of anaesthesia, spindle waves (alpha range) become dominant. At deeper levels, this activity decreases, and theta and delta waves predominate. At even deeper levels, EEG waveform changes into a burst and suppression pattern, and finally becomes flat. EEG waveforms vary in the presence of noxious stimuli (surgical skin incision), which is not always reflected in BIS™, or other processed EEG indices. Spindle waves are adequately sensitive, however, to noxious stimuli: under surgical anaesthesia they disappear when noxious stimuli are applied, and reappear when adequate analgesia is obtained. To prevent awareness during anaesthesia, I speculate that the most effective strategy is to administer anaesthetic agents in such a way as to maintain anaesthesia at a level where spindle waves predominate. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

myBrain: a novel EEG embedded system for epilepsy monitoring.

PubMed

Pinho, Francisco; Cerqueira, João; Correia, José; Sousa, Nuno; Dias, Nuno

2017-10-01

The World Health Organisation has pointed that a successful health care delivery, requires effective medical devices as tools for prevention, diagnosis, treatment and rehabilitation. Several studies have concluded that longer monitoring periods and outpatient settings might increase diagnosis accuracy and success rate of treatment selection. The long-term monitoring of epileptic patients through electroencephalography (EEG) has been considered a powerful tool to improve the diagnosis, disease classification, and treatment of patients with such condition. This work presents the development of a wireless and wearable EEG acquisition platform suitable for both long-term and short-term monitoring in inpatient and outpatient settings. The developed platform features 32 passive dry electrodes, analogue-to-digital signal conversion with 24-bit resolution and a variable sampling frequency from 250 Hz to 1000 Hz per channel, embedded in a stand-alone module. A computer-on-module embedded system runs a Linux ® operating system that rules the interface between two software frameworks, which interact to satisfy the real-time constraints of signal acquisition as well as parallel recording, processing and wireless data transmission. A textile structure was developed to accommodate all components. Platform performance was evaluated in terms of hardware, software and signal quality. The electrodes were characterised through electrochemical impedance spectroscopy and the operating system performance running an epileptic discrimination algorithm was evaluated. Signal quality was thoroughly assessed in two different approaches: playback of EEG reference signals and benchmarking with a clinical-grade EEG system in alpha-wave replacement and steady-state visual evoked potential paradigms. The proposed platform seems to efficiently monitor epileptic patients in both inpatient and outpatient settings and paves the way to new ambulatory clinical regimens as well as non-clinical EEG applications.

A case of schizencephaly has a normal surface EEG but abnormal intracranial EEG: epilepsia partialis continua or dystonia?

PubMed

Lv, Yudan; Ma, Dihui; Meng, Hongmei; Zan, Wang; Li, Cui

2013-10-01

Schizencephaly is a congenital malformation of the cerebral hemispheres, with communication between the lateral ventricle and the subarachnoid space. Marinelli reported that schizencephaly may be associated with continuous involuntary hand movements, such as dystonia or epilepsia partialis continua (EPC). We describe a young Chinese patient with continuous involuntary movements of the contralateral hand affected by schizencephaly. He has a normal scalp electroencephalogram (EEG) but abnormal intracranial EEG, with synchronized periodic lateralized epileptiform discharges. The results obtained from these EEG investigations and the clinical features of the involuntary movements are in favor of a diagnosis of secondary EPC.

Using EEG To Detect and Monitor Mental Fatigue

NASA Technical Reports Server (NTRS)

Montgomery, Leslie; Luna, Bernadette; Trejo, Leonard J.; Montgomery, Richard

2001-01-01

This project aims to develop EEG-based methods for detecting and monitoring mental fatigue. Mental fatigue poses a serious risk, even when performance is not apparently degraded. When such fatigue is associated with sustained performance of a single type of cognitive task it may be related to the metabolic energy required for sustained activation of cortical areas specialized for that task. The objective of this study was to adapt EEG to monitor cortical energy over a long period of performance of a cognitive task. Multielectrode event related potentials (ERPs) were collected every 15 minutes in nine subjects who performed a mental arithmetic task (algebraic sum of four randomly generated negative or positive digits). A new problem was presented on a computer screen 0.5 seconds after each response; some subjects endured for as long as three hours. ERPs were transformed to a quantitative measure of scalp electrical field energy. The average energy level at electrode P3 (near the left angular gyrus), 100-300 msec latency, was compared over the series of ERPs. For most subjects, scalp energy density at P3 gradually fell over the period of task performance and dramatically increased just before the subject was unable to continue the task. This neural response can be simulated for individual subjects using, a differential equation model in which it is assumed that the mental arithmetic task requires a commitment of metabolic energy that would otherwise be used for brain activities that are temporarily neglected. Their cumulative neglect eventually requires a reallocation of energy away from the mental arithmetic task.

Real-time monitoring of drowsiness through wireless nanosensor systems

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2016-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Generally, the bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper reviews the design aspects of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the textile based nanosensors mounted on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through ZigBee communication. This system is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the fatigue level. This approach of using a wireless, real time, dry sensor on a flexible substrate mitigates obtrusiveness that is expected from a wearable system. We have previously presented the results of the aforementioned wearable systems. This paper aims to extend our work conceptually through a review of engineering and medical techniques involved in wearable systems to detect drowsiness.

A brain-machine interface for control of medically-induced coma.

PubMed

Shanechi, Maryam M; Chemali, Jessica J; Liberman, Max; Solt, Ken; Brown, Emery N

2013-10-01

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.

PubMed

Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L

2010-02-15

EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.

Women need more propofol than men during EEG-monitored total intravenous anaesthesia / Frauen benötigen mehr Propofol als Männer während EEG-überwachter total-intravenöser Anästhesie.

PubMed

Haensch, Klaus; Schultz, Arthur; Krauss, Terence; Grouven, Ulrich; Schultz, Barbara

2009-04-01

Gender-related differences in the pharmacology of drugs used in anaesthesiology have been reported by different authors. The aim of this study was to compare propofol dosages in a greater number of male and female patients who had received electroencephalogram (EEG) monitoring to maintain a defined depth of anaesthesia. Data from an EEG-controlled study were analysed with regard to gender differences in the consumption of the short-acting hypnotic propofol during maintenance of total intravenous anaesthesia and with regard to recovery times. The 656 patients (239 male, 417 female) were 15 to 97 years old, underwent different surgical procedures, and received propofol in combination with remifentanil, a short-acting opioid. During the steady-state of anaesthesia the EEG stage D(2)/E(0), which corresponds to deep hypnosis, was the target level (EEG monitor: Narcotrend). Propofol dosages were calculated as mg/kg body weight/h and as mg/kg lean body mass/h. Significantly higher propofol dosages were observed in female patients compared to male patients, especially with lean body mass as a reference parameter. The dosages were characterised by a high interindividual variability. The time from stop of propofol until extubation was significantly shorter in women than in men. The propofol dosage for maintenance of anaesthesia at the EEG level D(2)/E(0) decreased with increasing age.

Computer EEG-monitoring of laserotherapy effects in patients with asteno-depressive syndrome.

PubMed

Omelchenko, V P; Baranchook, I S; Dmitriev, M N

1999-01-01

Nowadays the low-intensive laserotherapy is shown to be an effective and non-hazardous method of asteno-depressive syndrome treatment. The differences of EEG-reactions to laser influences have been revealed in patients of different age groups. And the close negative correlation between the therapy effect, on the one hand, and the patient's age and the disease duration, on the other hand, has been shown. No significant changes of the patient's state or integrative EEG-indices have been evoked by a placebo application. The results showed the advantages of the low-intensive laserotherapy in asteno-depressive syndrome treatment and confirmed the significance of computer EEG-monitoring for prediction, control and correction of the state of the patient.

Neural network classification of clinical neurophysiological data for acute care monitoring

NASA Technical Reports Server (NTRS)

Sgro, Joseph

1994-01-01

The purpose of neurophysiological monitoring of the 'acute care' patient is to allow the accurate recognition of changing or deteriorating neurological function as close to the moment of occurrence as possible, thus permitting immediate intervention. Results confirm that: (1) neural networks are able to accurately identify electroencephalogram (EEG) patterns and evoked potential (EP) wave components, and measuring EP waveform latencies and amplitudes; (2) neural networks are able to accurately detect EP and EEG recordings that have been contaminated by noise; (3) the best performance was obtained consistently with the back propagation network for EP and the HONN for EEG's; (4) neural network performed consistently better than other methods evaluated; and (5) neural network EEG and EP analyses are readily performed on multichannel data.

A Wearable EEG-HEG-HRV Multimodal System With Simultaneous Monitoring of tES for Mental Health Management.

PubMed

Ha, Unsoo; Lee, Yongsu; Kim, Hyunki; Roh, Taehwan; Bae, Joonsung; Kim, Changhyeon; Yoo, Hoi-Jun

2015-12-01

A multimodal mental management system in the shape of the wearable headband and earplugs is proposed to monitor electroencephalography (EEG), hemoencephalography (HEG) and heart rate variability (HRV) for accurate mental health monitoring. It enables simultaneous transcranial electrical stimulation (tES) together with real-time monitoring. The total weight of the proposed system is less than 200 g. The multi-loop low-noise amplifier (MLLNA) achieves over 130 dB CMRR for EEG sensing and the capacitive correlated-double sampling transimpedance amplifier (CCTIA) has low-noise characteristics for HEG and HRV sensing. Measured three-physiology domains such as neural, vascular and autonomic domain signals are combined with canonical correlation analysis (CCA) and temporal kernel canonical correlation analysis (tkCCA) algorithm to find the neural-vascular-autonomic coupling. It supports highly accurate classification with the 19% maximum improvement with multimodal monitoring. For the multi-channel stimulation functionality, after-effects maximization monitoring and sympathetic nerve disorder monitoring, the stimulator is designed as reconfigurable. The 3.37 × 2.25 mm(2) chip has 2-channel EEG sensor front-end, 2-channel NIRS sensor front-end, NIRS current driver to drive dual-wavelength VCSEL and 6-b DAC current source for tES mode. It dissipates 24 mW with 2 mA stimulation current and 5 mA NIRS driver current.

Non-invasive, home-based electroencephalography hypoglycaemia warning system for personal monitoring using skin surface electrodes: a single-case feasibility study.

PubMed

Clewett, Christopher J; Langley, Phillip; Bateson, Anthony D; Asghar, Aziz; Wilkinson, Antony J

2016-03-01

Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study. A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected. All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia. The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants.

Analysis and asynchronous detection of gradually unfolding errors during monitoring tasks

NASA Astrophysics Data System (ADS)

Omedes, Jason; Iturrate, Iñaki; Minguez, Javier; Montesano, Luis

2015-10-01

Human studies on cognitive control processes rely on tasks involving sudden-onset stimuli, which allow the analysis of these neural imprints to be time-locked and relative to the stimuli onset. Human perceptual decisions, however, comprise continuous processes where evidence accumulates until reaching a boundary. Surpassing the boundary leads to a decision where measured brain responses are associated to an internal, unknown onset. The lack of this onset for gradual stimuli hinders both the analyses of brain activity and the training of detectors. This paper studies electroencephalographic (EEG)-measurable signatures of human processing for sudden and gradual cognitive processes represented as a trajectory mismatch under a monitoring task. Time-locked potentials and brain-source analysis of the EEG of sudden mismatches revealed the typical components of event-related potentials and the involvement of brain structures related to cognitive control processing. For gradual mismatch events, time-locked analyses did not show any discernible EEG scalp pattern, despite related brain areas being, to a lesser extent, activated. However, and thanks to the use of non-linear pattern recognition algorithms, it is possible to train an asynchronous detector on sudden events and use it to detect gradual mismatches, as well as obtaining an estimate of their unknown onset. Post-hoc time-locked scalp and brain-source analyses revealed that the EEG patterns of detected gradual mismatches originated in brain areas related to cognitive control processing. This indicates that gradual events induce latency in the evaluation process but that similar brain mechanisms are present in sudden and gradual mismatch events. Furthermore, the proposed asynchronous detection model widens the scope of applications of brain-machine interfaces to other gradual processes.

Neural activity based biofeedback therapy for Autism spectrum disorder through wearable wireless textile EEG monitoring system

NASA Astrophysics Data System (ADS)

Sahi, Ahna; Rai, Pratyush; Oh, Sechang; Ramasamy, Mouli; Harbaugh, Robert E.; Varadan, Vijay K.

2014-04-01

Mu waves, also known as mu rhythms, comb or wicket rhythms are synchronized patterns of electrical activity involving large numbers of neurons, in the part of the brain that controls voluntary functions. Controlling, manipulating, or gaining greater awareness of these functions can be done through the process of Biofeedback. Biofeedback is a process that enables an individual to learn how to change voluntary movements for purposes of improving health and performance through the means of instruments such as EEG which rapidly and accurately 'feedback' information to the user. Biofeedback is used for therapeutic purpose for Autism Spectrum Disorder (ASD) by focusing on Mu waves for detecting anomalies in brain wave patterns of mirror neurons. Conventional EEG measurement systems use gel based gold cup electrodes, attached to the scalp with adhesive. It is obtrusive and wires sticking out of the electrodes to signal acquisition system make them impractical for use in sensitive subjects like infants and children with ASD. To remedy this, sensors can be incorporated with skull cap and baseball cap that are commonly used for infants and children. Feasibility of Textile based Sensor system has been investigated here. Textile based multi-electrode EEG, EOG and EMG monitoring system with embedded electronics for data acquisition and wireless transmission has been seamlessly integrated into fabric of these items for continuous detection of Mu waves. Textile electrodes were placed on positions C3, CZ, C4 according to 10-20 international system and their capability to detect Mu waves was tested. The system is ergonomic and can potentially be used for early diagnosis in infants and planning therapy for ASD patients.

Non-convulsive seizures and electroencephalography findings as predictors of clinical outcomes at a tertiary intensive care unit in Saudi Arabia.

PubMed

Al-Said, Youssef A; Baeesa, Saleh S; Shivji, Zaitoon; Kayyali, Husam; Alqadi, Khalid; Kadi, Ghada; Cupler, Edward J; Abuzinadah, Ahmad R

2018-06-05

Electroencephalography (EEG) in the intensive care unit (ICU) is often done to detect non-convulsive seizures (NCS). The outcome of ICU patients with NCS strongly depends on the underlying etiology. The implication of NCS and other EEG findings on clinical outcome independent from their etiology is not well understood and our aim to investigate it. We retrospectively identified all adult patients in the ICU who underwent EEG monitoring between January 2008 and December 2011. The main goals were to define the rate of NCS or non-convulsive status epilepticus (NCSE) occurrence in our center among patients who underwent EEG monitoring and to examine if NCS/NCSE are associated with poor outcome [defined as death or dependence] with and without adjustment for underlying etiology. The rate of poor outcome among different EEG categories were also investigated. During the study period, 177 patients underwent EEG monitoring in our ICU. The overall outcome was poor in 62.7% of those undergoing EEG. The rate of occurrence of NCS/NCSE was 8.5% and was associated with poor outcome in 86.7% with an odds ratio (OR) of 5.1 (95% confidence interval [CI] 1.09-23.8). This association was maintained after adjusting for underlying etiologies with OR 5.6 (95% CI 1.05-29.6). The rate of poor outcome was high in the presence of periodic discharges and sharp and slow waves of 75% and 61.5%, respectively. Our cohort of ICU patients undergoing EEGs had a poor outcome. Those who developed NCS/NCSE experienced an even worse outcome regardless of the underlying etiology. Copyright © 2018 Elsevier B.V. All rights reserved.

EFFECTIVE INDICES FOR MONITORING MENTAL WORKLOAD WHILE PERFORMING MULTIPLE TASKS.

PubMed

Hsu, Bin-Wei; Wang, Mao-Jiun J; Chen, Chi-Yuan; Chen, Fang

2015-08-01

This study identified several physiological indices that can accurately monitor mental workload while participants performed multiple tasks with the strategy of maintaining stable performance and maximizing accuracy. Thirty male participants completed three 10-min. simulated multitasks: MATB (Multi-Attribute Task Battery) with three workload levels. Twenty-five commonly used mental workload measures were collected, including heart rate, 12 HRV (heart rate variability), 10 EEG (electroencephalography) indices (α, β, θ, α/θ, θ/β from O1-O2 and F4-C4), and two subjective measures. Analyses of index sensitivity showed that two EEG indices, θ and α/θ (F4-C4), one time-domain HRV-SDNN (standard deviation of inter-beat intervals), and four frequency-domain HRV: VLF (very low frequency), LF (low frequency), %HF (percentage of high frequency), and LF/HF were sensitive to differentiate high workload. EEG α/θ (F4-C4) and LF/HF were most effective for monitoring high mental workload. LF/HF showed the highest correlations with other physiological indices. EEG α/θ (F4-C4) showed strong correlations with subjective measures across different mental workload levels. Operation strategy would affect the sensitivity of EEG α (F4-C4) and HF.

Intelligence Community Forum

DTIC Science & Technology

2008-11-05

Description Operationally Feasible? EEG ms ms cm Measures electrical activity in the brain. Practical tool for applications - real time monitoring or...Cognitive Systems Device Development & Processing Methods Brain activity can be monitored in real-time in operational environments with EEG Brain...biological and cognitive findings about the user to customize the learning environment Neurofeedback • Present the user with real-time feedback

[EEG-adjusted target-controlled infusion : Propofol target concentration with different doses of remifentanil].

PubMed

Büttner, N; Schultz, B; Grouven, U; Schultz, A

2010-02-01

The aim of this study was to examine to what extent the use of electroencephalography (EEG) monitoring leads to an adaptation of the target-controlled infusion (TCI) concentration of propofol during propofol anaesthesia with different doses of remifentanil. With ethics committee approval 60 patients (27-69 years old) with American Society of Anesthesiologists classification (ASA) I-III received anaesthestics with propofol (TCI, Diprifusor, AstraZeneca, Wedel, Deutschland) and 0.2, 0.4, or 0.6 microg/kg body weight remifentanil, respectively (groups 1-3). Anaesthesia was maintained at a level of deep hypnosis (EEG stages D(2)/E(0), EEG monitor: Narcotrend, version 2.0/5.0, manufacturer: MT MonitorTechnik, Bad Bramstedt, Germany). During the steady state the propofol concentration in groups 1-3 was 3.02+/-0.86, 1.93+/-0.53 and 1.60+/-0.55 microg/ml, respectively (p<0.001). Women had a higher propofol consumption than men (p<0.05). Dreams during anaesthesia were more often reported by women than by men (p<0.05). The need for postoperative analgesia decreased with an increasing intraoperative remifentanil dose (p<0.05). The study demonstrates that remifentanil has both analgetic and hypnotic effects. With increasing remifentanil dose the propofol requirement decreased and in this context EEG monitoring is useful to adapt the target concentrations of propofol to the patients' age and gender.

EEG

MedlinePlus

... injuries Infections Tumors EEG is also used to: Evaluate problems with sleep ( sleep disorders ) Monitor the brain ... Tissue death due to a blockage in blood flow (cerebral infarction) Drug or alcohol abuse Head injury ...

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring

PubMed Central

Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Objective Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Methods Six MSPE algorithms—derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis—were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. Results CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. Conclusions MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales. PMID:27723803

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

PubMed

Su, Cui; Liang, Zhenhu; Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales.

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy.

PubMed

Mishra, Vikas; Gautier, Nicole M; Glasscock, Edward

2018-01-29

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.

Automatic burst detection for the EEG of the preterm infant.

PubMed

Jennekens, Ward; Ruijs, Loes S; Lommen, Charlotte M L; Niemarkt, Hendrik J; Pasman, Jaco W; van Kranen-Mastenbroek, Vivianne H J M; Wijn, Pieter F F; van Pul, Carola; Andriessen, Peter

2011-10-01

To aid with prognosis and stratification of clinical treatment for preterm infants, a method for automated detection of bursts, interburst-intervals (IBIs) and continuous patterns in the electroencephalogram (EEG) is developed. Results are evaluated for preterm infants with normal neurological follow-up at 2 years. The detection algorithm (MATLAB®) for burst, IBI and continuous pattern is based on selection by amplitude, time span, number of channels and numbers of active electrodes. Annotations of two neurophysiologists were used to determine threshold values. The training set consisted of EEG recordings of four preterm infants with postmenstrual age (PMA, gestational age + postnatal age) of 29-34 weeks. Optimal threshold values were based on overall highest sensitivity. For evaluation, both observers verified detections in an independent dataset of four EEG recordings with comparable PMA. Algorithm performance was assessed by calculation of sensitivity and positive predictive value. The results of algorithm evaluation are as follows: sensitivity values of 90% ± 6%, 80% ± 9% and 97% ± 5% for burst, IBI and continuous patterns, respectively. Corresponding positive predictive values were 88% ± 8%, 96% ± 3% and 85% ± 15%, respectively. In conclusion, the algorithm showed high sensitivity and positive predictive values for bursts, IBIs and continuous patterns in preterm EEG. Computer-assisted analysis of EEG may allow objective and reproducible analysis for clinical treatment.

Wearable In-Ear Encephalography Sensor for Monitoring Sleep. Preliminary Observations from Nap Studies.

PubMed

Looney, David; Goverdovsky, Valentin; Rosenzweig, Ivana; Morrell, Mary J; Mandic, Danilo P

2016-12-01

To date, EEG is the only quantifiable measure of the neural changes that define sleep. Although it is used widely for clinical testing, scalp-electrode EEG is costly and is poorly tolerated by sleeping patients. This was a pilot study to assess the agreement between EEG recordings obtained from a new ear-EEG sensor and those obtained simultaneously from standard scalp electrodes. Participants were four healthy men, 25 to 36 years of age. During naps, EEG tracings were recorded simultaneously from the ear sensor and from standard scalp electrodes. A clinical expert, blinded to the data collection, analyzed 30-second epochs of recordings from both devices, using standardized criteria. The agreement between scalp- and ear-recordings was assessed. We scored 360 epochs (scalp-EEG and ear-EEG), of which 254 (70.6%) were scored as non-REM sleep using scalp-EEG. The ear-EEG sensor had a sensitivity of 0.88 (95% confidence interval [CI], 0.82-0.92) and a specificity of 0.78 (95% CI, 0.70-0.84) in detecting N2/N3 sleep. The kappa coefficient between the scalp- and the ear-EEG was 0.65 (95% CI, 0.58-0.73). As a sleep monitor (all non-REM sleep stages vs. wake), the in-ear sensor had a sensitivity of 0.91 (95% CI, 0.87-0.94) and a specificity of 0.66 (95% CI, 0.56-0.75). The kappa coefficient was 0.60 (95% CI, 0.50-0.69). Substantial agreement was observed between recordings derived from a new ear-EEG sensor and conventional scalp electrodes on four healthy volunteers during daytime naps.

Automatic classification of background EEG activity in healthy and sick neonates

NASA Astrophysics Data System (ADS)

Löfhede, Johan; Thordstein, Magnus; Löfgren, Nils; Flisberg, Anders; Rosa-Zurera, Manuel; Kjellmer, Ingemar; Lindecrantz, Kaj

2010-02-01

The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher's linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.

[Portable Epileptic Seizure Monitoring Intelligent System Based on Android System].

PubMed

Liang, Zhenhu; Wu, Shufeng; Yang, Chunlin; Jiang, Zhenzhou; Yu, Tao; Lu, Chengbiao; Li, Xiaoli

2016-02-01

The clinical electroencephalogram (EEG) monitoring systems based on personal computer system can not meet the requirements of portability and home usage. The epilepsy patients have to be monitored in hospital for an extended period of time, which imposes a heavy burden on hospitals. In the present study, we designed a portable 16-lead networked monitoring system based on the Android smart phone. The system uses some technologies including the active electrode, the WiFi wireless transmission, the multi-scale permutation entropy (MPE) algorithm, the back-propagation (BP) neural network algorithm, etc. Moreover, the software of Android mobile application can realize the processing and analysis of EEG data, the display of EEG waveform and the alarm of epileptic seizure. The system has been tested on the mobile phones with Android 2. 3 operating system or higher version and the results showed that this software ran accurately and steadily in the detection of epileptic seizure. In conclusion, this paper provides a portable and reliable solution for epileptic seizure monitoring in clinical and home applications.

Night-day-night sleep-wakefulness monitoring by ambulatory integrated circuit memories.

PubMed

Yamamoto, M; Nakao, M; Katayama, N; Waku, M; Suzuki, K; Irokawa, K; Abe, M; Ueno, T

1999-04-01

A medium-sized portable digital recorder with fully integrated circuit (IC) memories for sleep monitoring has been developed. It has five amplifiers for EEG, EMG, EOG, ECG, and a signal of body acceleration or respiration sound, four event markers, an 8 ch A/D converter, a digital signal processor (DSP), 192 Mbytes IC flash memories, and batteries. The whole system weighs 1200 g including batteries and is put into a small bag worn on the subject's waist or carried in their hand. The sampling rate for each input channel is programmable through the DSP. This apparatus is valuable for continuously monitoring the states of sleep-wakefulness over 24 h, making a night-day-night recording possible in a hospital, home, or car.

Mild Depression Detection of College Students: an EEG-Based Solution with Free Viewing Tasks.

PubMed

Li, Xiaowei; Hu, Bin; Shen, Ji; Xu, Tingting; Retcliffe, Martyn

2015-12-01

Depression is a common mental disorder with growing prevalence; however current diagnoses of depression face the problem of patient denial, clinical experience and subjective biases from self-report. By using a combination of linear and nonlinear EEG features in our research, we aim to develop a more accurate and objective approach to depression detection that supports the process of diagnosis and assists the monitoring of risk factors. By classifying EEG features during free viewing task, an accuracy of 99.1%, which is the highest to our knowledge by far, was achieved using kNN classifier to discriminate depressed and non-depressed subjects. Furthermore, through correlation analysis, comparisons of performance on each electrode were discussed on the availability of single channel EEG recording depression detection system. Combined with wearable EEG collecting devices, our method offers the possibility of cost effective wearable ubiquitous system for doctors to monitor their patients with depression, and for normal people to understand their mental states in time.

Monitoring and diagnosis of Alzheimer's disease using noninvasive compressive sensing EEG

NASA Astrophysics Data System (ADS)

Morabito, F. C.; Labate, D.; Morabito, G.; Palamara, I.; Szu, H.

2013-05-01

The majority of elderly with Alzheimer's Disease (AD) receive care at home from caregivers. In contrast to standard tethered clinical settings, a wireless, real-time, body-area smartphone-based remote monitoring of electroencephalogram (EEG) can be extremely advantageous for home care of those patients. Such wearable tools pave the way to personalized medicine, for example giving the opportunity to control the progression of the disease and the effect of drugs. By applying Compressive Sensing (CS) techniques it is in principle possible to overcome the difficulty raised by smartphones spatial-temporal throughput rate bottleneck. Unfortunately, EEG and other physiological signals are often non-sparse. In this paper, it is instead shown that the EEG of AD patients becomes actually more compressible with the progression of the disease. EEG of Mild Cognitive Impaired (MCI) subjects is also showing clear tendency to enhanced compressibility. This feature favor the use of CS techniques and ultimately the use of telemonitoring with wearable sensors.

Adaptive shut-down of EEG activity predicts critical acidemia in the near-term ovine fetus.

PubMed

Frasch, Martin G; Durosier, Lucien Daniel; Gold, Nathan; Cao, Mingju; Matushewski, Brad; Keenliside, Lynn; Louzoun, Yoram; Ross, Michael G; Richardson, Bryan S

2015-07-01

In fetal sheep, the electrocorticogram (ECOG) recorded directly from the cortex during repetitive heart rate (FHR) decelerations induced by umbilical cord occlusions (UCO) predictably correlates with worsening hypoxic-acidemia. In human fetal monitoring during labor, the equivalent electroencephalogram (EEG) can be recorded noninvasively from the scalp. We tested the hypothesis that combined fetal EEG - FHR monitoring allows for early detection of worsening hypoxic-acidemia similar to that shown for ECOG-FHR monitoring. Near-term fetal sheep (n = 9) were chronically instrumented with arterial and venous catheters, ECG, ECOG, and EEG electrodes and umbilical cord occluder, followed by 4 days of recovery. Repetitive UCOs of 1 min duration and increasing strength (with regard to the degree of reduction in umbilical blood flow) were induced each 2.5 min until pH dropped to <7.00. Repetitive UCOs led to marked acidosis (arterial pH 7.35 ± 0.01 to 7.00 ± 0.03). At pH of 7.22 ± 0.03 (range 7.32-7.07), and 45 ± 9 min (range 1 h 33 min-20 min) prior to attaining pH < 7.00, both ECOG and EEG amplitudes began to decrease ~fourfold during each FHR deceleration in a synchronized manner. Confirming our hypothesis, these findings support fetal EEG as a useful adjunct to FHR monitoring during human labor for early detection of incipient fetal acidemia. © 2015 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

EEG deficits in chronic marijuana abusers during monitored abstinence: preliminary findings.

PubMed

Herning, Ronald I; Better, Warren; Tate, Kimberly; Cadet, Jean L

2003-05-01

Cognitive, cerebrovascular, and psychiatric impairments have been documented with chronic marijuana users. To better understand the nature and duration of these neurocognitive changes in marijuana abusers, we recorded the resting EEG of 29 abstinent chronic marijuana abusers and 21 control subjects. The marijuana abusers were tested twice: the first evaluation occurred within 72 hours of admission to the inpatient research unit; the second evaluation occurred after 28 to 30 days of monitored abstinence. A three-minute period of EEG was recorded during resting eyes-closed conditions from eight electrodes (F(3), C(3), P(3), O(1), F(4), C(4), P(4), and O(2)). The artifacted EEG was converted to six frequency bands (delta, theta, alpha(1), alpha(2), beta(1), and beta(2)) using a fast Fourier transform. During early abstinence, absolute power was significantly lower (p < 0.05) for the marijuana abusers than for the control subjects for the theta and alpha(1) bands. These reductions in theta and alpha(1) power persisted for 28 days of monitored abstinence. These EEG changes, together with cerebral blood flow deficits, might underlie the cognitive alterations observed in marijuana abusers. Additional research is needed to determine how long these deficits persist during abstinence and if treatment with neuroprotective agents may reverse them.

Cortical network dysfunction in musicogenic epilepsy reflecting the role of snowballing emotional processes in seizure generation: an fMRI-EEG study.

PubMed

Diekmann, Volker; Hoppner, Anselm Cornelius

2014-03-01

Patients suffering from musicogenic epilepsy have focal seizures triggered by auditory stimuli. In some of these patients, the emotions associated with the music appear to play a role in the process triggering the seizure, however, the significance of these emotions and the brain regions involved are unclear. In order to shed some light on this, we conducted fMRI and EEG in a case of musicogenic epilepsy. In a 32-year-old male patient with seizures induced by a specific piece of Russian music, we performed video-EEG monitoring as well as simultaneous fMRI and EEG registration. Video-EEG monitoring revealed a left temporo-frontal epileptogenic focus. During fMRI-EEG co-registration, BOLD signal alterations were not only found in the epileptogenic focus but also in areas known for their role in the processing of emotions. Prior to a seizure in some of these areas, BOLD contrasts exponentially increased or decreased. These results suggest that in our case, dysfunction of the regulation processes of the musically-induced emotions, and not the musical stimulus itself, led to the seizures.

Consensus-based guidelines for Video EEG monitoring in the pre-surgical evaluation of children with epilepsy in the UK.

PubMed

Pressler, Ronit M; Seri, Stefano; Kane, Nick; Martland, Tim; Goyal, Sushma; Iyer, Anand; Warren, Elliott; Notghi, Lesley; Bill, Peter; Thornton, Rachel; Appleton, Richard; Doyle, Sarah; Rushton, Sarah; Worley, Alan; Boyd, Stewart G

2017-08-01

Paediatric Epilepsy surgery in the UK has recently been centralised in order to improve expertise and quality of service available to children. Video EEG monitoring or telemetry is a highly specialised and a crucial component of the pre-surgical evaluation. Although many Epilepsy Monitoring Units work to certain standards, there is no national or international guideline for paediatric video telemetry. Due to lack of evidence we used a modified Delphi process utilizing the clinical and academic expertise of the clinical neurophysiology sub-specialty group of Children's Epilepsy Surgical Service (CESS) centres in England and Wales. This process consisted of the following stages I: Identification of the consensus working group, II: Identification of key areas for guidelines, III: Consensus practice points and IV: Final review. Statements that gained consensus (median score of either 4 or 5 using a five-point Likerttype scale) were included in the guideline. Two rounds of feedback and amendments were undertaken. The consensus guidelines includes the following topics: referral pathways, neurophysiological equipment standards, standards of recording techniques, with specific emphasis on safety of video EEG monitoring both with and without drug withdrawal, a protocol for testing patient's behaviours, data storage and guidelines for writing factual reports and conclusions. All statements developed received a median score of 5 and were adopted by the group. Using a modified Delphi process we were able to develop universally-accepted video EEG guidelines for the UK CESS. Although these recommendations have been specifically developed for the pre-surgical evaluation of children with epilepsy, it is assumed that most components are transferable to any paediatric video EEG monitoring setting. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Techniques for chronic monitoring of brain activity in freely moving sheep using wireless EEG recording.

PubMed

Perentos, N; Nicol, A U; Martins, A Q; Stewart, J E; Taylor, P; Morton, A J

2017-03-01

Large mammals with complex central nervous systems offer new possibilities for translational research into basic brain function. Techniques for monitoring brain activity in large mammals, however, are not as well developed as they are in rodents. We have developed a method for chronic monitoring of electroencephalographic (EEG) activity in unrestrained sheep. We describe the methods for behavioural training prior to implantation, surgical procedures for implantation, a protocol for reliable anaesthesia and recovery, methods for EEG data collection, as well as data pertaining to suitability and longevity of different types of electrodes. Sheep tolerated all procedures well, and surgical complications were minimal. Electrode types used included epidural and subdural screws, intracortical needles and subdural disk electrodes, with the latter producing the best and most reliable results. The implants yielded longitudinal EEG data of consistent quality for periods of at least a year, and in some cases up to 2 years. This is the first detailed methodology to be described for chronic brain function monitoring in freely moving unrestrained sheep. The developed method will be particularly useful in chronic investigations of brain activity during normal behaviour that can include sleep, learning and memory. As well, within the context of disease, the method can be used to monitor brain pathology or the progress of therapeutic trials in transgenic or natural disease models in sheep. Copyright © 2016 Elsevier B.V. All rights reserved.

The Neu-Prem Trial: Neuromonitoring of Brains of Infants Born Preterm During Resuscitation-A Prospective Observational Cohort Study.

PubMed

Katheria, Anup C; Harbert, M J; Nagaraj, Sunil B; Arnell, Kathy; Poeltler, Debra M; Brown, Melissa K; Rich, Wade; Hassen, Kasim O; Finer, Neil

2018-04-16

To determine whether monitoring cerebral oxygen tissue saturation (StO 2 ) with near-infrared spectroscopy (NIRS) and brain activity with amplitude-integrated electroencephalography (aEEG) can predict infants at risk for intraventricular hemorrhage (IVH) and death in the first 72 hours of life. A NIRS sensor and electroencephalography leads were placed on 127 newborns <32 weeks of gestational age at birth. Ten minutes of continuous NIRS and aEEG along with heart rate, peripheral arterial oxygen saturation, fraction of inspired oxygen, and mean airway pressure measurements were obtained in the delivery room. Once the infant was transferred to the neonatal intensive care unit, NIRS, aEEG, and vital signs were recorded until 72 hours of life. An ultrasound scan of the head was performed within the first 12 hours of life and again at 72 hours of life. Thirteen of the infants developed any IVH or died; of these, 4 developed severe IVH (grade 3-4) within 72 hours. There were no differences in either cerebral StO 2 or aEEG in the infants with low-grade IVH. Infants who developed severe IVH or death had significantly lower cerebral StO 2 from 8 to 10 minutes of life. aEEG was not predictive of IVH or death in the delivery room or in the neonatal intensive care unit. It may be possible to use NIRS in the delivery room to predict severe IVH and early death. ClinicalTrials.gov: NCT02605733. Copyright © 2018 Elsevier Inc. All rights reserved.

Inflammatory and vascular placental lesions are associated with neonatal amplitude integrated EEG recording in early premature neonates

PubMed Central

Goshen, Sharon; Richardson, Justin; Drunov, VIadimir; Staretz Chacham, Orna; Shany, Eilon

2017-01-01

Introduction Placental histologic examination can assist in revealing the mechanism leading to preterm birth. Accumulating evidence suggests an association between intrauterine pathological processes, morbidity and mortality of premature infants, and their long term outcome. Neonatal brain activity is increasingly monitored in neonatal intensive care units by amplitude integrated EEG (aEEG) and indices of background activity and sleep cycling patterns were correlated with long term outcome. We hypothesized an association between types of placental lesions and abnormal neonatal aEEG patterns. Objective To determine the association between the placental lesions observed in extreme preterm deliveries, and their neonatal aEEG patterns and survival. Patients and methods This prospective cohort study included extreme premature infants, who were born ≤ 28 weeks of gestation, their placentas were available for histologic examination, and had a continues aEEG, soon after birth)n = 34). Infants and maternal clinical data were collected. aEEG data was assessed for percentage of depressed daily activity in the first 3 days of life and for sleep cycling. Associations of placental histology with clinical findings and aEEG activity were explored using parametric and non-parametric statistics. Results Twenty two out of the 34 newborns survived to discharge. Preterm prelabor rupture of membranes (PPROM) or chorioamnionitis were associated with placental lesions consistent with fetal amniotic fluid infection (AFI) or maternal under perfusion (MUP) (P < 0.05). Lesions consistent with fetal response to AFI were associated with absence of SWC pattern during the 1st day of life. Fetal-vascular-thrombo-occlusive lesions of inflammatory type were negatively associated with depressed cerebral activity during the 1st day of life, and with aEEG cycling during the 2nd day of life (P<0.05). Placental lesions associated with MUP were associated with depressed neonatal cerebral activity during the first 3 days of life (P = 0.007). Conclusions Depressed neonatal aEEG patterns are associated with placental lesions consistent with maternal under perfusion, and amniotic fluid infection of fetal type, but not with fetal thrombo-oclusive vascular disease of inflammatory type. Our findings highlight the association between the intrauterine mechanisms leading to preterm parturition and subsequent depressed neonatal cerebral function early after birth, which eventually may put premature infants at risk for abnormal neurodevelopmental outcome. PMID:28644831

Wireless and wearable EEG system for evaluating driver vigilance.

PubMed

Lin, Chin-Teng; Chuang, Chun-Hsiang; Huang, Chih-Sheng; Tsai, Shu-Fang; Lu, Shao-Wei; Chen, Yen-Hsuan; Ko, Li-Wei

2014-04-01

Brain activity associated with attention sustained on the task of safe driving has received considerable attention recently in many neurophysiological studies. Those investigations have also accurately estimated shifts in drivers' levels of arousal, fatigue, and vigilance, as evidenced by variations in their task performance, by evaluating electroencephalographic (EEG) changes. However, monitoring the neurophysiological activities of automobile drivers poses a major measurement challenge when using a laboratory-oriented biosensor technology. This work presents a novel dry EEG sensor based mobile wireless EEG system (referred to herein as Mindo) to monitor in real time a driver's vigilance status in order to link the fluctuation of driving performance with changes in brain activities. The proposed Mindo system incorporates the use of a wireless and wearable EEG device to record EEG signals from hairy regions of the driver conveniently. Additionally, the proposed system can process EEG recordings and translate them into the vigilance level. The study compares the system performance between different regression models. Moreover, the proposed system is implemented using JAVA programming language as a mobile application for online analysis. A case study involving 15 study participants assigned a 90 min sustained-attention driving task in an immersive virtual driving environment demonstrates the reliability of the proposed system. Consistent with previous studies, power spectral analysis results confirm that the EEG activities correlate well with the variations in vigilance. Furthermore, the proposed system demonstrated the feasibility of predicting the driver's vigilance in real time.

Dacrystic seizures: demographic, semiologic, and etiologic insights from a multicenter study in long-term video-EEG monitoring units.

PubMed

Blumberg, Julie; Fernández, Iván Sánchez; Vendrame, Martina; Oehl, Bernhard; Tatum, William O; Schuele, Stephan; Alexopoulos, Andreas V; Poduri, Annapurna; Kellinghaus, Christoph; Schulze-Bonhage, Andreas; Loddenkemper, Tobias

2012-10-01

To provide an estimate of the frequency of dacrystic seizures in video-electroencephalography (EEG) long-term monitoring units of tertiary referral epilepsy centers and to describe the clinical presentation of dacrystic seizures in relationship to the underlying etiology. We screened clinical records and video-EEG reports for the diagnosis of dacrystic seizures of all patients admitted for video-EEG long-term monitoring at five epilepsy referral centers in the United States and Germany. Patients with a potential diagnosis of dacrystic seizures were identified, and their clinical charts and video-EEG recordings were reviewed. We included only patients with: (1) stereotyped lacrimation, sobbing, grimacing, yelling, or sad facial expression; (2) long-term video-EEG recordings (at least 12 h); and (3) at least one brain magnetic resonance imaging (MRI) study. Nine patients (four female) with dacrystic seizures were identified. Dacrystic seizures were identified in 0.06-0.53% of the patients admitted for long-term video-EEG monitoring depending on the specific center. Considering our study population as a whole, the frequency was 0.13%. The presence of dacrystic seizures without other accompanying clinical features was found in only one patient. Gelastic seizures accompanied dacrystic seizures in five cases, and a hypothalamic hamartoma was found in all of these five patients. The underlying etiology in the four patients with dacrystic seizures without gelastic seizures was left mesial temporal sclerosis (three patients) and a frontal glioblastoma (one patient). All patients had a difficult-to-control epilepsy as demonstrated by the following: (1) at least three different antiepileptic drugs were tried in each patient, (2) epilepsy was well controlled with antiepileptic drugs in only two patients, (3) six patients were considered for epilepsy surgery and three of them underwent a surgical/radiosurgical or radioablative procedure. Regarding outcome, antiepileptic drugs alone achieved seizure freedom in two patients and did not change seizure frequency in another patient. Radiosurgery led to moderately good seizure control in one patient and did not improve seizure control in another patient. Three patients were or are being considered for epilepsy surgery on last follow-up. One patient remains seizure free 3 years after epilepsy surgery. Dacrystic seizures are a rare but clinically relevant finding during video-EEG monitoring. Our data show that when the patient has dacrystic and gelastic seizures, the cause is a hypothalamic hamartoma. In contrast, when dacrystic seizures are not accompanied by gelastic seizures the underlying lesion is most commonly located in the temporal cortex. Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.

Temporal lobe deficits in murderers: EEG findings undetected by PET.

PubMed

Gatzke-Kopp, L M; Raine, A; Buchsbaum, M; LaCasse, L

2001-01-01

This study evaluates electroencephalography (EEG) and positron emission tomography (PET) in the same subjects. Fourteen murderers were assessed by using both PET (while they were performing the continuous performance task) and EEG during a resting state. EEG revealed significant increases in slow-wave activity in the temporal, but not frontal, lobe in murderers, in contrast to prior PET findings that showed reduced prefrontal, but not temporal, glucose metabolism. Results suggest that resting EEG shows empirical utility distinct from PET activation findings.

Pharmacokinetics and clinical efficacy of phenobarbital in asphyxiated newborns treated with hypothermia: a thermopharmacological approach.

PubMed

van den Broek, M P H; Groenendaal, F; Toet, M C; van Straaten, H L M; van Hasselt, J G C; Huitema, A D R; de Vries, L S; Egberts, A C G; Rademaker, C M A

2012-10-01

Therapeutic hypothermia can influence the pharmacokinetics and pharmacodynamics of drugs, the discipline which is called thermopharmacology. We studied the effect of therapeutic hypothermia on the pharmacokinetics of phenobarbital in asphyxiated neonates, and the clinical efficacy and the effect of phenobarbital on the continuous amplitude-integrated electroencephalography (aEEG) in a prospective study. Data were obtained from the prospective SHIVER study, performed in two of the ten Dutch level III neonatal intensive care units. Phenobarbital data were collected between 2008 and 2010. Newborns were eligible for inclusion if they had a gestational age of at least 36 weeks and presented with perinatal asphyxia and encephalopathy. According to protocol in both hospitals an intravenous (repeated) loading dose of phenobarbital 20 mg/kg divided in 1-2 doses was administered if seizures occurred or were suspected before or during the hypothermic phase. Phenobarbital plasma concentrations were measured in plasma using a fluorescence polarization immunoassay. aEEG was monitored continuously. A one-compartmental population pharmacokinetic/pharmacodynamic model was developed using a multi-level Markov transition model. No (clinically relevant) effect of moderate therapeutic hypothermia on phenobarbital pharmacokinetics could be identified. The observed responsiveness was 66%. While we still advise an initial loading dose of 20 mg/kg, clinicians should not be reluctant to administer an additional dose of 10-20 mg/kg. An additional dose should be given before switching to a second-line anticonvulsant drug. Based on our pharmacokinetic/pharmacodynamic model, administration of phenobarbital under hypothermia seems to reduce the transition rate from a continuous normal voltage (CNV) to discontinuous normal voltage aEEG background level in hypothermic asphyxiated newborns, which may be attributed to the additional neuroprotection of phenobarbital in infants with a CNV pattern.

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery.

PubMed

Liu, Quan; Chen, Yi-Feng; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2017-08-01

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.

ERPS to Monitor Non-conscious Mentation

NASA Technical Reports Server (NTRS)

Donchin, E.

1984-01-01

Event Related Brain Potentials (or ERPs) are extracted from the EEG that can be recorded between a pair of electrodes placed on a person's scalp. The EEG is recorded as a continual fluctuation in voltage. It is the results of the integration of the potential fields generated by a multitude of neuronal ensembles that are active as the brain goes about its business. Within this ongoing signal it is possible to distinguish voltage fluctuations that are triggered in neural structures by the occurrence of specific events. This activity, evoked as it is by an external event, is known as the Evoked, or Event Related, Potential. The ERPs provide a unique opportunity to monitor non-conscious mentation. The inferences that can be based on ERP data are described and the limits of these inferences are emphasized. This, however, will not be an exhaustive review of the use of ERPs in Engineering Psychology. The application, its scope, and its limitations will be illustrated by means of one example. This example is preceded by a brief technical introduction to the methodology used in the study of ERPs. The manner in which ERPs are used to study cognition is described.

Intravenous levetiracetam terminates refractory status epilepticus in two patients with migrating partial seizures in infancy.

PubMed

Cilio, Maria Roberta; Bianchi, Roberto; Balestri, Martina; Onofri, Alfredo; Giovannini, Simona; Di Capua, Matteo; Vigevano, Federico

2009-09-01

To evaluate the efficacy and tolerability of intravenous (IV) levetiracetam in refractory status epilepticus of migrating partial seizures in infancy (MPSI). IV levetiracetam was infused in two infants, first as a loading dose of 60mg/kg in 30min, then at 30mg/kg twice a day. Both infants were continuously monitored with video-EEG before, during and after the drug trial. Blood count, liver enzymes, serum creatinine, ammonia and lactate blood levels were performed repeatedly before and after the IV levetiracetam administration. Follow-up was of 16 and 10 months. EEG monitoring allowed the diagnosis of MPSI, showing the typical seizures pattern in both patients. IV levetiracetam was effective in stopping status epilepticus in both infants. Levetiracetam also prevented the recurrence of status epilepticus during follow-up. No adverse reactions were observed during the infusion phase or during follow-up. MPSI is a newly recognized epileptic syndrome characterized by early onset of intractable partial seizures arisingly independently and sequentially from both hemispheres, migrating from one region of the brain to another and from one hemisphere to another. We report the efficacy of intravenous levetiracetam in resolving refractory status epilepticus in two infants with this new epilepsy syndrome.

Monitoring for neuroprotection. New technologies for the new millennium

NASA Technical Reports Server (NTRS)

Andrews, R. J.

2001-01-01

Monitoring for neuroprotection, like surgery, has placed on emphasis on minimal or non-invasiveness. Monitoring of parameters that truly reflect the degree of injury to the nervous system is another goal. Thus, two themes for the coming decade in neuromonitoring will be: (1) less-invasive monitoring; and (2) parameters that more closely reflect the etiological factors in ischemic or other neuroinjury. In this paper, we review neuromonitoring techniques and devices that can be used readily in the operating room or intensive care unit setting. Those that require transport of the patient to a special facility (e.g., for computed tomography or magnetic resonance imaging/spectroscopy) and those that have been in standard practice for neuromonitoring (e.g., electrophysiological monitoring--EEG, evoked potentials) are not considered. The two techniques considered in detail are (1) continuous multiparameter local brain tissue monitoring with microprobes, and (2) non-invasive continuous local brain tissue oxygenation monitoring by near infrared spectroscopy. Both techniques have been cleared by the Food and Drug Administration (FDA) for clinical use. The rationale for their use, the nature of the devices, and clinical results to date are reviewed. It is expected that both techniques will gain wide acceptance during the coming decade; further advances in neuromonitoring that can be expected further into the twenty-first century are also discussed.

In Vitro and In Vivo Studies for a Bio-Impedance Vital-Sign Monitor

DTIC Science & Technology

2006-10-01

O V SD SAP 0.83 0.11 0.12 0.03 PWV TM2204 1.87 0.73 0.13 0.03 PWV SP776 1.17 0.31 0.14 0.01 EEG F 1.10 0.10 0.52 0.02 EEG P 1.64 0.56...monitoring heart rate, PWV of the soldiers. 30 Impedance Cuff Pressure (max 200 mm Hg) Accelerometer signal (Actigraph) Ultrasound

Validation of a low-cost EEG device for mood induction studies.

PubMed

Rodríguez, Alejandro; Rey, Beatriz; Alcañiz, Mariano

2013-01-01

New electroencephalography (EEG) devices, more portable and cheaper, are appearing on the market. Studying the reliability of these EEG devices for emotional studies would be interesting, as these devices could be more economical and compatible with Virtual Reality (VR) settings. Therefore, the aim in this work was to validate a low-cost EEG device (Emotiv Epoc) to monitor brain activity during a positive emotional induction procedure. Emotional pictures (IAPS) were used to induce a positive mood in sixteen participants. Changes in the brain activity of subjects were compared between positive induction and neutral conditions. Obtained results were in accordance with previous scientific literature regarding frontal EEG asymmetry, which supports the possibility of using this low-cost EEG device in future mood induction studies combined with VR.

EEG - A Valuable Biomarker of Brain Injury in Preterm Infants.

PubMed

Pavlidis, Elena; Lloyd, Rhodri O; Boylan, Geraldine B

2017-01-01

This review focuses on the role of electroencephalography (EEG) in monitoring abnormalities of preterm brain function. EEG features of the most common developmental brain injuries in preterm infants, including intraventricular haemorrhage, periventricular leukomalacia, and perinatal asphyxia, are described. We outline the most common EEG biomarkers associated with these injuries, namely seizures, positive rolandic sharp waves, EEG suppression/increased interburst intervals, mechanical delta brush activity, and other deformed EEG waveforms, asymmetries, and asynchronies. The increasing survival rate of preterm infants, in particular those that are very and extremely preterm, has led to a growing demand for a specific and shared characterization of the patterns related to adverse outcome in this unique population. This review includes abundant high-quality images of the EEG patterns seen in premature infants and will provide a valuable resource for everyone working in developmental neuroscience. © 2017 S. Karger AG, Basel.

Somatosensory-evoked spikes on electroencephalography (EEG): longitudinal clinical and EEG aspects in 313 children.

PubMed

Fonseca, Lineu Corrêa; Tedrus, Gloria M A S

2012-01-01

Somatosensory-evoked spikes (ESp) are high-voltage potentials registered on the EEG, which accompany each of the percussions on the feet or hands. The objective of this research was to study the longitudinal clinical and EEG aspects of children with ESp. A total of 313 children, 53.7% male, showing ESp on the EEG and with an average initial age of 6.82 (range from 2 to 14 years) were followed for a mean period of 35.7 months. In the initial evaluation, 118 (37.7%) had a history of nonfebrile epileptic seizures (ES). Epileptiform activity (EA) was observed on the EEG in 61% and showed a significantly greater occurrence in children with ES than in those without (P = .000). Of the 118 showing seizures from the start, 53 (44.9%) continued to have seizures; of the 195 without seizures at the start, only 13 (6.67%) developed them. Thus, only 66 (21.1%) children showed ES during the follow-up. ESp disappeared in 237 (75.7%) cases and EA in 221 (70.6%). In the children with ES, it was found that the presence of EA on the first EEG did not indicate continuation of the ES throughout the remaining period, while the 13 children who presented their first ES in a later period showed a greater occurrence of EA on the initial EEG than those who did not develop ES (P = .001). Evidence of brain injury was observed in 43 (13.7%) children and was associated with a greater continuity of the ES during the study (P = .018). ESp, EA, and ES tend to disappear, suggesting an age-dependent phenomenon. The finding of ESp, particularly in the absence of any evidence of brain injury, indicates a low association with ES and benign outcome.

Using patient-specific hemodynamic response function in epileptic spike analysis of human epilepsy: a study based on EEG-fNIRS.

PubMed

Peng, Ke; Nguyen, Dang Khoa; Vannasing, Phetsamone; Tremblay, Julie; Lesage, Frédéric; Pouliot, Philippe

2016-02-01

Functional near-infrared spectroscopy (fNIRS) can be combined with electroencephalography (EEG) to continuously monitor the hemodynamic signal evoked by epileptic events such as seizures or interictal epileptiform discharges (IEDs, aka spikes). As estimation methods assuming a canonical shape of the hemodynamic response function (HRF) might not be optimal, we sought to model patient-specific HRF (sHRF) with a simple deconvolution approach for IED-related analysis with EEG-fNIRS data. Furthermore, a quadratic term was added to the model to account for the nonlinearity in the response when IEDs are frequent. Prior to analyzing clinical data, simulations were carried out to show that the HRF was estimable by the proposed deconvolution methods under proper conditions. EEG-fNIRS data of five patients with refractory focal epilepsy were selected due to the presence of frequent clear IEDs and their unambiguous focus localization. For each patient, both the linear sHRF and the nonlinear sHRF were estimated at each channel. Variability of the estimated sHRFs was seen across brain regions and different patients. Compared with the SPM8 canonical HRF (cHRF), including these sHRFs in the general linear model (GLM) analysis led to hemoglobin activations with higher statistical scores as well as larger spatial extents on all five patients. In particular, for patients with frequent IEDs, nonlinear sHRFs were seen to provide higher sensitivity in activation detection than linear sHRFs. These observations support using sHRFs in the analysis of IEDs with EEG-fNIRS data. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural network detects the effects of p-CPA pre-treatment on brain electrophysiology in a rat model of focal brain injury.

PubMed

Sinha, Rakesh Kumar; Aggarwal, Yogender

2009-04-01

To examine the performance of Artificial Neural Network (ANN) in evaluation of the effects of pretreatment of para-Chlorophenylalanine (p-CPA), a serotonin blocker, in experimental brain injury. Continuous 4 h digital electroencephalogram (EEG) recordings from male Charles Foster rats and its power spectrum analysis by using fast Fourier transform (FFT) were performed in two experimental (i) drug untreated injury group; (ii) p-CPA pretreated injury group as well as a control group. The EEG power spectrum data were tested by ANN containing 60 nodes in input layer, weighted from the digital values of power spectrum from 0 to 30 Hz, 18 nodes in hidden layer and an output node. The effects of injury and of the drug pretreatment were confirmed with the help of calculation of edematous swelling in the brain. The changes in EEG spectral patterns were compared with the ANN and the accuracy was determined in terms of percent (%). Overall performance of the network was found the best in control group (97.9%) in comparison to p-CPA untreated injury group (96.3%) and p-CPA pretreated injury group (71.9%). The decrease in accuracy in p-CPA pretreated injury group of subjects have occurred due to increase in misclassified patterns due to faster recovery in brain cortical potentials. EEG spectrum analysis with ANN was found successful in identifying the changes due to brain swelling as well as the effect of pretreatment of p-CPA in focal brain injury condition. Thus, the training and testing of ANN with EEG power spectra can be used as an effective diagnostic tool for early prediction and monitoring of brain injury as well as the effects of drugs in this condition.

Comparative sensitivity of quantitative EEG (QEEG) spectrograms for detecting seizure subtypes.

PubMed

Goenka, Ajay; Boro, Alexis; Yozawitz, Elissa

2018-02-01

To assess the sensitivity of Persyst version 12 QEEG spectrograms to detect focal, focal with secondarily generalized, and generalized onset seizures. A cohort of 562 seizures from 58 patients was analyzed. Successive recordings with 2 or more seizures during continuous EEG monitoring for clinical indications in the ICU or EMU between July 2016 and January 2017 were included. Patient ages ranged from 5 to 64 years (mean = 36 years). There were 125 focal seizures, 187 secondarily generalized and 250 generalized seizures from 58 patients analyzed. Seizures were identified and classified independently by two epileptologists. A correlate to the seizure pattern in the raw EEG was sought in the QEEG spectrograms in 4-6 h EEG epochs surrounding the identified seizures. A given spectrogram was interpreted as indicating a seizure, if at the time of a seizure it showed a visually significant departure from the pre-event baseline. Sensitivities for seizure detection using each spectrogram were determined for each seizure subtype. Overall sensitivities of the QEEG spectrograms for detecting seizures ranged from 43% to 72%, with highest sensitivity (402/562,72%) by the seizure detection trend. The asymmetry spectrogram had the highest sensitivity for detecting focal seizures (117/125,94%). The FFT spectrogram was most sensitive for detecting secondarily generalized seizures (158/187, 84%). The seizure detection trend was the most sensitive for generalized onset seizures (197/250,79%). Our study suggests that different seizure types have specific patterns in the Persyst QEEG spectrograms. Identifying these patterns in the EEG can significantly increase the sensitivity for seizure identification. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Identifying stereotypic evolving micro-scale seizures (SEMS) in the hypoxic-ischemic EEG of the pre-term fetal sheep with a wavelet type-II fuzzy classifier.

PubMed

Abbasi, Hamid; Bennet, Laura; Gunn, Alistair J; Unsworth, Charles P

2016-08-01

Perinatal hypoxic-ischemic encephalopathy (HIE) around the time of birth due to lack of oxygen can lead to debilitating neurological conditions such as epilepsy and cerebral palsy. Experimental data have shown that brain injury evolves over time, but during the first 6-8 hours after HIE the brain has recovered oxidative metabolism in a latent phase, and brain injury is reversible. Treatments such as therapeutic cerebral hypothermia (brain cooling) are effective when started during the latent phase, and continued for several days. Effectiveness of hypothermia is lost if started after the latent phase. Post occlusion monitoring of particular micro-scale transients in the hypoxic-ischemic (HI) Electroencephalogram (EEG), from an asphyxiated fetal sheep model in utero, could provide precursory evidence to identify potential biomarkers of injury when brain damage is still treatable. In our studies, we have reported how it is possible to automatically detect HI EEG transients in the form of spikes and sharp waves during the latent phase of the HI EEG of the preterm fetal sheep. This paper describes how to identify stereotypic evolving micro-scale seizures (SEMS) which have a relatively abrupt onset and termination in a frequency range of 1.8-3Hz (Delta waves) superimposed on a suppressed EEG amplitude background post occlusion. This research demonstrates how a Wavelet Type-II Fuzzy Logic System (WT-Type-II-FLS) can be used to automatically identify subtle abnormal SEMS that occur during the latent phase with a preliminary average validation overall performance of 78.71%±6.63 over the 390 minutes of the latent phase, post insult, using in utero pre-term hypoxic fetal sheep models.

A case-control study of wicket spikes using video-EEG monitoring.

PubMed

Vallabhaneni, Maya; Baldassari, Laura E; Scribner, James T; Cho, Yong Won; Motamedi, Gholam K

2013-01-01

To investigate clinical characteristics associated with wicket spikes in patients undergoing long-term video-EEG monitoring. A case-control study was performed in 479 patients undergoing video-EEG monitoring, with 3 age- (±3 years) and gender-matched controls per patient with wicket spikes. Logistic regression was utilized to investigate the association between wicket spikes and other factors, including conditions that have been previously associated with wicket spikes. Wicket spikes were recorded in 48 patients. There was a significantly higher prevalence of dizziness/vertigo (p=0.002), headaches (p=0.005), migraine (p=0.015), and seizures (p=0.016) in patients with wickets. The majority of patients with wicket spikes did not exhibit epileptiform activity on EEG; however, patients with history of seizures were more likely to have wickets (p=0.017). There was no significant difference in the prevalence of psychogenic non-epileptic seizures between the groups. Wickets were more common on the left, during sleep, and more likely to be first recorded on day 1-2 of monitoring. Patients with wicket spikes are more likely to have dizziness/vertigo, headaches, migraine, and seizures. Patients with history of seizures are more likely to have wickets. The prevalence of psychogenic non-epileptic seizures is not significantly higher in patients with wickets. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Hyperventilation revisited: physiological effects and efficacy on focal seizure activation in the era of video-EEG monitoring.

PubMed

Guaranha, Mirian S B; Garzon, Eliana; Buchpiguel, Carlos A; Tazima, Sérgio; Yacubian, Elza M T; Sakamoto, Américo C

2005-01-01

Hyperventilation is an activation method that provokes physiological slowing of brain rhythms, interictal discharges, and seizures, especially in generalized idiopathic epilepsies. In this study we assessed its effectiveness in inducing focal seizures during video-EEG monitoring. We analyzed the effects of hyperventilation (HV) during video-EEG monitoring (video-EEG) of patients with medically intractable focal epilepsies. We excluded children younger than 10 years, mentally retarded patients, and individuals with frequent seizures. We analyzed 97 patients; 24 had positive seizure activation (PSA), and 73 had negative seizure activation (NSA). No differences were found between groups regarding sex, age, age at epilepsy onset, duration of epilepsy, frequency of seizures, and etiology. Temporal lobe epilepsies were significantly more activated than frontal lobe epilepsies. Spontaneous and activated seizures did not differ in terms of their clinical characteristics, and the activation did not affect the performance of ictal single-photon emission computed tomography (SPECT). HV is a safe and effective method of seizure activation during monitoring. It does not modify any of the characteristics of the seizures and allows the obtaining of valuable ictal SPECTs. This observation is clinically relevant and suggests the effectiveness and the potential of HV in shortening the presurgical evaluation, especially of temporal lobe epilepsy patients, consequently reducing its costs and increasing the number of candidates for epilepsy surgery.

The relationship between seizures, interictal spikes and antiepileptic drugs.

PubMed

Goncharova, Irina I; Alkawadri, Rafeed; Gaspard, Nicolas; Duckrow, Robert B; Spencer, Dennis D; Hirsch, Lawrence J; Spencer, Susan S; Zaveri, Hitten P

2016-09-01

A considerable decrease in spike rate accompanies antiepileptic drug (AED) taper during intracranial EEG (icEEG) monitoring. Since spike rate during icEEG monitoring can be influenced by surgery to place intracranial electrodes, we studied spike rate during long-term scalp EEG monitoring to further test this observation. We analyzed spike rate, seizure occurrence and AED taper in 130 consecutive patients over an average of 8.9days (range 5-17days). We observed a significant relationship between time to the first seizure, spike rate, AED taper and seizure occurrence (F (3,126)=19.77, p<0.0001). A high spike rate was related to a longer time to the first seizure. Further, in a subset of 79 patients who experienced seizures on or after day 4 of monitoring, spike rate decreased initially from an on- to off-AEDs epoch (from 505.0 to 382.3 spikes per hour, p<0.00001), and increased thereafter with the occurrence of seizures. There is an interplay between seizures, spikes and AEDs such that spike rate decreases with AED taper and increases after seizure occurrence. The direct relationship between spike rate and AEDs and between spike rate and time to the first seizure suggests that spikes are a marker of inhibition rather than excitation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Clinical utility of EEG in diagnosing and monitoring epilepsy in adults.

PubMed

Tatum, W O; Rubboli, G; Kaplan, P W; Mirsatari, S M; Radhakrishnan, K; Gloss, D; Caboclo, L O; Drislane, F W; Koutroumanidis, M; Schomer, D L; Kasteleijn-Nolst Trenite, D; Cook, Mark; Beniczky, S

2018-05-01

Electroencephalography (EEG) remains an essential diagnostic tool for people with epilepsy (PWE). The International Federation of Clinical Neurophysiology produces new guidelines as an educational service for clinicians to address gaps in knowledge in clinical neurophysiology. The current guideline was prepared in response to gaps present in epilepsy-related neurophysiological assessment and is not intended to replace sound clinical judgement in the care of PWE. Furthermore, addressing specific pathophysiological conditions of the brain that produce epilepsy is of primary importance though is beyond the scope of this guideline. Instead, our goal is to summarize the scientific evidence for the utility of EEG when diagnosing and monitoring PWE. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Prediction of rhythmic and periodic EEG patterns and seizures on continuous EEG with early epileptiform discharges.

PubMed

Koren, J; Herta, J; Draschtak, S; Pötzl, G; Pirker, S; Fürbass, F; Hartmann, M; Kluge, T; Baumgartner, C

2015-08-01

Continuous EEG (cEEG) is necessary to document nonconvulsive seizures (NCS), nonconvulsive status epilepticus (NCSE), as well as rhythmic and periodic EEG patterns of 'ictal-interictal uncertainty' (RPPIIU) including periodic discharges, rhythmic delta activity, and spike-and-wave complexes in neurological intensive care patients. However, cEEG is associated with significant recording and analysis efforts. Therefore, predictors from short-term routine EEG with a reasonably high yield are urgently needed in order to select patients for evaluation with cEEG. The aim of this study was to assess the prognostic significance of early epileptiform discharges (i.e., within the first 30 min of EEG recording) on the following: (1) incidence of ictal EEG patterns and RPPIIU on subsequent cEEG, (2) occurrence of acute convulsive seizures during the ICU stay, and (3) functional outcome after 6 months of follow-up. We conducted a separate analysis of the first 30 min and the remaining segments of prospective cEEG recordings according to the ACNS Standardized Critical Care EEG Terminology as well as NCS criteria and review of clinical data of 32 neurological critical care patients. In 17 patients with epileptiform discharges within the first 30 min of EEG (group 1), electrographic seizures were observed in 23.5% (n = 4), rhythmic or periodic EEG patterns of 'ictal-interictal uncertainty' in 64.7% (n = 11), and neither electrographic seizures nor RPPIIU in 11.8% (n = 2). In 15 patients with no epileptiform discharges in the first 30 min of EEG (group 2), no electrographic seizures were recorded on subsequent cEEG, RPPIIU were seen in 26.7% (n = 4), and neither electrographic seizures nor RPPIIU in 73.3% (n = 11). The incidence of EEG patterns on cEEG was significantly different between the two groups (p = 0.008). Patients with early epileptiform discharges developed acute seizures more frequently than patients without early epileptiform discharges (p = 0.009). Finally, functional outcome six months after discharge was significantly worse in patients with early epileptiform discharges (p=0.01). Epileptiform discharges within the first 30 min of EEG recording are predictive for the occurrence of ictal EEG patterns and for RPPIIU on subsequent cEEG, for acute convulsive seizures during the ICU stay, and for a worse functional outcome after 6 months of follow-up. This article is part of a Special Issue entitled Status Epilepticus. Copyright © 2015 Elsevier Inc. All rights reserved.

Helmet system broadcasts electroencephalograms of wearer

NASA Technical Reports Server (NTRS)

Westbrook, R. M.; Zuccaro, J. J.

1966-01-01

EEG monitoring system consisting of nonirritating sponge-type electrodes, amplifiers, and a battery-powered wireless transmitter, all mounted in the subjects helmet, obtains electroencephalograms /EEGs/ of pilots and astronauts performing tasks under stress. After a quick initial fitting, the helmet can be removed and replaced without adjustments.

Bispectral index monitoring during electroconvulsive therapy under propofol anaesthesia.

PubMed

Gunawardane, P O; Murphy, P A; Sleigh, J W

2002-02-01

The accuracy of the bispectral index (BIS) as a monitor of consciousness has not been well studied in patients who have abnormal electroencephalograms (EEG). We studied the changes in BIS, its subparameters, and spectral entropy of the EEG during 18 electroconvulsive treatments under propofol and succinylcholine anaesthesia. A single bifrontal EEG, and second subocular channel (for eye movement estimation) was recorded. The median (interquartile range) BIS value at re-awakening was only 57 (47-78)--thus more than a quarter of the patients woke at BIS values of less than 50. The changes in spectral entropy values were similar: 0.84 (0.68-0.99) at the start, 0.65 (0.42-0.88) at the point of loss-of-consciousness, 0.63 (0.47-0.79) during the seizures, and 0.58 (0.31-0.85) at awakening. Post-ictal slow-wave activity in the EEG (acting via the SynchFastSlow subparameter) may cause low BIS values that do not correspond to the patient's clinical level of consciousness. This may be important in the interpretation of the BIS in other groups of patients who have increased delta-band power in their EEG.

Outcome of intracranial electroencephalography monitoring and surgery in magnetic resonance imaging-negative temporal lobe epilepsy.

PubMed

Lee, Ricky W; Hoogs, Marietta M; Burkholder, David B; Trenerry, Max R; Drazkowski, Joseph F; Shih, Jerry J; Doll, Karey E; Tatum, William O; Cascino, Gregory D; Marsh, W Richard; Wirrell, Elaine C; Worrell, Gregory A; So, Elson L

2014-07-01

We evaluated the outcomes of intracranial electroencephalography (iEEG) recording and subsequent resective surgery in patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). Thirty-two patients were identified from the Mayo Clinic Epilepsy Surgery Database (Arizona, Florida, and Minnesota). Eight (25.0%) had chronic iEEG monitoring that recorded neocortical temporal seizure onsets; 12 (37.5%) had mesial temporal seizure onsets; 5 (15.6%) had independent neocortical and mesial temporal seizure onsets; and 7 (21.9%) had simultaneous neocortical and mesial seizure onsets. Neocortical temporal lobe seizure semiology was the only factor significantly associated with neocortical temporal seizure onsets on iEEG. Only 33.3% of patients who underwent lateral temporal neocorticectomy had an Engel class 1 outcome, whereas 76.5% of patients with iEEG-guided anterior temporal lobectomy that included the amygdala and the hippocampus had an Engel class 1 outcome. Limitations in cohort size precluded statistical analysis of neuropsychological test data. Copyright © 2014 Elsevier B.V. All rights reserved.

Early EEG for outcome prediction of postanoxic coma: prospective cohort study with cost-minimization analysis.

PubMed

Sondag, Lotte; Ruijter, Barry J; Tjepkema-Cloostermans, Marleen C; Beishuizen, Albertus; Bosch, Frank H; van Til, Janine A; van Putten, Michel J A M; Hofmeijer, Jeannette

2017-05-15

We recently showed that electroencephalography (EEG) patterns within the first 24 hours robustly contribute to multimodal prediction of poor or good neurological outcome of comatose patients after cardiac arrest. Here, we confirm these results and present a cost-minimization analysis. Early prognosis contributes to communication between doctors and family, and may prevent inappropriate treatment. A prospective cohort study including 430 subsequent comatose patients after cardiac arrest was conducted at intensive care units of two teaching hospitals. Continuous EEG was started within 12 hours after cardiac arrest and continued up to 3 days. EEG patterns were visually classified as unfavorable (isoelectric, low-voltage, or burst suppression with identical bursts) or favorable (continuous patterns) at 12 and 24 hours after cardiac arrest. Outcome at 6 months was classified as good (cerebral performance category (CPC) 1 or 2) or poor (CPC 3, 4, or 5). Predictive values of EEG measures and cost-consequences from a hospital perspective were investigated, assuming EEG-based decision- making about withdrawal of life-sustaining treatment in the case of a poor predicted outcome. Poor outcome occurred in 197 patients (51% of those included in the analyses). Unfavorable EEG patterns at 24 hours predicted a poor outcome with specificity of 100% (95% CI 98-100%) and sensitivity of 29% (95% CI 22-36%). Favorable patterns at 12 hours predicted good outcome with specificity of 88% (95% CI 81-93%) and sensitivity of 51% (95% CI 42-60%). Treatment withdrawal based on an unfavorable EEG pattern at 24 hours resulted in a reduced mean ICU length of stay without increased mortality in the long term. This gave small cost reductions, depending on the timing of withdrawal. Early EEG contributes to reliable prediction of good or poor outcome of postanoxic coma and may lead to reduced length of ICU stay. In turn, this may bring small cost reductions.

Sort entropy-based for the analysis of EEG during anesthesia

NASA Astrophysics Data System (ADS)

Ma, Liang; Huang, Wei-Zhi

2010-08-01

The monitoring of anesthetic depth is an absolutely necessary procedure in the process of surgical operation. To judge and control the depth of anesthesia has become a clinical issue which should be resolved urgently. EEG collected wiil be processed by sort entrop in this paper. Signal response of the surface of the cerebral cortex is determined for different stages of patients in the course of anesthesia. EEG is simulated and analyzed through the fast algorithm of sort entropy. The results show that discipline of phasic changes for EEG is very detected accurately,and it has better noise immunity in detecting the EEG anaesthetized than approximate entropy. In conclusion,the computing of Sort entropy algorithm requires shorter time. It has high efficiency and strong anti-interference.

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model.

PubMed

Lopour, Beth A; Tasoglu, Savas; Kirsch, Heidi E; Sleigh, James W; Szeri, Andrew J

2011-04-01

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.

[The role of ambulatory electroencephalogram monitoring: experience and results in 264 records].

PubMed

González de la Aleja, J; Saiz Díaz, R A; Martín García, H; Juntas, R; Pérez-Martínez, D; de la Peña, P

2008-11-01

Ambulatory electroencephalogram (EEG) monitoring allows for long-term, mobile electroencephalographic recordings of patients. This study aims to describe and analyze the results obtained with ambulatory EEG in our clinical practice. We have analyzed the results of 264 ambulatory EEG records, grouped according to the reason for the request: a) group 1: diagnostic evaluation of episodes of epileptic nature; b) group 2: diagnostic evaluation of paroxysmal episodes, and c) group 3: evaluation of the risk of relapse during anti-seizure treatment withdrawal in certain epileptic patients. a) Group 1 (n=137): normal results were found in 54 records (39.4%). There was generalized epileptic activity in 20 (14.6%) of them (5 with ictal activity) and focal epileptic activity was detected in 57 cases (42%) (8 with ictal activity). No EEG diagnosis could be reached in 6 (4%) recordings due to the presence of artefacts; b) group 2 (n=99): in 47 records (47.5 %), there were no episodes and the Holter-EEG was normal. There was a clinically documented episode without anomalies during Holter-EEG registration in 14 cases (14.2%). In 29 records (29.3%), focal epileptic activity was recorded (ictal 4) and generalized epileptic activity (ictal in 1) was recorded in 4 patients (4%). No EEG diagnosis could be reached in 5 cases (5%), and c) group 3 (n=28): the study was normal in 15 cases (53.6%) and showed focal interictal epileptic activity in 8 (28.6 %) and generalized interictal epileptic activity in 5 of them (17.8%). We believe that the ambulatory EEG recordings in correctly selected cases can provide important additional information regarding global assessment of patients with epilepsy.

Effect of invasive EEG monitoring on cognitive outcome after left temporal lobe epilepsy surgery.

PubMed

Busch, Robyn M; Love, Thomas E; Jehi, Lara E; Ferguson, Lisa; Yardi, Ruta; Najm, Imad; Bingaman, William; Gonzalez-Martinez, Jorge

2015-10-27

The objective of this cohort study was to compare neuropsychological outcomes following left temporal lobe resection (TLR) in patients with epilepsy who had or had not undergone prior invasive monitoring. Data were obtained from an institutional review board-approved, neuropsychology registry for patients who underwent epilepsy surgery at Cleveland Clinic between 1997 and 2013. A total of 176 patients (45 with and 131 without invasive EEG) met inclusion criteria. Primary outcome measures were verbal memory and language scores. Other cognitive outcomes were also examined. Outcomes were assessed using difference in scores from before to after surgery and by presence/absence of clinically meaningful decline using reliable change indices (RCIs). Effect of invasive EEG on cognitive outcomes was estimated using weighting and propensity score adjustment to account for differences in baseline characteristics. Linear and logistic regression models compared surgical groups on all cognitive outcomes. Patients with invasive monitoring showed greater declines in confrontation naming; however, when RCIs were used to assess clinically meaningful change, there was no significant treatment effect on naming performance. No difference in verbal memory was observed, regardless of how the outcome was measured. In secondary outcomes, patients with invasive monitoring showed greater declines in working memory, which were no longer apparent using RCIs to define change. There were no outcome differences on other cognitive measures. Results suggest that invasive EEG monitoring conducted prior to left TLR is not associated with greater cognitive morbidity than left TLR alone. This information is important when counseling patients regarding cognitive risks associated with this elective surgery. © 2015 American Academy of Neurology.

Brain negativity as an indicator of predictive error processing: the contribution of visual action effect monitoring.

PubMed

Joch, Michael; Hegele, Mathias; Maurer, Heiko; Müller, Hermann; Maurer, Lisa Katharina

2017-07-01

The error (related) negativity (Ne/ERN) is an event-related potential in the electroencephalogram (EEG) correlating with error processing. Its conditions of appearance before terminal external error information suggest that the Ne/ERN is indicative of predictive processes in the evaluation of errors. The aim of the present study was to specifically examine the Ne/ERN in a complex motor task and to particularly rule out other explaining sources of the Ne/ERN aside from error prediction processes. To this end, we focused on the dependency of the Ne/ERN on visual monitoring about the action outcome after movement termination but before result feedback (action effect monitoring). Participants performed a semi-virtual throwing task by using a manipulandum to throw a virtual ball displayed on a computer screen to hit a target object. Visual feedback about the ball flying to the target was masked to prevent action effect monitoring. Participants received a static feedback about the action outcome (850 ms) after each trial. We found a significant negative deflection in the average EEG curves of the error trials peaking at ~250 ms after ball release, i.e., before error feedback. Furthermore, this Ne/ERN signal did not depend on visual ball-flight monitoring after release. We conclude that the Ne/ERN has the potential to indicate error prediction in motor tasks and that it exists even in the absence of action effect monitoring. NEW & NOTEWORTHY In this study, we are separating different kinds of possible contributors to an electroencephalogram (EEG) error correlate (Ne/ERN) in a throwing task. We tested the influence of action effect monitoring on the Ne/ERN amplitude in the EEG. We used a task that allows us to restrict movement correction and action effect monitoring and to control the onset of result feedback. We ascribe the Ne/ERN to predictive error processing where a conscious feeling of failure is not a prerequisite. Copyright © 2017 the American Physiological Society.

Electroencephalographic imaging of higher brain function

NASA Technical Reports Server (NTRS)

Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.

1999-01-01

High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

Entropy as an indicator of cerebral perfusion in patients with increased intracranial pressure.

PubMed

Khan, James; Mariappan, Ramamani; Venkatraghavan, Lashmi

2014-07-01

Changes in electroencephalogram (EEG) patterns correlate well with changes in cerebral perfusion pressure (CPP) and hence entropy and bispectral index values may also correlate with CPP. To highlight the potential application of entropy, an EEG-based anesthetic depth monitor, on indicating cerebral perfusion in patients with increased intracranial pressure (ICP), we report two cases of emergency neurosurgical procedure in patients with raised ICP where anesthesia was titrated to entropy values and the entropy values suddenly increased after cranial decompression, reflecting the increase in CPP. Maintaining systemic blood pressure in order to maintain the CPP is the anesthetic goal while managing patients with raised ICP. EEG-based anesthetic depth monitors may hold valuable information on guiding anesthetic management in patients with decreased CPP for better neurological outcome.

Use of EEG in critically ill children and neonates in the United States of America.

PubMed

Gaínza-Lein, Marina; Sánchez Fernández, Iván; Loddenkemper, Tobias

2017-06-01

The objective of the study was to estimate the proportion of patients who receive an electroencephalogram (EEG) among five common indications for EEG monitoring in the intensive care unit: traumatic brain injury (TBI), extracorporeal membrane oxygenation (ECMO), cardiac arrest, cardiac surgery and hypoxic-ischemic encephalopathy (HIE). We performed a retrospective cross-sectional descriptive study utilizing the Kids' Inpatient Database (KID) for the years 2010-2012. The KID is the largest pediatric inpatient database in the USA and it is based on discharge reports created by hospitals for billing purposes. We evaluated the use of electroencephalogram (EEG) or video-electroencephalogram in critically ill children who were mechanically ventilated. The KID database had a population of approximately 6,000,000 pediatric admissions. Among 22,127 admissions of critically ill children who had mechanical ventilation, 1504 (6.8%) admissions had ECMO, 9201 (41.6%) TBI, 4068 (18.4%) HIE, 2774 (12.5%) cardiac arrest, and 4580 (20.7%) cardiac surgery. All five conditions had a higher proportion of males, with the highest (69.8%) in the TBI group. The mortality rates ranged from 7.02 to 39.9% (lowest in cardiac surgery and highest in ECMO). The estimated use of EEG was 1.6% in cardiac surgery, 4.1% in TBI, 7.2% in ECMO, 8.2% in cardiac arrest, and 12.1% in HIE, with an overall use of 5.8%. Among common indications for EEG monitoring in critically ill children and neonates, the estimated proportion of patients actually having an EEG is low.

Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

PubMed

Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung

2007-01-01

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

A total patient monitoring system for point-of-care applications

NASA Astrophysics Data System (ADS)

Whitchurch, Ashwin K.; Abraham, Jose K.; Varadan, Vijay K.

2007-04-01

Traditionally, home care for chronically ill patients and the elderly requires periodic visits to the patient's home by doctors or healthcare personnel. During these visits, the visiting person usually records the patient's vital signs and takes decisions as to any change in treatment and address any issues that the patient may have. Patient monitoring systems have since changed this scenario by significantly reducing the number of home visits while not compromising on continuous monitoring. This paper describes the design and development of a patient monitoring systems capable of concurrent remote monitoring of 8 patient-worn sensors: Electroencephalogram (EEG), Electrocardiogram (ECG), temperature, airflow pressure, movement and chest expansion. These sensors provide vital signs useful for monitoring the health of chronically ill patients and alerts can be raised if certain specified signal levels fall above or below a preset threshold value. The data from all eight sensors are digitally transmitted to a PC or to a standalone network appliance which relays the data through an available internet connection to the remote monitoring client. Thus it provides a real-time rendering of the patient's health at a remote location.

A preliminary study of muscular artifact cancellation in single-channel EEG.

PubMed

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K

2014-10-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery

PubMed Central

Zhang, Jing; Liu, Qingzhu; Mei, Shanshan; Zhang, Xiaoming; Wang, Xiaofei; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Li, Yunlin

2013-01-01

Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome. PMID:23926432

Intraoperative seizures during craniotomy under general anesthesia.

PubMed

Howe, John; Lu, Xiaoying; Thompson, Zoe; Peterson, Gordon W; Losey, Travis E

2016-05-01

An acute symptomatic seizure is a clinical seizure occurring at the time of or in close temporal association with a brain insult. We report an acute symptomatic seizure occurring during a surgical procedure in a patient who did not have a prior history of epilepsy and who did not have a lesion associated with an increased risk of epilepsy. To characterize the incidence and clinical features of intraoperative seizures during craniotomy under general anesthesia, we reviewed cases where continuous EEG was acquired during craniotomy. Records of 400 consecutive cases with propofol as general anesthesia during craniotomy were reviewed. Demographic data, indication for surgery, clinical history, history of prior seizures, duration of surgery and duration of burst suppression were recorded. Cases where seizures were observed were analyzed in detail. Two out of 400 patients experienced intraoperative seizures, including one patient who appeared to have an acute symptomatic seizure related to the surgical procedure itself and a second patient who experienced two seizures likely related to an underlying diagnosis of epilepsy. This is the first report of an acute symptomatic seizure secondary to a neurosurgical procedure. Overall, 0.5% of patients monitored experienced seizures, indicating that intraoperative seizures are rare, and EEG monitoring during craniotomies is of low yield in detecting seizures. Copyright © 2016. Published by Elsevier Ltd.

Performance of Spectrogram-Based Seizure Identification of Adult EEGs by Critical Care Nurses and Neurophysiologists.

PubMed

Amorim, Edilberto; Williamson, Craig A; Moura, Lidia M V R; Shafi, Mouhsin M; Gaspard, Nicolas; Rosenthal, Eric S; Guanci, Mary M; Rajajee, Venkatakrishna; Westover, M Brandon

2017-07-01

Continuous EEG screening using spectrograms or compressed spectral arrays (CSAs) by neurophysiologists has shorter review times with minimal loss of sensitivity for seizure detection when compared with visual analysis of raw EEG. Limited data are available on the performance characteristics of CSA-based seizure detection by neurocritical care nurses. This is a prospective cross-sectional study that was conducted in two academic neurocritical care units and involved 33 neurointensive care unit nurses and four neurophysiologists. All nurses underwent a brief training session before testing. Forty two-hour CSA segments of continuous EEG were reviewed and rated for the presence of seizures. Two experienced clinical neurophysiologists masked to the CSA data performed conventional visual analysis of the raw EEG and served as the gold standard. The overall accuracy was 55.7% among nurses and 67.5% among neurophysiologists. Nurse seizure detection sensitivity was 73.8%, and the false-positive rate was 1-per-3.2 hours. Sensitivity and false-alarm rate for the neurophysiologists was 66.3% and 1-per-6.4 hours, respectively. Interrater agreement for seizure screening was fair for nurses (Gwet AC1 statistic: 43.4%) and neurophysiologists (AC1: 46.3%). Training nurses to perform seizure screening utilizing continuous EEG CSA displays is feasible and associated with moderate sensitivity. Nurses and neurophysiologists had comparable sensitivities, but nurses had a higher false-positive rate. Further work is needed to improve sensitivity and reduce false-alarm rates.

Real-Time Detection and Monitoring of Acute Brain Injury Utilizing Evoked Electroencephalographic Potentials.

PubMed

Fisher, Jonathan A N; Huang, Stanley; Ye, Meijun; Nabili, Marjan; Wilent, W Bryan; Krauthamer, Victor; Myers, Matthew R; Welle, Cristin G

2016-09-01

Rapid detection and diagnosis of a traumatic brain injury (TBI) can significantly improve the prognosis for recovery. Helmet-mounted sensors that detect impact severity based on measurements of acceleration or pressure show promise for aiding triage and transport decisions in active, field environments such as professional sports or military combat. The detected signals, however, report on the mechanics of an impact rather than directly indicating the presence and severity of an injury. We explored the use of cortical somatosensory evoked electroencephalographic potentials (SSEPs) to detect and track, in real-time, neural electrophysiological abnormalities within the first hour following head injury in an animal model. To study the immediate electrophysiological effects of injury in vivo, we developed an experimental paradigm involving focused ultrasound that permits continuous, real-time measurements and minimizes mechanical artifact. Injury was associated with a dramatic reduction of amplitude over the damaged hemisphere directly after the injury. The amplitude systematically improved over time but remained significantly decreased at one hour, compared with baseline. In contrast, at one hour there was a concomitant enhancement of the cortical SSEP amplitude evoked from the uninjured hemisphere. Analysis of the inter-trial electroencephalogram (EEG) also revealed significant changes in low-frequency components and an increase in EEG entropy up to 30 minutes after injury, likely reflecting altered EEG reactivity to somatosensory stimuli. Injury-induced alterations in SSEPs were also observed using noninvasive epidermal electrodes, demonstrating viability of practical implementation. These results suggest cortical SSEPs recorded at just a few locations by head-mounted sensors and associated multiparametric analyses could potentially be used to rapidly detect and monitor brain injury in settings that normally present significant levels of mechanical and electrical noise.

Odds Ratio Product of Sleep EEG as a Continuous Measure of Sleep State

PubMed Central

Younes, Magdy; Ostrowski, Michele; Soiferman, Marc; Younes, Henry; Younes, Mark; Raneri, Jill; Hanly, Patrick

2015-01-01

Study Objectives: To develop and validate an algorithm that provides a continuous estimate of sleep depth from the electroencephalogram (EEG). Design: Retrospective analysis of polysomnograms. Setting: Research laboratory. Participants: 114 patients who underwent clinical polysomnography in sleep centers at the University of Manitoba (n = 58) and the University of Calgary (n = 56). Interventions: None. Measurements and Results: Power spectrum of EEG was determined in 3-second epochs and divided into delta, theta, alpha-sigma, and beta frequency bands. The range of powers in each band was divided into 10 aliquots. EEG patterns were assigned a 4-digit number that reflects the relative power in the 4 frequency ranges (10,000 possible patterns). Probability of each pattern occurring in 30-s epochs staged awake was determined, resulting in a continuous probability value from 0% to 100%. This was divided by 40 (% of epochs staged awake) producing the odds ratio product (ORP), with a range of 0–2.5. In validation testing, average ORP decreased progressively as EEG progressed from wakefulness (2.19 ± 0.29) to stage N3 (0.13 ± 0.05). ORP < 1.0 predicted sleep and ORP > 2.0 predicted wakefulness in > 95% of 30-s epochs. Epochs with intermediate ORP occurred in unstable sleep with a high arousal index (> 70/h) and were subject to much interrater scoring variability. There was an excellent correlation (r2 = 0.98) between ORP in current 30-s epochs and the likelihood of arousal or awakening occurring in the next 30-s epoch. Conclusions: Our results support the use of the odds ratio product (ORP) as a continuous measure of sleep depth. Citation: Younes M, Ostrowski M, Soiferman M, Younes H, Younes M, Raneri J, Hanly P. Odds ratio product of sleep EEG as a continuous measure of sleep state. SLEEP 2015;38(4):641–654. PMID:25348125

Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients' Consciousness Level Based on Anesthesiologists Experience

PubMed Central

Jiang, George J. A.; Fan, Shou-Zen; Abbod, Maysam F.; Huang, Hui-Hsun; Lan, Jheng-Yan; Tsai, Feng-Fang; Chang, Hung-Chi; Yang, Yea-Wen; Chuang, Fu-Lan; Chiu, Yi-Fang; Jen, Kuo-Kuang; Wu, Jeng-Fu; Shieh, Jiann-Shing

2015-01-01

Electroencephalogram (EEG) signals, as it can express the human brain's activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully. PMID:25738152

[Magnetoencephalography in the presurgical evaluation of patients with drug-resistant epilepsy].

PubMed

Koptelova, A M; Arkhipova, N A; Golovteev, A L; Chadaev, V A; Grinenko, O A; Kozlova, A B; Novikova, S I; Stepanenko, A Iu; Melikian, A G; Stroganova, T A

2013-01-01

Magnetoencephalography (MEG) in combination with structural MRI (magnetic source imaging, MSI) plays an increasingly important role as one of the tools for presurgical evaluation of medically intractable focal epilepsy. The aim of the study was to compare the MSI and commonly used video EEG monitoring method (vEEG) in their sensitivity to interictal epileptic discharges (IED) in 22 patients with drug resistant epilepsy. Furthermore, the detection and localization results obtained by both methods were verified using the data of electrocorticography (ECoG) and postsurgical outcome in 13 patients who underwent invasive EEG monitoring and surgery. The results showed that MSI was superior to vEEC in terms of sensitivity to IED with difference in sensitivity of 22%. The data also suggested that MSI superiority to vEEG in detecting epileptic discharges might, at least partly, arise from better MEG responsiveness to epileptic events coming from the medial, opercular and basal aspects of cortical lobes. MSI localization estimates were in the same cortical lobe and at the same lobar aspects as the epileptic foci detected by ECoG in all patients. Thus, magnetic source imaging can provide critical localization information that is not available when other noninvasive methods, such as vEEG and MRI, are used.

Exploring resting-state EEG brain oscillatory activity in relation to cognitive functioning in multiple sclerosis.

PubMed

Keune, Philipp M; Hansen, Sascha; Weber, Emily; Zapf, Franziska; Habich, Juliane; Muenssinger, Jana; Wolf, Sebastian; Schönenberg, Michael; Oschmann, Patrick

2017-09-01

Neurophysiologic monitoring parameters related to cognition in Multiple Sclerosis (MS) are sparse. Previous work reported an association between magnetoencephalographic (MEG) alpha-1 activity and information processing speed. While this remains to be replicated by more available electroencephalographic (EEG) methods, also other established EEG markers, e.g. the slow-wave/fast-wave ratio (theta/beta ratio), remain to be explored in this context. Performance on standard tests addressing information processing speed and attention (Symbol-Digit Modalities Test, SDMT; Test of Attention Performance, TAP) was examined in relation to resting-state EEG alpha-1 and alpha-2 activity and the theta/beta ratio in 25MS patients. Increased global alpha-1 and alpha-2 activity and an increased frontal theta/beta ratio (pronounced slow-wave relative to fast-wave activity) were associated with lower SDMT processing speed. In an exploratory analysis, clinically impaired attention was associated with a significantly increased frontal theta/beta ratio whereas alpha power did not show sensitivity to clinical impairment. EEG global alpha power and the frontal theta/beta ratio were both associated with attention. The theta/beta ratio involved potential clinical sensitivity. Resting-state EEG recordings can be obtained during the routine clinical process. The examined resting-state measures may represent feasible monitoring parameters in MS. This notion should be explored in future intervention studies. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring.

PubMed

Lv, Jun; Liu, Dongdong; Ma, Jing; Wang, Xiaoying; Zhang, Jue

2015-01-01

Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) time series. In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD) images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep. In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.

Portable Amplifier Design for a Novel EEG Monitor in Point-of-Care Applications.

PubMed

Luan, Bo; Sun, Mingui; Jia, Wenyan

2012-01-01

The Electroencephalography (EEG) is a common diagnostic tool for neurological diseases and dysfunctions, such as epilepsy and insomnia. However, the current EEG technology cannot be utilized quickly and conveniently at the point of care due to the complex skin preparation procedures required and the inconvenient EEG data acquisition systems. This work presents a portable amplifier design that integrates a set of skin screw electrodes and a wireless data link. The battery-operated amplifier contains an instrumentation amplifier, two noninverting amplifiers, two high-pass filters, and a low-pass filter. It is able to magnify the EEG signals over 10,000 times and has a high impedance, low noise, small size and low weight. Our electrode and amplifier are ideal for point-of-care applications, especially during transportation of patients suffering from traumatic brain injury or stroke.

Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation.

PubMed

Luu, Phan; Tucker, Don M; Makeig, Scott

2004-08-01

The error-related negativity (ERN) is an event-related potential (ERP) peak occurring between 50 and 100 ms after the commission of a speeded motor response that the subject immediately realizes to be in error. The ERN is believed to index brain processes that monitor action outcomes. Our previous analyses of ERP and EEG data suggested that the ERN is dominated by partial phase-locking of intermittent theta-band EEG activity. In this paper, this possibility is further evaluated. The possibility that the ERN is produced by phase-locking of theta-band EEG activity was examined by analyzing the single-trial EEG traces from a forced-choice speeded response paradigm before and after applying theta-band (4-7 Hz) filtering and by comparing the averaged and single-trial phase-locked (ERP) and non-phase-locked (other) EEG data. Electrical source analyses were used to estimate the brain sources involved in the generation of the ERN. Beginning just before incorrect button presses in a speeded choice response paradigm, midfrontal theta-band activity increased in amplitude and became partially and transiently phase-locked to the subject's motor response, accounting for 57% of ERN peak amplitude. The portion of the theta-EEG activity increase remaining after subtracting the response-locked ERP from each trial was larger and longer lasting after error responses than after correct responses, extending on average 400 ms beyond the ERN peak. Multiple equivalent-dipole source analysis suggested 3 possible equivalent dipole sources of the theta-bandpassed ERN, while the scalp distribution of non-phase-locked theta amplitude suggested the presence of additional frontal theta-EEG sources. These results appear consistent with a body of research that demonstrates a relationship between limbic theta activity and action regulation, including error monitoring and learning.

Reproducibility of EEG-fMRI results in a patient with fixation-off sensitivity.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Bongiovanni, Luigi Giuseppe; Cerini, Roberto; Fiaschi, Antonio; Manganotti, Paolo

2014-07-01

Blood oxygenation level-dependent (BOLD) activation associated with interictal epileptiform discharges in a patient with fixation-off sensitivity (FOS) was studied using a combined electroencephalography-functional magnetic resonance imaging (EEG-fMRI) technique. An automatic approach for combined EEG-fMRI analysis and a subject-specific hemodynamic response function was used to improve general linear model analysis of the fMRI data. The EEG showed the typical features of FOS, with continuous epileptiform discharges during elimination of central vision by eye opening and closing and fixation; modification of this pattern was clearly visible and recognizable. During all 3 recording sessions EEG-fMRI activations indicated a BOLD signal decrease related to epileptiform activity in the parietal areas. This study can further our understanding of this EEG phenomenon and can provide some insight into the reliability of the EEG-fMRI technique in localizing the irritative zone.

The effects of mild hypothermia on thiopental-induced electroencephalogram burst suppression.

PubMed

Kim, J H; Kim, S H; Yoo, S K; Kim, J Y; Nam, Y T

1998-07-01

Thiopental intravenous injections before temporary clipping and mild hypothermia have protective effects in the setting of cerebral ischemia, and are used clinically in some centers. However, it is not known whether mild hypothermia affects thiopental-induced electroencephalogram (EEG) burst suppression. In this study, the authors compared the onset and duration of EEG suppression by thiopental in normothermic (n=10) and mildly hypothermic (n=10) patients undergoing cerebral aneurysm surgery. Spectral analysis was used to compare the prethiopentonal continuous EEG patterns in normothermic and mild hypothermic patients. The patients' body temperatures were controlled by a circulating water mattress and intravenous fluids (normothermia = 36.4+/-0.1 degrees C, mild hypothermia = 33.3+/-0.1 degrees C). Immediately before temporary clipping, thiopental sodium (5 mg/kg) was administered intravenously. Onset time (the amount of time from thiopental injection to the first complete EEG suppression), duration of suppression (the amount of time from the first complete EEG suppression to recovery on continuous EEG from burst suppression), and maximum duration of isoelectric EEG (the longest time interval between two bursts during burst suppression) were measured. Onset time was shortened (25.8+/-1.4 versus 43.5+/-5.6 seconds), and duration of suppression (531.0+/-56.6 versus 165.0+/-16.9 seconds) and the maximum duration of isoelectric EEG (47.7+/-5.8 versus 22.8+/-2.0 seconds) were prolonged in the patients with mild hypothermia. In two normothermic patients, the standard dose of thiopental did not produce burst suppression, but only a mild decrease in spectral edge frequency. The authors concluded that the effects of mild hypothermia on thiopental-induced EEG suppression are not simply additive, but synergistic.

Analysis of bioelectric records and fabrication of phototype sleep analysis equipment

NASA Technical Reports Server (NTRS)

Kellaway, P.

1972-01-01

A computer-analysis technique was used to evaluate the changes in the waking EEGs of 5 normal subjects which occurred during the oral administration of flurazepam hydrochloride (Dalmane). While the subjects were receiving the drug, there was an increase in the amount of beta (14-38 c/sec) activity in fronto-central EEG leads in all 5 subjects. This increase in beta activity was characterized by a highly consistent increase in the number of waves that occurred during an EEG recording interval of fixed duration and by a less consistent increase in average wave amplitude. There was no detectable change in mean EEG wavelength (frequency) within the beta frequency range. The EEG patterns reverted to their baseline condition during 2-3 weeks after withdrawal of the drug. Analysis of the alpha, theta and delta components of the EEG indicated no changes during or following administration of the drug. This study clearly illustrates the usefulness of specific computer-analysis techniques in the characterization and quantification of sleep-promoting drugs upon the EEG of the normal young adults in the waking state. Two preamplifiers and 150 EEG monitoring caps with electrodes were delivered to MSC.

Real-time Adaptive EEG Source Separation using Online Recursive Independent Component Analysis

PubMed Central

Hsu, Sheng-Hsiou; Mullen, Tim; Jung, Tzyy-Ping; Cauwenberghs, Gert

2016-01-01

Independent Component Analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: (a) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; (b) capability to detect and adapt to non-stationarity in 64-ch simulated EEG data; and (c) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces. PMID:26685257

Quantitative EEG and its Correlation with Cardiovascular, Cognition and mood State: an Integrated Study in Simulated Microgravity

NASA Astrophysics Data System (ADS)

Zhang, Jianyuan; Hu, Bin; Chen, Wenjuan; Moore, Philip; Xu, Tingting; Dong, Qunxi; Liu, Zhenyu; Luo, Yuejia; Chen, Shanguang

2014-12-01

The focus of the study is the estimation of the effects of microgravity on the central nervous activity and its underlying influencing mechanisms. To validate the microgravity-induced physiological and psychological effects on EEG, quantitative EEG features, cardiovascular indicators, mood state, and cognitive performances data collection was achieved during a 45 day period using a -6°head-down bed rest (HDBR) integrated approach. The results demonstrated significant differences in EEG data, as an increased Theta wave, a decreased Beta wave and a reduced complexity of brain, accompanied with an increased heart rate and pulse rate, decreased positive emotion, and degraded emotion conflict monitoring performance. The canonical correlation analysis (CCA) based cardiovascular and cognitive related EEG model showed the cardiovascular effect on EEG mainly affected bilateral temporal region and the cognitive effect impacted parietal-occipital and frontal regions. The results obtained in the study support the use of an approach which combines a multi-factor influential mechanism hypothesis. The changes in the EEG data may be influenced by both cardiovascular and cognitive effects.

EEG entropy measures in anesthesia

PubMed Central

Liang, Zhenhu; Wang, Yinghua; Sun, Xue; Li, Duan; Voss, Logan J.; Sleigh, Jamie W.; Hagihira, Satoshi; Li, Xiaoli

2015-01-01

Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression. Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents. Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared. Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation efficiency compared with MDFA. Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure. Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA. PMID:25741277

Protocol Based Real-Time Continuous Electroencephalography for Detecting Vasospasm in Subarachnoid Hemorrhage.

PubMed

Hong, Jeong-Ho; Bang, Jae Seung; Chung, Jin-Heon; Han, Moon-Ku

2016-03-01

A continuous electroencephalography (cEEG) can be helpful in detecting vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage (SAH). We describe a patient with an aneurysmal SAH whose symptomatic vasospasm was detected promptly by using a real-time cEEG. Patient was immediately treated by intraarterial vasodilator therapy. A 50-year-old woman without any significant medical history presented with a severe bifrontal headache due to acute SAH with a ruptured aneurysm on the anterior communicating artery (Fisher grade 3). On bleed day 6, she developed a sudden onset of global aphasia and left hemiparesis preceded by cEEG changes consistent with vasospasm. A stat chemical dilator therapy was performed and she recovered without significant neurological deficits. A real-time and protocol-based cEEG can be utilized in order to avoid any delay in detection of vasospasm in aneurysmal SAH and thereby improve clinical outcomes.

Qualitative and Quantitative Characteristics of the Electroencephalogram in Normal Horses during Administration of Inhaled Anesthesia.

PubMed

Williams, D C; Brosnan, R J; Fletcher, D J; Aleman, M; Holliday, T A; Tharp, B; Kass, P H; LeCouteur, R A; Steffey, E P

2016-01-01

The effects of anesthesia on the equine electroencephalogram (EEG) after administration of various drugs for sedation, induction, and maintenance are known, but not that the effect of inhaled anesthetics alone for EEG recording. To determine the effects of isoflurane and halothane, administered as single agents at multiple levels, on the EEG and quantitative EEG (qEEG) of normal horses. Six healthy horses. Prospective study. Digital EEG with video and quantitative EEG (qEEG) were recorded after the administration of one of the 2 anesthetics, isoflurane or halothane, at 3 alveolar doses (1.2, 1.4 and 1.6 MAC). Segments of EEG during controlled ventilation (CV), spontaneous ventilation (SV), and with peroneal nerve stimulation (ST) at each MAC multiple for each anesthetic were selected, analyzed, and compared. Multiple non-EEG measurements were also recorded. Specific raw EEG findings were indicative of changes in the depth of anesthesia. However, there was considerable variability in EEG between horses at identical MAC multiples/conditions and within individual horses over segments of a given epoch. Statistical significance for qEEG variables differed between anesthetics with bispectral index (BIS) CV MAC and 95% spectral edge frequency (SEF95) SV MAC differences in isoflurane only and median frequency (MED) differences in SV MAC with halothane only. Unprocessed EEG features (background and transients) appear to be beneficial for monitoring the depth of a particular anesthetic, but offer little advantage over the use of changes in mean arterial pressure for this purpose. Copyright © 2015 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Reduction of the Dimensionality of the EEG Channels during Scoliosis Correction Surgeries Using a Wavelet Decomposition Technique

PubMed Central

Al-Kadi, Mahmoud I.; Reaz, Mamun Bin Ibne; Ali, Mohd Alauddin Mohd; Liu, Chian Yong

2014-01-01

This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria's value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded from six patients who underwent scoliosis correction surgeries in the Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) (the Medical center of National University of Malaysia). The combinational signal was tested by power spectral density, cross-correlation function and wavelet coherence. The experimental results show that the system-outputted EEG signals are neatly switched without any substantial changes in the consistency of EEG components. This paper provides an efficient procedure for analyzing EEG signals in order to avoid averaging the channels that lead to redistribution of the noise on both channels, reducing the dimensionality of the EEG features and preparing the best EEG stream for the classification and monitoring stage. PMID:25051031

Pharmacological classification of herbal extracts by means of comparison to spectral EEG signatures induced by synthetic drugs in the freely moving rat.

PubMed

Dimpfel, Wilfried

2013-09-16

Herbal extracts targeting at the brain remain a continuous challenge to pharmacology. Usually, a number of different animal tests have to be performed in order to find a potential clinical use. Due to manifold possibly active ingredients biochemical approaches are difficult. A more holistic approach using a neurophysiological technique has been developed earlier in order to characterise synthetic drugs. Stereotactic implantation of four semi-microelectrodes into frontal cortex, hippocampus, striatum and reticular formation of rats allowed continuous wireless monitoring of field potentials (EEG) before and after drug intake. After frequency analysis (Fast Fourier Transformation) electric power was calculated for 6 ranges (delta, theta, alpha1, alpha2, beta1 and beta2). Data from 14 synthetic drugs - tested earlier and representative for different clinical indications - were taken for construction of discriminant functions showing the projection of the frequency patterns in a six-dimensional graph. Quantitative analysis of the EEG frequency pattern from the depth of the brain succeeded in discrimination of drug effects according to their known clinical indication (Dimpfel and Schober, 2003). Extracts from Valerian root, Ginkgo leaves, Paullinia seed, Hop strobile, Rhodiola rosea root and Sideritis scardica herb were tested now under identical conditions. Classification of these extracts based on the matrix from synthetic drugs revealed that Valerian root and hop induced a pattern reminiscent of physiological sleep. Ginkgo and Paullinia appeared in close neighbourhood of stimulatory drugs like caffeine or to an analgesic profile (tramadol). Rhodiola and Sideritis developed similar frequency patterns comparable to a psychostimulant drug (methylphenidate) as well to an antidepressive drug (paroxetine). © 2013 The Author. Published by Elsevier Ireland Ltd. All rights reserved.

Processed electroencephalogram during donation after cardiac death.

PubMed

Auyong, David B; Klein, Stephen M; Gan, Tong J; Roche, Anthony M; Olson, Daiwai; Habib, Ashraf S

2010-05-01

We present a case series of increased bispectral index values during donation after cardiac death (DCD). During the DCD process, a patient was monitored with processed electroencephalogram (EEG), which showed considerable changes traditionally associated with lighter planes of anesthesia immediately after withdrawal of care. Subsequently, to validate the findings of this case, processed EEG was recorded during 2 other cases in which care was withdrawn without the use of hypnotic or anesthetic drugs. We found that changes in processed EEG immediately after withdrawal of care were not only reproducible, but can happen in the absence of changes in major electromyographic or electrocardiographic artifact. It is well documented that processed EEG is prone to artifacts. However, in the setting of DCD, these changes in processed EEG deserve some consideration. If these changes are not due to artifact, dosing of hypnotic or anesthetic drugs might be warranted. Use of these drugs during DCD based primarily on processed EEG values has never been addressed.

Monitoring alert and drowsy states by modeling EEG source nonstationarity

NASA Astrophysics Data System (ADS)

Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

2017-10-01

Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to monitoring cognitive or mental states of human operators in attention-critical settings or in passive brain-computer interfaces.

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

PubMed Central

Bleichner, Martin G.; Debener, Stefan

2017-01-01

Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG. PMID:28439233

Effects of Neurofeekback Training on EEG, Continuous Performance Task (CPT), and ADHD Symptoms in ADHD-prone College Students.

PubMed

Ryoo, Manhee; Son, Chongnak

2015-12-01

This study explored the effects of neurofeedback training on Electroencephalogram (EEG), Continuous Performance Task (CPT) and ADHD symptoms in ADHD prone college students. Two hundred forty seven college students completed Korean Version of Conners' Adult ADHD Rating Scales (CAARS-K) and Korean Version of Beck Depression Inventory (K-BDI). The 16 participants who ranked in the top 25% of CAARS-K score and had 16 less of K-BDI score participated in this study. Among them, 8 participants who are fit for the research schedule were assigned to neurofeedback training group and 8 not fit for the research schedule to the control group. All participants completed Adult Attention Deficiency Questionnaire, CPT and EEG measurement at pretest. The neurofeedback group received 15 neurofeedback training sessions (5 weeks, 3 sessions per week). The control group did not receive any treatment. Four weeks after completion of the program, all participants completed CAARS-K, Adult Attention Deficiency Questionnaire, CPT and EEG measurement for post-test. The neurofeedback group showed more significant improvement in EEG, CPT performance and ADHD symptoms than the control group. The improvements were maintained at follow up. Neurofeedback training adjusted abnormal EEG and was effective in improving objective and subjective ADHD symptoms in ADHD prone college students.

Using a virtual training program to train community neurologist on EEG reading skills.

PubMed

Ochoa, Juan; Naritoku, Dean K

2012-01-01

EEG training requires iterative exposure of different patterns with continuous feedback from the instructor. This training is traditionally acquired through a traditional fellowship program, but only 28% of neurologists in training plan to do a fellowship in EEG. The purpose of this study was to determine the value of online EEG training to improve EEG knowledge among general neurologists. The participants were general neurologists invited through bulk e-mail and paid a fee to enroll in the virtual EEG program. A 40-question pretest exam was performed before training. The training included 4 online learning units about basic EEG principles and 40 online clinical EEG tutorials. In addition there were weekly live teleconferences for Q&A sessions. At the end of the program, the participants were asked to complete a posttest exam. Fifteen of 20 participants successfully completed the program and took both the pre- and posttest exams. All the subjects scored significantly higher in the posttest compared to their baseline score. The average score in the pretest evaluation was 61.7% and the posttest average was 87.8% (p = .0002, two-tailed). Virtual EEG training can improve EEG knowledge among community neurologists.

Long-term monitoring of cardiorespiratory patterns in drug-resistant epilepsy.

PubMed

Goldenholz, Daniel M; Kuhn, Amanda; Austermuehle, Alison; Bachler, Martin; Mayer, Christopher; Wassertheurer, Siegfried; Inati, Sara K; Theodore, William H

2017-01-01

Sudden unexplained death in epilepsy (SUDEP) during inpatient electroencephalography (EEG) monitoring has been a rare but potentially preventable event, with associated cardiopulmonary markers. To date, no systematic evaluation of alarm settings for a continuous pulse oximeter (SpO 2 ) has been performed. In addition, evaluation of the interrelationship between the ictal and interictal states for cardiopulmonary measures has not been reported. Patients with epilepsy were monitored using video-EEG, SpO 2 , and electrocardiography (ECG). Alarm thresholds were tested systematically, balancing the number of false alarms with true seizure detections. Additional cardiopulmonary patterns were explored using automated ECG analysis software. One hundred ninety-three seizures (32 generalized) were evaluated from 45 patients (7,104 h recorded). Alarm thresholds of 80-86% SpO 2 detected 63-73% of all generalized convulsions and 20-28% of all focal seizures (81-94% of generalized and 25-36% of focal seizures when considering only evaluable data). These same thresholds resulted in 25-146 min between false alarms. The sequential probability of ictal SpO 2 revealed a potential common seizure termination pathway of desaturation. A statistical model of corrected QT intervals (QTc), heart rate (HR), and SpO 2 revealed close cardiopulmonary coupling ictally. Joint probability maps of QTc and SpO 2 demonstrated that many patients had baseline dysfunction in either cardiac, pulmonary, or both domains, and that ictally there was dissociation-some patients exhibited further dysfunction in one or both domains. Optimal selection of continuous pulse oximetry thresholds involves a tradeoff between seizure detection accuracy and false alarm frequency. Alarming at 86% for patients that tend to have fewer false alarms and at 80% for those who have more, would likely result in a reasonable tradeoff. The cardiopulmonary findings may lead to SUDEP biomarkers and early seizure termination therapies. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Visual cortex responses reflect temporal structure of continuous quasi-rhythmic sensory stimulation.

PubMed

Keitel, Christian; Thut, Gregor; Gross, Joachim

2017-02-01

Neural processing of dynamic continuous visual input, and cognitive influences thereon, are frequently studied in paradigms employing strictly rhythmic stimulation. However, the temporal structure of natural stimuli is hardly ever fully rhythmic but possesses certain spectral bandwidths (e.g. lip movements in speech, gestures). Examining periodic brain responses elicited by strictly rhythmic stimulation might thus represent ideal, yet isolated cases. Here, we tested how the visual system reflects quasi-rhythmic stimulation with frequencies continuously varying within ranges of classical theta (4-7Hz), alpha (8-13Hz) and beta bands (14-20Hz) using EEG. Our findings substantiate a systematic and sustained neural phase-locking to stimulation in all three frequency ranges. Further, we found that allocation of spatial attention enhances EEG-stimulus locking to theta- and alpha-band stimulation. Our results bridge recent findings regarding phase locking ("entrainment") to quasi-rhythmic visual input and "frequency-tagging" experiments employing strictly rhythmic stimulation. We propose that sustained EEG-stimulus locking can be considered as a continuous neural signature of processing dynamic sensory input in early visual cortices. Accordingly, EEG-stimulus locking serves to trace the temporal evolution of rhythmic as well as quasi-rhythmic visual input and is subject to attentional bias. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

[EEG-correlates of pilots' functional condition in simulated flight dynamics].

PubMed

Kiroy, V N; Aslanyan, E V; Bakhtin, O M; Minyaeva, N R; Lazurenko, D M

2015-01-01

The spectral characteristics of the EEG recorded on two professional pilots in the simulator TU-154 aircraft in flight dynamics, including takeoff, landing and horizontal flight (in particular during difficult conditions) were analyzed. EEG recording was made with frequency band 0.1-70 Hz continuously from 15 electrodes. The EEG recordings were evaluated using analysis of variance and discriminant analysis. Statistical significant of the identified differences and the influence of the main factors and their interactions were evaluated using Greenhouse - Gaiser corrections. It was shown that the spectral characteristics of the EEG are highly informative features of the state of the pilots, reflecting the different flight phases. High validity ofthe differences including individual characteristic, indicates their non-random nature and the possibility of constructing a system of pilots' state control during all phases of flight, based on EEG features.

EEG patterns in theta and gamma frequency range and their probable relation to human voluntary movement organization.

PubMed

Popivanov, D; Mineva, A; Krekule, I

1999-05-21

In experiments with EEG accompanying continuous slow goal-directed voluntary movements we found abrupt short-term transients (STs) of the coefficients of EEG time-varying autoregressive (TVAR) model. The onset of STs indicated (i) a positive EEG wave related to an increase of 3-7 Hz oscillations in time period before the movement start, (ii) synchronization of 35-40 Hz prior to movement start and during the movement when the target is nearly reached. Both these phenomena are expressed predominantly over supplementary motor area, premotor and parietal cortices. These patterns were detected after averaging of EEG segments synchronized to the abrupt changes of the TVAR coefficients computed in the time course of EEG single records. The results are discussed regarding the cognitive aspect of organization of goal-directed movements.

Graph Theory at the Service of Electroencephalograms.

PubMed

Iakovidou, Nantia D

2017-04-01

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

Comparison of intraosseous pentobarbital administration and thoracic compression for euthanasia of anesthetized sparrows (Passer domesticus) and starlings (Sturnus vulgaris).

PubMed

Paul-Murphy, Joanne R; Engilis, Andrew; Pascoe, Peter J; Williams, D Colette; Gustavsen, Kate A; Drazenovich, Tracy L; Keel, M Kevin; Polley, Tamsen M; Engilis, Irene E

2017-08-01

OBJECTIVE To compare intraosseous pentobarbital treatment (IPT) and thoracic compression (TC) on time to circulatory arrest and an isoelectric electroencephalogram (EEG) in anesthetized passerine birds. ANIMALS 30 wild-caught adult birds (17 house sparrows [Passer domesticus] and 13 European starlings [Sturnus vulgaris]). PROCEDURES Birds were assigned to receive IPT or TC (n = 6/species/group). Birds were anesthetized, and carotid arterial pulses were monitored by Doppler methodology. Five subdermal braided-wire electrodes were used for EEG. Anesthetic depth was adjusted until a continuous EEG pattern was maintained, then euthanasia was performed. Times from initiation of euthanasia to cessation of carotid pulse and irreversible isoelectric EEG (indicators of death) were measured. Data (medians and first to third quartiles) were summarized and compared between groups within species. Necropsies were performed for all birds included in experiments and for another 6 birds euthanized under anesthesia by TC (4 sparrows and 1 starling) or IPT (1 sparrow). RESULTS Median time to isoelectric EEG did not differ significantly between treatment groups for sparrows (19.0 and 6.0 seconds for TC and IPT, respectively) or starlings (88.5 and 77.5 seconds for TC and IPT, respectively). Median times to cessation of pulse were significantly shorter for TC than for IPT in sparrows (0.0 vs 18.5 seconds) and starlings (9.5 vs 151.0 seconds). On necropsy, most (14/17) birds that underwent TC had grossly visible coelomic, pericardial, or perihepatic hemorrhage. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that TC might be an efficient euthanasia method for small birds. Digital pressure directly over the heart during TC obstructed venous return, causing rapid circulatory arrest, with rupture of the atria or vena cava in several birds. The authors propose that cardiac compression is a more accurate description than TC for this procedure.

PRISM: A DATA-DRIVEN PLATFORM FOR MONITORING MENTAL HEALTH

PubMed Central

KAMDAR, MAULIK R.; WU, MICHELLE J.

2018-01-01

Neuropsychiatric disorders are the leading cause of disability worldwide and there is no gold standard currently available for the measurement of mental health. This issue is exacerbated by the fact that the information physicians use to diagnose these disorders is episodic and often subjective. Current methods to monitor mental health involve the use of subjective DSM-5 guidelines, and advances in EEG and video monitoring technologies have not been widely adopted due to invasiveness and inconvenience. Wearable technologies have surfaced as a ubiquitous and unobtrusive method for providing continuous, quantitative data about a patient. Here, we introduce PRISM — Passive, Real-time Information for Sensing Mental Health. This platform integrates motion, light and heart rate data from a smart watch application with user interactions and text insights from a web application. We have demonstrated a proof of concept by collecting preliminary data through a pilot study of 13 subjects. We have engineered appropriate features and applied both unsupervised and supervised learning to develop models that can recapitulate user-reported ratings of their emotional state. This demonstrates that the data has the potential to be useful for evaluating mental health. This platform will allow us to leverage continuous streams of passive data for early and accurate diagnosis as well as constant monitoring of patients suffering from mental disorders. PMID:26776198

Continuous EEG-fMRI in Pre-Surgical Evaluation of a Patient with Symptomatic Seizures: Bold Activation Linked to Interictal Epileptic Discharges Caused by Cavernoma.

PubMed

Avesani, M; Formaggio, E; Milanese, F; Baraldo, A; Gasparini, A; Cerini, R; Bongiovanni, L G; Pozzi Mucelli, R; Fiaschi, A; Manganotti, P

2008-04-07

We used continuous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to identify the linkage between the "epileptogenic" and the "irritative" area in a patient with symptomatic epilepsy (cavernoma, previously diagnosed and surgically treated), i.e. a patient with a well known "epileptogenic area", and to increase the possibility of a non invasive pre-surgical evaluation of drug-resistant epilepsies. A compatible MRI system was used (EEG with 29 scalp electrodes and two electrodes for ECG and EMG) and signals were recorded with a 1.5 Tesla MRI scanner. After the recording session and MRI artifact removal, EEG data were analyzed offline and used as paradigms in fMRI study. Activation (EEG sequences with interictal slow-spiked-wave activity) and rest (sequences of normal EEG) conditions were compared to identify the potential resulting focal increase in BOLD signal and to consider if this is spatially linked to the interictal focus used as a paradigm and to the lesion. We noted an increase in the BOLD signal in the left neocortical temporal region, laterally and posteriorly to the poro-encephalic cavity (residual of cavernoma previously removed), that is around the "epileptogenic area". In our study "epileptogenic" and "irritative" areas were connected with each other. Combined EEG-fMRI may become routine in clinical practice for a better identification of an irritative and lesional focus in patients with symptomatic drug-resistant epilepsy.

Do patients need to stay in bed all day in the Epilepsy Monitoring Unit? Safety data from a non-restrictive setting.

PubMed

Craciun, Laura; Alving, Jørgen; Gardella, Elena; Terney, Daniella; Meritam, Pirgit; Cacic Hribljan, Melita; Beniczky, Sándor

2017-07-01

To assess whether injuries occur more often in an Epilepsy Monitoring Unit (EMU) where portable EEG amplifiers are used, and where patients can freely move within a large area during the monitoring. Patients were monitored at the Danish Epilepsy Center, in an EMU specifically designed for this purpose, and they were under continuous surveillance by personnel dedicated to the EMU. Adverse events (AEs) - including injuries, were prospectively noted, as part of the safety policy of the hospital. Other data were retrospectively extracted from the electronic database, for a 5-year period (January 2012-December 2016). 976 patients were admitted to the EMU. Falls occurred in 19 patients (1.9%) but none of them resulted in injury. Only one serious AE occurred: a patient had a convulsive status epilepticus, which did not respond to first-line treatment in the EMU and was transferred to the intensive care unit. The rate of AEs were similar or lower than previously reported by other centers, where the mobility of the patients had been restricted during monitoring. In an EMU specially designed for this purpose, where patients are under continuous surveillance by personnel dedicated to the EMU, injuries can be avoided even when the mobility of the patients is not restricted. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Flexible electroencephalogram (EEG) headband

NASA Technical Reports Server (NTRS)

Raggio, L. J.

1973-01-01

Headband incorporates sensors which are embedded in sponges and are exposed only on surface that touches skin. Electrode sponge system is continually fed electrolyte through forced feed vacuum system. Headband may be used for EEG testing in hospitals, clinical laboratories, rest homes, and law enforcement agencies.

Detection of burst suppression patterns in EEG using recurrence rate.

PubMed

Liang, Zhenhu; Wang, Yinghua; Ren, Yongshao; Li, Duan; Voss, Logan; Sleigh, Jamie; Li, Xiaoli

2014-01-01

Burst suppression is a unique electroencephalogram (EEG) pattern commonly seen in cases of severely reduced brain activity such as overdose of general anesthesia. It is important to detect burst suppression reliably during the administration of anesthetic or sedative agents, especially for cerebral-protective treatments in various neurosurgical diseases. This study investigates recurrent plot (RP) analysis for the detection of the burst suppression pattern (BSP) in EEG. The RP analysis is applied to EEG data containing BSPs collected from 14 patients. Firstly we obtain the best selection of parameters for RP analysis. Then, the recurrence rate (RR), determinism (DET), and entropy (ENTR) are calculated. Then RR was selected as the best BSP index one-way analysis of variance (ANOVA) and multiple comparison tests. Finally, the performance of RR analysis is compared with spectral analysis, bispectral analysis, approximate entropy, and the nonlinear energy operator (NLEO). ANOVA and multiple comparison tests showed that the RR could detect BSP and that it was superior to other measures with the highest sensitivity of suppression detection (96.49%, P = 0.03). Tracking BSP patterns is essential for clinical monitoring in critically ill and anesthetized patients. The purposed RR may provide an effective burst suppression detector for developing new patient monitoring systems.

The state of everyday quantitative EEG use in Canada: A national technologist survey.

PubMed

Ng, Marcus C; Gillis, Kara

2017-07-01

This study sought to determine the state of quantitative EEG (QEEG) use in Canada, as QEEG may provide a partial solution to the issue of escalating EEG demand against insufficient health care resources. A 10-item survey questionnaire was administered to participants at the annual meeting of the Canadian Association of Electroneurophysiology Technologists, which was held in parallel with the annual meeting of the Canadian Neurological Sciences Federation. At least 70% of the Canadian population has QEEG access through academic medical institutions with applicability to adults and children. QEEG was clinically used 50% in real-time and 50% retrospectively in the critical care and epilepsy monitoring units for long-term monitoring and automated seizure detection. QEEG trend use, montage use, and duration were variable. To cope with insufficient health care resources, QEEG is in surprisingly frequent clinical use across Canada. There is no consensus on optimal QEEG trends and montages. The relative ubiquity of QEEG affords an excellent opportunity for research as increasing EEG demand outpaces dwindling health care resources into the foreseeable future. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Narcolepsy in a three-year-old girl: A case report.

PubMed

Park, Eu Gene; Lee, Jiwon; Joo, Eun Yeon; Lee, Munhyang; Lee, Jeehun

2016-01-01

Narcolepsy is characterized by excessive daytime somnolence associated with sleep paralysis, hallucinations when falling asleep or awakening, and cataplexy. Early recognition of pediatric narcolepsy is essential for growth and development. We experienced a case of narcolepsy in a three-year-old girl. The patient underwent brain MRI and 24h video-electroencephalogram (EEG) monitoring. Polysomnography (PSG) with multiple sleep latency test (MSLT) and human leukocyte antigen (HLA) DQ typing was performed. The brain MRI was normal. 24h video-EEG monitoring revealed no abnormal slow or epileptiform discharge on interictal EEG, and no EEG change during tongue thrusting, dropping head with laughter, or flopping down, which was consistent with cataplexy associated with narcolepsy. A mean sleep latency of 2.5 min and four episodes of sleep-onset REM periods in five naps were observed in PSG with MSLT. She was positive in HLA-DQB1*0602. Based on these findings, she was diagnosed as narcoleptic with cataplexy. The history, combined with PSG and MSLT, was helpful in the diagnosis of narcolepsy. We report a case of early-onset narcolepsy presenting with excessive sleepiness and cataplexy. Copyright © 2015 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Removing ballistocardiogram (BCG) artifact from full-scalp EEG acquired inside the MR scanner with Orthogonal Matching Pursuit (OMP)

PubMed Central

Xia, Hongjing; Ruan, Dan; Cohen, Mark S.

2014-01-01

Ballistocardiogram (BCG) artifact remains a major challenge that renders electroencephalographic (EEG) signals hard to interpret in simultaneous EEG and functional MRI (fMRI) data acquisition. Here, we propose an integrated learning and inference approach that takes advantage of a commercial high-density EEG cap, to estimate the BCG contribution in noisy EEG recordings from inside the MR scanner. To estimate reliably the full-scalp BCG artifacts, a near-optimal subset (20 out of 256) of channels first was identified using a modified recording setup. In subsequent recordings inside the MR scanner, BCG-only signal from this subset of channels was used to generate continuous estimates of the full-scalp BCG artifacts via inference, from which the intended EEG signal was recovered. The reconstruction of the EEG was performed with both a direct subtraction and an optimization scheme. We evaluated the performance on both synthetic and real contaminated recordings, and compared it to the benchmark Optimal Basis Set (OBS) method. In the challenging non-event-related-potential (non-ERP) EEG studies, our reconstruction can yield more than fourteen-fold improvement in reducing the normalized RMS error of EEG signals, compared to OBS. PMID:25120421

Nonconvulsive Status Epilepticus After Electroconvulsive Therapy: A Review of Literature.

PubMed

Aftab, Awais; VanDercar, Ashley; Alkhachroum, Ayham; LaGrotta, Christine; Gao, Keming

The clinical presentation and risk factors of nonconvulsive status epilepticus (NCSE) in the context of electroconvulsive therapy (ECT) are poorly understood, and guidance regarding diagnosis and management remains scarce. In this article, we identify case reports of ECT-induced NCSE from literature, and discuss the presentation, diagnosis, and management of these cases in the context of what is known about NCSE from the neurology literature. A literature search on PubMed for case reports of NCSE after ECT. We identified 13 cases for this review. Diagnosis in all cases was based on clinical features and electroencephalogram (EEG) findings. Clinical presentation was altered mental status or unresponsiveness, with subtle motor phenomena in some cases. All cases had nonspecific risk factors that have been associated with prolonged seizures and convulsions, such as recent discontinuation/reduction of benzodiazepines or anticonvulsants, and concurrent use of antipsychotics and antidepressants. All patients were treated with either benzodiazepines or antiepileptic agents. Outcomes in these post-ECT NCSE cases were generally favorable. Although rare, post-ECT NCSE should be kept in mind by physicians when confusion or unresponsiveness develops and continues after ECT; multilead EEG is gold standard for diagnosis. An intravenous (IV) antiepileptic drug (AED) challenge can help clarify the diagnosis. Initial treatment is recommended with IV benzodiazepines, with a repeat dose if necessary. If seizures persist, IV AEDs are warranted. NCSE refractory to this treatment should be treated with a scheduled IV or oral AED. Serial multilead EEGs should be used to monitor resolution of symptoms. NCSE after ECT is a rare but recognizable clinical event. A high clinical suspicion and low threshold for EEG is necessary for prompt diagnosis. Copyright © 2018 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

Initial experience with SPECT imaging of the brain using I-123 p-iodoamphetamine in focal epilepsy

DOE Office of Scientific and Technical Information (OSTI.GOV)

LaManna, M.M.; Sussman, N.M.; Harner, R.N.

1989-06-01

Nineteen patients with complex partial seizures refractory to medical treatment were examined with routine electroencephalography (EEG), video EEG monitoring, computed tomography or magnetic resonance imaging, neuropsychological tests and interictal single photon emission computed tomography (SPECT) with I-123 iodoamphetamine (INT). In 18 patients, SPECT identified areas of focal reduction in tracer uptake that correlated with the epileptogenic focus identified on the EEG. In addition, SPECT disclosed other areas of neurologic dysfunction as elicited on neuropsychological tests. Thus, IMP SPECT is a useful tool for localizing epileptogenic foci and their associated dynamic deficits.

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

Preterm EEG: a multimodal neurophysiological protocol.

PubMed

Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa

2012-02-18

Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.

Association of Electroencephalography (EEG) Power Spectra with Corneal Nerve Fiber Injury in Retinoblastoma Patients.

PubMed

Liu, Jianliang; Sun, Juanjuan; Diao, Yumei; Deng, Aijun

2016-09-04

BACKGROUND In our clinical experience we discovered that EEG band power may be correlated with corneal nerve injury in retinoblastoma patients. This study aimed to investigate biomarkers obtained from electroencephalography (EEG) recordings to reflect corneal nerve injury in retinoblastoma patients. MATERIAL AND METHODS Our study included 20 retinoblastoma patients treated at the Department of Ophthalmology, Affiliated Hospital of Weifang Medical University between 2010 and 2014. Twenty normal individuals were included in the control group. EEG activity was recorded continuously with 32 electrodes using standard EEG electrode placement for detecting EEG power. A cornea confocal microscope was used to examine corneal nerve injury in retinoblastoma patients and normal individuals. Spearman rank correlation analysis was used to analyze the correlation between corneal nerve injury and EEG power changes. The sensitivity and specificity of changed EEG power in diagnosis of corneal nerve injury were also analyzed. RESULTS The predominantly slow EEG oscillations changed gradually into faster waves in retinoblastoma patients. The EEG pattern in retinoblastoma patients was characterized by a distinct increase of delta (P<0.01) and significant decrease of theta power P<0.05). Corneal nerves were damaged in corneas of retinoblastoma patients. Corneal nerve injury was positively correlated with delta EEG spectra power and negatively correlated with theta EEG spectra power. The diagnostic sensitivity and specificity by compounding in the series were 60% and 67%, respectively. CONCLUSIONS Changes in delta and theta of EEG appear to be associated with occurrence of corneal nerve injury. Useful information can be provided for evaluating corneal nerve damage in retinoblastoma patients through analyzing EEG power bands.

Tele-transmission of EEG recordings.

PubMed

Lemesle, M; Kubis, N; Sauleau, P; N'Guyen The Tich, S; Touzery-de Villepin, A

2015-03-01

EEG recordings can be sent for remote interpretation. This article aims to define the tele-EEG procedures and technical guidelines. Tele-EEG is a complete medical act that needs to be carried out with the same quality requirements as a local one in terms of indications, formulation of the medical request and medical interpretation. It adheres to the same quality requirements for its human resources and materials. It must be part of a medical organization (technical and medical network) and follow all rules and guidelines of good medical practices. The financial model of this organization must include costs related to performing the EEG recording, operating and maintenance of the tele-EEG network and medical fees of the physician interpreting the EEG recording. Implementing this organization must be detailed in a convention between all parties involved: physicians, management of the healthcare structure, and the company providing the tele-EEG service. This convention will set rules for network operation and finance, and also the continuous training of all staff members. The tele-EEG system must respect all rules for safety and confidentiality, and ensure the traceability and storing of all requests and reports. Under these conditions, tele-EEG can optimize the use of human resources and competencies in its zone of utilization and enhance the organization of care management. Copyright © 2015. Published by Elsevier SAS.

Real-Time Processing of Continuous Physiological Signals in a Neurocritical Care Unit on a Stream Data Analytics Platform.

PubMed

Bai, Yong; Sow, Daby; Vespa, Paul; Hu, Xiao

2016-01-01

Continuous high-volume and high-frequency brain signals such as intracranial pressure (ICP) and electroencephalographic (EEG) waveforms are commonly collected by bedside monitors in neurocritical care. While such signals often carry early signs of neurological deterioration, detecting these signs in real time with conventional data processing methods mainly designed for retrospective analysis has been extremely challenging. Such methods are not designed to handle the large volumes of waveform data produced by bedside monitors. In this pilot study, we address this challenge by building a prototype system using the IBM InfoSphere Streams platform, a scalable stream computing platform, to detect unstable ICP dynamics in real time. The system continuously receives electrocardiographic and ICP signals and analyzes ICP pulse morphology looking for deviations from a steady state. We also designed a Web interface to display in real time the result of this analysis in a Web browser. With this interface, physicians are able to ubiquitously check on the status of their patients and gain direct insight into and interpretation of the patient's state in real time. The prototype system has been successfully tested prospectively on live hospitalized patients.

Predictive Value of an Early Amplitude Integrated Electroencephalogram and Neurologic Examination

PubMed Central

Pappas, Athina; McDonald, Scott A.; Laptook, Abbot R.; Bara, Rebecca; Ehrenkranz, Richard A.; Tyson, Jon E.; Goldberg, Ronald; Donovan, Edward F.; Fanaroff, Avroy A.; Das, Abhik; Poole, W. Kenneth; Walsh, Michele; Higgins, Rosemary D.; Welsh, Cherie; Salhab, Walid; Carlo, Waldemar A.; Poindexter, Brenda; Stoll, Barbara J.; Guillet, Ronnie; Finer, Neil N.; Stevenson, David K.; Bauer, Charles R.

2011-01-01

OBJECTIVE: To examine the predictive validity of the amplitude integrated electroencephalogram (aEEG) and stage of encephalopathy among infants with hypoxic-ischemic encephalopathy (HIE) eligible for therapeutic whole-body hypothermia. DESIGN: Neonates were eligible for this prospective study if moderate or severe HIE occurred at <6 hours and an aEEG was obtained at <9 hours of age. The primary outcome was death or moderate/severe disability at 18 months. RESULTS: There were 108 infants (71 with moderate HIE and 37 with severe HIE) enrolled in the study. aEEG findings were categorized as normal, with continuous normal voltage (n = 12) or discontinuous normal voltage (n = 12), or abnormal, with burst suppression (n = 22), continuous low voltage (n = 26), or flat tracing (n = 36). At 18 months, 53 infants (49%) experienced death or disability. Severe HIE and an abnormal aEEG were related to the primary outcome with univariate analysis, whereas severe HIE alone was predictive of outcome with multivariate analysis. Addition of aEEG pattern to HIE stage did not add to the predictive value of the model; the area under the curve changed from 0.72 to 0.75 (P = .19). CONCLUSIONS: The aEEG background pattern did not significantly enhance the value of the stage of encephalopathy at study entry in predicting death and disability among infants with HIE. PMID:21669899

EEG-Informed fMRI: A Review of Data Analysis Methods

PubMed Central

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

The effect of methylphenidate on very low frequency electroencephalography oscillations in adult ADHD.

PubMed

Cooper, Ruth E; Skirrow, Caroline; Tye, Charlotte; McLoughlin, Grainne; Rijsdijk, Fruhling; Banaschweski, Tobias; Brandeis, Daniel; Kuntsi, Jonna; Asherson, Philip

2014-04-01

Altered very low-frequency electroencephalographic (VLF-EEG) activity is an endophenotype of ADHD in children and adolescents. We investigated VLF-EEG case-control differences in adult samples and the effects of methylphenidate (MPH). A longitudinal case-control study was conducted examining the effects of MPH on VLF-EEG (.02-0.2Hz) during a cued continuous performance task. 41 untreated adults with ADHD and 47 controls were assessed, and 21 cases followed up after MPH treatment, with a similar follow-up for 38 controls (mean follow-up=9.4months). Cases had enhanced frontal and parietal VLF-EEG and increased omission errors. In the whole sample, increased parietal VLF-EEG correlated with increased omission errors. After controlling for subthreshold comorbid symptoms, VLF-EEG case-control differences and treatment effects remained. Post-treatment, a time by group interaction emerged; VLF-EEG and omission errors reduced to the same level as controls, with decreased inattentive symptoms in cases. Reduced VLF-EEG following MPH treatment provides preliminary evidence that changes in VLF-EEG may relate to MPH treatment effects on ADHD symptoms; and that VLF-EEG may be an intermediate phenotype of ADHD. Further studies of the treatment effect of MPH in larger controlled studies are required to formally evaluate any causal link between MPH, VLF-EEG and ADHD symptoms. Copyright © 2014 Elsevier Inc. All rights reserved.

Automatic detection of rhythmic and periodic patterns in critical care EEG based on American Clinical Neurophysiology Society (ACNS) standardized terminology.

PubMed

Fürbass, F; Hartmann, M M; Halford, J J; Koren, J; Herta, J; Gruber, A; Baumgartner, C; Kluge, T

2015-09-01

Continuous EEG from critical care patients needs to be evaluated time efficiently to maximize the treatment effect. A computational method will be presented that detects rhythmic and periodic patterns according to the critical care EEG terminology (CCET) of the American Clinical Neurophysiology Society (ACNS). The aim is to show that these detected patterns support EEG experts in writing neurophysiological reports. First of all, three case reports exemplify the evaluation procedure using graphically presented detections. Second, 187 hours of EEG from 10 critical care patients were used in a comparative trial study. For each patient the result of a review session using the EEG and the visualized pattern detections was compared to the original neurophysiology report. In three out of five patients with reported seizures, all seizures were reported correctly. In two patients, several subtle clinical seizures with unclear EEG correlation were missed. Lateralized periodic patterns (LPD) were correctly found in 2/2 patients and EEG slowing was correctly found in 7/9 patients. In 8/10 patients, additional EEG features were found including LPDs, EEG slowing, and seizures. The use of automatic pattern detection will assist in review of EEG and increase efficiency. The implementation of bedside surveillance devices using our detection algorithm appears to be feasible and remains to be confirmed in further multicenter studies. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

21 CFR 882.1855 - Electroencephalogram (EEG) telemetry system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Electroencephalogram (EEG) telemetry system. 882.1855 Section 882.1855 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882.1855...

21 CFR 882.1855 - Electroencephalogram (EEG) telemetry system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Electroencephalogram (EEG) telemetry system. 882.1855 Section 882.1855 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882.1855...

Using Electroencephalography to Measure Cognitive Load

ERIC Educational Resources Information Center

Antonenko, Pavlo; Paas, Fred; Grabner, Roland; van Gog, Tamara

2010-01-01

Application of physiological methods, in particular electroencephalography (EEG), offers new and promising approaches to educational psychology research. EEG is identified as a physiological index that can serve as an online, continuous measure of cognitive load detecting subtle fluctuations in instantaneous load, which can help explain effects of…

Burst Suppression on Processed Electroencephalography as a Predictor of Post-Coma Delirium in Mechanically Ventilated ICU Patients

PubMed Central

Andresen, Jennifer M.; Girard, Timothy D.; Pandharipande, Pratik P.; Davidson, Mario A.; Ely, E. Wesley; Watson, Paula L.

2015-01-01

Objectives Many patients, due to a combination of illness and sedatives, spend a considerable amount of time in a comatose state that can include time in burst suppression. We sought to determine if burst suppression measured by processed electroencephalography (pEEG) during coma in sedative-exposed patients is a predictor of post-coma delirium during critical illness. Design Observational convenience sample cohort Setting Medical and surgical ICUs in a tertiary care medical center Patients Cohort of 124 mechanically ventilated ICU patients Measurements and Main Results Depth of sedation was monitored twice daily using the Richmond Agitation-Sedation Scale and continuously monitored by pEEG. When non-comatose, patients were assessed for delirium twice daily using Confusion Assessment Method for the ICU (CAM-ICU). Multiple logistic regression and Cox proportional hazards regression were used to assess associations between time in burst suppression and both incidence and time to resolution of delirium, respectively, adjusting for time in deep sedation and a principal component score consisting of APACHE II score and cumulative doses of sedatives while comatose. Of the 124 patients enrolled and monitored, 55 patients either never had coma or never emerged from coma yielding 69 patients for whom we performed these analyses; 42 of these 69 (61%) had post-coma delirium. Most patients had burst-suppression during coma, though often short-lived [ median (intraquartile range) time in burst suppression, 6.4 (1-58) minutes]. After adjusting for covariates, even this short time in burst suppression independently predicted a higher incidence of post-coma delirium [odds ratio 4.16; 95% confidence interval (CI) 1.27-13.62; p=0.02] and a lower likelihood (delayed) resolution of delirium (hazard ratio 0.78; 95% CI 0.53-0.98; p=0.04). Conclusions Time in burst suppression during coma, as measured by processed EEG, was an independent predictor of incidence and time to resolution of post-coma/post-deep sedation delirium. These findings of this single center investigation support lighter sedation strategies. PMID:25072756

Postictal psychosis and its electrophysiological correlates in invasive EEG: a case report study and literature review.

PubMed

Kuba, Robert; Brázdil, Milan; Rektor, Ivan

2012-04-01

We identified two patients with medically refractory temporal lobe epilepsy, from whom intracranial EEG recordings were obtained at the time of postictal psychosis. Both patients had mesial temporal epilepsy associated with hippocampal sclerosis. In both patients, the postictal psychosis was associated with a continual "epileptiform" EEG pattern that differed from their interictal and ictal EEG findings (rhythmical slow wave and "abortive" spike-slow wave complex activity in the right hippocampus and lateral temporal cortex in case 1 and a periodic pattern of triphasic waves in the contacts recording activity from the left anterior cingulate gyrus). Some cases of postictal psychosis might be caused by the transient impairment of several limbic system structures due to the "continual epileptiform discharge" in some brain regions. Case 2 is the first report of a patient with TLE in whom psychotic symptoms were associated with the epileptiform impairment of the anterior cingulate gyrus. Copyright © 2012 Elsevier Inc. All rights reserved.

Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes.

PubMed

Hamid, Laith; Al Farawn, Ali; Merlet, Isabelle; Japaridze, Natia; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Wendling, Fabrice; Siniatchkin, Michael

2017-07-01

The clinical routine of non-invasive electroencephalography (EEG) is usually performed with 8-40 electrodes, especially in long-term monitoring, infants or emergency care. There is a need in clinical and scientific brain imaging to develop inverse solution methods that can reconstruct brain sources from these low-density EEG recordings. In this proof-of-principle paper we investigate the performance of the spatiotemporal Kalman filter (STKF) in EEG source reconstruction with 9-, 19- and 32- electrodes. We used simulated EEG data of epileptic spikes generated from lateral frontal and lateral temporal brain sources using state-of-the-art neuronal population models. For validation of source reconstruction, we compared STKF results to the location of the simulated source and to the results of low-resolution brain electromagnetic tomography (LORETA) standard inverse solution. STKF consistently showed less localization bias compared to LORETA, especially when the number of electrodes was decreased. The results encourage further research into the application of the STKF in source reconstruction of brain activity from low-density EEG recordings.

Automatic detection and classification of artifacts in single-channel EEG.

PubMed

Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W; Sorensen, Helge B D

2014-01-01

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated. The detection algorithm yield an average sensitivity and specificity above 95% for both the subject-specific and generic models. The classification algorithm show a mean accuracy of 78 and 64% for the subject-specific and generic model, respectively. The classification model was additionally validated on a reference dataset with similar results.

EEG and ocular correlates of circadian melatonin phase and human performance decrements during sleep loss

NASA Technical Reports Server (NTRS)

Cajochen, C.; Khalsa, S. B.; Wyatt, J. K.; Czeisler, C. A.; Dijk, D. J.

1999-01-01

The aim of this study was to quantify the associations between slow eye movements (SEMs), eye blink rate, waking electroencephalogram (EEG) power density, neurobehavioral performance, and the circadian rhythm of plasma melatonin in a cohort of 10 healthy men during up to 32 h of sustained wakefulness. The time course of neurobehavioral performance was characterized by fairly stable levels throughout the first 16 h of wakefulness followed by deterioration during the phase of melatonin secretion. This deterioration was closely associated with an increase in SEMs. Frontal low-frequency EEG activity (1-7 Hz) exhibited a prominent increase with time awake and little circadian modulation. EEG alpha activity exhibited circadian modulation. The dynamics of SEMs and EEG activity were phase locked to changes in neurobehavioral performance and lagged the plasma melatonin rhythm. The data indicate that frontal areas of the brain are more susceptible to sleep loss than occipital areas. Frontal EEG activity and ocular parameters may be used to monitor and predict changes in neurobehavioral performance associated with sleep loss and circadian misalignment.

Surface mapping of spike potential fields: experienced EEGers vs. computerized analysis.

PubMed

Koszer, S; Moshé, S L; Legatt, A D; Shinnar, S; Goldensohn, E S

1996-03-01

An EEG epileptiform spike focus recorded with scalp electrodes is clinically localized by visual estimation of the point of maximal voltage and the distribution of its surrounding voltages. We compared such estimated voltage maps, drawn by experienced electroencephalographers (EEGers), with a computerized spline interpolation technique employed in the commercially available software package FOCUS. Twenty-two spikes were recorded from 15 patients during long-term continuous EEG monitoring. Maps of voltage distribution from the 28 electrodes surrounding the points of maximum change in slope (the spike maximum) were constructed by the EEGer. The same points of maximum spike and voltage distributions at the 29 electrodes were mapped by computerized spline interpolation and a comparison between the two methods was made. The findings indicate that the computerized spline mapping techniques employed in FOCUS construct voltage maps with similar maxima and distributions as the maps created by experienced EEGers. The dynamics of spike activity, including correlations, are better visualized using the computerized technique than by manual interpretation alone. Its use as a technique for spike localization is accurate and adds information of potential clinical value.

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

NASA Astrophysics Data System (ADS)

Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.

2012-10-01

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

A multimodal approach to estimating vigilance using EEG and forehead EOG.

PubMed

Zheng, Wei-Long; Lu, Bao-Liang

2017-04-01

Covert aspects of ongoing user mental states provide key context information for user-aware human computer interactions. In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. The PERCLOS index as vigilance annotation is obtained from eye tracking glasses. To improve the feasibility and wearability of vigilance estimation devices for real-world applications, we adopt a novel electrode placement for forehead EOG and extract various eye movement features, which contain the principal information of traditional EOG. We explore the effects of EEG from different brain areas and combine EEG and forehead EOG to leverage their complementary characteristics for vigilance estimation. Considering that the vigilance of users is a dynamic changing process because the intrinsic mental states of users involve temporal evolution, we introduce continuous conditional neural field and continuous conditional random field models to capture dynamic temporal dependency. We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training. The experimental results demonstrate that modality fusion can improve the performance compared with a single modality, EOG and EEG contain complementary information for vigilance estimation, and the temporal dependency-based models can enhance the performance of vigilance estimation. From the experimental results, we observe that theta and alpha frequency activities are increased, while gamma frequency activities are decreased in drowsy states in contrast to awake states. The forehead setup allows for the simultaneous collection of EEG and EOG and achieves comparative performance using only four shared electrodes in comparison with the temporal and posterior sites.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

PubMed

Astrand, Elaine

2018-06-01

Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

NASA Astrophysics Data System (ADS)

Astrand, Elaine

2018-06-01

Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

21 CFR 882.1420 - Electroencephalogram (EEG) signal spectrum analyzer.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Electroencephalogram (EEG) signal spectrum analyzer. 882.1420 Section 882.1420 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882...

21 CFR 882.1420 - Electroencephalogram (EEG) signal spectrum analyzer.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Electroencephalogram (EEG) signal spectrum analyzer. 882.1420 Section 882.1420 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES NEUROLOGICAL DEVICES Neurological Diagnostic Devices § 882...

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals

DTIC Science & Technology

2013-04-24

DETECT: A MATLAB Toolbox for Event Detection and Identification in Time Series, with Applications to Artifact Detection in EEG Signals Vernon...datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal . We have developed...As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and

Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG.

PubMed

Fu, Yunfa; Xiong, Xin; Jiang, Changhao; Xu, Baolei; Li, Yongcheng; Li, Hongyi

2017-09-01

Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class classification of these imagined motor parameters by NIRS-EEG were explored. Near infrared probes were aligned with C3 and C4, and EEG electrodes were placed midway between the NIRS probes. NIRS and EEG signals were acquired from six healthy subjects during six imagined hand clenching force and speed tasks involving the right hand. The results showed that NIRS combined with EEG is effective for simultaneously measuring brain activity of the sensorimotor area. The study also showed that in the duration of (0, 10) s for imagined force and speed of hand clenching, HbO first exhibited a negative variation trend, which was followed by a negative peak. After the negative peak, it exhibited a positive variation trend with a positive peak about 6-8 s after termination of imagined movement. During (-2, 1) s, the EEG may have indicated neural processing during the preparation, execution, and monitoring of a given imagined force and speed of hand clenching. The instantaneous phase, frequency, and amplitude feature of the EEG were calculated by Hilbert transform; HbO and the difference between HbO and Hb concentrations were extracted. The features of NIRS and EEG were combined to classify three levels of imagined force [at 20/50/80% MVGF (maximum voluntary grip force)] and speed (at 0.5/1/2 Hz) of hand clenching by SVM. The average classification accuracy of the NIRS-EEG fusion feature was 0.74 ± 0.02. These results may provide increased control commands of force and speed for a brain-controlled robot based on NIRS-EEG.

Computer-aided diagnosis of alcoholism-related EEG signals.

PubMed

Acharya, U Rajendra; S, Vidya; Bhat, Shreya; Adeli, Hojjat; Adeli, Amir

2014-12-01

Alcoholism is a severe disorder that affects the functionality of neurons in the central nervous system (CNS) and alters the behavior of the affected person. Electroencephalogram (EEG) signals can be used as a diagnostic tool in the evaluation of subjects with alcoholism. The neurophysiological interpretation of EEG signals in persons with alcoholism (PWA) is based on observation and interpretation of the frequency and power in their EEGs compared to EEG signals from persons without alcoholism. This paper presents a review of the known features of EEGs obtained from PWA and proposes that the impact of alcoholism on the brain can be determined by computer-aided analysis of EEGs through extracting the minute variations in the EEG signals that can differentiate the EEGs of PWA from those of nonaffected persons. The authors advance the idea of automated computer-aided diagnosis (CAD) of alcoholism by employing the EEG signals. This is achieved through judicious combination of signal processing techniques such as wavelet, nonlinear dynamics, and chaos theory and pattern recognition and classification techniques. A CAD system is cost-effective and efficient and can be used as a decision support system by physicians in the diagnosis and treatment of alcoholism especially those who do not specialize in alcoholism or neurophysiology. It can also be of great value to rehabilitation centers to assess PWA over time and to monitor the impact of treatment aimed at minimizing or reversing the effects of the disease on the brain. A CAD system can be used to determine the extent of alcoholism-related changes in EEG signals (low, medium, high) and the effectiveness of therapeutic plans. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison

NASA Astrophysics Data System (ADS)

Bleichner, Martin G.; Mirkovic, Bojana; Debener, Stefan

2016-12-01

Objective. This study presents a direct comparison of a classical EEG cap setup with a new around-the-ear electrode array (cEEGrid) to gain a better understanding of the potential of ear-centered EEG. Approach. Concurrent EEG was recorded from a classical scalp EEG cap and two cEEGrids that were placed around the left and the right ear. Twenty participants performed a spatial auditory attention task in which three sound streams were presented simultaneously. The sound streams were three seconds long and differed in the direction of origin (front, left, right) and the number of beats (3, 4, 5 respectively), as well as the timbre and pitch. The participants had to attend to either the left or the right sound stream. Main results. We found clear attention modulated ERP effects reflecting the attended sound stream for both electrode setups, which agreed in morphology and effect size. A single-trial template matching classification showed that the direction of attention could be decoded significantly above chance (50%) for at least 16 out of 20 participants for both systems. The comparably high classification results of the single trial analysis underline the quality of the signal recorded with the cEEGrids. Significance. These findings are further evidence for the feasibility of around the-ear EEG recordings and demonstrate that well described ERPs can be measured. We conclude that concealed behind-the-ear EEG recordings can be an alternative to classical cap EEG acquisition for auditory attention monitoring.

Identifying auditory attention with ear-EEG: cEEGrid versus high-density cap-EEG comparison.

PubMed

Bleichner, Martin G; Mirkovic, Bojana; Debener, Stefan

2016-12-01

This study presents a direct comparison of a classical EEG cap setup with a new around-the-ear electrode array (cEEGrid) to gain a better understanding of the potential of ear-centered EEG. Concurrent EEG was recorded from a classical scalp EEG cap and two cEEGrids that were placed around the left and the right ear. Twenty participants performed a spatial auditory attention task in which three sound streams were presented simultaneously. The sound streams were three seconds long and differed in the direction of origin (front, left, right) and the number of beats (3, 4, 5 respectively), as well as the timbre and pitch. The participants had to attend to either the left or the right sound stream. We found clear attention modulated ERP effects reflecting the attended sound stream for both electrode setups, which agreed in morphology and effect size. A single-trial template matching classification showed that the direction of attention could be decoded significantly above chance (50%) for at least 16 out of 20 participants for both systems. The comparably high classification results of the single trial analysis underline the quality of the signal recorded with the cEEGrids. These findings are further evidence for the feasibility of around the-ear EEG recordings and demonstrate that well described ERPs can be measured. We conclude that concealed behind-the-ear EEG recordings can be an alternative to classical cap EEG acquisition for auditory attention monitoring.

Focused attention, open monitoring and automatic self-transcending: Categories to organize meditations from Vedic, Buddhist and Chinese traditions.

PubMed

Travis, Fred; Shear, Jonathan

2010-12-01

This paper proposes a third meditation-category--automatic self-transcending--to extend the dichotomy of focused attention and open monitoring proposed by Lutz. Automatic self-transcending includes techniques designed to transcend their own activity. This contrasts with focused attention, which keeps attention focused on an object; and open monitoring, which keeps attention involved in the monitoring process. Each category was assigned EEG bands, based on reported brain patterns during mental tasks, and meditations were categorized based on their reported EEG. Focused attention, characterized by beta/gamma activity, included meditations from Tibetan Buddhist, Buddhist, and Chinese traditions. Open monitoring, characterized by theta activity, included meditations from Buddhist, Chinese, and Vedic traditions. Automatic self-transcending, characterized by alpha1 activity, included meditations from Vedic and Chinese traditions. Between categories, the included meditations differed in focus, subject/object relation, and procedures. These findings shed light on the common mistake of averaging meditations together to determine mechanisms or clinical effects. Copyright © 2010 Elsevier Inc. All rights reserved.

Effect of intravenous sodium salicylate administration prior to castration on plasma cortisol and electroencephalography parameters in calves.

PubMed

Bergamasco, L; Coetzee, J F; Gehring, R; Murray, L; Song, T; Mosher, R A

2011-12-01

Nociception is an unavoidable consequence of many routine management procedures such as castration in cattle. This study investigated electroencephalography (EEG) parameters and cortisol levels in calves receiving intravenous sodium salicylate in response to a castration model. Twelve Holstein calves were randomly assigned to the following groups: (i) castrated, untreated controls, (ii) 50 mg/kg sodium salicylate IV precastration, were blood sampled at 0, 5, 10, 20, 30, 45, 60, 90, 120, 150, 180, 240, 360, and 480 min postcastration. The EEG recording included baseline, castration, immediate recovery (0-5 min after castration), middle recovery (5-10 min after castration), and late recovery (10-20 min after castration). Samples were analyzed by competitive chemiluminescent immunoassay and fluorescence polarization immunoassay for cortisol and salicylate, respectively. EEG visual inspection and spectral analysis were performed. Statistical analyses included anova repeated measures and correlations between response variable. No treatment effect was noted between the two groups for cortisol and EEG measurements, namely an attenuation of acute cortisol response and EEG desynchronization in sodium salicylate group. Time effects were noted for EEG measurements, cortisol and salicylates levels. Significant correlations between cortisol and EEG parameters were noted. These findings have implications for designing effective analgesic regimens, and they suggest that EEG can be useful to monitor pain attributable to castration. © 2011 Blackwell Publishing Ltd.

Towards deep brain monitoring with superficial EEG sensors plus neuromodulatory focused ultrasound

PubMed Central

Darvas, F; Mehić, E; Caler, CJ; Ojemann, JG; Mourad, PD

2017-01-01

Noninvasive recordings of electrophysiological activity have limited anatomical specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalogram (EEG) signal induced by pulsed focused ultrasound (pFU) could overcome those limitations. As a first step towards testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200 microsecond-long pulses applied at 1050 Hz for one second at a spatial peak temporal average intensity of 1.4 W/cm2) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050 Hz electrophysiological signal only when ultrasound was applied to living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pFU as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution. PMID:27181686

Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.

PubMed

Shahin, Mostafa; Ahmed, Beena; Hamida, Sana Tmar-Ben; Mulaffer, Fathima Lamana; Glos, Martin; Penzel, Thomas

2017-11-01

Effective sleep analysis is hampered by the lack of automated tools catering to disordered sleep patterns and cumbersome monitoring hardware. In this paper, we apply deep learning on a set of 57 EEG features extracted from a maximum of two EEG channels to accurately differentiate between patients with insomnia or controls with no sleep complaints. We investigated two different approaches to achieve this. The first approach used EEG data from the whole sleep recording irrespective of the sleep stage (stage-independent classification), while the second used only EEG data from insomnia-impacted specific sleep stages (stage-dependent classification). We trained and tested our system using both healthy and disordered sleep collected from 41 controls and 42 primary insomnia patients. When compared with manual assessments, an NREM + REM based classifier had an overall discrimination accuracy of 92% and 86% between two groups using both two and one EEG channels, respectively. These results demonstrate that deep learning can be used to assist in the diagnosis of sleep disorders such as insomnia.

Electroencephalogram-based indices applied to dogs' depth of anaesthesia monitoring.

PubMed

Brás, S; Georgakis, A; Ribeiro, L; Ferreira, D A; Silva, A; Antunes, L; Nunes, C S

2014-12-01

Hypnotic drug administration causes alterations in the electroencephalogram (EEG) in a dose-dependent manner. These changes cannot be identified easily in the raw EEG, therefore EEG based indices were adopted for assessing depth of anaesthesia (DoA). This study examines several indices for estimating dogs' DoA. Data (EEG, clinical end-points) were collected from 8 dogs anaesthetized with propofol. EEG was initially collected without propofol. Then, 100 ml h⁻¹ (1000 mg h⁻¹) of propofol 1% infusion rate was administered until a deep anaesthetic stage was reached. The infusion rate was temporarily increased to 200 ml h⁻¹ (2000 mg h⁻¹) to achieve 80% of burst suppression. The index performance was accessed by correlation coefficient with the propofol concentrations, and prediction probability with the anaesthetic clinical end-points. The temporal entropy and the averaged instantaneous frequency were the best indices because they exhibit: (a) strong correlations with propofol concentrations, (b) high probabilities of predicting anaesthesia clinical end-points. Copyright © 2014 Elsevier Ltd. All rights reserved.

Continuous EEG signal analysis for asynchronous BCI application.

PubMed

Hsu, Wei-Yen

2011-08-01

In this study, we propose a two-stage recognition system for continuous analysis of electroencephalogram (EEG) signals. An independent component analysis (ICA) and correlation coefficient are used to automatically eliminate the electrooculography (EOG) artifacts. Based on the continuous wavelet transform (CWT) and Student's two-sample t-statistics, active segment selection then detects the location of active segment in the time-frequency domain. Next, multiresolution fractal feature vectors (MFFVs) are extracted with the proposed modified fractal dimension from wavelet data. Finally, the support vector machine (SVM) is adopted for the robust classification of MFFVs. The EEG signals are continuously analyzed in 1-s segments, and every 0.5 second moves forward to simulate asynchronous BCI works in the two-stage recognition architecture. The segment is first recognized as lifted or not in the first stage, and then is classified as left or right finger lifting at stage two if the segment is recognized as lifting in the first stage. Several statistical analyses are used to evaluate the performance of the proposed system. The results indicate that it is a promising system in the applications of asynchronous BCI work.

Performance of a New Portable Wireless Sleep Monitor

PubMed Central

Younes, Magdy; Soiferman, Marc; Thompson, Wayne; Giannouli, Eleni

2017-01-01

Study Objectives: To determine if signals generated by a new sleep monitor (Prodigy) are comparable to signals generated during in-laboratory polysomnography (PSG). Methods: Fifty-nine patients with various sleep disorders (25 with moderate/severe sleep apnea) were studied. Full PSG was performed using standard acquisition systems. Prodigy was attached to the forehead with four disposable snap electrodes. Four additional electrodes were attached to monitor eye movements and muscle activity, and to serve as reference (mastoid). One frontal EEG signal was outputted in real time from the monitor and stored in the PSG record along with the other PSG signals. PSG was scored for sleep variables manually, and monitor records were scored by a validated automatic system (MSS) (MSS-Prodigy). MSS-Prodigy was briefly edited following suggestions of an Editing Helper feature of MSS. Results: Technical failures resulted in one study being unusable and another with data for only 3 hours. Prodigy EEG signal stored in the PSG record was visually indistinguishable from the PSG-derived EEG signals. Important differences between manual scores and unedited MSS-Prodigy were seen in a few patients in some sleep variables (notably onset latencies and REM time). Editing Helper issued 2.1 ± 0.8 suggestions/file. Only these suggestions were pursued during editing. Intraclass correlation coefficients for manual vs. edited MSS-Prodigy were > 0.83 for all sleep variables except for stages N1 and N3 (0.57 and 0.58). Conclusions: When scored with MSS, and with only very minor editing, the monitor's results show excellent agreement with manual scoring of polysomnography data, even in patients with severe sleep disorders. Citation: Younes M, Soiferman M, Thompson W, Giannouli E. Performance of a new portable wireless sleep monitor. J Clin Sleep Med. 2017;13(2):245–258. PMID:27784419

EEG patterns from acute to chronic stroke phases in focal cerebral ischemic rats: correlations with functional recovery.

PubMed

Zhang, Shao-jie; Ke, Zheng; Li, Le; Yip, Shea-ping; Tong, Kai-yu

2013-04-01

Monitoring the neural activities from the ischemic penumbra provides critical information on neurological recovery after stroke. The purpose of this study is to evaluate the temporal alterations of neural activities using electroencephalography (EEG) from the acute phase to the chronic phase, and to compare EEG with the degree of post-stroke motor function recovery in a rat model of focal ischemic stroke. Male Sprague-Dawley rats were subjected to 90 min transient middle cerebral artery occlusion surgery followed by reperfusion for seven days (n = 58). The EEG signals were recorded at the pre-stroke phase (0 h), acute phase (3, 6 h), subacute phase (12, 24, 48, 72 h) and chronic phase (96, 120, 144, 168 h) (n = 8). This study analyzed post-stroke seizures and polymorphic delta activities (PDAs) and calculated quantitative EEG parameters such as the alpha-to-delta ratio (ADR). The ADR represented the ratio between alpha power and delta power, which indicated how fast the EEG activities were. Forelimb and hindlimb motor functions were measured by De Ryck's test and the beam walking test, respectively. In the acute phase, delta power increased fourfold with the occurrence of PDAs, and the histological staining showed that the infarct was limited to the striatum and secondary sensory cortex. In the subacute phase, the alpha power reduced to 50% of the baseline, and the infarct progressed to the forelimb cortical region. ADRs reduced from 0.23 ± 0.09 to 0.04 ± 0.01 at 3 h in the acute phase and gradually recovered to 0.22 ± 0.08 at 168 h in the chronic phase. In the comparison of correlations between the EEG parameters and the limb motor function from the acute phase to the chronic phase, ADRs were found to have the highest correlation coefficients with the beam walking test (r = 0.9524, p < 0.05) and De Ryck's test (r = 0.8077, p < 0.05). This study measured EEG activities after focal cerebral ischemia and showed that functional recovery was closely correlated with the neural activities in the penumbra. Longitudinal EEG monitoring at different phases after a stroke can provide information on the neural activities, which are well correlated with the motor function recovery.

Studentized continuous wavelet transform (t-CWT) in the analysis of individual ERPs: real and simulated EEG data

PubMed Central

Real, Ruben G. L.; Kotchoubey, Boris; Kübler, Andrea

2014-01-01

This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings. PMID:25309308

Studentized continuous wavelet transform (t-CWT) in the analysis of individual ERPs: real and simulated EEG data.

PubMed

Real, Ruben G L; Kotchoubey, Boris; Kübler, Andrea

2014-01-01

This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

PubMed Central

Adib, Mani; Cretu, Edmond

2013-01-01

We present a new method for removing artifacts in electroencephalography (EEG) records during Galvanic Vestibular Stimulation (GVS). The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters. PMID:23956786

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

The Effect of Fentanyl on Bispectral Index (BIS) Values and Recall

DTIC Science & Technology

2002-12-01

BIS Values CHAPTER ONE: INTRODUCTION Anesthesia has three main components known as the anesthesia triad: hypnosis (loss of consciousness), adequate...monitor, the primary way to estimate level of hypnosis was through changes in vital signs and the anesthesia provider’s previous experiences. Many...different EEG patterns. Another reason that EEG is difficult to use for assessing hypnosis is that most anesthesia providers use multiple classes of

Diagnosis of Epilepsy and Related Episodic Disorders.

PubMed

St Louis, Erik K; Cascino, Gregory D

2016-02-01

This review identifies the diverse and variable clinical presentations associated with epilepsy that may create challenges in diagnosis and treatment. Epilepsy has recently been redefined as a disease characterized by one or more seizures with a relatively high recurrence risk (ie, 60% or greater likelihood). The implication of this definition for therapy is that antiepileptic drug therapy may be initiated following a first seizure in certain situations.EEG remains the most commonly used study in the evaluation of people with epilepsy. Routine EEG may assist in diagnosis, classification of seizure type(s), identification of treatment, and monitoring the efficacy of therapy. Video-EEG monitoring permits seizure classification, assessment of psychogenic nonepileptic seizures, and evaluation of candidacy for epilepsy surgery. MRI is pivotal in elucidating the etiology of the seizure disorder and in suggesting the localization of seizure onset. This article reviews the new International League Against Epilepsy practical clinical definition for epilepsy and the differential diagnosis of other physiologic paroxysmal spells, including syncope, parasomnias, transient ischemic attacks, and migraine, as well as psychogenic nonepileptic seizures. The initial investigational approaches to new-onset epilepsy are considered, including neuroimaging and neurophysiologic investigations with interictal and ictal video-EEG. Neurologists should maintain a high index of suspicion for epilepsy when children or adults present with a single paroxysmal spell or recurrent episodic events.

Underlying neurological dysfunction in children with language, speech or learning difficulties and a verbal IQ--performance IQ discrepancy.

PubMed

Meulemans, J; Goeleven, A; Zink, I; Loyez, L; Lagae, L; Debruyne, F

2012-01-01

We investigated the relationship between possible underlying neurological dysfunction and a significant discrepancy between verbal IQ/performance IQ (VIQ-PIQ) in children with language, speech or learning difficulties. In a retrospective study, we analysed data obtained from intelligence testing and neurological evaluation in 49 children with a significant VIQ-PIQ discrepancy (> or = 25 points) who were referred because of language, speech or learning difficulties to the Multidisciplinary University Centre for Logopedics and Audiology (MUCLA) of the University Hospitals of Leuven, Belgium. The group of children broke down into a group of 35 children with PIQ > VIQ and a group of 14 children with VIQ > PIQ. In the first group, neurological data were present for 24 children. The neurological history and clinical neurological examination were normal in all cases. Brain MRI was performed in 15 cases and proved to be normal in all children. Brain activity was assessed with long-term video EEG monitoring in ten children. In two children, the EEG results were abnormal: there was an epileptic focus in one child and a manifest alteration in the EEG typical of Landau-Kleffner syndrome in the other. In the second group of 14 children whose VIQ was higher than the PIQ, neurological data were available for ten children. Neurological history and clinical neurological examination were normal in all cases. Brain MRI was performed in five cases and was normal in all children. EEG monitoring was performed in one child. This revealed benign childhood epilepsy with centrotemporal spikes. In a small number of children (9%) with speech, language and learning difficulties and a discrepancy between VIQ and PIQ, an underlying neurological abnormality is present. We recommend referring children with a significant VIQ-PIQ mismatch to a paediatric neurologist. As an epileptic disorder seems to be the most common underlying neurological pathology in this specific group of children, EEG monitoring should be recommended in these children. Neuro-imaging should only be used in selected patients.

How long do most seizures last? A systematic comparison of seizures recorded in the epilepsy monitoring unit.

PubMed

Jenssen, Sigmund; Gracely, Edward J; Sperling, Michael R

2006-09-01

More information is needed regarding how long seizures typically last, since this influences treatment decisions. Seizure type and other factors could influence seizure duration. Data were collected from a random sample of patients being evaluated with continuous video and scalp EEG. Seizure duration was defined as time from early sign of seizure (clinical or EEG) until the end of seizure on EEG. Seizures were categorized as simple partial (SPS), complex partial (CPS), secondarily generalized tonic-clonic (SGTCS), primary generalized tonic-clonic (PGTCS) and tonic (TS). SGTCS were divided into a complex partial part (SGTCS/CP) and a tonic-clonic part (SGTCS/TC). Median and longest duration of each seizure type in each individual were used. Comparisons of seizure types, first and last seizure, area of onset, and state of onset were performed. Five hundred seventy-nine seizures were recorded in 159 adult patients. Seizures with partial onset spreading to both hemispheres had the longest duration. SGTCS were unlikely to last more than 660 s, CPS more than 600 s, and SPS more than 240 s. PGTCS and TS had shorter durations, but the number of subjects with those two types was small. CPS did not differ in duration according to sleep state at onset nor side of origin. A working definition of status epilepticus in adults with cryptogenic or symptomatic epilepsy can be drawn from these data for purposes of future epidemiologic research. More information is needed for the idiopathic epilepsies and in children.

Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology

PubMed Central

Zao, John K.; Gan, Tchin-Tze; You, Chun-Kai; Chung, Cheng-En; Wang, Yu-Te; Rodríguez Méndez, Sergio José; Mullen, Tim; Yu, Chieh; Kothe, Christian; Hsiao, Ching-Teng; Chu, San-Liang; Shieh, Ce-Kuen; Jung, Tzyy-Ping

2014-01-01

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system. PMID:24917804

Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology.

PubMed

Zao, John K; Gan, Tchin-Tze; You, Chun-Kai; Chung, Cheng-En; Wang, Yu-Te; Rodríguez Méndez, Sergio José; Mullen, Tim; Yu, Chieh; Kothe, Christian; Hsiao, Ching-Teng; Chu, San-Liang; Shieh, Ce-Kuen; Jung, Tzyy-Ping

2014-01-01

EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system.

EEG-Annotate: Automated identification and labeling of events in continuous signals with applications to EEG.

PubMed

Su, Kyung-Min; Hairston, W David; Robbins, Kay

2018-01-01

In controlled laboratory EEG experiments, researchers carefully mark events and analyze subject responses time-locked to these events. Unfortunately, such markers may not be available or may come with poor timing resolution for experiments conducted in less-controlled naturalistic environments. We present an integrated event-identification method for identifying particular responses that occur in unlabeled continuously recorded EEG signals based on information from recordings of other subjects potentially performing related tasks. We introduce the idea of timing slack and timing-tolerant performance measures to deal with jitter inherent in such non-time-locked systems. We have developed an implementation available as an open-source MATLAB toolbox (http://github.com/VisLab/EEG-Annotate) and have made test data available in a separate data note. We applied the method to identify visual presentation events (both target and non-target) in data from an unlabeled subject using labeled data from other subjects with good sensitivity and specificity. The method also identified actual visual presentation events in the data that were not previously marked in the experiment. Although the method uses traditional classifiers for initial stages, the problem of identifying events based on the presence of stereotypical EEG responses is the converse of the traditional stimulus-response paradigm and has not been addressed in its current form. In addition to identifying potential events in unlabeled or incompletely labeled EEG, these methods also allow researchers to investigate whether particular stereotypical neural responses are present in other circumstances. Timing-tolerance has the added benefit of accommodating inter- and intra- subject timing variations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

A multimodal approach to estimating vigilance using EEG and forehead EOG

NASA Astrophysics Data System (ADS)

Zheng, Wei-Long; Lu, Bao-Liang

2017-04-01

Objective. Covert aspects of ongoing user mental states provide key context information for user-aware human computer interactions. In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. Approach. The PERCLOS index as vigilance annotation is obtained from eye tracking glasses. To improve the feasibility and wearability of vigilance estimation devices for real-world applications, we adopt a novel electrode placement for forehead EOG and extract various eye movement features, which contain the principal information of traditional EOG. We explore the effects of EEG from different brain areas and combine EEG and forehead EOG to leverage their complementary characteristics for vigilance estimation. Considering that the vigilance of users is a dynamic changing process because the intrinsic mental states of users involve temporal evolution, we introduce continuous conditional neural field and continuous conditional random field models to capture dynamic temporal dependency. Main results. We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training. The experimental results demonstrate that modality fusion can improve the performance compared with a single modality, EOG and EEG contain complementary information for vigilance estimation, and the temporal dependency-based models can enhance the performance of vigilance estimation. From the experimental results, we observe that theta and alpha frequency activities are increased, while gamma frequency activities are decreased in drowsy states in contrast to awake states. Significance. The forehead setup allows for the simultaneous collection of EEG and EOG and achieves comparative performance using only four shared electrodes in comparison with the temporal and posterior sites.

Long term impairment of cognitive functions and alterations of NMDAR subunits after continuous microwave exposure.

PubMed

Wang, Hui; Tan, Shengzhi; Xu, Xinping; Zhao, Li; Zhang, Jing; Yao, Binwei; Gao, Yabing; Zhou, Hongmei; Peng, Ruiyun

2017-11-01

The long term effects of continuous microwave exposure cannot be ignored for the simulation of the real environment and increasing concerns about the negative cognitive effects of microwave exposure. In this study, 220 male Wistar rats were exposed by a 2.856GHz radiation source with the average power density of 0, 2.5, 5 and 10mW/cm 2 for 6min/day, 5days/week and up to 6weeks. The MWM task, the EEG analysis, the hippocampus structure observation and the western blot were applied until the 12months after microwave exposure to detect the spatial learning and memory abilities, the cortical electrical activity, changes of hippocampal structure and the NMDAR subunits expressions. Results found that the rats in the 10mW/cm 2 group showed the decline of spatial learning and memory abilities and EEG disorders (the decrease of EEG frequencies, and increase of EEG amplitudes and delta wave powers). Moreover, changes of basic structure and ultrastructure of hippocampus also found in the 10 and 5mW/cm 2 groups. The decrease of NR 2A, 2B and p-NR2B might contribute to the impairment of cognitive functions. Our findings suggested that the continuous microwave exposure could cause the dose-dependent long term impairment of spatial learning and memory, the abnormalities of EEG and the hippocampal structure injuries. The decrease of NMDAR key subunits and phosphorylation of NR 2B might contribute to the cognitive impairment. Copyright © 2017 Elsevier Inc. All rights reserved.

Epileptic encephalopathy with continuous spike-waves during sleep: the need for transition from childhood to adulthood medical care appears to be related to etiology.

PubMed

de Saint-Martin, Anne; Rudolf, Gabrielle; Seegmuller, Caroline; Valenti-Hirsch, Maria Paola; Hirsch, Edouard

2014-08-01

Epileptic encephalopathy with continuous diffuse spike-waves during slow-wave sleep (ECSWS) presents clinically with infrequent nocturnal focal seizures, atypical absences related to secondary bilateral synchrony, negative myoclonia, and atonic and rare generalized tonic-clonic seizures. The unique electroencephalography (EEG) pattern found in ECSWS consists of continuous, diffuse, bilateral spike-waves during slow-wave sleep. Despite the eventual disappearance of clinical seizures and EEG abnormalities by adolescence, the prognosis is guarded in most cases because of neuropsychological and behavioral deficits. ECSWS has a heterogeneous etiology (genetic, structural, and unknown). Because epilepsy and electroencephalography (EEG) abnormalities in epileptic encephalopathy with continuous diffuse spike-waves during slow-wave sleep (ECSWS) are self-limited and age related, the need for ongoing medical care and transition to adult care might be questioned. For adolescents in whom etiology remains unknown (possibly genetic) and who experience the disappearance of seizures and EEG abnormalities, there is rarely need for long-term neurologic follow-up, because often a relatively normal cognitive and social evolution follows. However, the majority of patients with structural and possibly "genetic syndromic" etiologies will have persistent cognitive deficits and will need suitable socioeducative care. Therefore, the transition process in ECSWS will depend mainly on etiology and its related features (epileptic active phase duration, and cognitive and behavioral evolution) and revolve around neuropsychological and social support rather than medical and pharmacologic follow-up. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆

PubMed Central

Zhang, Jing; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Mei, Shanshan; Liu, Qingzhu; Li, Yunlin

2013-01-01

Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy. PMID:24282678

Eye-closure-triggered paroxysmal activity and cognitive impairment: a case report.

PubMed

Termine, Cristiano; Rubboli, Guido; Veggiotti, Pierangelo

2006-01-01

To study the neuropsychological status of an epileptic patient presenting with epileptic activity triggered by eye closure in a 14-year follow-up period. The patient was studied at 12 and 26 years of age; during this period he underwent periodical clinical evaluations and EEG investigations; brain magnetic resonance imaging (MRI) was performed at 12 years of age. A neuropsychological assessment was carried out both at 12 years of age (T0) and at 26 years of age. At T0 and T1, neuropsychological tests (digits and words span, graphoestesia, reactions time to auditory stimuli, sentences repetition, words repetition, digital gnosis, backward counting [i.e.,100-0]) were performed during video-EEG monitoring either with eyes closed or with eyes open, to evaluate possible transitory effects related to ongoing epileptic activity. Moreover, at T0 the patient underwent Wechsler Intelligence Scale for Children-Revised, and at T1 to Wechsler Adult Intelligence Scale-Revised. EEG recordings showed continuous epileptic activity triggered by eye closure, disappearing only with eyes opening, both at T0 and T1 (in this latter case, anteriorly predominant). The results of neuropsychological assessment during eyes closed as compared to performances with eyes open did not show significant differences, at T0 as well as at T1. Wechsler Intelligence scales showed a deterioration of performances at T1 with respect to T0; in addition, at T1, attention and short-term memory abnormalities, impairment in facial recognition and block design, and defective results in Continuous Performance Test and Wisconsin Card Sorting Test were observed. Lack of differences between the results of neuropsychological tests performed with eyes closed as compared to the eyes open condition suggests that in our patient epileptic activity did not cause transitory cognitive abnormalities. Deterioration of Wechsler Intelligence Scales in the follow-up period might be interpreted as the result of a disruption of cognitive processes possibly related to the persistence of a continuous epileptic activity during eye closure over the years. We speculate whether a dysfunction in posterior cortical areas involved in visual processing might be related to the impairment in face recognition and block design tests as well to eye closure sensitivity.

Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy.

PubMed

Klamer, Silke; Rona, Sabine; Elshahabi, Adham; Lerche, Holger; Braun, Christoph; Honegger, Jürgen; Erb, Michael; Focke, Niels K

2015-06-01

Dynamic causal modeling (DCM) is a method to non-invasively assess effective connectivity between brain regions. 'Musicogenic epilepsy' is a rare reflex epilepsy syndrome in which seizures can be elicited by musical stimuli and thus represents a unique possibility to investigate complex human brain networks and test connectivity analysis tools. We investigated effective connectivity in a case of musicogenic epilepsy using DCM for fMRI, high-density (hd-) EEG and MEG and validated results with intracranial EEG recordings. A patient with musicogenic seizures was examined using hd-EEG/fMRI and simultaneous '256-channel hd-EEG'/'whole head MEG' to characterize the epileptogenic focus and propagation effects using source analysis techniques and DCM. Results were validated with invasive EEG recordings. We recorded one seizure with hd-EEG/fMRI and four auras with hd-EEG/MEG. During the seizures, increases of activity could be observed in the right mesial temporal region as well as bilateral mesial frontal regions. Effective connectivity analysis of fMRI and hd-EEG/MEG indicated that right mesial temporal neuronal activity drives changes in the frontal areas consistently in all three modalities, which was confirmed by the results of invasive EEG recordings. Seizures thus seem to originate in the right mesial temporal lobe and propagate to mesial frontal regions. Using DCM for fMRI, hd-EEG and MEG we were able to correctly localize focus and propagation of epileptic activity and thereby characterize the underlying epileptic network in a patient with musicogenic epilepsy. The concordance between all three functional modalities validated by invasive monitoring is noteworthy, both for epileptic activity spread as well as for effective connectivity analysis in general. Copyright © 2015 Elsevier Inc. All rights reserved.

Efficacy and safety of a video-EEG protocol for genetic generalized epilepsies.

PubMed

De Marchi, Luciana Rodrigues; Corso, Jeana Torres; Zetehaku, Ana Carolina; Uchida, Carina Gonçalves Pedroso; Guaranha, Mirian Salvadori Bittar; Yacubian, Elza Márcia Targas

2017-05-01

Video-EEG has been used to characterize genetic generalized epilepsies (GGE). For best performance, sleep recording, photic stimulation, hyperventilation, and neuropsychological protocols are added to the monitoring. However, risks and benefits of these video-EEG protocols are not well established. The aim of this study was to analyze the efficacy and safety of a video-EEG neuropsychological protocol (VNPP) tailored for GGE and compare its value with that of routine EEG (R-EEG). We reviewed the VNPP and R-EEG of patients with GGE. We considered confirmation of the clinical suspicion of a GGE syndrome and characterization of reflex traits as benefits; and falls, injuries, psychiatric and behavioral changes, generalized tonic-clonic (GTC) seizures, and status epilepticus (SE) as the main risks of the VNPP. The VNPPs of 113 patients were analyzed. The most common epileptic syndrome was juvenile myoclonic epilepsy (85.8%). The protocol confirmed a GGE syndrome in 97 patients and 62 had seizures. Sleep recording had a provocative effect in 51.2% of patients. The second task that showed highest efficacy was praxis (39.3%) followed by hyperventilation (31.3%). Among the risks, 1.8% had GTC seizures and another 1.8%, SE. Eighteen percent of patients had persistently normal R-EEG, 72.2% of them had discharges during VNPP. Generalized tonic-clonic seizures, myoclonic status epilepticus, and repeated seizures were the main risks of VNPP present in 6 (5.31%) patients while there were no complications during R-EEG. The VNPP in GGE is a useful tool in diagnosis and characterization of reflex traits, and is a safe procedure. Its use might preclude multiple R-EEG exams. Copyright © 2017 Elsevier Inc. All rights reserved.

Unfavorable surgical outcomes in partial epilepsy with secondary bilateral synchrony: Intracranial electroencephalography study.

PubMed

Sunwoo, Jun-Sang; Byun, Jung-Ick; Moon, Jangsup; Lim, Jung-Ah; Kim, Tae-Joon; Lee, Soon-Tae; Jung, Keun-Hwa; Park, Kyung-Il; Chu, Kon; Kim, Manho; Chung, Chun-Kee; Jung, Ki-Young; Lee, Sang Kun

2016-05-01

Secondary bilateral synchrony (SBS) indicates bilaterally synchronous epileptiform discharges arising from a focal cortical origin. The present study aims to investigate SBS in partial epilepsy with regard to surgical outcomes and intracranial EEG findings. We retrospectively reviewed consecutive patients who underwent epilepsy surgery following extraoperative intracranial electroencephalography (EEG) study from 2008 to 2012. The presence of SBS was determined based upon the results of scalp EEG monitoring performed for presurgical evaluations. We reviewed scalp EEG, neuroimaging, intracranial EEG findings, and surgical outcomes in patients with SBS. We found 12 patients with SBS who were surgically treated for intractable partial epilepsy. Nine (75%) patients had lateralized ictal semiology and only two (16.6%) patients showed localized ictal onset in scalp EEG. Brain MRI showed epileptogenic lesion in three (25%) patients. Intracranial EEG demonstrated that ictal onset zone was widespread or non-localized in six (50%) patients. Low-voltage fast activity was the most common ictal onset EEG pattern. Rapid propagation of ictal onset was noted in 10 (83.3%) patients. Eleven patients underwent resective epilepsy surgery and only two patients (18.2%) achieved seizure-freedom (median follow-up 56 months). MRI-visible brain lesions were associated with favorable outcomes (p=0.024). Patients with SBS, compared to frontal lobe epilepsy without SBS, showed lesser localization in ictal onset EEG (p=0.029) and more rapid propagation during evolution of ictal rhythm (p=0.015). The present results suggested that resective surgery for partial epilepsy with SBS should be decided carefully, especially in case of nonlesional epilepsy. Poor localization and rapid spread of ictal onset were prominent in intracranial EEG, which might contribute to incomplete resection of the epileptogenic zone and poor surgical outcomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Optically measured NADH concentrations are unaffected by propofol induced EEG silence during transient cerebral hypoperfusion in anesthetized rabbits☆

PubMed Central

Wang, Mei; Agarwal, Sachin; Mayevsky, Avraham; Joshi, Shailendra

2014-01-01

The neuroprotective benefit of intra-operative anesthetics is widely described and routinely aimed to invoke electroencephalographic (EEG) silence in anticipation of transient cerebral ischemia. Previous rat survival studies have questioned an additional benefit from achieving EEG silence during transient global cerebral hypoperfusion. Surgical preparation on twelve New Zealand white rabbits under ketamine–propofol anesthesia, included placement of skull screws for bilateral EEG monitoring, skull shaving for laser Doppler probes, and a 5 mm diameter right temporal craniotomy for the NADH probe. Transient global cerebral hypoperfusion was achieved with bilateral internal carotid artery occlusion and pharmacologically induced systemic hypotension. All animals acted as controls, and had cerebral hypoperfusion under baseline propofol anesthesia with an active EEG. Thereafter, animals were randomized to receive bolus injection of intracarotid (3–5 mg) or intravenous (10–20 mg) 1% propofol to create EEG silence for 1–2 min. The data collected at baseline, peak hypoperfusion, and 5 and 10 min post hypoperfusion was analyzed by repeated measures ANOVA with post hoc Bonferroni–Dunn test. Eleven of the twelve rabbits completed the protocol. Hemodynamics and cerebral blood flow changes were comparable in all the animals. Compared to controls, the increase in NADH during ischemia was unaffected by EEG silence with either intravenous or intraarterial propofol. We failed to observe any significant additional attenuation of the elevation in NADH levels with propofol induced EEG silence during transient global cerebral hypoperfusion. This is consistent with previous rat survival studies showing that EEG silence was not required for full neuroprotective effects of pentothal anesthesia. PMID:21570061

Multi-feature classifiers for burst detection in single EEG channels from preterm infants

NASA Astrophysics Data System (ADS)

Navarro, X.; Porée, F.; Kuchenbuch, M.; Chavez, M.; Beuchée, Alain; Carrault, G.

2017-08-01

Objective. The study of electroencephalographic (EEG) bursts in preterm infants provides valuable information about maturation or prognostication after perinatal asphyxia. Over the last two decades, a number of works proposed algorithms to automatically detect EEG bursts in preterm infants, but they were designed for populations under 35 weeks of post menstrual age (PMA). However, as the brain activity evolves rapidly during postnatal life, these solutions might be under-performing with increasing PMA. In this work we focused on preterm infants reaching term ages (PMA  ⩾36 weeks) using multi-feature classification on a single EEG channel. Approach. Five EEG burst detectors relying on different machine learning approaches were compared: logistic regression (LR), linear discriminant analysis (LDA), k-nearest neighbors (kNN), support vector machines (SVM) and thresholding (Th). Classifiers were trained by visually labeled EEG recordings from 14 very preterm infants (born after 28 weeks of gestation) with 36-41 weeks PMA. Main results. The most performing classifiers reached about 95% accuracy (kNN, SVM and LR) whereas Th obtained 84%. Compared to human-automatic agreements, LR provided the highest scores (Cohen’s kappa  =  0.71) using only three EEG features. Applying this classifier in an unlabeled database of 21 infants  ⩾36 weeks PMA, we found that long EEG bursts and short inter-burst periods are characteristic of infants with the highest PMA and weights. Significance. In view of these results, LR-based burst detection could be a suitable tool to study maturation in monitoring or portable devices using a single EEG channel.

Propofol and non-propofol based sedation for outpatient colonoscopy-prospective comparison of depth of sedation using an EEG based SEDLine monitor.

PubMed

Goudra, Basavana; Singh, Preet Mohinder; Gouda, Gowri; Borle, Anuradha; Carlin, Augustus; Yadwad, Avantika

2016-10-01

Propofol is a popular anesthetic sedative employed in colonoscopy. It is known to increase the patient satisfaction and improve throughput. However, there are concerns among the clinicians with regard to the depth of sedation, as a deeper degree of sedation is known to increase the incidence of aspiration and other adverse events. So we planned to compare the depth of sedation between propofol and non-propofol based sedation in patients undergoing outpatient colonoscopy, as measured by an electroencephalogram (EEG) based monitor SEDLine monitor (SedlineInc., San Diego, CA). The non-randomized prospective observational study was performed in the outpatient gastroenterology suite of the Hospital of the University of Pennsylvania, Philadelphia. Patients included ASA class I-III aged more than 18 years scheduled for colonoscopy under Propofol or non-propofol based sedation. After an institutional review board approval, a written consent was obtained from prospective patients. Sedation (propofol or non-propofol based) was administered by either a certified nurse anesthetist under the supervision of an anesthesiologist (propofol) or a registered endoscopy nurse under the guidance of the endoscopist performing the procedure (non-propofol sedation). Depth of sedation was measured with an EEG based SEDLine monitor. The sedation providers were blinded to the patient state index-the indicator of depth of sedation. PSI (patient state index-SEDLine reading) was documented at colonoscope insertion, removal and at the return of verbal responsiveness after colonoscope withdrawal. Sedation spectrum was retrieved from the data stored on the SEDLine monitor. Patients sedated with propofol experience significantly deeper degrees of sedation at all times during the procedure. Additionally, during significant part of the procedure, they are at PSI levels associated with deep general anesthesia. The group that received propofol was more deeply sedated and had lower PSI values. Lighter propofol titration protocols may lead to improved patient care such as lowering risk of aspiration and hypotension. The role of processed EEG monitors such as the SEDLine monitor to improve sedation protocols remains to be determined. Trial registration We obtained an ethical clearance from the Institute. No trial registration was mandated, as no interventional drug or investigational device were used during the study.

Automatic interpretation and writing report of the adult waking electroencephalogram.

PubMed

Shibasaki, Hiroshi; Nakamura, Masatoshi; Sugi, Takenao; Nishida, Shigeto; Nagamine, Takashi; Ikeda, Akio

2014-06-01

Automatic interpretation of the EEG has so far been faced with significant difficulties because of a large amount of spatial as well as temporal information contained in the EEG, continuous fluctuation of the background activity depending on changes in the subject's vigilance and attention level, the occurrence of paroxysmal activities such as spikes and spike-and-slow-waves, contamination of the EEG with a variety of artefacts and the use of different recording electrodes and montages. Therefore, previous attempts of automatic EEG interpretation have been focussed only on a specific EEG feature such as paroxysmal abnormalities, delta waves, sleep stages and artefact detection. As a result of a long-standing cooperation between clinical neurophysiologists and system engineers, we report for the first time on a comprehensive, computer-assisted, automatic interpretation of the adult waking EEG. This system analyses the background activity, intermittent abnormalities, artefacts and the level of vigilance and attention of the subject, and automatically presents its report in written form. Besides, it also detects paroxysmal abnormalities and evaluates the effects of intermittent photic stimulation and hyperventilation on the EEG. This system of automatic EEG interpretation was formed by adopting the strategy that the qualified EEGers employ for the systematic visual inspection. This system can be used as a supplementary tool for the EEGer's visual inspection, and for educating EEG trainees and EEG technicians. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The effect of CPAP treatment on EEG of OSAS patients.

PubMed

Zhang, Cheng; Lv, Jun; Zhou, Junhong; Su, Li; Feng, Liping; Ma, Jing; Wang, Guangfa; Zhang, Jue

2015-12-01

Continuous positive airway pressure (CPAP) is currently the most effective treatment method for obstructive sleep apnea syndrome (OSAS). The purpose of this study was to compare the sleep electroencephalogram (EEG) changes before and after the application of CPAP to OSAS patients. A retrospective study was conducted and 45 sequential patients who received both polysomnography (PSG) and CPAP titration were included. The raw data of sleep EEG were extracted and analyzed by engineers using two main factors: fractal dimension (FD) and the zero-crossing rate of detrended FD (zDFD). FD was an effective indicator reflecting the EEG complexity and zDFD was useful to reflect the variability of the EEG complexity. The FD and zDFD indexes of sleep EEG of 45 OSAS patients before and after CPAP titration were analyzed. The age of 45 OSAS patients was 52.7 ± 5.6 years old and the patients include 12 females and 33 males. After CPAP treatment, FD of EEG in non-rapid eye movement (NREM) sleep decreased significantly (P < 0.05), while FD of EEG increased in rapid eye movement (REM) sleep (P < 0.05). Meanwhile, zDFD were decreased remarkably in both NREM and REM sleep after CPAP therapy (P < 0.05, respectively). CPAP therapy had a significant influence on sleep EEG in patients with OSAHS, which lead to a more stable EEG pattern. This may be one of the mechanisms that CPAP could improve sleep quality and brain function of OSAS patients.

Entropy is more resistant to artifacts than bispectral index in brain-dead organ donors.

PubMed

Wennervirta, Johanna; Salmi, Tapani; Hynynen, Markku; Yli-Hankala, Arvi; Koivusalo, Anna-Maria; Van Gils, Mark; Pöyhiä, Reino; Vakkuri, Anne

2007-01-01

To evaluate the usefulness of entropy and the bispectral index (BIS) in brain-dead subjects. A prospective, open, nonselective, observational study in the university hospital. 16 brain-dead organ donors. Time-domain electroencephalography (EEG), spectral entropy of the EEG, and BIS were recorded during solid organ harvest. State entropy differed significantly from 0 (isoelectric EEG) 28%, response entropy 29%, and BIS 68% of the total recorded time. The median values during the operation were state entropy 0.0, response entropy 0.0, and BIS 3.0. In four of 16 organ donors studied the EEG was not isoelectric, and nonreactive rhythmic activity was noted in time-domain EEG. After excluding the results from subjects with persistent residual EEG activity state entropy, response entropy, and BIS values differed from zero 17%, 18%, and 62% of the recorded time, respectively. Median values were 0.0, 0.0, and 2.0 for state entropy, response entropy, and BIS, respectively. The highest index values in entropy and BIS monitoring were recorded without neuromuscular blockade. The main sources of artifacts were electrocauterization, 50-Hz artifact, handling of the donor, ballistocardiography, electromyography, and electrocardiography. Both entropy and BIS showed nonzero values due to artifacts after brain death diagnosis. BIS was more liable to artifacts than entropy. Neither of these indices are diagnostic tools, and care should be taken when interpreting EEG and EEG-derived indices in the evaluation of brain death.

[Electroencephalography (EEG) recording techniques and artifact detection in early premature babies].

PubMed

Wallois, F; Vecchierini, M-F; Héberlé, C; Walls-Esquivel, E

2007-01-01

EEG recording techniques in early premature babies are not very different from those used for full-term neonates. Here, we emphasise the most important points: asepsis precautions, full knowledge of the clinical data and drug therapies, the fundamental role of a well-trained technician in supervising the EEG recording and monitoring the baby. The best electrode positions, the most informative montages and their standardisation between neurophysiological laboratories, are suggested. Artifact detection constitutes an important aspect of EEG signal analysis in preterm babies of less than 30 weeks. It is obviously necessary to discriminate between meaningful information and artefacts. The complexity of the signal in neonates makes artifact detection difficult. We present some characteristic features and describe some methods for eliminating them. We underline the positive aspect of some artifacts and their clinical use. We emphasise the crucial role of the technicians.

Serial EEG findings in anti-NMDA receptor encephalitis: correlation between clinical course and EEG.

PubMed

Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo

2017-12-01

Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.

Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy: A computational study.

PubMed

Ruijter, B J; Hofmeijer, J; Meijer, H G E; van Putten, M J A M

2017-09-01

In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically evolve in time. We aim to improve the understanding of pathophysiological mechanisms underlying these EEG abnormalities. We used a mean field model comprising excitatory and inhibitory neurons, local synaptic connections, and input from thalamic afferents. Anoxic damage is modeled as aggravated short-term synaptic depression, with gradual recovery over many hours. Additionally, excitatory neurotransmission is potentiated, scaling with the severity of anoxic encephalopathy. Simulations were compared with continuous EEG recordings of 155 comatose patients after cardiac arrest. The simulations agree well with six common categories of EEG rhythms in postanoxic encephalopathy, including typical transitions in time. Plausible results were only obtained if excitatory synapses were more severely affected by short-term synaptic depression than inhibitory synapses. In postanoxic encephalopathy, the evolution of EEG patterns presumably results from gradual improvement of complete synaptic failure, where excitatory synapses are more severely affected than inhibitory synapses. The range of EEG patterns depends on the excitation-inhibition imbalance, probably resulting from long-term potentiation of excitatory neurotransmission. Our study is the first to relate microscopic synaptic dynamics in anoxic brain injury to both typical EEG observations and their evolution in time. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

EEG-fMRI evaluation of patients with mesial temporal lobe sclerosis.

PubMed

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-02-01

This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques.

EEG-fMRI Evaluation of Patients with Mesial Temporal Lobe Sclerosis

PubMed Central

Avesani, Mirko; Giacopuzzi, Silvia; Bongiovanni, Luigi Giuseppe; Borelli, Paolo; Cerini, Roberto; Pozzi Mucelli, Roberto; Fiaschi, Antonio

2014-01-01

Summary This preliminary study sought more information on blood oxygen level dependent (BOLD) activation, especially contralateral temporal/extratemporal spread, during continuous EEG-fMRI recordings in four patients with mesial temporal sclerosis (MTS). In two patients, EEG showed unilateral focal activity during the EEG-fMRI session concordant with the interictal focus previously identified with standard and video-poly EEG. In the other two patients EEG demonstrated a contralateral diffusion of the irritative focus. In the third patient (with the most drug-resistant form and also extratemporal clinical signs), there was an extratemporal diffusion over frontal regions, ipsilateral to the irritative focus. fMRI analysis confirmed a single activation in the mesial temporal region in two patients whose EEG showed unilateral focal activity, while it demonstrated a bilateral activation in the mesial temporal regions in the other two patients. In the third patient, fMRI demonstrated an activation in the supplementary motxor area. This study confirms the most significant activation with a high firing rate of the irritative focus, but also suggests the importance of using new techniques (such as EEG-fMRI to examine cerebral blood flow) to identify the controlateral limbic activation, and any other extratemporal activations, possible causes of drug resistance in MTS that may require a more precise pre-surgical evaluation with invasive techniques. PMID:24571833

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form.

PubMed

Martínez-Rodrigo, Arturo; Fernández-Sotos, Alicia; Latorre, José Miguel; Moncho-Bogani, José; Fernández-Caballero, Antonio

2017-01-01

This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form.

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form

PubMed Central

Martínez-Rodrigo, Arturo; Fernández-Sotos, Alicia; Latorre, José Miguel; Moncho-Bogani, José; Fernández-Caballero, Antonio

2017-01-01

This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG) by using a brain–computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency. Our experiment shows statistical differences in theta and alpha bands in the phrase rhythm variations of two classical sonatas, one in bipartite form and the other in rondo form. PMID:28496406

An innovative nonintrusive driver assistance system for vital signal monitoring.

PubMed

Sun, Ye; Yu, Xiong Bill

2014-11-01

This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary parameters such as heart rate and HR variability are good indicators of health state as well as driver fatigue. A conventional biopotential measurement system requires the electrodes to be in contact with human body. This not only interferes with the driver operation, but also is not feasible for long-term monitoring purpose. The driver assistance system in this paper can remotely detect the biopotential signals with no physical contact with human skin. With delicate sensor and electronic design, ECG, EEG, and eye blinking can be measured. Experiments were conducted on a high fidelity driving simulator to validate the system performance. The system was found to be able to detect the ECG/EEG signals through cloth or hair with no contact with skin. Eye blinking activities can also be detected at a distance of 10 cm. Digital signal processing algorithms were developed to decimate the signal noise and extract the physiological features. The extracted features from the vital signals were further analyzed to assess the potential criterion for alertness and drowsiness determination.

Refractory status epilepticus

PubMed Central

Singh, Sanjay P; Agarwal, Shubhi; Faulkner, M

2014-01-01

Refractory status epilepticus is a potentially life-threatening medical emergency. It requires early diagnosis and treatment. There is a lack of consensus upon its semantic definition of whether it is status epilepticus that continues despite treatment with benzodiazepine and one antiepileptic medication (AED), i.e., Lorazepam + phenytoin. Others regard refractory status epilepticus as failure of benzodiazepine and 2 antiepileptic medications, i.e., Lorazepam + phenytoin + phenobarb. Up to 30% patients in SE fail to respond to two antiepileptic drugs (AEDs) and 15% continue to have seizure activity despite use of three drugs. Mechanisms that have made the treatment even more challenging are GABA-R that is internalized during status epilepticus and upregulation of multidrug transporter proteins. All patients of refractory status epilepticus require continuous EEG monitoring. There are three main agents used in the treatment of RSE. These include pentobarbital or thiopental, midazolam and propofol. RSE was shown to result in mortality in 35% cases, 39.13% of patients were left with severe neurological deficits, while another 13% had mild neurological deficits. PMID:24791086

Quantitative EEG analysis in minimally conscious state patients during postural changes.

PubMed

Greco, A; Carboncini, M C; Virgillito, A; Lanata, A; Valenza, G; Scilingo, E P

2013-01-01

Mobilization and postural changes of patients with cognitive impairment are standard clinical practices useful for both psychic and physical rehabilitation process. During this process, several physiological signals, such as Electroen-cephalogram (EEG), Electrocardiogram (ECG), Photopletysmography (PPG), Respiration activity (RESP), Electrodermal activity (EDA), are monitored and processed. In this paper we investigated how quantitative EEG (qEEG) changes with postural modifications in minimally conscious state patients. This study is quite novel and no similar experimental data can be found in the current literature, therefore, although results are very encouraging, a quantitative analysis of the cortical area activated in such postural changes still needs to be deeply investigated. More specifically, this paper shows EEG power spectra and brain symmetry index modifications during a verticalization procedure, from 0 to 60 degrees, of three patients in Minimally Consciousness State (MCS) with focused region of impairment. Experimental results show a significant increase of the power in β band (12 - 30 Hz), commonly associated to human alertness process, thus suggesting that mobilization and postural changes can have beneficial effects in MCS patients.

Distribution entropy analysis of epileptic EEG signals.

PubMed

Li, Peng; Yan, Chang; Karmakar, Chandan; Liu, Changchun

2015-01-01

It is an open-ended challenge to accurately detect the epileptic seizures through electroencephalogram (EEG) signals. Recently published studies have made elaborate attempts to distinguish between the normal and epileptic EEG signals by advanced nonlinear entropy methods, such as the approximate entropy, sample entropy, fuzzy entropy, and permutation entropy, etc. Most recently, a novel distribution entropy (DistEn) has been reported to have superior performance compared with the conventional entropy methods for especially short length data. We thus aimed, in the present study, to show the potential of DistEn in the analysis of epileptic EEG signals. The publicly-accessible Bonn database which consisted of normal, interictal, and ictal EEG signals was used in this study. Three different measurement protocols were set for better understanding the performance of DistEn, which are: i) calculate the DistEn of a specific EEG signal using the full recording; ii) calculate the DistEn by averaging the results for all its possible non-overlapped 5 second segments; and iii) calculate it by averaging the DistEn values for all the possible non-overlapped segments of 1 second length, respectively. Results for all three protocols indicated a statistically significantly increased DistEn for the ictal class compared with both the normal and interictal classes. Besides, the results obtained under the third protocol, which only used very short segments (1 s) of EEG recordings showed a significantly (p <; 0.05) increased DistEn for the interictal class in compassion with the normal class, whereas both analyses using relatively long EEG signals failed in tracking this difference between them, which may be due to a nonstationarity effect on entropy algorithm. The capability of discriminating between the normal and interictal EEG signals is of great clinical relevance since it may provide helpful tools for the detection of a seizure onset. Therefore, our study suggests that the DistEn analysis of EEG signals is very promising for clinical and even portable EEG monitoring.

Quantitative EEG Monitoring of Vigilance: Effects of Sleep Deprivation, Circadian Phase and Sympathetic Activation

NASA Technical Reports Server (NTRS)

Dijk, Derk-Jan

1999-01-01

Shuttle astronauts typically sleep only 6 to 6.5 hours per day while in orbit. This sleep loss is related to recurrent sleep cycle shifting--due to mission-dependent orbital mechanics and mission duration requirements-- and associated circadian displacement of sleep, the operational demands of space flight, noise and space motion sickness. Such sleep schedules are known to produce poor subjective sleep quality, daytime sleepiness, reduced attention, negative mood, slower reaction times, and impaired daytime alertness. Countermeasures to allow crew members to obtain an adequate amount of sleep and maintain adequate levels of neurobehavioral performance are being developed and investigated. However, it is necessary to develop methods that allow effective and attainable in-flight monitoring of vigilance to evaluate the effectiveness of these countermeasures and to detect and predict online critical decrements in alertness/performance. There is growing evidence to indicate that sleep loss and associated decrements in neurobehavioral function are reflected in the spectral composition of the electroencephalogram (EEG) during wakefulness as well as in the incidence of slow eye movements recorded by the electro-oculogram (EOG). Further-more, our preliminary data indicated that these changes in the EEG during wakefulness are more pronounced when subjects are in a supine posture, which mimics some of the physiologic effects of microgravity. Therefore, we evaluate the following hypotheses: (1) that during a 40-hour period of wakefulness (i.e., one night of total sleep deprivation) neurobehavioral function deteriorates, the incidence of slow eye-movements and EEG power density in the theta frequencies increases especially in frontal areas of the brain; (2) that the sleep deprivation induced deterioration of neurobehavioral function and changes in the incidence of slow eye movements and the spectral composition of the EEG are more pronounced when subjects are in a supine position; and (3) that based on assessment of slow-eye movements and quantitative on-line topographical analyses of EEG during wakefulness an EEG and or EOG parameter can be derived/constructed which accurately predicts changes in neurobehavioral function.

Biocybernetic Control of Vigilance Task Parameters

NASA Technical Reports Server (NTRS)

Freeman, Frederick G.

2000-01-01

The major focus of the present proposal was to examine psychophysiological variables that are related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Utility of video-EEG monitoring in a tertiary care epilepsy center.

PubMed

Kumar-Pelayo, M; Oller-Cramsie, M; Mihu, N; Harden, C

2013-09-01

Our video-EEG monitoring (VEEG) unit is part of a typical metropolitan tertiary care center that services a diverse patient population. We aimed to determine if the specific clinical reason for inpatient VEEG was actually resolved. Our method was to retrospectively determine the stated goal of inpatient VEEG and to analyze the outcome of one hundred consecutive adult patients admitted for VEEG. The reason for admission fit into one of four categories: 1) to characterize paroxysmal events as either epileptic or nonepileptic, 2) to localize epileptic foci, 3) to characterize the epilepsy syndrome, and 4) to attempt safe antiepileptic drug adjustment. We found that VEEG was successful in accomplishing the goal of admission in 77% of cases. The remaining 23% failed primarily due to lack of typical events during monitoring. Furthermore, of the overall study cohort, VEEG outcomes altered medical management in 53% and surgery was pursued in 5%. © 2013.

Nonconvulsive status epilepticus after cessation of convulsive status epilepticus in pediatric intensive care unit patients.

PubMed

Chen, Jin; Xie, Lingling; Hu, Yue; Lan, Xinghui; Jiang, Li

2018-05-01

Little is known about pediatric patients suffering from nonconvulsive status epilepticus (NCSE) after convulsive status epilepticus (CSE) cessation. The aim of this study was to identify in pediatric patients the clinical characteristics of NCSE after CSE cessation and the factors that contribute to patient outcomes. Data from clinical features, electroencephalography (EEG) characteristics, neuroimaging findings, treatments, and prognosis were systematically summarized, and the associations between clinical characteristics and prognosis were quantified. Thirty-eight children aged 51days-14years, 2months were identified in the Chongqing Medical University pediatric intensive care unit as having experienced NCSE after CSE cessation between October 1, 2014 and April 1, 2017. All patients were comatose, 15 of whom presented subtle motor signs. The most common underlying etiology was acute central nervous system (CNS) infection. Electroencephalography (EEG) data showed that, during the NCSE period, all patients had several discrete episodes (lasting from 30s to 6h long), and the most common duration was 1-5min. The ictal onset locations were classified as focal (16 patients, 42.1%), multiregional independent (10 patients, 26.3%), and generalized (12 patients, 31.6%). Wave morphologies varied during the ictal and interictal periods. Neuroimaging detected signal abnormalities in the cerebral cortex or subcortex of 33 patients with NCSE (87%), which were classified as either multifocal and consistent with extensive cortical edema (21 patients, 55.3%) or focal (12 patients, 31.6%). Twelve patients were on continuous intravenous phenobarbital, and 31 were on continuous infusion of either midazolam (27 patients) or propofol (4 patients). At least one other antiepileptic drug was prescribed for 32 patients. Three patients were on mild hypothermia therapy. The duration of NCSE lasted <24h for 20 patients and >24h for 18 patients. The mortality rate was 21.1%, and half of the surviving patients had severe neurological morbidity. Our results indicated that EEG monitoring after treatment of CSE was essential to the recognition of persistent seizures. The clinical features, EEG characteristics, and neuroimaging findings varied during the NCSE period. The morbidity is high in pediatric patients who had NCSE after CSE. Convulsive status epilepticus (CSE) duration and neuroimaging results may be related to the prognosis. Copyright © 2018 Elsevier Inc. All rights reserved.

[Verification of skin paste electrodes used in wireless polysomnography].

PubMed

Ma, Y D; Huang, D; Chen, Y F; Jiang, H Y; Liu, J H; Sun, H Q; Li, Z H

2018-04-18

To explore an electrode suitable for wireless portable sleep monitoring equipment and analyze the result of the signals of electrooculogram (EOG) and electroencephalography (EEG) collected by this kind of flexible electrodes. The flexible electrodes were prepared by microelectromechanical systems (MEMS) technology. This kind of electrodes consisted parylene, chromium, and gold. Parylene, the flexible substrate of this kind of flexible electrodes, was of biocompatibility. Between parylene and gold there was an adhesion layer of chromium, which connected parylene and gold tightly. Then the flexible electrodes were stuck to medical adhesive tape. The electrodes were designed and made into a grid to make sure that the medical adhesive tape could tape on the skin tightly, so that the contact impedance between the electrodes and the skin would be reduced. Then the alternating current impedance of the electrode were tested by the CHI660E electrochemical workstation after the electrode was achieved. To make sure that this kind of electrodes could be used in EOG monitoring, the electrodes were connected to a wireless signal acquisition suite containing special biological signal acquisition and digital processing chip to gather different sites around the eyes and the electrical signals of different directions of the eye movements, then analyzed the signal-to-noise ratio of the EOG. At the end, the Philips A6 polysomnography was used to compare the noise amplitude of the EEG signals collected by the flexible electrode and the gold cup electrode. The electrodes stuck to the skin tightly, and these electrodes could collect signals that we wanted while the experiment was performed. The alternating current impedance of the flexible electrode was between 4 kΩ and 13 kΩ while with the frequency of alternating current under 100 Hz, most EEG signal frequencies were at this range. The EOG signals collected by the flexible electrodes were in line with the clinical requirements. The noise amplitude of EEG signals collected by the flexible electrodes was lower than that of the electrical signals collected by the gold cup electrodes. The flexible electrode could be taken into consideration as an alternative electrode for monitoring EOG and EEG signals, and the wireless portable sleep monitoring devices are to be further developed in the future.

Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

PubMed

Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

2018-08-01

An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in augmenting clinical decision making.

EEG-based learning system for online motion sickness level estimation in a dynamic vehicle environment.

PubMed

Lin, Chin-Teng; Tsai, Shu-Fang; Ko, Li-Wei

2013-10-01

Motion sickness is a common experience for many people. Several previous researches indicated that motion sickness has a negative effect on driving performance and sometimes leads to serious traffic accidents because of a decline in a person's ability to maintain self-control. This safety issue has motivated us to find a way to prevent vehicle accidents. Our target was to determine a set of valid motion sickness indicators that would predict the occurrence of a person's motion sickness as soon as possible. A successful method for the early detection of motion sickness will help us to construct a cognitive monitoring system. Such a monitoring system can alert people before they become sick and prevent them from being distracted by various motion sickness symptoms while driving or riding in a car. In our past researches, we investigated the physiological changes that occur during the transition of a passenger's cognitive state using electroencephalography (EEG) power spectrum analysis, and we found that the EEG power responses in the left and right motors, parietal, lateral occipital, and occipital midline brain areas were more highly correlated to subjective sickness levels than other brain areas. In this paper, we propose the use of a self-organizing neural fuzzy inference network (SONFIN) to estimate a driver's/passenger's sickness level based on EEG features that have been extracted online from five motion sickness-related brain areas, while either in real or virtual vehicle environments. The results show that our proposed learning system is capable of extracting a set of valid motion sickness indicators that originated from EEG dynamics, and through SONFIN, a neuro-fuzzy prediction model, we successfully translated the set of motion sickness indicators into motion sickness levels. The overall performance of this proposed EEG-based learning system can achieve an average prediction accuracy of ~82%.

Monitoring sleepiness with on-board electrophysiological recordings for preventing sleep-deprived traffic accidents.

PubMed

Papadelis, Christos; Chen, Zhe; Kourtidou-Papadeli, Chrysoula; Bamidis, Panagiotis D; Chouvarda, Ioanna; Bekiaris, Evangelos; Maglaveras, Nikos

2007-09-01

The objective of this study is the development and evaluation of efficient neurophysiological signal statistics, which may assess the driver's alertness level and serve as potential indicators of sleepiness in the design of an on-board countermeasure system. Multichannel EEG, EOG, EMG, and ECG were recorded from sleep-deprived subjects exposed to real field driving conditions. A number of severe driving errors occurred during the experiments. The analysis was performed in two main dimensions: the macroscopic analysis that estimates the on-going temporal evolution of physiological measurements during the driving task, and the microscopic event analysis that focuses on the physiological measurements' alterations just before, during, and after the driving errors. Two independent neurophysiologists visually interpreted the measurements. The EEG data were analyzed by using both linear and non-linear analysis tools. We observed the occurrence of brief paroxysmal bursts of alpha activity and an increased synchrony among EEG channels before the driving errors. The alpha relative band ratio (RBR) significantly increased, and the Cross Approximate Entropy that quantifies the synchrony among channels also significantly decreased before the driving errors. Quantitative EEG analysis revealed significant variations of RBR by driving time in the frequency bands of delta, alpha, beta, and gamma. Most of the estimated EEG statistics, such as the Shannon Entropy, Kullback-Leibler Entropy, Coherence, and Cross-Approximate Entropy, were significantly affected by driving time. We also observed an alteration of eyes blinking duration by increased driving time and a significant increase of eye blinks' number and duration before driving errors. EEG and EOG are promising neurophysiological indicators of driver sleepiness and have the potential of monitoring sleepiness in occupational settings incorporated in a sleepiness countermeasure device. The occurrence of brief paroxysmal bursts of alpha activity before severe driving errors is described in detail for the first time. Clear evidence is presented that eye-blinking statistics are sensitive to the driver's sleepiness and should be considered in the design of an efficient and driver-friendly sleepiness detection countermeasure device.

Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms.

PubMed

Rommens, Nicole; Geertsema, Evelien; Jansen Holleboom, Lisanne; Cox, Fieke; Visser, Gerhard

2018-05-11

User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time. EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU. EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h. EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures. Copyright © 2018. Published by Elsevier Inc.

Video Game Adapts To Brain Waves

NASA Technical Reports Server (NTRS)

Pope, Alan T.; Bogart, Edward H.

1994-01-01

Electronic training system based on video game developed to help children afflicted with attention-deficit disorder (ADD) learn to prolong their attention spans. Uses combination of electroencephalography (EEG) and adaptive control to encourage attentiveness. Monitors trainee's brain-wave activity: if EEG signal indicates attention is waning, system increases difficulty of game, forcing trainee to devote more attention to it. Game designed to make trainees want to win and, in so doing, learn to pay attention for longer times.

Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI

DTIC Science & Technology

2016-04-01

but these delays are nearing resolution and we anticipate the initiation of the neuroimaging portion of the study early in Year 3. The fMRI task...resonance imagining ( fMRI ) and diffusion tensor imaging (DTI) to characterize the extent of functional cortical recruitment and white matter injury...respectively. The inclusion of fMRI and DTI will provide an objective basis for cross-validating the EEG and eye tracking system. Both the EEG and eye

The use of EEG to measure cerebral changes during computer-based motion-sickness-inducing tasks

NASA Astrophysics Data System (ADS)

Strychacz, Christopher; Viirre, Erik; Wing, Shawn

2005-05-01

Motion sickness (MS) is a stressor commonly attributed with causing serious navigational and performance errors. The distinct nature of MS suggests this state may have distinct neural markers distinguishable from other states known to affect performance (e.g., stress, fatigue, sleep deprivation, high workload). This pilot study used new high-resolution electro-encephalograph (EEG) technologies to identify distinct neuronal activation changes that occur during MS. Brain EEG activity was monitored while subjects performed a ball-tracking task and viewed stimuli on a projection screen intended to induce motion sickness/spatial disorientation. Results show the presence of EEG spectral changes in all subjects who developed motion sickness when compared to baseline levels. These changes included: 1) low frequency (1 to 10 Hz) changes that may reflect oculomotor movements rather than intra-cerebral sources; 2) increased spectral power across all frequencies (attributable to increased scalp conductivity related to sweating), 3) local increases of power spectra in the 20-50 Hz range (likely attributable to external muscles on the skull) and; 4) a central posterior (occipital) independent component that shows suppression of a 20 Hz peak in the MS condition when compared to baseline. Further research is necessary to refine neural markers, characterize their origin and physiology, to distinguish between motion sickness and other states and to enable markers to be used for operator state monitoring and the designing of interventions for motion sickness.

Causality within the Epileptic Network: An EEG-fMRI Study Validated by Intracranial EEG.

PubMed

Vaudano, Anna Elisabetta; Avanzini, Pietro; Tassi, Laura; Ruggieri, Andrea; Cantalupo, Gaetano; Benuzzi, Francesca; Nichelli, Paolo; Lemieux, Louis; Meletti, Stefano

2013-01-01

Accurate localization of the Seizure Onset Zone (SOZ) is crucial in patients with drug-resistance focal epilepsy. EEG with fMRI recording (EEG-fMRI) has been proposed as a complementary non-invasive tool, which can give useful additional information in the pre-surgical work-up. However, fMRI maps related to interictal epileptiform activities (IED) often show multiple regions of signal change, or "networks," rather than highly focal ones. Effective connectivity approaches like Dynamic Causal Modeling (DCM) applied to fMRI data potentially offers a framework to address which brain regions drives the generation of seizures and IED within an epileptic network. Here, we present a first attempt to validate DCM on EEG-fMRI data in one patient affected by frontal lobe epilepsy. Pre-surgical EEG-fMRI demonstrated two distinct clusters of blood oxygenation level dependent (BOLD) signal increases linked to IED, one located in the left frontal pole and the other in the ipsilateral dorso-lateral frontal cortex. DCM of the IED-related BOLD signal favored a model corresponding to the left dorso-lateral frontal cortex as driver of changes in the fronto-polar region. The validity of DCM was supported by: (a) the results of two different non-invasive analysis obtained on the same dataset: EEG source imaging (ESI), and "psycho-physiological interaction" analysis; (b) the failure of a first surgical intervention limited to the fronto-polar region; (c) the results of the intracranial EEG monitoring performed after the first surgical intervention confirming a SOZ located over the dorso-lateral frontal cortex. These results add evidence that EEG-fMRI together with advanced methods of BOLD signal analysis is a promising tool that can give relevant information within the epilepsy surgery diagnostic work-up.

Design and validation of a wearable "DRL-less" EEG using a novel fully-reconfigurable architecture.

PubMed

Mahajan, Ruhi; Morshed, Bashir I; Bidelman, Gavin M

2016-08-01

The conventional EEG system consists of a driven-right-leg (DRL) circuit, which prohibits modularization of the system. We propose a Lego-like connectable fully reconfigurable architecture of wearable EEG that can be easily customized and deployed at naturalistic settings for collecting neurological data. We have designed a novel Analog Front End (AFE) that eliminates the need for DRL while maintaining a comparable signal quality of EEG. We have prototyped this AFE for a single channel EEG, referred to as Smart Sensing Node (SSN), that senses brain signals and sends it to a Command Control Node (CCN) via an I2C bus. The AFE of each SSN (referential-montage) consists of an off-the-shelf instrumentation amplifier (gain=26), an active notch filter fc = 60Hz), 2nd-order active Butterworth low-pass filter followed by a passive low pass filter (fc = 47.5 Hz, gain = 1.61) and a passive high pass filter fc = 0.16 Hz, gain = 0.83). The filtered signals are digitized using a low-power microcontroller (MSP430F5528) with a 12-bit ADC at 512 sps, and transmitted to the CCN every 1 s at a bus rate of 100 kbps. The CCN can further transmit this data wirelessly using Bluetooth to the paired computer at a baud rate of 115.2 kbps. We have compared temporal and frequency-domain EEG signals of our system with a research-grade EEG. Results show that the proposed reconfigurable EEG captures comparable signals, and is thus promising for practical routine neurological monitoring in non-clinical settings where a flexible number of EEG channels are needed.

Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state

PubMed Central

Gosseries, Olivia; Schnakers, Caroline; Ledoux, Didier; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Demertzi, Athéna; Noirhomme, Quentin; Lehembre, Rémy; Damas, Pierre; Goldman, Serge; Peeters, Erika; Moonen, Gustave; Laureys, Steven

Summary Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic – albeit not prognostic – tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false negative and false positive findings. PMID:21693085

Recent Advances in Resting-State Electroencephalography Biomarkers for Autism Spectrum Disorder-A Review of Methodological and Clinical Challenges.

PubMed

Heunis, Tosca-Marie; Aldrich, Chris; de Vries, Petrus J

2016-08-01

Electroencephalography (EEG) has been used for almost a century to identify seizure-related disorders in humans, typically through expert interpretation of multichannel recordings. Attempts have been made to quantify EEG through frequency analyses and graphic representations. These "traditional" quantitative EEG analysis methods were limited in their ability to analyze complex and multivariate data and have not been generally accepted in clinical settings. There has been growing interest in identification of novel EEG biomarkers to detect early risk of autism spectrum disorder, to identify clinically meaningful subgroups, and to monitor targeted intervention strategies. Most studies to date have, however, used quantitative EEG approaches, and little is known about the emerging multivariate analytical methods or the robustness of candidate biomarkers in the context of the variability of autism spectrum disorder. Here, we present a targeted review of methodological and clinical challenges in the search for novel resting-state EEG biomarkers for autism spectrum disorder. Three primary novel methodologies are discussed: (1) modified multiscale entropy, (2) coherence analysis, and (3) recurrence quantification analysis. Results suggest that these methods may be able to classify resting-state EEG as "autism spectrum disorder" or "typically developing", but many signal processing questions remain unanswered. We suggest that the move to novel EEG analysis methods is akin to the progress in neuroimaging from visual inspection, through region-of-interest analysis, to whole-brain computational analysis. Novel resting-state EEG biomarkers will have to evaluate a range of potential demographic, clinical, and technical confounders including age, gender, intellectual ability, comorbidity, and medication, before these approaches can be translated into the clinical setting. Copyright © 2016 Elsevier Inc. All rights reserved.

Losing the struggle to stay awake: divergent thalamic and cortical activity during microsleeps.

PubMed

Poudel, Govinda R; Innes, Carrie R H; Bones, Philip J; Watts, Richard; Jones, Richard D

2014-01-01

Maintaining alertness is critical for safe and successful performance of most human activities. Consequently, microsleeps during continuous visuomotor tasks, such as driving, can be very serious, not only disrupting performance but sometimes leading to injury or death due to accidents. We have investigated the neural activity underlying behavioral microsleeps--brief (0.5-15 s) episodes of complete failure to respond accompanied by slow eye-closures--and EEG theta activity during drowsiness in a continuous task. Twenty healthy normally-rested participants performed a 50-min continuous tracking task while fMRI, EEG, eye-video, and responses were simultaneously recorded. Visual rating of performance and eye-video revealed that 70% of the participants had frequent microsleeps. fMRI analysis revealed a transient decrease in thalamic, posterior cingulate, and occipital cortex activity and an increase in frontal, posterior parietal, and parahippocampal activity during microsleeps. The transient activity was modulated by the duration of the microsleep. In subjects with frequent microsleeps, power in the post-central EEG theta was positively correlated with the BOLD signal in the thalamus, basal forebrain, and visual, posterior parietal, and prefrontal cortices. These results provide evidence for distinct neural changes associated with microsleeps and with EEG theta activity during drowsiness in a continuous task. They also suggest that the occurrence of microsleeps during an active task is not a global deactivation process but involves localized activation of fronto-parietal cortex, which, despite a transient loss of arousal, may constitute a mechanism by which these regions try to restore responsiveness. Copyright © 2012 Wiley Periodicals, Inc.

Understanding the pathophysiology of reflex epilepsy using simultaneous EEG-fMRI.

PubMed

Sandhya, Manglore; Bharath, Rose Dawn; Panda, Rajanikant; Chandra, S R; Kumar, Naveen; George, Lija; Thamodharan, A; Gupta, Arun Kumar; Satishchandra, P

2014-03-01

Measuring neuro-haemodynamic correlates in the brain of epilepsy patients using EEG-fMRI has opened new avenues in clinical neuroscience, as these are two complementary methods for understanding brain function. In this study, we investigated three patients with drug-resistant reflex epilepsy using EEG-fMRI. Different types of reflex epilepsy such as eating, startle myoclonus, and hot water epilepsy were included in the study. The analysis of EEG-fMRI data was based on the visual identification of interictal epileptiform discharges on scalp EEG. The convolution of onset time and duration of these epilepsy spikes was estimated, and using these condition-specific effects in a general linear model approach, we evaluated activation of fMRI. Patients with startle myoclonus epilepsy experienced epilepsy in response to sudden sound or touch, in association with increased delta and theta activity with a spike-and-slow-wave pattern of interictal epileptiform discharges on EEG and fronto-parietal network activation pattern on SPECT and EEG-fMRI. Eating epilepsy was triggered by sight or smell of food and fronto-temporal discharges were noted on video-EEG (VEEG). Similarly, fronto-temporo-parietal involvement was noted on SPECT and EEG-fMRI. Hot water epilepsy was triggered by contact with hot water either in the bath or by hand immersion, and VEEG showed fronto-parietal involvement. SPECT and EEG fMRI revealed a similar fronto-parietal-occipital involvement. From these results, we conclude that continuous EEG recording can improve the modelling of BOLD changes related to interictal epileptic activity and this can thus be used to understand the neuro-haemodynamic substrates involved in reflex epilepsy.

A wearable neuro-feedback system with EEG-based mental status monitoring and transcranial electrical stimulation.

PubMed

Roh, Taehwan; Song, Kiseok; Cho, Hyunwoo; Shin, Dongjoo; Yoo, Hoi-Jun

2014-12-01

A wearable neuro-feedback system is proposed with a low-power neuro-feedback SoC (NFS), which supports mental status monitoring with encephalography (EEG) and transcranial electrical stimulation (tES) for neuro-modulation. Self-configured independent component analysis (ICA) is implemented to accelerate source separation at low power. Moreover, an embedded support vector machine (SVM) enables online source classification, configuring the ICA accelerator adaptively depending on the types of the decomposed components. Owing to the hardwired accelerating functions, the NFS dissipates only 4.45 mW to yield 16 independent components. For non-invasive neuro-modulation, tES stimulation up to 2 mA is implemented on the SoC. The NFS is fabricated in 130-nm CMOS technology.

Novel bifunctional cap for simultaneous electroencephalography and transcranial electrical stimulation.

PubMed

Wunder, Sophia; Hunold, Alexander; Fiedler, Patrique; Schlegelmilch, Falk; Schellhorn, Klaus; Haueisen, Jens

2018-05-08

Neuromodulation induced by transcranial electric stimulation (TES) exhibited promising potential for clinical practice. However, the underlying mechanisms remain subject of research. The combination of TES and electroencephalography (EEG) offers great potential for investigating these mechanisms and brain function in general, especially when performed simultaneously. In conventional applications, the combination of EEG and TES suffers from limitations on the electrode level (gel for electrode-skin interface) and the usability level (preparation time, reproducibility of positioning). To overcome these limitations, we designed a bifunctional cap for simultaneous TES-EEG applications. We used novel electrode materials, namely textile stimulation electrodes and dry EEG electrodes integrated in a flexible textile cap. We verified the functionality of this cap by analysing the effect of TES on visual evoked potentials (VEPs). In accordance with previous reports using standard TES, the amplitude of the N75 component was significantly decreased post-stimulation, indicating the feasibility of using this novel flexible cap for simultaneous TES and EEG. Further, we found a significant reduction of the P100 component only during TES, indicating a different brain modulation effect during and after TES. In conclusion, the novel bifunctional cap offers a novel tool for simultaneous TES-EEG applications in clinical research, therapy monitoring and closed-loop stimulation.

Proepileptic patterns in EEG of WAG/Rij rats

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Sitnikova, Evgenia Yu.; Nedaivozov, Vladimir O.; Koronovskii, Alexey A.

2018-04-01

In this paper we study specific oscillatory patterns on EEG signals of WAG/Rij rats. These patterns are known as proepileptic because they occur in time period during the development of absence-epilepsy before fully-formed epileptic seizures. In the paper we analyze EEG signals of WAG/Rij rats with continuous wavelet transform and empirical mode decomposition in order to find particular features of epileptic spike-wave discharges and nonepileptic sleep spindles. Then we introduce proepileptic activity as patterns that combine features of epileptic and non-epileptic activity. We analyze proepileptic activity in order to specify its features and time-frequency structure.

Applying support vector machine on hybrid fNIRS/EEG signal to classify driver's conditions (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nguyen, Thien; Ahn, Sangtae; Jang, Hyojung; Jun, Sung C.; Kim, Jae G.

2016-03-01

Driver's condition plays a critical role in driving safety. The fact that about 20 percent of automobile accidents occurred due to driver fatigue leads to a demand for developing a method to monitor driver's status. In this study, we acquired brain signals such as oxy- and deoxyhemoglobin and neuronal electrical activity by a hybrid fNIRS/EEG system. Experiments were conducted with 11 subjects under two conditions: Normal condition, when subjects had enough sleep, and sleep deprivation condition, when subject did not sleep previous night. During experiment, subject performed a driving task with a car simulation system for 30 minutes. After experiment, oxy-hemoglobin and deoxy-hemoglobin changes were derived from fNIRS data, while beta and alpha band relative power were calculated from EEG data. Decrement of oxy-hemoglobin, beta band power, and increment of alpha band power were found in sleep deprivation condition compare to normal condition. These features were then applied to classify two conditions by Fisher's linear discriminant analysis (FLDA). The ratio of alpha-beta relative power showed classification accuracy with a range between 62% and 99% depending on a subject. However, utilization of both EEG and fNIRS features increased accuracy in the range between 68% and 100%. The highest increase of accuracy is from 63% using EEG to 99% using both EEG and fNIRS features. In conclusion, the enhancement of classification accuracy is shown by adding a feature from fNIRS to the feature from EEG using FLDA which provides the need of developing a hybrid fNIRS/EEG system.

Instantaneous frequency based newborn EEG seizure characterisation

NASA Astrophysics Data System (ADS)

Mesbah, Mostefa; O'Toole, John M.; Colditz, Paul B.; Boashash, Boualem

2012-12-01

The electroencephalogram (EEG), used to noninvasively monitor brain activity, remains the most reliable tool in the diagnosis of neonatal seizures. Due to their nonstationary and multi-component nature, newborn EEG seizures are better represented in the joint time-frequency domain than in either the time domain or the frequency domain. Characterising newborn EEG seizure nonstationarities helps to better understand their time-varying nature and, therefore, allow developing efficient signal processing methods for both modelling and seizure detection and classification. In this article, we used the instantaneous frequency (IF) extracted from a time-frequency distribution to characterise newborn EEG seizures. We fitted four frequency modulated (FM) models to the extracted IFs, namely a linear FM, a piecewise-linear FM, a sinusoidal FM, and a hyperbolic FM. Using a database of 30-s EEG seizure epochs acquired from 35 newborns, we were able to show that, depending on EEG channel, the sinusoidal and piecewise-linear FM models best fitted 80-98% of seizure epochs. To further characterise the EEG seizures, we calculated the mean frequency and frequency span of the extracted IFs. We showed that in the majority of the cases (>95%), the mean frequency resides in the 0.6-3 Hz band with a frequency span of 0.2-1 Hz. In terms of the frequency of occurrence of the four seizure models, the statistical analysis showed that there is no significant difference( p = 0.332) between the two hemispheres. The results also indicate that there is no significant differences between the two hemispheres in terms of the mean frequency ( p = 0.186) and the frequency span ( p = 0.302).

Nonparametric Signal Extraction and Measurement Error in the Analysis of Electroencephalographic Activity During Sleep

PubMed Central

Crainiceanu, Ciprian M.; Caffo, Brian S.; Di, Chong-Zhi; Punjabi, Naresh M.

2009-01-01

We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-continuous EEG signals for each subject. The signal features extracted from EEG data are then used in second level analyses to investigate the relation between health, behavioral, or biometric outcomes and sleep. Using subject specific signals estimated with known variability in a second level regression becomes a nonstandard measurement error problem. We propose and implement methods that take into account cross-sectional and longitudinal measurement error. The research presented here forms the basis for EEG signal processing for the SHHS. PMID:20057925

Heart Rate Variability Can Be Used to Estimate Sleepiness-related Decrements in Psychomotor Vigilance during Total Sleep Deprivation

PubMed Central

Chua, Eric Chern-Pin; Tan, Wen-Qi; Yeo, Sing-Chen; Lau, Pauline; Lee, Ivan; Mien, Ivan Ho; Puvanendran, Kathiravelu; Gooley, Joshua J.

2012-01-01

Study Objectives: To assess whether changes in psychomotor vigilance during sleep deprivation can be estimated using heart rate variability (HRV). Design: HRV, ocular, and electroencephalogram (EEG) measures were compared for their ability to predict lapses on the Psychomotor Vigilance Task (PVT). Setting: Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. Participants: Twenty-four healthy Chinese men (mean age ± SD = 25.9 ± 2.8 years). Interventions: Subjects were kept awake continuously for 40 hours under constant environmental conditions. Every 2 hours, subjects completed a 10-minute PVT to assess their ability to sustain visual attention. Measurements and Results: During each PVT, we examined the electrocardiogram (ECG), EEG, and percentage of time that the eyes were closed (PERCLOS). Similar to EEG power density and PERCLOS measures, the time course of ECG RR-interval power density in the 0.02- 0.08-Hz range correlated with the 40-hour profile of PVT lapses. Based on receiver operating characteristic curves, RR-interval power density performed as well as EEG power density at identifying a sleepiness-related increase in PVT lapses above threshold. RR-interval power density (0.02-0.08 Hz) also classified subject performance with sensitivity and specificity similar to that of PERCLOS. Conclusions: The ECG carries information about a person's vigilance state. Hence, HRV measures could potentially be used to predict when an individual is at increased risk of attentional failure. Our results suggest that HRV monitoring, either alone or in combination with other physiologic measures, could be incorporated into safety devices to warn drowsy operators when their performance is impaired. Citation: Chua ECP; Tan WQ; Yeo SC; Lau P; Lee I; Mien IH; Puvanendran K; Gooley JJ. Heart rate variability can be used to estimate sleepiness-related decrements in psychomotor vigilance during total sleep deprivation. SLEEP 2012;35(3):325-334. PMID:22379238

A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

NASA Astrophysics Data System (ADS)

Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

2013-08-01

Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.

Monitoring Cortical Excitability during Repetitive Transcranial Magnetic Stimulation in Children with ADHD: A Single-Blind, Sham-Controlled TMS-EEG Study

PubMed Central

Helfrich, Christian; Pierau, Simone S.; Freitag, Christine M.; Roeper, Jochen; Ziemann, Ulf; Bender, Stephan

2012-01-01

Background Repetitive transcranial magnetic stimulation (rTMS) allows non-invasive stimulation of the human brain. However, no suitable marker has yet been established to monitor the immediate rTMS effects on cortical areas in children. Objective TMS-evoked EEG potentials (TEPs) could present a well-suited marker for real-time monitoring. Monitoring is particularly important in children where only few data about rTMS effects and safety are currently available. Methods In a single-blind sham-controlled study, twenty-five school-aged children with ADHD received subthreshold 1 Hz-rTMS to the primary motor cortex. The TMS-evoked N100 was measured by 64-channel-EEG pre, during and post rTMS, and compared to sham stimulation as an intraindividual control condition. Results TMS-evoked N100 amplitude decreased during 1 Hz-rTMS and, at the group level, reached a stable plateau after approximately 500 pulses. N100 amplitude to supra-threshold single pulses post rTMS confirmed the amplitude reduction in comparison to the pre-rTMS level while sham stimulation had no influence. EEG source analysis indicated that the TMS-evoked N100 change reflected rTMS effects in the stimulated motor cortex. Amplitude changes in TMS-evoked N100 and MEPs (pre versus post 1 Hz-rTMS) correlated significantly, but this correlation was also found for pre versus post sham stimulation. Conclusion The TMS-evoked N100 represents a promising candidate marker to monitor rTMS effects on cortical excitability in children with ADHD. TMS-evoked N100 can be employed to monitor real-time effects of TMS for subthreshold intensities. Though TMS-evoked N100 was a more sensitive parameter for rTMS-specific changes than MEPs in our sample, further studies are necessary to demonstrate whether clinical rTMS effects can be predicted from rTMS-induced changes in TMS-evoked N100 amplitude and to clarify the relationship between rTMS-induced changes in TMS-evoked N100 and MEP amplitudes. The TMS-evoked N100 amplitude reduction after 1 Hz-rTMS could either reflect a globally decreased cortical response to the TMS pulse or a specific decrease in inhibition. PMID:23185537

Asynchronous detection of kinesthetic attention during mobilization of lower limbs using EEG measurements.

PubMed

Melinscak, Filip; Montesano, Luis; Minguez, Javier

2016-02-01

Attention is known to modulate the plasticity of the motor cortex, and plasticity is crucial for recovery in motor rehabilitation. This study addresses the possibility of using an EEG-based brain-computer interface (BCI) to detect kinesthetic attention to movement. A novel experiment emulating physical rehabilitation was designed to study kinesthetic attention. The protocol involved continuous mobilization of lower limbs during which participants reported levels of attention to movement-from focused kinesthetic attention to mind wandering. For this protocol an asynchronous BCI detector of kinesthetic attention and deliberate mind wandering was designed. EEG analysis showed significant differences in theta, alpha, and beta bands, related to the attentional state. These changes were further pinpointed to bands relative to the frequency of the individual alpha peak. The accuracy of the designed BCI ranged between 60.8% and 68.4% (significantly above chance level), depending on the used analysis window length, i.e. acceptable detection delay. This study shows it is possible to use self-reporting to study attention-related changes in EEG during continuous mobilization. Such a protocol is used to develop an asynchronous BCI detector of kinesthetic attention, with potential applications to motor rehabilitation.

Asynchronous detection of kinesthetic attention during mobilization of lower limbs using EEG measurements

NASA Astrophysics Data System (ADS)

Melinscak, Filip; Montesano, Luis; Minguez, Javier

2016-02-01

Objective. Attention is known to modulate the plasticity of the motor cortex, and plasticity is crucial for recovery in motor rehabilitation. This study addresses the possibility of using an EEG-based brain-computer interface (BCI) to detect kinesthetic attention to movement. Approach. A novel experiment emulating physical rehabilitation was designed to study kinesthetic attention. The protocol involved continuous mobilization of lower limbs during which participants reported levels of attention to movement—from focused kinesthetic attention to mind wandering. For this protocol an asynchronous BCI detector of kinesthetic attention and deliberate mind wandering was designed. Main results. EEG analysis showed significant differences in theta, alpha, and beta bands, related to the attentional state. These changes were further pinpointed to bands relative to the frequency of the individual alpha peak. The accuracy of the designed BCI ranged between 60.8% and 68.4% (significantly above chance level), depending on the used analysis window length, i.e. acceptable detection delay. Significance. This study shows it is possible to use self-reporting to study attention-related changes in EEG during continuous mobilization. Such a protocol is used to develop an asynchronous BCI detector of kinesthetic attention, with potential applications to motor rehabilitation.

Action Monitoring and Perfectionism in Anorexia Nervosa

ERIC Educational Resources Information Center

Pieters, Guido L. M.; de Bruijn, Ellen R. A.; Maas, Yvonne; Hulstijn, Wouter; Vandereycken, Walter; Peuskens, Joseph; Sabbe, Bernard G.

2007-01-01

To study action monitoring in anorexia nervosa, behavioral and EEG measures were obtained in underweight anorexia nervosa patients (n=17) and matched healthy controls (n=19) while performing a speeded choice-reaction task. Our main measures of interest were questionnaire outcomes, reaction times, error rates, and the error-related negativity ERP…

[Electroencephalographic characteristics of the deja vu phenomenon].

PubMed

Vlasov, P N; Cherviakov, A V; Gnezdinsiĭ, V V

2013-01-01

Déjà vu (DV, from French "already seen") is an aberration of psychic activity associated with transitory erroneous perception of novel circumstances, objects, or people as already known. An aim of the study was to investigate EEG characteristics of DV in patients with epilepsy. We studied 166 people (63.2% women, mean age 25.17±9.19 years). The DV phenomenon was studied in patients (27 people) and in a control group (139 healthy people). Patients were interviewed for DV characteristics and underwent a long (12-16 h) ambulatory EEG-monitoring study. In EEG, DV episodes in patients began with polyspike activity in the right temporal lobe and, in some cases, ended with the slow-wave theta-delta activity in the right hemisphere.

Wavelet analysis of epileptic spikes

NASA Astrophysics Data System (ADS)

Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Acute hyperglycemia produces transient improvement in glucose transporter type 1 deficiency.

PubMed

Akman, Cigdem I; Engelstad, Kristin; Hinton, Veronica J; Ullner, Paivi; Koenigsberger, Dorcas; Leary, Linda; Wang, Dong; De Vivo, Darryl C

2010-01-01

Glucose transporter type 1 deficiency syndrome (Glut1-DS) is characterized clinically by acquired microcephaly, infantile-onset seizures, psychomotor retardation, choreoathetosis, dystonia, and ataxia. The laboratory signature is hypoglycorrhachia. The 5-hour oral glucose tolerance test (OGTT) was performed to assess cerebral function and systemic carbohydrate homeostasis during acute hyperglycemia, in the knowledge that GLUT1 is constitutively expressed ubiquitously and upregulated in the brain. Thirteen Glut1-DS patients completed a 5-hour OGTT. Six patients had prolonged electroencephalographic (EEG)/video monitoring, 10 patients had plasma glucose and serum insulin measurements, and 5 patients had repeated measures of attention, memory, fine motor coordination, and well-being. All patients had a full neuropsychological battery prior to OGTT. The glycemic profile and insulin response during the OGTT were normal. Following the glucose load, transient improvement of clinical seizures and EEG findings were observed, with the most significant improvement beginning within the first 30 minutes and continuing for 180 minutes. Thereafter, clinical seizures returned, and EEG findings worsened. Additionally, transient improvement in attention, fine motor coordination, and reported well-being were observed without any change in memory performance. This study documents transient neurological improvement in Glut1-DS patients following acute hyperglycemia, associated with improved fine motor coordination and attention. Also, systemic carbohydrate homeostasis was normal, despite GLUT1 haploinsufficiency, confirming the specific role of GLUT1 as the transporter of metabolic fuel across the blood-brain barrier. The transient improvement in brain function underscores the rate-limiting role of glucose transport and the critical minute-to-minute dependence of cerebral function on fuel availability for energy metabolism.

Ambulatory Seizure Monitoring: From Concept to Prototype Device.

PubMed

Myers, Mark H; Threatt, Madeline; Solies, Karsten M; McFerrin, Brent M; Hopf, Lindsey B; Birdwell, J Douglas; Sillay, Karl A

2016-07-01

The brain, made up of billions of neurons and synapses, is the marvelous core of human thought, action and memory. However, if neuronal activity manifests into abnormal electrical activity across the brain, neural behavior may exhibit synchronous neural firings known as seizures. If unprovoked seizures occur repeatedly, a patient may be diagnosed with epilepsy. The scope of this project is to develop an ambulatory seizure monitoring system that can be used away from a hospital, making it possible for the user to stay at home, and primary care personnel to monitor a patient's seizure activity in order to provide deeper analysis of the patient's condition and apply personalized intervention techniques. The ambulatory seizure monitoring device is a research device that has been developed with the objective of acquiring a portable, clean electroencephalography (EEG) signal and transmitting it wirelessly to a handheld device for processing and notification. This device is comprised of 4 phases: acquisition, transmission, processing and notification. During the acquisition stage, the EEG signal is detected using EEG electrodes; these signals are filtered and amplified before being transmitted in the second stage. The processing stage encompasses the signal processing and seizure prediction. A notification is sent to the patient and designated contacts, given an impending seizure. Each of these phases is comprised of various design components, hardware and software. The experimental findings illustrate that there may be a triggering mechanism through the phase lock value method that enables seizure prediction. The device addresses the need for long-term monitoring of the patient's seizure condition in order to provide the clinician a better understanding of the seizure's duration and frequency and ultimately provide the best remedy for the patient.

Ambulatory Seizure Monitoring: From Concept to Prototype Device

PubMed Central

Myers, Mark H.; Threatt, Madeline; Solies, Karsten M.; McFerrin, Brent M.; Hopf, Lindsey B.; Birdwell, J. Douglas; Sillay, Karl A.

2016-01-01

Background The brain, made up of billions of neurons and synapses, is the marvelous core of human thought, action and memory. However, if neuronal activity manifests into abnormal electrical activity across the brain, neural behavior may exhibit synchronous neural firings known as seizures. If unprovoked seizures occur repeatedly, a patient may be diagnosed with epilepsy. Purpose The scope of this project is to develop an ambulatory seizure monitoring system that can be used away from a hospital, making it possible for the user to stay at home, and primary care personnel to monitor a patient's seizure activity in order to provide deeper analysis of the patient's condition and apply personalized intervention techniques. Methods The ambulatory seizure monitoring device is a research device that has been developed with the objective of acquiring a portable, clean electroencephalography (EEG) signal and transmitting it wirelessly to a handheld device for processing and notification. Result This device is comprised of 4 phases: acquisition, transmission, processing and notification. During the acquisition stage, the EEG signal is detected using EEG electrodes; these signals are filtered and amplified before being transmitted in the second stage. The processing stage encompasses the signal processing and seizure prediction. A notification is sent to the patient and designated contacts, given an impending seizure. Each of these phases is comprised of various design components, hardware and software. The experimental findings illustrate that there may be a triggering mechanism through the phase lock value method that enables seizure prediction. Conclusion The device addresses the need for long-term monitoring of the patient's seizure condition in order to provide the clinician a better understanding of the seizure's duration and frequency and ultimately provide the best remedy for the patient. PMID:27647960

Objective quantification of seizure frequency and treatment success via long-term outpatient video-EEG monitoring: a feasibility study.

PubMed

Stefan, H; Kreiselmeyer, G; Kasper, B; Graf, W; Pauli, E; Kurzbuch, K; Hopfengärtner, R

2011-03-01

A reliable method for the estimation of seizure frequency and severity is indispensable in assessing the efficacy of drug treatment in epilepsies. These quantities are usually deduced from subjective patient reports, which may cause considerable problems due to insufficient or false descriptions of seizures and their frequency. We present data from two difficult-to-treat patients with intractable epilepsy. Pat. 1 has had an unknown number of CP seizures. Here, a prolonged outpatient video-EEG monitoring over 160 h and 137 h (over an interval of three months) was performed with an automated seizure detection method. Pat. 2 suffered exclusively from nocturnal seizures originating from the frontal lobe. In this case, an objective quantification of the efficacy of drug treatment over a time period of 22 weeks was established. For the reliable quantification of seizures, a prolonged outpatient video/video-EEG monitoring was appended after a short-term inpatient monitoring period. Patient 1: The seizure detection algorithm was capable of detecting 10 out of 11 seizures. The number of false-positive events was <0.03/h. It was clearly demonstrated that the patient showed more seizures than originally reported. Patient 2: The add-on medication of lacosamide led to a significant reduction in seizure frequency and to a marked decrease in the mean duration of seizures. The severity of seizures was reduced from numerous hypermotoric seizures to few mild, head-turning seizures. Outpatient monitoring may be helpful to guide treatment for severe epilepsies and offers the possibility to more reliably quantify the efficacy of treatment in the long-term, even over several months. Copyright © 2010 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

PubMed

Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K

2010-10-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an estimate of the current density at every time point. We then carried out a correlation between the time series of visual contrast changes in the movie with that of EEG voxels. We found the most significant correlations in visual area V1, just as seen in previous fMRI studies (Bartels A, Zeki, S, Logothetis NK. Natural vision reveals regional specialization to local motion and to contrast-invariant, global flow in the human brain. Cereb Cortex 2008;18(3):705-717), but on the time scale of milliseconds rather than of seconds. To obtain an estimate of how the EEG signal relates to the BOLD signal, we calculated the IRF between the BOLD signal and the estimated current density in area V1. We found that this IRF was very similar to that observed using combined intracortical recordings and fMRI experiments in nonhuman primates. Taken together, these findings open a new approach to noninvasive mapping of the brain. It allows, firstly, the localization of feature-selective brain areas during natural viewing conditions with the temporal resolution of EEG. Secondly, it provides a tool to assess EEG/BOLD transfer functions during processing of more natural stimuli. This is especially useful in combined EEG/fMRI experiments, where one can now potentially study neural-hemodynamic relationships across the whole brain volume in a noninvasive manner. Copyright © 2010 Elsevier Inc. All rights reserved.

Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI

DTIC Science & Technology

2016-04-01

and we anticipate the initiation of the neuroimaging portion of the study early in Year 3. The fMRI task has been completed and is in beta testing...neurocognitive test battery, and self-report measures of cognitive efficacy. We will also include functional magnetic resonance imagining ( fMRI ) and... fMRI and DTI will provide an objective basis for cross-validating the EEG and eye tracking system. Both the EEG and eye tracking data will be

Wearable dry sensors with bluetooth connection for use in remote patient monitoring systems.

PubMed

Gargiulo, Gaetano; Bifulco, Paolo; Cesarelli, Mario; Jin, Craig; McEwan, Alistair; van Schaik, Andre

2010-01-01

Cost reduction has become the primary theme of healthcare reforms globally. More providers are moving towards remote patient monitoring, which reduces the length of hospital stays and frees up their physicians and nurses for acute cases and helps them to tackle staff shortages. Physiological sensors are commonly used in many human specialties e.g. electrocardiogram (ECG) electrodes, for monitoring heart signals, and electroencephalogram (EEG) electrodes, for sensing the electrical activity of the brain, are the most well-known applications. Consequently there is a substantial unmet need for physiological sensors that can be simply and easily applied by the patient or primary carer, are comfortable to wear, can accurately sense parameters over long periods of time and can be connected to data recording systems using Bluetooth technology. We have developed a small, battery powered, user customizable portable monitor. This prototype is capable of recording three-axial body acceleration, skin temperature, and has up to four bio analogical front ends. Moreover, it is also able of continuous wireless transmission to any Bluetooth device including a PDA or a cellular phone. The bio-front end can use long-lasting dry electrodes or novel textile electrodes that can be embedded in clothes. The device can be powered by a standard mobile phone which has a Ni-MH 3.6 V battery, to sustain more than seven days continuous functioning when using the Bluetooth Sniff mode to reduce TX power. In this paper, we present some of the evaluation experiments of our wearable personal monitor device with a focus on ECG applications.

Resected Brain Tissue, Seizure Onset Zone and Quantitative EEG Measures: Towards Prediction of Post-Surgical Seizure Control

PubMed Central

Andrzejak, Ralph G.; Hauf, Martinus; Pollo, Claudio; Müller, Markus; Weisstanner, Christian; Wiest, Roland; Schindler, Kaspar

2015-01-01

Background Epilepsy surgery is a potentially curative treatment option for pharmacoresistent patients. If non-invasive methods alone do not allow to delineate the epileptogenic brain areas the surgical candidates undergo long-term monitoring with intracranial EEG. Visual EEG analysis is then used to identify the seizure onset zone for targeted resection as a standard procedure. Methods Despite of its great potential to assess the epileptogenicty of brain tissue, quantitative EEG analysis has not yet found its way into routine clinical practice. To demonstrate that quantitative EEG may yield clinically highly relevant information we retrospectively investigated how post-operative seizure control is associated with four selected EEG measures evaluated in the resected brain tissue and the seizure onset zone. Importantly, the exact spatial location of the intracranial electrodes was determined by coregistration of pre-operative MRI and post-implantation CT and coregistration with post-resection MRI was used to delineate the extent of tissue resection. Using data-driven thresholding, quantitative EEG results were separated into normally contributing and salient channels. Results In patients with favorable post-surgical seizure control a significantly larger fraction of salient channels in three of the four quantitative EEG measures was resected than in patients with unfavorable outcome in terms of seizure control (median over the whole peri-ictal recordings). The same statistics revealed no association with post-operative seizure control when EEG channels contributing to the seizure onset zone were studied. Conclusions We conclude that quantitative EEG measures provide clinically relevant and objective markers of target tissue, which may be used to optimize epilepsy surgery. The finding that differentiation between favorable and unfavorable outcome was better for the fraction of salient values in the resected brain tissue than in the seizure onset zone is consistent with growing evidence that spatially extended networks might be more relevant for seizure generation, evolution and termination than a single highly localized brain region (i.e. a “focus”) where seizures start. PMID:26513359

Increasing trend of wearables and multimodal interface for human activity monitoring: A review.

PubMed

Kumari, Preeti; Mathew, Lini; Syal, Poonam

2017-04-15

Activity recognition technology is one of the most important technologies for life-logging and for the care of elderly persons. Elderly people prefer to live in their own houses, within their own locality. If, they are capable to do so, several benefits can follow in terms of society and economy. However, living alone may have high risks. Wearable sensors have been developed to overcome these risks and these sensors are supposed to be ready for medical uses. It can help in monitoring the wellness of elderly persons living alone by unobtrusively monitoring their daily activities. The study aims to review the increasing trends of wearable devices and need of multimodal recognition for continuous or discontinuous monitoring of human activity, biological signals such as Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG), Electrocardiogram (ECG) and parameters along with other symptoms. This can provide necessary assistance in times of ominous need, which is crucial for the advancement of disease-diagnosis and treatment. Shared control architecture with multimodal interface can be used for application in more complex environment where more number of commands is to be used to control with better results in terms of controlling. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic Seizure Detection Based on Morphological Features Using One-Dimensional Local Binary Pattern on Long-Term EEG.

PubMed

Shanir, P P Muhammed; Khan, Kashif Ahmad; Khan, Yusuf Uzzaman; Farooq, Omar; Adeli, Hojjat

2017-12-01

Epileptic neurological disorder of the brain is widely diagnosed using the electroencephalography (EEG) technique. EEG signals are nonstationary in nature and show abnormal neural activity during the ictal period. Seizures can be identified by analyzing and obtaining features of EEG signal that can detect these abnormal activities. The present work proposes a novel morphological feature extraction technique based on the local binary pattern (LBP) operator. LBP provides a unique decimal value to a sample point by weighing the binary outcomes after thresholding the neighboring samples with the present sample point. These LBP values assist in capturing the rising and falling edges of the EEG signal, thus providing a morphologically featured discriminating pattern for epilepsy detection. In the present work, the variability in the LBP values is measured by calculating the sum of absolute difference of the consecutive LBP values. Interquartile range is calculated over the preprocessed EEG signal to provide dispersion measure in the signal. For classification purpose, K-nearest neighbor classifier is used, and the performance is evaluated on 896.9 hours of data from CHB-MIT continuous EEG database. Mean accuracy of 99.7% and mean specificity of 99.8% is obtained with average false detection rate of 0.47/h and sensitivity of 99.2% for 136 seizures.

Hemimegalencephaly: Clinical, EEG, neuroimaging, and IMP-SPECT correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konkol, R.J.; Maister, B.H.; Wells, R.G.

1990-11-01

Iofetamine-single photon emission computed tomography (IMP-SPECT) was performed on 2 girls (5 1/2 and 6 years of age) with histories of intractable seizures, developmental delay, and unilateral hemiparesis secondary to hemimegalencephaly. Electroencephalography (EEG) revealed frequent focal discharges in 1 patient, while a nearly continuous burst suppression pattern over the malformed hemisphere was recorded in the other. IMP-SPECT demonstrated a good correlation with neuroimaging studies. In spite of the different EEG patterns, which had been proposed to predict contrasting clinical outcomes, both IMP-SPECT scans disclosed a similar decrease in tracer uptake in the malformed hemisphere. These results are consistent with themore » pattern of decreased tracer uptake found in other interictal studies of focal seizures without cerebral malformations. In view of recent recommendations for hemispherectomy in these patients, we suggest that the IMP-SPECT scan be used to compliment EEG as a method to define the extent of abnormality which may be more relevant to long-term prognosis than EEG alone.« less

Recognizing of stereotypic patterns in epileptic EEG using empirical modes and wavelets

NASA Astrophysics Data System (ADS)

Grubov, V. V.; Sitnikova, E.; Pavlov, A. N.; Koronovskii, A. A.; Hramov, A. E.

2017-11-01

Epileptic activity in the form of spike-wave discharges (SWD) appears in the electroencephalogram (EEG) during absence seizures. This paper evaluates two approaches for detecting stereotypic rhythmic activities in EEG, i.e., the continuous wavelet transform (CWT) and the empirical mode decomposition (EMD). The CWT is a well-known method of time-frequency analysis of EEG, whereas EMD is a relatively novel approach for extracting signal's waveforms. A new method for pattern recognition based on combination of CWT and EMD is proposed. It was found that this combined approach resulted to the sensitivity of 86.5% and specificity of 92.9% for sleep spindles and 97.6% and 93.2% for SWD, correspondingly. Considering strong within- and between-subjects variability of sleep spindles, the obtained efficiency in their detection was high in comparison with other methods based on CWT. It is concluded that the combination of a wavelet-based approach and empirical modes increases the quality of automatic detection of stereotypic patterns in rat's EEG.

Wireless behind-the-ear EEG recording device with wireless interface to a mobile device (iPhone/iPod touch).

PubMed

Do Valle, Bruno G; Cash, Sydney S; Sodini, Charlie G

2014-01-01

EEG remains the mainstay test for the diagnosis and treatment of patients with epilepsy. Unfortunately, ambulatory EEG systems are far from ideal for patients that have infrequent seizures. The systems only last up to 3 days and if a seizure is not captured during the recordings, the doctor cannot give a definite diagnosis of the patient's condition. The ambulatory systems also suffers from being too bulky and posing some constraints on the patient, such as not being able to shower during the recordings. This paper presents a novel behind-the-ear EEG recording device that uses an iPhone or iPod Touch to continuously upload the patient's data to a secure server. This device not only gives the doctors access to the EEG data in real time but it can be easily removed and re-applied by the patient at any time, thus reducing the interference with quality of life.

A generic EEG artifact removal algorithm based on the multi-channel Wiener filter

NASA Astrophysics Data System (ADS)

Somers, Ben; Francart, Tom; Bertrand, Alexander

2018-06-01

Objective. The electroencephalogram (EEG) is an essential neuro-monitoring tool for both clinical and research purposes, but is susceptible to a wide variety of undesired artifacts. Removal of these artifacts is often done using blind source separation techniques, relying on a purely data-driven transformation, which may sometimes fail to sufficiently isolate artifacts in only one or a few components. Furthermore, some algorithms perform well for specific artifacts, but not for others. In this paper, we aim to develop a generic EEG artifact removal algorithm, which allows the user to annotate a few artifact segments in the EEG recordings to inform the algorithm. Approach. We propose an algorithm based on the multi-channel Wiener filter (MWF), in which the artifact covariance matrix is replaced by a low-rank approximation based on the generalized eigenvalue decomposition. The algorithm is validated using both hybrid and real EEG data, and is compared to other algorithms frequently used for artifact removal. Main results. The MWF-based algorithm successfully removes a wide variety of artifacts with better performance than current state-of-the-art methods. Significance. Current EEG artifact removal techniques often have limited applicability due to their specificity to one kind of artifact, their complexity, or simply because they are too ‘blind’. This paper demonstrates a fast, robust and generic algorithm for removal of EEG artifacts of various types, i.e. those that were annotated as unwanted by the user.

Stage-independent, single lead EEG sleep spindle detection using the continuous wavelet transform and local weighted smoothing.

PubMed

Tsanas, Athanasios; Clifford, Gari D

2015-01-01

Sleep spindles are critical in characterizing sleep and have been associated with cognitive function and pathophysiological assessment. Typically, their detection relies on the subjective and time-consuming visual examination of electroencephalogram (EEG) signal(s) by experts, and has led to large inter-rater variability as a result of poor definition of sleep spindle characteristics. Hitherto, many algorithmic spindle detectors inherently make signal stationarity assumptions (e.g., Fourier transform-based approaches) which are inappropriate for EEG signals, and frequently rely on additional information which may not be readily available in many practical settings (e.g., more than one EEG channels, or prior hypnogram assessment). This study proposes a novel signal processing methodology relying solely on a single EEG channel, and provides objective, accurate means toward probabilistically assessing the presence of sleep spindles in EEG signals. We use the intuitively appealing continuous wavelet transform (CWT) with a Morlet basis function, identifying regions of interest where the power of the CWT coefficients corresponding to the frequencies of spindles (11-16 Hz) is large. The potential for assessing the signal segment as a spindle is refined using local weighted smoothing techniques. We evaluate our findings on two databases: the MASS database comprising 19 healthy controls and the DREAMS sleep spindle database comprising eight participants diagnosed with various sleep pathologies. We demonstrate that we can replicate the experts' sleep spindles assessment accurately in both databases (MASS database: sensitivity: 84%, specificity: 90%, false discovery rate 83%, DREAMS database: sensitivity: 76%, specificity: 92%, false discovery rate: 67%), outperforming six competing automatic sleep spindle detection algorithms in terms of correctly replicating the experts' assessment of detected spindles.

Dynamic timecourse of typical childhood absence seizures: EEG, behavior and fMRI

PubMed Central

Bai, X; Vestal, M; Berman, R; Negishi, M; Spann, M; Vega, C; Desalvo, M; Novotny, EJ; Constable, RT; Blumenfeld, H

2010-01-01

Absence seizures are 5–10 second episodes of impaired consciousness accompanied by 3–4Hz generalized spike-and-wave discharge on electroencephalography (EEG). The timecourse of functional magnetic resonance imaging (fMRI) changes in absence seizures in relation to EEG and behavior is not known. We acquired simultaneous EEG-fMRI in 88 typical childhood absence seizures from 9 pediatric patients. We investigated behavior concurrently using a continuous performance task (CPT) or simpler repetitive tapping task (RTT). EEG time-frequency analysis revealed abrupt onset and end of 3–4 Hz spike-wave discharges with a mean duration of 6.6 s. Behavioral analysis also showed rapid onset and end of deficits associated with electrographic seizure start and end. In contrast, we observed small early fMRI increases in the orbital/medial frontal and medial/lateral parietal cortex >5s before seizure onset, followed by profound fMRI decreases continuing >20s after seizure end. This timecourse differed markedly from the hemodynamic response function (HRF) model used in conventional fMRI analysis, consisting of large increases beginning after electrical event onset, followed by small fMRI decreases. Other regions, such as the lateral frontal cortex, showed more balanced fMRI increases followed by approximately equal decreases. The thalamus showed delayed increases after seizure onset followed by small decreases, most closely resembling the HRF model. These findings reveal a complex and long lasting sequence of fMRI changes in absence seizures, which are not detectible by conventional HRF modeling in many regions. These results may be important mechanistically for seizure initiation and termination and may also contribute to changes in EEG and behavior. PMID:20427649

Prospective multi-center study of an automatic online seizure detection system for epilepsy monitoring units.

PubMed

Fürbass, F; Ossenblok, P; Hartmann, M; Perko, H; Skupch, A M; Lindinger, G; Elezi, L; Pataraia, E; Colon, A J; Baumgartner, C; Kluge, T

2015-06-01

A method for automatic detection of epileptic seizures in long-term scalp-EEG recordings called EpiScan will be presented. EpiScan is used as alarm device to notify medical staff of epilepsy monitoring units (EMUs) in case of a seizure. A prospective multi-center study was performed in three EMUs including 205 patients. A comparison between EpiScan and the Persyst seizure detector on the prospective data will be presented. In addition, the detection results of EpiScan on retrospective EEG data of 310 patients and the public available CHB-MIT dataset will be shown. A detection sensitivity of 81% was reached for unequivocal electrographic seizures with false alarm rate of only 7 per day. No statistical significant differences in the detection sensitivities could be found between the centers. The comparison to the Persyst seizure detector showed a lower false alarm rate of EpiScan but the difference was not of statistical significance. The automatic seizure detection method EpiScan showed high sensitivity and low false alarm rate in a prospective multi-center study on a large number of patients. The application as seizure alarm device in EMUs becomes feasible and will raise the efficiency of video-EEG monitoring and the safety levels of patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Using the nonlinear control of anaesthesia-induced hypersensitivity of EEG at burst suppression level to test the effects of radiofrequency radiation on brain function

PubMed Central

Lipping, Tarmo; Rorarius, Michael; Jäntti, Ville; Annala, Kari; Mennander, Ari; Ferenets, Rain; Toivonen, Tommi; Toivo, Tim; Värri, Alpo; Korpinen, Leena

2009-01-01

Background In this study, investigating the effects of mobile phone radiation on test animals, eleven pigs were anaesthetised to the level where burst-suppression pattern appears in the electroencephalogram (EEG). At this level of anaesthesia both human subjects and animals show high sensitivity to external stimuli which produce EEG bursts during suppression. The burst-suppression phenomenon represents a nonlinear control system, where low-amplitude EEG abruptly switches to very high amplitude bursts. This switching can be triggered by very minor stimuli and the phenomenon has been described as hypersensitivity. To test if also radio frequency (RF) stimulation can trigger this nonlinear control, the animals were exposed to pulse modulated signal of a GSM mobile phone at 890 MHz. In the first phase of the experiment electromagnetic field (EMF) stimulation was randomly switched on and off and the relation between EEG bursts and EMF stimulation onsets and endpoints were studied. In the second phase a continuous RF stimulation at 31 W/kg was applied for 10 minutes. The ECG, the EEG, and the subcutaneous temperature were recorded. Results No correlation between the exposure and the EEG burst occurrences was observed in phase I measurements. No significant changes were observed in the EEG activity of the pigs during phase II measurements although several EEG signal analysis methods were applied. The temperature measured subcutaneously from the pigs' head increased by 1.6°C and the heart rate by 14.2 bpm on the average during the 10 min exposure periods. Conclusion The hypothesis that RF radiation would produce sensory stimulation of somatosensory, auditory or visual system or directly affect the brain so as to produce EEG bursts during suppression was not confirmed. PMID:19615084

Skylab

NASA Image and Video Library

1973-01-01

This photograph is of Astronaut Kerwin wearing the Sleep Monitoring cap (Experiment M133) taken during the Skylab-2 mission. The Sleep Monitoring Experiment was a medical evaluation designed to objectively determine the amount and quality of crew members' inflight sleep. The experiment monitored and recorded electroencephalographic (EEG) and electrooculographic (EOG) activity during astronauts' sleep periods. One of the astronauts was selected for this experiment and wore a fitted cap during his sleep periods.

Confirming psychogenic nonepileptic seizures with video-EEG: sex matters.

PubMed

Noe, Katherine H; Grade, Madeline; Stonnington, Cynthia M; Driver-Dunckley, Erika; Locke, Dona E C

2012-03-01

The influence of gender on psychogenic nonepileptic seizures (PNES) diagnosis was examined retrospectively in 439 subjects undergoing video-EEG (vEEG) for spell classification, of whom 142 women and 42 men had confirmed PNES. The epileptologist's predicted diagnosis was correct in 72% overall. Confirmed epilepsy was correctly predicted in 94% men and 88% women. In contrast, confirmed PNES was accurately predicted in 86% women versus 61% men (p=0.003). Sex-based differences in likelihood of an indeterminate admission were not observed for predicted epilepsy or physiologic events, but were for predicted PNES (39% men, 12% women, p=0.0002). More frequent failure to record spells in men than women with predicted PNES was not explained by spell frequency, duration of monitoring, age, medication use, or personality profile. PNES are not only less common in men, but also more challenging to recognize in the clinic, and even when suspected more difficult to confirm with vEEG. Copyright © 2012 Elsevier Inc. All rights reserved.

Temporal Comparison Between NIRS and EEG Signals During a Mental Arithmetic Task Evaluated with Self-Organizing Maps.

PubMed

Oyama, Katsunori; Sakatani, Kaoru

2016-01-01

Simultaneous monitoring of brain activity with near-infrared spectroscopy and electroencephalography allows spatiotemporal reconstruction of the hemodynamic response regarding the concentration changes in oxyhemoglobin and deoxyhemoglobin that are associated with recorded brain activity such as cognitive functions. However, the accuracy of state estimation during mental arithmetic tasks is often different depending on the length of the segment for sampling of NIRS and EEG signals. This study compared the results of a self-organizing map and ANOVA, which were both used to assess the accuracy of state estimation. We conducted an experiment with a mental arithmetic task performed by 10 participants. The lengths of the segment in each time frame for observation of NIRS and EEG signals were compared with the 30-s, 1-min, and 2-min segment lengths. The optimal segment lengths were different for NIRS and EEG signals in the case of classification of feature vectors into the states of performing a mental arithmetic task and being at rest.

Design of a mobile brain computer interface-based smart multimedia controller.

PubMed

Tseng, Kevin C; Lin, Bor-Shing; Wong, Alice May-Kuen; Lin, Bor-Shyh

2015-03-06

Music is a way of expressing our feelings and emotions. Suitable music can positively affect people. However, current multimedia control methods, such as manual selection or automatic random mechanisms, which are now applied broadly in MP3 and CD players, cannot adaptively select suitable music according to the user's physiological state. In this study, a brain computer interface-based smart multimedia controller was proposed to select music in different situations according to the user's physiological state. Here, a commercial mobile tablet was used as the multimedia platform, and a wireless multi-channel electroencephalograph (EEG) acquisition module was designed for real-time EEG monitoring. A smart multimedia control program built in the multimedia platform was developed to analyze the user's EEG feature and select music according his/her state. The relationship between the user's state and music sorted by listener's preference was also examined in this study. The experimental results show that real-time music biofeedback according a user's EEG feature may positively improve the user's attention state.

High-Frequency EEG Variations in Children with Autism Spectrum Disorder during Human Faces Visualization

PubMed Central

Reategui, Camille; Costa, Bruna Karen de Sousa; da Fonseca, Caio Queiroz; da Silva, Luana; Morya, Edgard

2017-01-01

Autism spectrum disorder (ASD) is a neuropsychiatric disorder characterized by the impairment in the social reciprocity, interaction/language, and behavior, with stereotypes and signs of sensory function deficits. Electroencephalography (EEG) is a well-established and noninvasive tool for neurophysiological characterization and monitoring of the brain electrical activity, able to identify abnormalities related to frequency range, connectivity, and lateralization of brain functions. This research aims to evidence quantitative differences in the frequency spectrum pattern between EEG signals of children with and without ASD during visualization of human faces in three different expressions: neutral, happy, and angry. Quantitative clinical evaluations, neuropsychological evaluation, and EEG of children with and without ASD were analyzed paired by age and gender. The results showed stronger activation in higher frequencies (above 30 Hz) in frontal, central, parietal, and occipital regions in the ASD group. This pattern of activation may correlate with developmental characteristics in the children with ASD. PMID:29018811

Awareness during drowsiness: dynamics and electrophysiological correlates

NASA Technical Reports Server (NTRS)

Makeig, S.; Jung, T. P.; Sejnowski, T. J.

2000-01-01

During drowsy periods, performance on tasks requiring continuous attention becomes intermittent. Previously, we have reported that during drowsy periods of intermittent performance, 7 of 10 participants performing an auditory detection task exhibited episodes of non-responding lasting about 18 s (Makeig & Jung, 1996). Further, the time patterns of these episodes were repeated precisely in subsequent sessions. The 18-s cycles were accompanied by counterbalanced power changes within two frequency bands in the vertex EEG (near 4 Hz and circa 40 Hz). In the present experiment, performance patterns and concurrent EEG spectra were examined in four participants performing a continuous visuomotor compensatory tracking task in 15-20 minute bouts during a 42-hour sleep deprivation study. During periods of good performance, participants made compensatory trackball movements about twice per second, attempting to keep a target disk near a central ring. Autocorrelations of time series representing the distance of the target disk from the ring centre showed that during periods of poor performance marked near-18-s cycles in performance again appeared. There were phases of poor or absent performance accompanied by an increase in EEG power that was largest at 3-4 Hz. These studies show that in drowsy humans, opening and closing of the gates of behavioural awareness is marked not by the appearance of (12-14 Hz) sleep spindles, but by prominent EEG amplitude changes in the low theta band. Further, both EEG and behavioural changes during drowsiness often exhibit stereotyped 18-s cycles.

Relationship between speed and EEG activity during imagined and executed hand movements

NASA Astrophysics Data System (ADS)

Yuan, Han; Perdoni, Christopher; He, Bin

2010-04-01

The relationship between primary motor cortex and movement kinematics has been shown in nonhuman primate studies of hand reaching or drawing tasks. Studies have demonstrated that the neural activities accompanying or immediately preceding the movement encode the direction, speed and other information. Here we investigated the relationship between the kinematics of imagined and actual hand movement, i.e. the clenching speed, and the EEG activity in ten human subjects. Study participants were asked to perform and imagine clenching of the left hand and right hand at various speeds. The EEG activity in the alpha (8-12 Hz) and beta (18-28 Hz) frequency bands were found to be linearly correlated with the speed of imagery clenching. Similar parametric modulation was also found during the execution of hand movements. A single equation relating the EEG activity to the speed and the hand (left versus right) was developed. This equation, which contained a linear independent combination of the two parameters, described the time-varying neural activity during the tasks. Based on the model, a regression approach was developed to decode the two parameters from the multiple-channel EEG signals. We demonstrated the continuous decoding of dynamic hand and speed information of the imagined clenching. In particular, the time-varying clenching speed was reconstructed in a bell-shaped profile. Our findings suggest an application to providing continuous and complex control of noninvasive brain-computer interface for movement-impaired paralytics.

The inverse problem in electroencephalography using the bidomain model of electrical activity.

PubMed

Lopez Rincon, Alejandro; Shimoda, Shingo

2016-12-01

Acquiring information about the distribution of electrical sources in the brain from electroencephalography (EEG) data remains a significant challenge. An accurate solution would provide an understanding of the inner mechanisms of the electrical activity in the brain and information about damaged tissue. In this paper, we present a methodology for reconstructing brain electrical activity from EEG data by using the bidomain formulation. The bidomain model considers continuous active neural tissue coupled with a nonlinear cell model. Using this technique, we aim to find the brain sources that give rise to the scalp potential recorded by EEG measurements taking into account a non-static reconstruction. We simulate electrical sources in the brain volume and compare the reconstruction to the minimum norm estimates (MNEs) and low resolution electrical tomography (LORETA) results. Then, with the EEG dataset from the EEG Motor Movement/Imagery Database of the Physiobank, we identify the reaction to visual stimuli by calculating the time between stimulus presentation and the spike in electrical activity. Finally, we compare the activation in the brain with the registered activation using the LinkRbrain platform. Our methodology shows an improved reconstruction of the electrical activity and source localization in comparison with MNE and LORETA. For the Motor Movement/Imagery Database, the reconstruction is consistent with the expected position and time delay generated by the stimuli. Thus, this methodology is a suitable option for continuously reconstructing brain potentials. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Adaptive estimation of hand movement trajectory in an EEG based brain-computer interface system

NASA Astrophysics Data System (ADS)

Robinson, Neethu; Guan, Cuntai; Vinod, A. P.

2015-12-01

Objective. The various parameters that define a hand movement such as its trajectory, speed, etc, are encoded in distinct brain activities. Decoding this information from neurophysiological recordings is a less explored area of brain-computer interface (BCI) research. Applying non-invasive recordings such as electroencephalography (EEG) for decoding makes the problem more challenging, as the encoding is assumed to be deep within the brain and not easily accessible by scalp recordings. Approach. EEG based BCI systems can be developed to identify the neural features underlying movement parameters that can be further utilized to provide a detailed and well defined control command set to a BCI output device. A real-time continuous control is better suited for practical BCI systems, and can be achieved by continuous adaptive reconstruction of movement trajectory than discrete brain activity classifications. In this work, we adaptively reconstruct/estimate the parameters of two-dimensional hand movement trajectory, namely movement speed and position, from multi-channel EEG recordings. The data for analysis is collected by performing an experiment that involved center-out right-hand movement tasks in four different directions at two different speeds in random order. We estimate movement trajectory using a Kalman filter that models the relation between brain activity and recorded parameters based on a set of defined predictors. We propose a method to define these predictor variables that includes spatial, spectral and temporally localized neural information and to select optimally informative variables. Main results. The proposed method yielded correlation of (0.60 ± 0.07) between recorded and estimated data. Further, incorporating the proposed predictor subset selection, the correlation achieved is (0.57 ± 0.07, p {\\lt }0.004) with significant gain in stability of the system, as well as dramatic reduction in number of predictors (76%) for the savings of computational time. Significance. The proposed system provides a real time movement control system using EEG-BCI with control over movement speed and position. These results are higher and statistically significant compared to existing techniques in EEG based systems and thus promise the applicability of the proposed method for efficient estimation of movement parameters and for continuous motor control.

Real-time mental arithmetic task recognition from EEG signals.

PubMed

Wang, Qiang; Sourina, Olga

2013-03-01

Electroencephalography (EEG)-based monitoring the state of the user's brain functioning and giving her/him the visual/audio/tactile feedback is called neurofeedback technique, and it could allow the user to train the corresponding brain functions. It could provide an alternative way of treatment for some psychological disorders such as attention deficit hyperactivity disorder (ADHD), where concentration function deficit exists, autism spectrum disorder (ASD), or dyscalculia where the difficulty in learning and comprehending the arithmetic exists. In this paper, a novel method for multifractal analysis of EEG signals named generalized Higuchi fractal dimension spectrum (GHFDS) was proposed and applied in mental arithmetic task recognition from EEG signals. Other features such as power spectrum density (PSD), autoregressive model (AR), and statistical features were analyzed as well. The usage of the proposed fractal dimension spectrum of EEG signal in combination with other features improved the mental arithmetic task recognition accuracy in both multi-channel and one-channel subject-dependent algorithms up to 97.87% and 84.15% correspondingly. Based on the channel ranking, four channels were chosen which gave the accuracy up to 97.11%. Reliable real-time neurofeedback system could be implemented based on the algorithms proposed in this paper.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG.

PubMed

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-03-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver's brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety.

Ictal EEG fractal dimension in ECT predicts outcome at 2 weeks in schizophrenia.

PubMed

Abhishekh, Hulegar A; Thirthalli, Jagadisha; Manjegowda, Anusha; Phutane, Vivek H; Muralidharan, Kesavan; Gangadhar, Bangalore N

2013-09-30

Studies of electroconvulsive therapy (ECT) have found an association between ictal electroencephalographic (EEG) measures and clinical outcome in depression. Such studies are lacking in schizophrenia. Consenting schizophrenia patients receiving ECT were assessed using the Brief Psychiatric Rating Scale (BPRS) before and 2 weeks after the start of ECT. The patients' seizure was monitored using EEG. In 26 patients, completely artifact-free EEG derived from the left frontal-pole (FP1) channel and electrocardiography (ECG) were available. The fractal dimension (FD) was computed to assess 4-s EEG epochs, and the maximal value from the earliest ECT session (2nd, 3rd or 4th) was used for analysis. There was a significant inverse correlation between the maximum FD and the total score following 6th ECT. An inverse Inverse correlation was also observed between the maximum FD and the total number of ECTs administered as well as the maximum heart rate (HR) and BPRS scores following 6th ECT. In patients with schizophrenia greater intensity of seizures (higher FD) during initial sessions of ECT is associated with better response at the end of 2 weeks. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Error, rather than its probability, elicits specific electrocortical signatures: a combined EEG-immersive virtual reality study of action observation.

PubMed

Pezzetta, Rachele; Nicolardi, Valentina; Tidoni, Emmanuele; Aglioti, Salvatore Maria

2018-06-06

Detecting errors in one's own actions, and in the actions of others, is a crucial ability for adaptable and flexible behavior. Studies show that specific EEG signatures underpin the monitoring of observed erroneous actions (error-related negativity, error-positivity, mid-frontal theta oscillations). However, the majority of studies on action observation used sequences of trials where erroneous actions were less frequent than correct actions. Therefore, it was not possible to disentangle whether the activation of the performance monitoring system was due to an error - as a violation of the intended goal - or a surprise/novelty effect, associated with a rare and unexpected event. Combining EEG and immersive virtual reality (IVR-CAVE system), we recorded the neural signal of 25 young adults who observed in first-person perspective, simple reach-to-grasp actions performed by an avatar aiming for a glass. Importantly, the proportion of erroneous actions was higher than correct actions. Results showed that the observation of erroneous actions elicits the typical electro-cortical signatures of error monitoring and therefore the violation of the action goal is still perceived as a salient event. The observation of correct actions elicited stronger alpha suppression. This confirmed the role of the alpha frequency band in the general orienting response to novel and infrequent stimuli. Our data provides novel evidence that an observed goal error (the action slip) triggers the activity of the performance monitoring system even when erroneous actions, which are, typically, relevant events, occur more often than correct actions and thus are not salient because of their rarity.

The anesthesia and brain monitor (ABM). Concept and performance.

PubMed

Kay, B

1984-01-01

Three integral components of the ABM, the frontalis electromyogram (EMG), the processed unipolar electroencephalogram (EEG) and the neuromuscular transmission monitor (NMT) were compared with standard research methods, and their clinical utility indicated. The EMG was compared with the method of Dundee et al (2) for measuring the induction dose of thiopentone; the EEG was compared with the SLE Galileo E8-b and the NMT was compared with the Medelec MS6. In each case correlation of results was extremely high, and the ABM offered some advantages over the standard research methods. We conclude that each of the integral units of the ABM is simple to apply and interpret, yet as accurate as standard apparatus used for research. In addition the ABM offers excellent display and recording facilities and alarm systems.

Modulation of EEG Theta Band Signal Complexity by Music Therapy

NASA Astrophysics Data System (ADS)

Bhattacharya, Joydeep; Lee, Eun-Jeong

The primary goal of this study was to investigate the impact of monochord (MC) sounds, a type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal complexity values for monochords with those for progressive muscle relaxation (PMR), an alternative therapy for relaxation. Forty cancer patients were randomly allocated to one of the two relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were recorded during the first and last sessions. EEG signals were analyzed by applying signal mode complexity, a measure of complexity of neuronal oscillations. Across sessions, both groups showed a modulation of complexity of beta-2 band (20-29Hz) at midfrontal regions, but only MC group showed a modulation of complexity of theta band (3.5-7.5Hz) at posterior regions. Therefore, the neuronal complexity patterns showed different changes in EEG frequency band specific complexity resulting in two different types of interventions. Moreover, the different neural responses to listening to monochords and PMR were observed after regular relaxation interventions over a short time span.

[Use of quantitative electroencephalogram in patients with septic shock].

PubMed

Ma, Yujie; Ouyang, Bin; Guan, Xiangdong

2016-01-19

To observe the quantitative electroencephalogram (qEEG) characteristics of the patients with septic shock in intensive care unit (ICU), and to find the early presence and severity of septic-associated encephalopathy (SAE) in these patients. During November 2014 to August 2015, 26 cases with septic shock were included from the ICU of the First Affiliated Hospital, Sun Yat-sen University.During the same period, 14 healthy volunteers were included as control. The brain function instrument was used to monitor the patients by the bed, placing leads as the internationally used 10-20 system, bipolar longitudinal F3-P3, F4-P4 four channels, and then consecutive clips of 5 minutes was chosen, using the average value of the clips, the amplitude integrated electroencephalogram (aEEG), relative frequency band energy, spectrum entropy, relative alpha ariability to carry out statistical analysis.And the qEEG features of septic shock patients with different Glasgow coma scale (GCS) levels were also analyzed. (1) 96% of the patients with septic shock had EEG abnormalities.Alpha frequency band energy, alpha ariability, aEEG amplitude, spectrum entropy decreased significantly (P<0.05=, while the delta frequency band energy significantly increased (P<0.05=. (2) aEEG amplitude decline appeared in 34% of patients with septic shock, and within the septic shock groups, amplitude decreased significantly (P<0.05= in patients with GCS under five. Patients with septic shock tends to have diffuse inhibition in EEG, and the inhibition degree can reflect cerebral lesion degree; changes of EEG frequency as early warning indicators of brain damage are sensitive, and the decline of amplitude often indicates critical injury.

Pulse Wave Amplitude Drops during Sleep are Reliable Surrogate Markers of Changes in Cortical Activity

PubMed Central

Delessert, Alexandre; Espa, Fabrice; Rossetti, Andrea; Lavigne, Gilles; Tafti, Mehdi; Heinzer, Raphael

2010-01-01

Background: During sleep, sudden drops in pulse wave amplitude (PWA) measured by pulse oximetry are commonly associated with simultaneous arousals and are thought to result from autonomic vasoconstriction. In the present study, we determine whether PWA drops were associated with changes in cortical activity as determined by EEG spectral analysis. Methods: A 20% decrease in PWA was chosen as a minimum for a drop. A total of 1085 PWA drops from 10 consecutive sleep recordings were analyzed. EEG spectral analysis was performed over 5 consecutive epochs of 5 seconds: 2 before, 1 during, and 2 after the PWA drop. EEG spectral analysis was performed over delta, theta, alpha, sigma, and beta frequency bands. Within each frequency band, power density was compared across the five 5-sec epochs. Presence or absence of visually scored EEG arousals were adjudicated by an investigator blinded to the PWA signal and considered associated with PWA drop if concomitant. Results: A significant increase in EEG power density in all EEG frequency bands was found during PWA drops (P < 0.001) compared to before and after drop. Even in the absence of visually scored arousals, PWA drops were associated with a significant increase in EEG power density (P < 0.001) in most frequency bands. Conclusions: Drops in PWA are associated with a significant increase in EEG power density, suggesting that these events can be used as a surrogate for changes in cortical activity during sleep. This approach may prove of value in scoring respiratory events on limited-channel (type III) portable monitors. Citation: Delessert A; Espa F; Rossetti A; Lavigne G; Tafti M; Heinzer R. Pulse wave amplitude drops during sleep are reliable surrogate markers of changes in cortical activity. SLEEP 2010;33(12):1687-1692. PMID:21120131

Change in Mean Frequency of Resting-State Electroencephalography after Transcranial Direct Current Stimulation

PubMed Central

Boonstra, Tjeerd W.; Nikolin, Stevan; Meisener, Ann-Christin; Martin, Donel M.; Loo, Colleen K.

2016-01-01

Transcranial direct current stimulation (tDCS) is proposed as a tool to investigate cognitive functioning in healthy people and as a treatment for various neuropathological disorders. However, the underlying cortical mechanisms remain poorly understood. We aim to investigate whether resting-state electroencephalography (EEG) can be used to monitor the effects of tDCS on cortical activity. To this end we tested whether the spectral content of ongoing EEG activity is significantly different after a single session of active tDCS compared to sham stimulation. Twenty participants were tested in a sham-controlled, randomized, crossover design. Resting-state EEG was acquired before, during and after active tDCS to the left dorsolateral prefrontal cortex (15 min of 2 mA tDCS) and sham stimulation. Electrodes with a diameter of 3.14 cm2 were used for EEG and tDCS. Partial least squares (PLS) analysis was used to examine differences in power spectral density (PSD) and the EEG mean frequency to quantify the slowing of EEG activity after stimulation. PLS revealed a significant increase in spectral power at frequencies below 15 Hz and a decrease at frequencies above 15 Hz after active tDCS (P = 0.001). The EEG mean frequency was significantly reduced after both active tDCS (P < 0.0005) and sham tDCS (P = 0.001), though the decrease in mean frequency was smaller after sham tDCS than after active tDCS (P = 0.073). Anodal tDCS of the left DLPFC using a high current density bi-frontal electrode montage resulted in general slowing of resting-state EEG. The similar findings observed following sham stimulation question whether the standard sham protocol is an appropriate control condition for tDCS. PMID:27375462

Role of ictal baseline shifts and ictal high-frequency oscillations in stereo-electroencephalography analysis of mesial temporal lobe seizures.

PubMed

Wu, Shasha; Kunhi Veedu, Hari Prasad; Lhatoo, Samden D; Koubeissi, Mohamad Z; Miller, Jonathan P; Lüders, Hans O

2014-05-01

To assess the role of ictal baseline shifts (IBS) and ictal high-frequency oscillations (iHFOs) in intracranial electroencephalography (EEG) presurgical evaluation by analysis of the spatial and temporal relationship of IBS, iHFOs with ictal conventional stereo-electroencephalography (icEEG) in mesial temporal lobe seizures (MTLS). We studied 15 adult patients with medically refractory MTLS who underwent monitoring with depth electrodes. Seventy-five ictal EEG recordings at 1,000 Hz sampling rate were studied. Visual comparison of icEEG, IBS, and iHFOs were performed using Nihon-Kohden Neurofax systems (acquisition range 0.016-300 Hz). Each recorded ictal EEG was analyzed with settings appropriate for displaying icEEG, IBS, and iHFOs. IBS and iHFOs were observed in all patients and in 91% and 81% of intracranial seizures, respectively. IBS occurred before (22%), at (57%), or after (21%) icEEG onset. In contrast, iHFOs occurred at (30%) or after (70%) icEEG onset. The onset of iHFOs was 11.5 s later than IBS onset (p < 0.0001). All of the earliest onset of IBS and 70% of the onset of iHFOs overlapped with the ictal onset zone (IOZ). Compared with iHFOs, interictal HFOs (itHFOs) were less correlated with IOZ. In contrast to icEEG, IBS and iHFOs had smaller spatial distributions in 70% and 100% of the seizures, respectively. An IBS dipole was observed in 66% of the seizures. Eighty-seven percent of the dipoles had a negative pole at the anterior/medial part of amygdala/hippocampus complex (A-H complex) and a positive pole at the posterior/lateral part of the A-H complex. The results suggest that evaluation of IBS and iHFOs, in addition to routine icEEG, helps in more accurately defining the IOZ. This study also shows that the onset and the spatial distribution of icEEG, IBS, and iHFOs do not overlap, suggesting that they reflect different cellular or network dynamics. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

Microstates in resting-state EEG: current status and future directions.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M; Farzan, Faranak

2015-02-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable "microstates" that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microstates in Resting-State EEG: Current Status and Future Directions

PubMed Central

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M.; Farzan, Faranak

2015-01-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. PMID:25526823

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

PubMed Central

Lee, Boon-Giin; Lee, Boon-Leng; Chung, Wan-Young

2014-01-01

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG) and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz) regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT) method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI) technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM) and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals. PMID:25264954

Diagnostic accuracy of EEG changes during carotid endarterectomy in predicting perioperative strokes.

PubMed

Thirumala, Parthasarathy D; Thiagarajan, Karthy; Gedela, Satyanarayana; Crammond, Donald J; Balzer, Jeffrey R

2016-03-01

The 30 day stroke rate following carotid endarterectomy (CEA) ranges between 2-6%. Such periprocedural strokes are associated with a three-fold increased risk of mortality. Our primary aim was to determine the diagnostic accuracy of electroencephalogram (EEG) in predicting perioperative strokes through meta-analysis of existing literature. An extensive search for relevant literature was undertaken using PubMed and Web of Science databases. Studies were included after screening using predetermined criteria. Data was extracted and analyzed. Summary sensitivity, specificity and diagnostic odds ratio were obtained. Subgroup analysis of studies using eight or more EEG channels was done. Perioperative stroke rate for the cohort of 8765 patients was 1.75%. Pooled sensitivity and specificity of EEG changes in predicting these strokes were 52% (95% confidence interval [CI], 43-61%) and 84% (95% CI, 81-86%) respectively. Summary estimates of the subgroup were similar. The diagnostic odds ratio was 5.85 (95% CI, 3.71-9.22). For the observed stroke rate, the positive likelihood ratio was 3.25 while the negative predictive value was 98.99%. According to these results, patients with perioperative strokes have six times greater odds of experiencing an intraoperative change in EEG during CEA. EEG monitoring was found to be highly specific in predicting perioperative strokes after CEA. Copyright © 2015 Elsevier Ltd. All rights reserved.

Investigating social cognition in infants and adults using dense array electroencephalography ((d)EEG).

PubMed

Akano, Adekemi J; Haley, David W; Dudek, Joanna

2011-06-27

Dense array electroencephalography ((d)EEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology¹, ² is being used increasingly in the study of social cognitive functioning in infants and adults. While (d)EEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization³,⁴2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of (d)EEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution⁴,⁵(,)⁶ compared to standard (d)EEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults⁷,⁸ children⁹,¹⁰, ¹¹,¹² and infants¹², in both research and clinical ⁴,⁵,⁶,¹³,¹⁴,¹⁵settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other (d)EEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of (d)EEG data. The HCGSN features a low-profile electrode pedestal, which, when filled with electrolyte solution, creates a sealed microenvironment and an electrode-scalp interface. In all Geodesic (d;)EEG systems, EEG sensors detect changes in voltage originating from the participant's scalp, along with a small amount of electrical noise originating from the room environment. Electrical signals from all sensors of the Geodesic sensor net are received simultaneously by the amplifier, where they are automatically processed, packaged, and sent to the data-acquisition computer (DAC). Once received by the DAC, scalp electrical activity can be isolated from artifacts for analysis using the filtering and artifact detection tools included in the EGI software. Typically, the HCGSN can be used continuously for only up to two hours because the electrolyte solution dries out over time, gradually decreasing the quality of the scalp-electrode interface. In the Parent-Infant Research Lab at the University of Toronto, we are using (d)EEG to study social cognitive processes including memory, emotion, goals, intentionality, anticipation, and executive functioning in both adult and infant participants.

The efficacy of routine hyperventilation for seizure activation during prolonged video-electroencephalography monitoring.

PubMed

Abubakr, Abuhuziefa; Ifeayni, Iwuchukwu; Wambacq, Ilse

2010-12-01

Hyperventilation (HV) is considered to be one of the activation procedures that provokes epileptic potentials and clinical seizures. However, the true clinical yield of HV is not well established. We retrospectively reviewed the records of all patients admitted to JFK Hospital, Edison, New Jersey, between October 2001 and December 2004 for long-term video-electroencephalography (EEG). A total of 475 patients (193 males; 282 females; age range 5-89 years) were included in the study. All patients underwent routine 3-minute HV as part of the evaluation of their clinical episodes. During the initial assessment, 165 patients did not experience a seizure event, 92 had non-epileptic events, 16 experienced psychogenic non-epileptic seizures (PNES) and six had a clinical event. During HV, of the 43 patients who had primary generalized epilepsy, nine had an abnormal EEG and two experienced seizures; however, out of the 159 patients who had partial seizures, only one patient demonstrated an abnormal EEG. Our study demonstrates that routine HV generally has a very low yield in our Epilepsy-Monitoring Unit. This finding also lends support to the idea that partial seizures are relatively resistant to HV activation. Copyright © 2010 Elsevier Ltd. All rights reserved.

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.

An unusual complication of invasive video-EEG monitoring: subelectrode hematoma without subdural component: case report.

PubMed

Bozkurt, Gokhan; Ayhan, Selim; Dericioglu, Nese; Saygi, Serap; Akalan, Nejat

2010-08-01

The potential complications of the subdural electrode implantation providing identification of the seizure focus and direct stimulation of the cerebral cortex for defining the eloquent cortical areas are epidural and subdural hematoma, cortical contusions, infection, brain edema, raised intracranial pressure, CSF leakage, and venous infarction have been previously reported in the literature. To present the first case of subelectrode hematoma without subdural component that was detected during invasive EEG monitoring after subdural electrode implantation. A 19-year-old female with drug resistant seizures was decided to undergo invasive monitoring with subdural electrodes. While good quality recordings had been initially obtained from all electrodes placed on the right parietal convexity, no cerebral cortical activity could be obtained from one electrode 2 days after the first operation. Explorative surgery revealed a circumscribed subelectrode hematoma without a subdural component. Awareness of the potential complications of subdural electrode implantation and close follow-up of the clinical findings of the patient are of highest value for early detection and successful management.

A comparative study of electrical potential sensors and Ag/AgCl electrodes for characterising spontaneous and event related electroencephalagram signals.

PubMed

Fatoorechi, M; Parkinson, J; Prance, R J; Prance, H; Seth, A K; Schwartzman, D J

2015-08-15

Electroencephalography (EEG) is still a widely used imaging tool that combines high temporal resolution with a relatively low cost. Ag/AgCl metal electrodes have been the gold standard for non-invasively monitoring electrical brain activity. Although reliable, these electrodes have multiple drawbacks: they suffer from noise, such as offset potential drift, and usability issues, for example, difficult skin preparation and cross-coupling of adjacent electrodes. In order to tackle these issues a prototype Electric Potential Sensor (EPS) device based on an auto-zero operational amplifier was developed and evaluated. The EPS is a novel active ultrahigh impedance capacitively coupled sensor. The absence of 1/f noise makes the EPS ideal for use with signal frequencies of ∼10Hz or less. A comprehensive study was undertaken to compare neural signals recorded by the EPS with a standard commercial EEG system. Quantitatively, highly similar signals were observed between the EPS and EEG sensors for both free running and evoked brain activity with cross correlations of higher than 0.9 between the EPS and a standard benchmark EEG system. These studies comprised measurements of both free running EEG and Event Related Potentials (ERPs) from a commercial EEG system and EPS. The EPS provides a promising alternative with many added benefits compared to standard EEG sensors, including reduced setup time and elimination of sensor cross-coupling. In the future the scalability of the EPS will allow the implementation of a whole head ultra-dense EPS array. Copyright © 2015 Elsevier B.V. All rights reserved.

[EEG alpha indices in dependence on the menstrual cycle phase and salivary progesterone].

PubMed

Bazanova, O M; Kondratenko, A V; Kuz'minova, O I; Muravleva, K B; Petrova, S E

2014-01-01

The effects of the neurohumoral status on the EEG alpha - activity indices were studied in a within-subject design with 78 women aged 18-27 years during 1-2 menstrual cycle. Psychometric and EEG indices of alpha waves basal body temperature, saliva progesterone and cortisol level were monitored every 2-3 days. Menstrual and follicular recording sessions occurred before the ovulatory temperature rise, luteal recording session--after increasing progesterone level more than 20% respect to previous day and premenstrual sessions after decreasing progesterone level more that 20% respect to previous day. The design consisted of rest and task periods EEG, EMG and ECG recordings. Half the subjects began during their menstrual phase and half began during their luteal phase. All 5 phases were compared for differences between psychometric features EEG alpha activity, EMG and ECG baseline resting levels, as well as for reactivity to cognitive task. The results showed menstrual phase differences in all psychometric and alpha EEG indices. The cognitive fluency, alpha peak frequency, alpha band width, power in alpha-2 frequency range are maximal at luteal, alpha visual activation and reactivity to cognitive task performance--at follicular phase. The hypothesis that the EEG alpha activity depends on the hormonal status supported by the positive association salivary progesterone level with the alpha peak frequency, power in the alpha-2 band and negative--with the power of the alpha-1 band. According these results, we conclude that psycho-physiological recording sessions with women might be provided with a glance to phase of menstrual cycle.

Limited short-term prognostic utility of cerebral NIRS during neonatal therapeutic hypothermia.

PubMed

Shellhaas, Renée A; Thelen, Brian J; Bapuraj, Jayapalli R; Burns, Joseph W; Swenson, Aaron W; Christensen, Mary K; Wiggins, Stephanie A; Barks, John D E

2013-07-16

We evaluated the utility of amplitude-integrated EEG (aEEG) and regional oxygen saturation (rSO2) measured using near-infrared spectroscopy (NIRS) for short-term outcome prediction in neonates with hypoxic ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Neonates with HIE were monitored with dual-channel aEEG, bilateral cerebral NIRS, and systemic NIRS throughout cooling and rewarming. The short-term outcome measure was a composite of neurologic examination and brain MRI scores at 7 to 10 days. Multiple regression models were developed to assess NIRS and aEEG recorded during the 6 hours before rewarming and the 6-hour rewarming period as predictors of short-term outcome. Twenty-one infants, mean gestational age 38.8 ± 1.6 weeks, median 10-minute Apgar score 4 (range 0-8), and mean initial pH 6.92 ± 0.19, were enrolled. Before rewarming, the most parsimonious model included 4 parameters (adjusted R(2) = 0.59; p = 0.006): lower values of systemic rSO2 variability (p = 0.004), aEEG bandwidth variability (p = 0.019), and mean aEEG upper margin (p = 0.006), combined with higher mean aEEG bandwidth (worse discontinuity; p = 0.013), predicted worse short-term outcome. During rewarming, lower systemic rSO2 variability (p = 0.007) and depressed aEEG lower margin (p = 0.034) were associated with worse outcome (model-adjusted R(2) = 0.49; p = 0.005). Cerebral NIRS data did not contribute to either model. During day 3 of cooling and during rewarming, loss of physiologic variability (by systemic NIRS) and invariant, discontinuous aEEG patterns predict poor short-term outcome in neonates with HIE. These parameters, but not cerebral NIRS, may be useful to identify infants suitable for studies of adjuvant neuroprotective therapies or modification of the duration of cooling and/or rewarming.

Acquired auditory agnosia in childhood and normal sleep electroencephalography subsequently diagnosed as Landau-Kleffner syndrome: a report of three cases.

PubMed

van Bogaert, Patrick; King, Mary D; Paquier, Philippe; Wetzburger, Catherine; Labasse, Catherine; Dubru, Jean-Marie; Deonna, Thierry

2013-06-01

  We report three cases of Landau-Kleffner syndrome (LKS) in children (two females, one male) in whom diagnosis was delayed because the sleep electroencephalography (EEG) was initially normal.   Case histories including EEG, positron emission tomography findings, and long-term outcome were reviewed.   Auditory agnosia occurred between the age of 2 years and 3 years 6 months, after a period of normal language development. Initial awake and sleep EEG, recorded weeks to months after the onset of language regression, during a nap period in two cases and during a full night of sleep in the third case, was normal. Repeat EEG between 2 months and 2 years later showed epileptiform discharges during wakefulness and strongly activated by sleep, with a pattern of continuous spike-waves during slow-wave sleep in two patients. Patients were diagnosed with LKS and treated with various antiepileptic regimens, including corticosteroids. One patient in whom EEG became normal on hydrocortisone is making significant recovery. The other two patients did not exhibit a sustained response to treatment and remained severely impaired.   Sleep EEG may be normal in the early phase of acquired auditory agnosia. EEG should be repeated frequently in individuals in whom a firm clinical diagnosis is made to facilitate early treatment. © The Authors. Developmental Medicine & Child Neurology © 2012 Mac Keith Press.

Neuromodulating Attention and Mind-Wandering Processes with a Single Session Real Time EEG.

PubMed

Gonçalves, Óscar F; Carvalho, Sandra; Mendes, Augusto J; Leite, Jorge; Boggio, Paulo S

2018-06-01

Our minds are continuously alternating between external attention (EA) and mind wandering (MW). An appropriate balance between EA and MW is important for promoting efficient perceptual processing, executive functioning, decision-making, auto-biographical memory, and creativity. There is evidence that EA processes are associated with increased activity in high-frequency EEG bands (e.g., SMR), contrasting with the dominance of low-frequency bands during MW (e.g., Theta). The aim of the present study was to test the effects of two distinct single session real-time EEG (rtEEG) protocols (SMR up-training/Theta down-training-SMR⇑Theta⇓; Theta up-training/SMR down-training-Theta⇑SMR⇓) on EA and MW processes. Thirty healthy volunteers were randomly assigned to one of two rtEEG training protocols (SMR⇑Theta⇓; Theta⇑SMR⇓). Before and after the rtEEG training, participants completed the attention network task (ANT) along with several MW measures. Both training protocols were effective in increasing SMR (SMR⇑Theta⇓) and theta (Theta⇑SMR⇓) amplitudes but not in decreasing the amplitude of down-trained bands. There were no significant effects of the rtEEG training in either EA or MW measures. However, there was a significant positive correlation between post-training SMR increases and the use of deliberate MW (rather than spontaneous) strategies. Additionally, for the Theta⇑SMR⇓ protocol, increase in post-training Theta amplitude was significantly associated with a decreased efficiency in the orientation network.

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Low-Power, 8-Channel EEG Recorder and Seizure Detector ASIC for a Subdermal Implantable System.

PubMed

Do Valle, Bruno G; Cash, Sydney S; Sodini, Charles G

2016-12-01

EEG remains the mainstay test for the diagnosis and treatment of patients with epilepsy. Unfortunately, ambulatory EEG systems are far from ideal for patients who have infrequent seizures. These systems only last up to 3 days and if a seizure is not captured during the recordings, a definite diagnosis of the patient's condition cannot be given. This work aims to address this need by proposing a subdermal implantable, eight-channel EEG recorder and seizure detector that has two modes of operation: diagnosis and seizure counting. In the diagnosis mode, EEG is continuously recorded until a number of seizures are recorded. In the seizure counting mode, the system uses a low-power algorithm to track the number of seizures a patient has, providing doctors with a reliable count to help determine medication efficacy or other clinical endpoint. An ASIC that implements the EEG recording and seizure detection algorithm was designed and fabricated in a 0.18 μm CMOS process. The ASIC includes eight EEG channels and is designed to minimize the system's power and size. The result is a power-efficient analog front end that requires 2.75 μW per channel in diagnosis mode and 0.84 μW per channel in seizure counting mode. Both modes have an input referred noise of approximately 1.1 μVrms.

Non-thermal continuous and modulated electromagnetic radiation fields effects on sleep EEG of rats☆

PubMed Central

Mohammed, Haitham S.; Fahmy, Heba M.; Radwan, Nasr M.; Elsayed, Anwar A.

2012-01-01

In the present study, the alteration in the sleep EEG in rats due to chronic exposure to low-level non-thermal electromagnetic radiation was investigated. Two types of radiation fields were used; 900 MHz unmodulated wave and 900 MHz modulated at 8 and 16 Hz waves. Animals has exposed to radiation fields for 1 month (1 h/day). EEG power spectral analyses of exposed and control animals during slow wave sleep (SWS) and rapid eye movement sleep (REM sleep) revealed that the REM sleep is more susceptible to modulated radiofrequency radiation fields (RFR) than the SWS. The latency of REM sleep increased due to radiation exposure indicating a change in the ultradian rhythm of normal sleep cycles. The cumulative and irreversible effect of radiation exposure was proposed and the interaction of the extremely low frequency radiation with the similar EEG frequencies was suggested. PMID:25685416

Resting EEG deficits in accused murderers with schizophrenia.

PubMed

Schug, Robert A; Yang, Yaling; Raine, Adrian; Han, Chenbo; Liu, Jianghong; Li, Liejia

2011-10-31

Empirical evidence continues to suggest a biologically distinct violent subtype of schizophrenia. The present study examined whether murderers with schizophrenia would demonstrate resting EEG deficits distinguishing them from both non-violent schizophrenia patients and murderers without schizophrenia. Resting EEG data were collected from five diagnostic groups (normal controls, non-murderers with schizophrenia, murderers with schizophrenia, murderers without schizophrenia, and murderers with psychiatric conditions other than schizophrenia) at a brain hospital in Nanjing, China. Murderers with schizophrenia were characterized by increased left-hemispheric fast-wave EEG activity relative to non-violent schizophrenia patients, while non-violent schizophrenia patients instead demonstrated increased diffuse slow-wave activity compared to all other groups. Results are discussed within the framework of a proposed left-hemispheric over-processing hypothesis specific to violent individuals with schizophrenia, involving left hemispheric hyperarousal deficits, which may lead to a homicidally violent schizophrenia outcome. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Neuromonitoring after major neurosurgical procedures.

PubMed

Messerer, M; Daniel, R T; Oddo, M

2012-07-01

Postoperative care of major neurosurgical procedures is aimed at the prevention, detection and treatment of secondary brain injury. This consists of a series of pathological events (i.e. brain edema and intracranial hypertension, cerebral hypoxia/ischemia, brain energy dysfunction, non-convulsive seizures) that occur early after the initial insult and surgical intervention and may add further burden to primary brain injury and thus impact functional recovery. Management of secondary brain injury requires specialized neuroscience intensive care units (ICU) and continuous advanced monitoring of brain physiology. Monitoring of intracranial pressure (ICP) is a mainstay of care and is recommended by international guidelines. However, ICP monitoring alone may be insufficient to detect all episodes of secondary brain insults. Additional invasive (i.e. brain tissue PO2, cerebral microdialysis, regional cerebral blood flow) and non-invasive (i.e. transcranial doppler, near-infrared spectroscopy, EEG) brain monitoring devices might complement ICP monitoring and help clinicians to target therapeutic interventions (e.g. management of cerebral perfusion pressure, blood transfusion, glucose control) to patient-specific pathophysiology. Several independent studies demonstrate such multimodal approach may optimize patient care after major neurosurgical procedures. The aim of this review is to evaluate some of the available monitoring systems and summarize recent important data showing the clinical utility of multimodal neuromonitoring for the management of main acute neurosurgical conditions, including traumatic brain injury, subarachnoid hemorrhage and stroke.

Translating the Science of Alertness and Performance from Laboratory to Field: Using State-of-the-Art Monitoring Imaging and Performance Enhancement Technologies to Improve the Alertness and Safety of the Military and Civilian Workforce

DTIC Science & Technology

2008-06-01

imaging (fMRI) environments, b) custom 32 channel electrode caps for use in fMRI environmentsnew EEG/ EOG signal analysts software, c) ambulatory...personnel 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: REPORT b. ABSTRACT u c. THIS PAGE U 17. LIMITATION OF ABSTRACT SAR 18. NUMBER...digital electroencephalogram (EEG) and electrooculogram ( EOG ) recording systems for ambulatory use as well as for use in functional magnet-resonance

[Syncope, transient ischemic attacks, transient global amnesia and migraine].

PubMed

Hartl, E

2017-10-01

Epileptic seizures can manifest with a variety of clinical symptoms. Depending on the dominant symptom, several differential diagnoses have to be considered. Their differentiation can be challenging, especially after the first episode. The review article summarizes the most common differential diagnoses as well as their characteristics compared to epileptic seizures, aiming at providing guidelines for their clinical differentiation. Whenever a clear diagnosis is not possible based on the patient history and clinical signs, diagnostic evaluation with, e. g. an electroencephalogram (EEG) and finally EEG video monitoring can be helpful.

Duality and nonduality in meditation research.

PubMed

Josipovic, Zoran

2010-12-01

The great variety of meditation techniques found in different contemplative traditions presents a challenge when attempting to create taxonomies based on the constructs of contemporary cognitive sciences. In the current issue of Consciousness and Cognition, Travis and Shear add 'automatic self-transcending' to the previously proposed categories of 'focused attention' and 'open monitoring', and suggest characteristic EEG bands as the defining criteria for each of the three categories. Accuracy of current taxonomies and potential limitations of EEG measurements as classifying criteria are discussed. Copyright © 2010 Elsevier Inc. All rights reserved.

Combining early post-resuscitation EEG and HRV features improves the prognostic performance in cardiac arrest model of rats.

PubMed

Dai, Chenxi; Wang, Zhi; Wei, Liang; Chen, Gang; Chen, Bihua; Zuo, Feng; Li, Yongqin

2018-04-09

Early and reliable prediction of neurological outcome remains a challenge for comatose survivors of cardiac arrest (CA). The purpose of this study was to evaluate the predictive ability of EEG, heart rate variability (HRV) features and the combination of them for outcome prognostication in CA model of rats. Forty-eight male Sprague-Dawley rats were randomized into 6 groups (n=8 each) with different cause and duration of untreated arrest. Cardiopulmonary resuscitation was initiated after 5, 6 and 7min of ventricular fibrillation or 4, 6 and 8min of asphyxia. EEG and ECG were continuously recorded for 4h under normothermia after resuscitation. The relationships between features of early post-resuscitation EEG, HRV and 96-hour outcome were investigated. Prognostic performances were evaluated using the area under receiver operating characteristic curve (AUC). All of the animals were successfully resuscitated and 27 of them survived to 96h. Weighted-permutation entropy (WPE) and normalized high frequency (nHF) outperformed other EEG and HRV features for the prediction of survival. The AUC of WPE was markedly higher than that of nHF (0.892 vs. 0.759, p<0.001). The AUC was 0.954 when WPE and nHF were combined using a logistic regression model, which was significantly higher than the individual EEG (p=0.018) and HRV (p<0.001) features. Earlier post-resuscitation HRV provided prognostic information complementary to quantitative EEG in the CA model of rats. The combination of EEG and HRV features leads to improving performance of outcome prognostication compared to either EEG or HRV based features alone. Copyright © 2018. Published by Elsevier Inc.

Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research

PubMed Central

Krigolson, Olave E.; Williams, Chad C.; Norton, Angela; Hassall, Cameron D.; Colino, Francisco L.

2017-01-01

In recent years there has been an increase in the number of portable low-cost electroencephalographic (EEG) systems available to researchers. However, to date the validation of the use of low-cost EEG systems has focused on continuous recording of EEG data and/or the replication of large system EEG setups reliant on event-markers to afford examination of event-related brain potentials (ERP). Here, we demonstrate that it is possible to conduct ERP research without being reliant on event markers using a portable MUSE EEG system and a single computer. Specifically, we report the results of two experiments using data collected with the MUSE EEG system—one using the well-known visual oddball paradigm and the other using a standard reward-learning task. Our results demonstrate that we could observe and quantify the N200 and P300 ERP components in the visual oddball task and the reward positivity (the mirror opposite component to the feedback-related negativity) in the reward-learning task. Specifically, single sample t-tests of component existence (all p's < 0.05), computation of Bayesian credible intervals, and 95% confidence intervals all statistically verified the existence of the N200, P300, and reward positivity in all analyses. We provide with this research paper an open source website with all the instructions, methods, and software to replicate our findings and to provide researchers with an easy way to use the MUSE EEG system for ERP research. Importantly, our work highlights that with a single computer and a portable EEG system such as the MUSE one can conduct ERP research with ease thus greatly extending the possible use of the ERP methodology to a variety of novel contexts. PMID:28344546

Choosing MUSE: Validation of a Low-Cost, Portable EEG System for ERP Research.

PubMed

Krigolson, Olave E; Williams, Chad C; Norton, Angela; Hassall, Cameron D; Colino, Francisco L

2017-01-01

In recent years there has been an increase in the number of portable low-cost electroencephalographic (EEG) systems available to researchers. However, to date the validation of the use of low-cost EEG systems has focused on continuous recording of EEG data and/or the replication of large system EEG setups reliant on event-markers to afford examination of event-related brain potentials (ERP). Here, we demonstrate that it is possible to conduct ERP research without being reliant on event markers using a portable MUSE EEG system and a single computer. Specifically, we report the results of two experiments using data collected with the MUSE EEG system-one using the well-known visual oddball paradigm and the other using a standard reward-learning task. Our results demonstrate that we could observe and quantify the N200 and P300 ERP components in the visual oddball task and the reward positivity (the mirror opposite component to the feedback-related negativity) in the reward-learning task. Specifically, single sample t -tests of component existence (all p 's < 0.05), computation of Bayesian credible intervals, and 95% confidence intervals all statistically verified the existence of the N200, P300, and reward positivity in all analyses. We provide with this research paper an open source website with all the instructions, methods, and software to replicate our findings and to provide researchers with an easy way to use the MUSE EEG system for ERP research. Importantly, our work highlights that with a single computer and a portable EEG system such as the MUSE one can conduct ERP research with ease thus greatly extending the possible use of the ERP methodology to a variety of novel contexts.

Impact of brain injury on functional measures of amplitude-integrated EEG at term equivalent age in premature infants.

PubMed

El Ters, N M; Vesoulis, Z A; Liao, S M; Smyser, C D; Mathur, A M

2017-08-01

To evaluate the association between qualitative and quantitative amplitude-integrated EEG (aEEG) measures at term equivalent age (TEA) and brain injury on magnetic resonance imaging (MRI) in preterm infants. A cohort of premature infants born at <30 weeks of gestation and with moderate-to-severe MRI injury on a TEA MRI scan was identified. A contemporaneous group of gestational age-matched control infants also born at <30 weeks of gestation with none/mild injury on MRI was also recruited. Quantitative aEEG measures, including maximum and minimum amplitudes, bandwidth span and spectral edge frequency (SEF 90 ), were calculated using an offline software package. The aEEG recordings were qualitatively scored using the Burdjalov system. MRI scans, performed on the same day as aEEG, occurred at a mean postmenstrual age of 38.0 (range 37 to 42) weeks and were scored for abnormality in a blinded manner using an established MRI scoring system. Twenty-eight (46.7%) infants had a normal MRI or mild brain abnormality, while 32 (53.3%) infants had moderate-to-severe brain abnormality. Univariate regression analysis demonstrated an association between severity of brain abnormality and quantitative measures of left and right SEF 90 and bandwidth span (β=-0.38, -0.40 and 0.30, respectively) and qualitative measures of cyclicity, continuity and total Burdjalov score (β=-0.10, -0.14 and -0.12, respectively). After correcting for confounding variables, the relationship between MRI abnormality score and aEEG measures of SEF 90 , bandwidth span and Burdjalov score remained significant. Brain abnormalities on MRI at TEA in premature infants are associated with abnormalities on term aEEG measures, suggesting that anatomical brain injury may contribute to delay in functional brain maturation as assessed using aEEG.

ToTCompute: A Novel EEG-Based TimeOnTask Threshold Computation Mechanism for Engagement Modelling and Monitoring

ERIC Educational Resources Information Center

Ghergulescu, Ioana; Muntean, Cristina Hava

2016-01-01

Engagement influences participation, progression and retention in game-based e-learning (GBeL). Therefore, GBeL systems should engage the players in order to support them to maximize their learning outcomes, and provide the players with adequate feedback to maintain their motivation. Innovative engagement monitoring solutions based on players'…

Detection of seizures from small samples using nonlinear dynamic system theory.

PubMed

Yaylali, I; Koçak, H; Jayakar, P

1996-07-01

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.

Reproducibility of the spectral components of the electroencephalogram during driver fatigue.

PubMed

Lal, Saroj K L; Craig, Ashley

2005-02-01

To date, no study has tested the reproducibility of EEG changes that occur during driver fatigue. For the EEG changes to be useful in the development of a fatigue countermeasure device the EEG response during each onset period of fatigue in individuals needs to be reproducible. It should be noted that fatigue during driving is not a continuous process but consists of successive episodes of 'microsleeps' where the subject may go in and out of a fatigue state. The aim of the present study was to investigate the reproducibility of fatigue during driving in both professional and non-professional drivers. Thirty five non-professional drivers and twenty professional drivers were tested during two separate sessions of a driver simulator task. EEG, EOG and behavioural measurements of fatigue were obtained during the driving task. The results showed high reproducibility for the delta and theta bands (r>0.95) in both groups of drivers. The results are discussed in light of implications for future studies and for the development of an EEG based fatigue countermeasure device.

Multichannel continuous electroencephalography-functional near-infrared spectroscopy recording of focal seizures and interictal epileptiform discharges in human epilepsy: a review

PubMed Central

Peng, Ke; Pouliot, Philippe; Lesage, Frédéric; Nguyen, Dang Khoa

2016-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging technique as it allows noninvasive and long-term monitoring of cortical hemodynamics. Recent work by our group and others has revealed the potential of fNIRS, combined with electroencephalography (EEG), in the context of human epilepsy. Hemodynamic brain responses attributed to epileptic events, such as seizures and interictal epileptiform discharges (IEDs), are routinely observed with a good degree of statistical significance and in concordance with clinical presentation. Recording done with over 100 channels allows sufficiently large coverage of the epileptic focus and other areas. Three types of seizures have been documented: frontal lobe seizures, temporal lobe seizures, and posterior seizures. Increased oxygenation was observed in the epileptic focus in most cases, while rapid but similar hemodynamic variations were identified in the contralateral homologous region. While investigating IEDs, it was shown that their hemodynamic effect is observable with fNIRS, that their response is associated with significant (inhibitive) nonlinearities, and that the sensitivity and specificity of fNIRS to localize the epileptic focus can be estimated in a sample of 40 patients. This paper first reviews recent EEG-fNIRS developments in epilepsy research and then describes applications to the study of focal seizures and IEDs. PMID:26958576

Exploration of EEG features of Alzheimer's disease using continuous wavelet transform.

PubMed

Ghorbanian, Parham; Devilbiss, David M; Hess, Terry; Bernstein, Allan; Simon, Adam J; Ashrafiuon, Hashem

2015-09-01

We have developed a novel approach to elucidate several discriminating EEG features of Alzheimer's disease. The approach is based on the use of a variety of continuous wavelet transforms, pairwise statistical tests with multiple comparison correction, and several decision tree algorithms, in order to choose the most prominent EEG features from a single sensor. A pilot study was conducted to record EEG signals from Alzheimer's disease (AD) patients and healthy age-matched control (CTL) subjects using a single dry electrode device during several eyes-closed (EC) and eyes-open (EO) resting conditions. We computed the power spectrum distribution properties and wavelet and sample entropy of the wavelet coefficients time series at scale ranges approximately corresponding to the major brain frequency bands. A predictive index was developed using the results from statistical tests and decision tree algorithms to identify the most reliable significant features of the AD patients when compared to healthy controls. The three most dominant features were identified as larger absolute mean power and larger standard deviation of the wavelet scales corresponding to 4-8 Hz (θ) during EO and lower wavelet entropy of the wavelet scales corresponding to 8-12 Hz (α) during EC, respectively. The fourth reliable set of distinguishing features of AD patients was lower relative power of the wavelet scales corresponding to 12-30 Hz (β) followed by lower skewness of the wavelet scales corresponding to 2-4 Hz (upper δ), both during EO. In general, the results indicate slowing and lower complexity of EEG signal in AD patients using a very easy-to-use and convenient single dry electrode device.

Rewards-driven control of robot arm by decoding EEG signals.

PubMed

Tanwani, Ajay Kumar; del R Millan, Jose; Billard, Aude

2014-01-01

Decoding the user intention from non-invasive EEG signals is a challenging problem. In this paper, we study the feasibility of predicting the goal for controlling the robot arm in self-paced reaching movements, i.e., spontaneous movements that do not require an external cue. Our proposed system continuously estimates the goal throughout a trial starting before the movement onset by online classification and generates optimal trajectories for driving the robot arm to the estimated goal. Experiments using EEG signals of one healthy subject (right arm) yield smooth reaching movements of the simulated 7 degrees of freedom KUKA robot arm in planar center-out reaching task with approximately 80% accuracy of reaching the actual goal.

The study of cognitive processes in the brain EEG during the perception of bistable images using wavelet skeleton

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Zhuravlev, Maksim O.; Pysarchik, Alexander N.; Khramova, Marina V.; Grubov, Vadim V.

2017-03-01

In the paper we study the appearance of the complex patterns in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. A new method based on the calculation of the maximum energy component for the continuous wavelet transform (skeletons) is proposed. Skeleton analysis allows us to identify specific patterns in the EEG data set, appearing in the perception of ambiguous objects. Thus, it becomes possible to diagnose some cognitive processes associated with the concentration of attention and recognition of complex visual objects. The article presents the processing results of experimental data for 6 male volunteers.

An Integrated Approach for the Monitoring of Brain and Autonomic Response of Children with Autism Spectrum Disorders during Treatment by Wearable Technologies

PubMed Central

Billeci, Lucia; Tonacci, Alessandro; Tartarisco, Gennaro; Narzisi, Antonio; Di Palma, Simone; Corda, Daniele; Baldus, Giovanni; Cruciani, Federico; Anzalone, Salvatore M.; Calderoni, Sara; Pioggia, Giovanni; Muratori, Filippo

2016-01-01

Autism Spectrum Disorders (ASD) are associated with physiological abnormalities, which are likely to contribute to the core symptoms of the condition. Wearable technologies can provide data in a semi-naturalistic setting, overcoming the limitations given by the constrained situations in which physiological signals are usually acquired. In this study an integrated system based on wearable technologies for the acquisition and analysis of neurophysiological and autonomic parameters during treatment is proposed and an application on five children with ASD is presented. Signals were acquired during a therapeutic session based on an imitation protocol in ASD children. Data were analyzed with the aim of extracting quantitative EEG (QEEG) features from EEG signals as well as heart rate and heart rate variability (HRV) from ECG. The system allowed evidencing changes in neurophysiological and autonomic response from the state of disengagement to the state of engagement of the children, evidencing a cognitive involvement in the children in the tasks proposed. The high grade of acceptability of the monitoring platform is promising for further development and implementation of the tool. In particular if the results of this feasibility study would be confirmed in a larger sample of subjects, the system proposed could be adopted in more naturalistic paradigms that allow real world stimuli to be incorporated into EEG/psychophysiological studies for the monitoring of the effect of the treatment and for the implementation of more individualized therapeutic programs. PMID:27445652

Temporal lobe epilepsy is a predisposing factor for sleep apnea: A questionnaire study in video-EEG monitoring unit.

PubMed

Yildiz, F Gokcem; Tezer, F Irsel; Saygi, Serap

2015-07-01

The interaction between epilepsy and sleep is known. It has been shown that patients with epilepsy have more sleep problems than the general population. However, there is no recent study that compares the frequency of sleep disorders in groups with medically refractory temporal lobe epilepsy (TLE) and extratemporal lobe epilepsy (ETLE). The main purpose of this study was to investigate the occurrence of sleep disorders in two subtypes of epilepsy by using sleep questionnaire forms. One hundred and eighty-nine patients, out of 215 who were monitored for refractory epilepsy and were followed by the video-EEG monitoring unit, were divided into a group with TLE and a group with ETLE. The medical outcome study-sleep scale (MOS-SS), Epworth sleepiness scale (ESS), and sleep apnea scale of the sleep disorders questionnaire (SD-SDQ) were completed after admission to the video-EEG monitoring unit. The total scores in the group with TLE and group with ETLE were compared. Of the patients, TLE was diagnosed in 101 (53.4%) (45 females), and ETLE was diagnosed in 88 (46.6%) (44 females). Comparison of MOS-SS and Epworth sleepiness scale scores in the two subgroups did not reveal significant differences. In the group with TLE, SD-SDQ scores were significantly higher compared to that in the group with ETLE. Patients with temporal lobe epilepsy have higher risk of obstructive sleep apnea (OSA) according to their reported symptoms. Detection of OSA in patients with epilepsy by using questionnaire forms may decrease the risk of ictal or postictal respiratory-related 'Sudden Unexpected Death in Epilepsy'. Copyright © 2015 Elsevier Inc. All rights reserved.

Differences between state entropy and bispectral index during analysis of identical electroencephalogram signals: a comparison with two randomised anaesthetic techniques.

PubMed

Pilge, Stefanie; Kreuzer, Matthias; Karatchiviev, Veliko; Kochs, Eberhard F; Malcharek, Michael; Schneider, Gerhard

2015-05-01

It is claimed that bispectral index (BIS) and state entropy reflect an identical clinical spectrum, the hypnotic component of anaesthesia. So far, it is not known to what extent different devices display similar index values while processing identical electroencephalogram (EEG) signals. To compare BIS and state entropy during analysis of identical EEG data. Inspection of raw EEG input to detect potential causes of erroneous index calculation. Offline re-analysis of EEG data from a randomised, single-centre controlled trial using the Entropy Module and an Aspect A-2000 monitor. Klinikum rechts der Isar, Technische Universität München, Munich. Forty adult patients undergoing elective surgery under general anaesthesia. Blocked randomisation of 20 patients per anaesthetic group (sevoflurane/remifentanil or propofol/remifentanil). Isolated forearm technique for differentiation between consciousness and unconsciousness. Prediction probability (PK) of state entropy to discriminate consciousness from unconsciousness. Correlation and agreement between state entropy and BIS from deep to light hypnosis. Analysis of raw EEG compared with index values that are in conflict with clinical examination, with frequency measures (frequency bands/Spectral Edge Frequency 95) and visual inspection for physiological EEG patterns (e.g. beta or delta arousal), pathophysiological features such as high-frequency signals (electromyogram/high-frequency EEG or eye fluttering/saccades), different types of electro-oculogram or epileptiform EEG and technical artefacts. PK of state entropy was 0.80 and of BIS 0.84; correlation coefficient of state entropy with BIS 0.78. Nine percent BIS and 14% state entropy values disagreed with clinical examination. Highest incidence of disagreement occurred after state transitions, in particular for state entropy after loss of consciousness during sevoflurane anaesthesia. EEG sequences which led to false 'conscious' index values often showed high-frequency signals and eye blinks. High-frequency EEG/electromyogram signals were pooled because a separation into EEG and fast electro-oculogram, for example eye fluttering or saccades, on the basis of a single EEG channel may not be very reliable. These signals led to higher Spectral Edge Frequency 95 and ratio of relative beta and gamma band power than EEG signals, indicating adequate unconscious classification. The frequency of other artefacts that were assignable, for example technical artefacts, movement artefacts, was negligible and they were excluded from analysis. High-frequency signals and eye blinks may account for index values that falsely indicate consciousness. Compared with BIS, state entropy showed more false classifications of the clinical state at transition between consciousness and unconsciousness.

Recording brain waves at the supermarket: what can we learn from a shopper's brain?

PubMed

Sands, Stephen F; Sands, J Andrew

2012-01-01

Communication and marketing campaigns have traditionally been divided into two lines: above the line (ATL) and below the line (BTL). ATL campaigns refer to communications such as TV, print, and outdoor displays that are intended to reach large audiences. The effects of ATL are inherently difficult to measure; we do not see the direct consequences of viewing an advertisement (i.e., a talking baby giving financial advice) and actual purchase of the product. ATL is intended to indirectly improve the impression of a brand. BTL campaigns refer to promotions and in-store displays and are designed to affect the point-of-purchase behavior. The effects of BTL are easier to measure; we see direct consequences of viewing a display (i.e., “Today Only, Two for the Price of One”) and eventual purchase of the product. BTL is intended to directly improve the impression of a brand. Neuroscience plays an important role in measuring the effects of marketing campaigns. Traditional methods of measurement (such as surveys and interviews) depend on the verbal ability of the consumer to articulate their motivations for purchasing a product. It is well known that participants are poor at introspective reasoning, leading to an eventual purchase that omits emotional elements. Recently, methods normally employed in cognitive neuroscience have been adapted for use in the evaluation of campaign effectiveness. These methods have increased our understanding of factors leading to economic decisions. The application of neuroscience in ATL campaigns is relatively straightforward. Participants view TV commercials, for example, seated in a comfortable setting with minimal movement while electroencephalogram (EEG) measures are monitored. These brain waves reveal cognitive events related to the media. Participants are exposed to a functional magnetic resonance imaging (fMRI) scanner to monitor changes in blood flow in various regions of the brain. Both of these methods are sensitive to underlying cognitive and emotional activity and are complimentary. EEG is more sensitive to time-locked events (i.e., story lines), whereas fMRI is more sensitive to the brain regions involved. The application of neuroscience in BTL campaigns is significantly more difficult to achieve. Participants move unconstrained in a shopping environment while EEG and eye movements are monitored. In this scenario, fMRI is not possible. fMRI can be used with virtual store mock-ups, but it is expensive and seldom used. We have developed a technology that allows for the measurement of EEG in an unobtrusive manner. The intent is to record the brain waves of participants during their day-to-day shopping experience. A miniaturized video recorder, EEG amplifiers, and eye-tracking systems are used. Digital signal processing is employed to remove the substantial artifact generated by eye movements and motion. Eye fixations identify specific viewings of products and displays, and they are used for synchronizing the behavior with EEG response. The location of EEG sources is determined by the use of a source reconstruction software.

COSBID-M3: a platform for multimodal monitoring, data collection, and research in neurocritical care.

PubMed

Wilson, J Adam; Shutter, Lori A; Hartings, Jed A

2013-01-01

Neuromonitoring in patients with severe brain trauma and stroke is often limited to intracranial pressure (ICP); advanced neuroscience intensive care units may also monitor brain oxygenation (partial pressure of brain tissue oxygen, P(bt)O(2)), electroencephalogram (EEG), cerebral blood flow (CBF), or neurochemistry. For example, cortical spreading depolarizations (CSDs) recorded by electrocorticography (ECoG) are associated with delayed cerebral ischemia after subarachnoid hemorrhage and are an attractive target for novel therapeutic approaches. However, to better understand pathophysiologic relations and realize the potential of multimodal monitoring, a common platform for data collection and integration is needed. We have developed a multimodal system that integrates clinical, research, and imaging data into a single research and development (R&D) platform. Our system is adapted from the widely used BCI2000, a brain-computer interface tool which is written in the C++ language and supports over 20 data acquisition systems. It is optimized for real-time analysis of multimodal data using advanced time and frequency domain analyses and is extensible for research development using a combination of C++, MATLAB, and Python languages. Continuous streams of raw and processed data, including BP (blood pressure), ICP, PtiO2, CBF, ECoG, EEG, and patient video are stored in an open binary data format. Selected events identified in raw (e.g., ICP) or processed (e.g., CSD) measures are displayed graphically, can trigger alarms, or can be sent to researchers or clinicians via text message. For instance, algorithms for automated detection of CSD have been incorporated, and processed ECoG signals are projected onto three-dimensional (3D) brain models based on patient magnetic resonance imaging (MRI) and computed tomographic (CT) scans, allowing real-time correlation of pathoanatomy and cortical function. This platform will provide clinicians and researchers with an advanced tool to investigate pathophysiologic relationships and novel measures of cerebral status, as well as implement treatment algorithms based on such multimodal measures.

Practical Designs of Brain-Computer Interfaces Based on the Modulation of EEG Rhythms

NASA Astrophysics Data System (ADS)

Wang, Yijun; Gao, Xiaorong; Hong, Bo; Gao, Shangkai

A brain-computer interface (BCI) is a communication channel which does not depend on the brain's normal output pathways of peripheral nerves and muscles [1-3]. It supplies paralyzed patients with a new approach to communicate with the environment. Among various brain monitoring methods employed in current BCI research, electroencephalogram (EEG) is the main interest due to its advantages of low cost, convenient operation and non-invasiveness. In present-day EEG-based BCIs, the following signals have been paid much attention: visual evoked potential (VEP), sensorimotor mu/beta rhythms, P300 evoked potential, slow cortical potential (SCP), and movement-related cortical potential (MRCP). Details about these signals can be found in chapter "Brain Signals for Brain-Computer Interfaces". These systems offer some practical solutions (e.g., cursor movement and word processing) for patients with motor disabilities.

Masturbation mimicking seizure in an infant.

PubMed

Deda, G; Caksen, H; Suskan, E; Gümüs, D

2001-08-01

A 3.5-month-old boy was referred to our hospital with the diagnosis of infantile spasm. His developmental milestones and physical examination were normal. During the follow-up we recorded about six to nine attacks a day and the duration of attacks was changed between 15 seconds-1.5 minutes. During the episodic attacks he was flushed and had tonic posturing associated with crossing of thighs, without loss of consciousness and his eye movements were normal. Routine and long-term electroencephalogram (EEG) were normal during attack. The patient was diagnosed as masturbation according to the clinical and EEG findings. In conclusion, we would like to stress that masturbation should also be considered in infants who were admitted with complaint of seizure, and aside from EEG monitoring a detailed history and careful observation are very important factors in differential diagnosis of these two different conditions.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.

PubMed

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Frontal-posterior coherence and cognitive function in older adults.

PubMed

Fleck, Jessica I; Kuti, Julia; Brown, Jessica; Mahon, Jessica R; Gayda-Chelder, Christine

2016-12-01

The reliable measurement of brain health and cognitive function is essential in mitigating the negative effects associated with cognitive decline through early and accurate diagnosis of change. The present research explored the relationship between EEG coherence for electrodes within frontal and posterior regions, as well as coherence between frontal and posterior electrodes and performance on standard neuropsychological measures of memory and executive function. EEG coherence for eyes-closed resting-state EEG activity was calculated for delta, theta, alpha, beta, and gamma frequency bands. Participants (N=66; mean age=67.15years) had their resting-state EEGs recorded and completed a neuropsychological battery that assessed memory and executive function, two cognitive domains that are significantly affected during aging. A positive relationship was observed between coherence within the frontal region and performance on measures of memory and executive function for delta and beta frequency bands. In addition, an inverse relationship was observed for coherence between frontal and posterior electrode pairs, particularly within the theta frequency band, and performance on Digit Span Sequencing, a measure of working memory. The present research supports a more substantial link between EEG coherence, rather than spectral power, and cognitive function. Continued study in this area may enable EEG to be applied broadly as a diagnostic measure of cognitive ability. Copyright © 2016 Elsevier B.V. All rights reserved.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

PubMed Central

Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard

2016-01-01

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators. PMID:26955362

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.

PubMed

Li, Yang; Cui, Weigang; Luo, Meilin; Li, Ke; Wang, Lina

2018-01-25

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This paper presents a novel automatic EEG signal classification method for epileptic seizure detection. The proposed method first employs a continuous wavelet transform (CWT) method for obtaining the time-frequency images (TFI) of EEG signals. The processed EEG signals are then decomposed into five sub-band frequency components of clinical interest since these sub-band frequency components indicate much better discriminative characteristics. Both Gaussian Mixture Model (GMM) features and Gray Level Co-occurrence Matrix (GLCM) descriptors are then extracted from these sub-band TFI. Additionally, in order to improve classification accuracy, a compact feature selection method by combining the ReliefF and the support vector machine-based recursive feature elimination (RFE-SVM) algorithm is adopted to select the most discriminative feature subset, which is an input to the SVM with the radial basis function (RBF) for classifying epileptic seizure EEG signals. The experimental results from a publicly available benchmark database demonstrate that the proposed approach provides better classification accuracy than the recently proposed methods in the literature, indicating the effectiveness of the proposed method in the detection of epileptic seizures.

Frontal brain electrical activity (EEG) and heart rate in response to affective infant-directed (ID) speech in 9-month-old infants.

PubMed

Santesso, Diane L; Schmidt, Louis A; Trainor, Laurel J

2007-10-01

Many studies have shown that infants prefer infant-directed (ID) speech to adult-directed (AD) speech. ID speech functions to aid language learning, obtain and/or maintain an infant's attention, and create emotional communication between the infant and caregiver. We examined psychophysiological responses to ID speech that varied in affective content (i.e., love/comfort, surprise, fear) in a group of typically developing 9-month-old infants. Regional EEG and heart rate were collected continuously during stimulus presentation. We found the pattern of overall frontal EEG power was linearly related to affective intensity of the ID speech, such that EEG power was greatest in response to fear, than surprise than love/comfort; this linear pattern was specific to the frontal region. We also noted that heart rate decelerated to ID speech independent of affective content. As well, infants who were reported by their mothers as temperamentally distressed tended to exhibit greater relative right frontal EEG activity during baseline and in response to affective ID speech, consistent with previous work with visual stimuli and extending it to the auditory modality. Findings are discussed in terms of how increases in frontal EEG power in response to different affective intensity may reflect the cognitive aspects of emotional processing across sensory domains in infancy.

Reduction in time-to-sleep through EEG based brain state detection and audio stimulation.

PubMed

Zhuo Zhang; Cuntai Guan; Ti Eu Chan; Juanhong Yu; Aung Aung Phyo Wai; Chuanchu Wang; Haihong Zhang

2015-08-01

We developed an EEG- and audio-based sleep sensing and enhancing system, called iSleep (interactive Sleep enhancement apparatus). The system adopts a closed-loop approach which optimizes the audio recording selection based on user's sleep status detected through our online EEG computing algorithm. The iSleep prototype comprises two major parts: 1) a sleeping mask integrated with a single channel EEG electrode and amplifier, a pair of stereo earphones and a microcontroller with wireless circuit for control and data streaming; 2) a mobile app to receive EEG signals for online sleep monitoring and audio playback control. In this study we attempt to validate our hypothesis that appropriate audio stimulation in relation to brain state can induce faster onset of sleep and improve the quality of a nap. We conduct experiments on 28 healthy subjects, each undergoing two nap sessions - one with a quiet background and one with our audio-stimulation. We compare the time-to-sleep in both sessions between two groups of subjects, e.g., fast and slow sleep onset groups. The p-value obtained from Wilcoxon Signed Rank Test is 1.22e-04 for slow onset group, which demonstrates that iSleep can significantly reduce the time-to-sleep for people with difficulty in falling sleep.

Frontal-temporal synchronization of EEG signals quantified by order patterns cross recurrence analysis during propofol anesthesia.

PubMed

Shalbaf, Reza; Behnam, Hamid; Sleigh, Jamie W; Steyn-Ross, D Alistair; Steyn-Ross, Moira L

2015-05-01

Characterizing brain dynamics during anesthesia is a main current challenge in anesthesia study. Several single channel electroencephalogram (EEG)-based commercial monitors like the Bispectral index (BIS) have suggested to examine EEG signal. But, the BIS index has obtained numerous critiques. In this study, we evaluate the concentration-dependent effect of the propofol on long-range frontal-temporal synchronization of EEG signals collected from eight subjects during a controlled induction and recovery design. We used order patterns cross recurrence plot and provide an index named order pattern laminarity (OPL) to assess changes in neuronal synchronization as the mechanism forming the foundation of conscious perception. The prediction probability of 0.9 and 0.84 for OPL and BIS specified that the OPL index correlated more strongly with effect-site propofol concentration. Also, our new index makes faster reaction to transients in EEG recordings based on pharmacokinetic and pharmacodynamic model parameters and demonstrates less variability at the point of loss of consciousness (standard deviation of 0.04 for OPL compared with 0.09 for BIS index). The result show that the OPL index can estimate anesthetic state of patient more efficiently than the BIS index in lightly sedated state with more tolerant of artifacts.

Stage 2 Sleep EEG Sigma Activity and Motor Learning in Childhood ADHD: A Pilot Study

PubMed Central

Saletin, Jared M.; Coon, William G.; Carskadon, Mary A.

2017-01-01

Objective Attention deficit hyperactivity disorder (ADHD) is associated with deficits in motor learning and sleep. In healthy adults, overnight motor skill learning improvement is associated with sleep spindle activity in the sleep EEG. This association is poorly characterized in children, particularly in pediatric ADHD. Method Polysomnographic sleep was monitored in seven children with ADHD and fourteen typically developing controls. All children trained on a validated motor sequence task (MST) in the evening with retesting the following morning. Analyses focused on MST precision (speed-accuracy trade-off). NREM Stage 2 sleep EEG power spectral analyses focused on spindle-frequency EEG activity in the sigma (12–15 Hz) band. Results The ADHD group demonstrated a selective decrease in power within the sigma band. Evening MST precision was lower in ADHD, yet no difference in performance was observed following sleep. Moreover, ADHD-status moderated the association between slow sleep spindle activity (12–13.5 Hz) and overnight improvement; spindle-frequency EEG activity was positively associated with performance improvements in children with ADHD but not in controls. Conclusions These data highlight the importance of sleep in supporting next day behavior in ADHD, while indicating that differences in sleep neurophysiology may, in part, underlie cognitive deficits in this population. PMID:27267670

Stage 2 Sleep EEG Sigma Activity and Motor Learning in Childhood ADHD: A Pilot Study.

PubMed

Saletin, Jared M; Coon, William G; Carskadon, Mary A

2017-01-01

Attention deficit hyperactivity disorder (ADHD) is associated with deficits in motor learning and sleep. In healthy adults, overnight improvements in motor skills are associated with sleep spindle activity in the sleep electroencephalogram (EEG). This association is poorly characterized in children, particularly in pediatric ADHD. Polysomnographic sleep was monitored in 7 children with ADHD and 14 typically developing controls. All children were trained on a validated motor sequence task (MST) in the evening with retesting the following morning. Analyses focused on MST precision (speed-accuracy trade-off). NREM Stage 2 sleep EEG power spectral analyses focused on spindle-frequency EEG activity in the sigma (12-15 Hz) band. The ADHD group demonstrated a selective decrease in power within the sigma band. Evening MST precision was lower in ADHD, yet no difference in performance was observed following sleep. Moreover, ADHD status moderated the association between slow sleep spindle activity (12-13.5 Hz) and overnight improvement; spindle-frequency EEG activity was positively associated with performance improvements in children with ADHD but not in controls. These data highlight the importance of sleep in supporting next-day behavior in ADHD while indicating that differences in sleep neurophysiology may contribute to deficits in this population.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

PubMed Central

Zhang, Xiaoliang; Li, Jiali; Liu, Yugang; Zhang, Zutao; Wang, Zhuojun; Luo, Dianyuan; Zhou, Xiang; Zhu, Miankuan; Salman, Waleed; Hu, Guangdi; Wang, Chunbai

2017-01-01

The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety. PMID:28257073

Cannabinoid antagonist SLV326 induces convulsive seizures and changes in the interictal EEG in rats

PubMed Central

de Bruin, Natasja; Heijink, Liesbeth; Kruse, Chris; Vinogradova, Lyudmila; Lüttjohann, Annika; van Luijtelaar, Gilles; van Rijn, Clementina M.

2017-01-01

Cannabinoid CB1 antagonists have been investigated for possible treatment of e.g. obesity-related disorders. However, clinical application was halted due to their symptoms of anxiety and depression. In addition to these adverse effects, we have shown earlier that chronic treatment with the CB1 antagonist rimonabant may induce EEG-confirmed convulsive seizures. In a regulatory repeat-dose toxicity study violent episodes of “muscle spasms” were observed in Wistar rats, daily dosed with the CB1 receptor antagonist SLV326 during 5 months. The aim of the present follow-up study was to investigate whether these violent movements were of an epileptic origin. In selected SLV326-treated and control animals, EEG and behavior were monitored for 24 hours. 25% of SLV326 treated animals showed 1 to 21 EEG-confirmed generalized convulsive seizures, whereas controls were seizure-free. The behavioral seizures were typical for a limbic origin. Moreover, interictal spikes were found in 38% of treated animals. The frequency spectrum of the interictal EEG of the treated rats showed a lower theta peak frequency, as well as lower gamma power compared to the controls. These frequency changes were state-dependent: they were only found during high locomotor activity. It is concluded that long term blockade of the endogenous cannabinoid system can provoke limbic seizures in otherwise healthy rats. Additionally, SLV326 alters the frequency spectrum of the EEG when rats are highly active, suggesting effects on complex behavior and cognition. PMID:28151935

Assessing the feasibility of online SSVEP decoding in human walking using a consumer EEG headset.

PubMed

Lin, Yuan-Pin; Wang, Yijun; Jung, Tzyy-Ping

2014-08-09

Bridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience. An urgent need is to explore the feasibility of using a low-cost, ease-of-use electroencephalogram (EEG) headset for monitoring individuals' EEG signals in their natural head/body positions and movements. This study aimed to assess the feasibility of using a consumer-level EEG headset to realize an online steady-state visual-evoked potential (SSVEP)-based BCI during human walking. This study adopted a 14-channel Emotiv EEG headset to implement a four-target online SSVEP decoding system, and included treadmill walking at the speeds of 0.45, 0.89, and 1.34 meters per second (m/s) to initiate the walking locomotion. Seventeen participants were instructed to perform the online BCI tasks while standing or walking on the treadmill. To maintain a constant viewing distance to the visual targets, participants held the hand-grip of the treadmill during the experiment. Along with online BCI performance, the concurrent SSVEP signals were recorded for offline assessment. Despite walking-related attenuation of SSVEPs, the online BCI obtained an information transfer rate (ITR) over 12 bits/min during slow walking (below 0.89 m/s). SSVEP-based BCI systems are deployable to users in treadmill walking that mimics natural walking rather than in highly-controlled laboratory settings. This study considerably promotes the use of a consumer-level EEG headset towards the real-life BCI applications.

The long-term course of temporal lobe epilepsy: From unilateral to bilateral interictal epileptiform discharges in repeated video-EEG monitorings.

PubMed

Gollwitzer, Stephanie; Scott, Catherine A; Farrell, Fiona; Bell, Gail S; de Tisi, Jane; Walker, Matthew C; Wehner, Tim; Sander, Josemir W; Hamer, Hajo M; Diehl, Beate

2017-03-01

Bilateral interictal epileptiform discharges (IED) and ictal patterns are common in temporal lobe epilepsy (TLE) and have been associated with decreased chances of seizure freedom after epilepsy surgery. It is unclear whether secondary epileptogenesis, although demonstrated in experimental models, exists in humans and may account for progression of epilepsy. We reviewed consecutive video-EEG recordings from 1992 to 2014 repeated at least two years apart (mean interval 6.14years) in 100 people diagnosed with TLE. Ictal EEG patterns and IED remained restricted to one hemisphere in 36 people (group 1), 46 exhibited bilateral abnormalities from the first recording (group 2), 18 progressed from unilateral to bilateral EEG pathology over time (group 3). No significant differences between the three groups were seen with respect to age at epilepsy onset, duration, or underlying pathology. Extra-temporal IED during the first EEG recording were associated with an increased risk of developing bilateral epileptiform changes over time (hazard ratio 3.67; 95% CI 1.4, 9.4). Our findings provide some support of progression in TLE and raise the possibility of secondary epileptogenesis in humans. The development of an independent contra-lateral epileptogenic focus is known to be associated with a less favorable surgical outcome. We defined reliable EEG markers for an increased risk of progression to more widespread or independent bitemporal epileptogenicity at an early stage, thus allowing for individualized pre-surgical counselling. Copyright © 2016 Elsevier Inc. All rights reserved.

Source localization of temporal lobe epilepsy using PCA-LORETA analysis on ictal EEG recordings.

PubMed

Stern, Yaki; Neufeld, Miriam Y; Kipervasser, Svetlana; Zilberstein, Amir; Fried, Itzhak; Teicher, Mina; Adi-Japha, Esther

2009-04-01

Localizing the source of an epileptic seizure using noninvasive EEG suffers from inaccuracies produced by other generators not related to the epileptic source. The authors isolated the ictal epileptic activity, and applied a source localization algorithm to identify its estimated location. Ten ictal EEG scalp recordings from five different patients were analyzed. The patients were known to have temporal lobe epilepsy with a single epileptic focus that had a concordant MRI lesion. The patients had become seizure-free following partial temporal lobectomy. A midinterval (approximately 5 seconds) period of ictal activity was used for Principal Component Analysis starting at ictal onset. The level of epileptic activity at each electrode (i.e., the eigenvector of the component that manifest epileptic characteristic), was used as an input for low-resolution tomography analysis for EEG inverse solution (Zilberstain et al., 2004). The algorithm accurately and robustly identified the epileptic focus in these patients. Principal component analysis and source localization methods can be used in the future to monitor the progression of an epileptic seizure and its expansion to other areas.

Study of heart-brain interactions through EEG, ECG, and emotions

NASA Astrophysics Data System (ADS)

Ramasamy, Mouli; Varadan, Vijay K.

2017-04-01

Neurocardiology is the exploration of neurophysiological, neurological and neuroanatomical facets of neuroscience's influence in cardiology. The paraphernalia of emotions on the heart and brain are premeditated because of the interaction between the central and peripheral nervous system. This is an investigative attempt to study emotion based neurocardiology and the factors that influence this phenomenon. The factors include: interaction between sleep EEG (electroencephalogram) and ECG (electrocardiogram), relationship between emotion and music, psychophysiological coherence between the heart and brain, emotion recognition techniques, and biofeedback mechanisms. Emotions contribute vitally to the mundane life and are quintessential to a numerous biological and everyday-functional modality of a human being. Emotions are best represented through EEG signals, and to a certain extent, can be observed through ECG and body temperature. Confluence of medical and engineering science has enabled the monitoring and discrimination of emotions influenced by happiness, anxiety, distress, excitement and several other factors that influence the thinking patterns and the electrical activity of the brain. Similarly, HRV (Heart Rate Variability) widely investigated for its provision and discerning characteristics towards EEG and the perception in neurocardiology.

The physiological correlates of Kundalini Yoga meditation: a study of a yoga master.

PubMed

Arambula, P; Peper, E; Kawakami, M; Gibney, K H

2001-06-01

This study explores the physiological correlates of a highly practiced Kundalini Yoga meditator. Thoracic and abdominal breathing patterns, heart rate (HR), occipital parietal electroencephalograph (EEG), skin conductance level (SCL), and blood volume pulse (BVP) were monitored during prebaseline, meditation, and postbaseline periods. Visual analyses of the data showed a decrease in respiration rate during the meditation from a mean of 11 breaths/min for the pre- and 13 breaths/min for the postbaseline to a mean of 5 breaths/min during the meditation, with a predominance of abdominal/diaphragmatic breathing. There was also more alpha EEG activity during the meditation (M = 1.71 microV) compared to the pre- (M = .47 microV) and postbaseline (M = .78 microV) periods, and an increase in theta EEG activity immediately following the meditation (M = .62 microV) compared to the pre-baseline and meditative periods (each with M = .26 microV). These findings suggest that a shift in breathing patterns may contribute to the development of alpha EEG, and those patterns need to be investigated further.

Design of a Mobile Brain Computer Interface-Based Smart Multimedia Controller

PubMed Central

Tseng, Kevin C.; Lin, Bor-Shing; Wong, Alice May-Kuen; Lin, Bor-Shyh

2015-01-01

Music is a way of expressing our feelings and emotions. Suitable music can positively affect people. However, current multimedia control methods, such as manual selection or automatic random mechanisms, which are now applied broadly in MP3 and CD players, cannot adaptively select suitable music according to the user’s physiological state. In this study, a brain computer interface-based smart multimedia controller was proposed to select music in different situations according to the user’s physiological state. Here, a commercial mobile tablet was used as the multimedia platform, and a wireless multi-channel electroencephalograph (EEG) acquisition module was designed for real-time EEG monitoring. A smart multimedia control program built in the multimedia platform was developed to analyze the user’s EEG feature and select music according his/her state. The relationship between the user’s state and music sorted by listener’s preference was also examined in this study. The experimental results show that real-time music biofeedback according a user’s EEG feature may positively improve the user’s attention state. PMID:25756862

[Non-linear research of alertness levels under sleep deprivation].

PubMed

Xue, Ranting; Zhou, Peng; Gao, Xiang; Dong, Xinming; Wang, Xiaolu; Ming, Dong; Qi, Hongzhi; Wang, Xuemin

2014-06-01

We applied Lempel-Ziv complexity (LZC) combined with brain electrical activity mapping (BEAM) to study the change of alertness under sleep deprivation in our research. Ten subjects were involved in 36 hours sleep deprivation (SD), during which spontaneous electroencephalogram (EEG) experiments and auditory evoked EEG experiments-Oddball were recorded once every 6 hours. Spontaneous and evoked EEG data were calculated and BEAMs were structured. Results showed that during the 36 hours of SD, alertness could be divided into three stages, i. e. the first 12 hours as the high stage, the middle 12 hours as the rapid decline stage and the last 12 hours as the low stage. During the period SD, LZC of Spontaneous EEG decreased over the whole brain to some extent, but remained consistent with the subjective scales. By BEAMs of event related potential, LZC on frontal cortex decreased, but kept consistent with the behavioral responses. Therefore, LZC can be effective to reflect the change of brain alertness. At the same time LZC could be used as a practical index to monitor real-time alertness because of its simple computation and fast calculation.

Protocol for the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) study: a pragmatic, randomised clinical trial

PubMed Central

Wildes, T S; Winter, A C; Maybrier, H R; Mickle, A M; Lenze, E J; Stark, S; Lin, N; Inouye, S K; Schmitt, E M; McKinnon, S L; Muench, M R; Murphy, M R; Upadhyayula, R T; Fritz, B A; Escallier, K E; Apakama, G P; Emmert, D A; Graetz, T J; Stevens, T W; Palanca, B J; Hueneke, R L; Melby, S; Torres, B; Leung, J; Jacobsohn, E; Avidan, M S

2016-01-01

Introduction Postoperative delirium, arbitrarily defined as occurring within 5 days of surgery, affects up to 50% of patients older than 60 after a major operation. This geriatric syndrome is associated with longer intensive care unit and hospital stay, readmission, persistent cognitive deterioration and mortality. No effective preventive methods have been identified, but preliminary evidence suggests that EEG monitoring during general anaesthesia, by facilitating reduced anaesthetic exposure and EEG suppression, might decrease incident postoperative delirium. This study hypothesises that EEG-guidance of anaesthetic administration prevents postoperative delirium and downstream sequelae, including falls and decreased quality of life. Methods and analysis This is a 1232 patient, block-randomised, double-blinded, comparative effectiveness trial. Patients older than 60, undergoing volatile agent-based general anaesthesia for major surgery, are eligible. Patients are randomised to 1 of 2 anaesthetic approaches. One group receives general anaesthesia with clinicians blinded to EEG monitoring. The other group receives EEG-guidance of anaesthetic agent administration. The outcomes of postoperative delirium (≤5 days), falls at 1 and 12 months and health-related quality of life at 1 and 12 months will be compared between groups. Postoperative delirium is assessed with the confusion assessment method, falls with ProFaNE consensus questions and quality of life with the Veteran's RAND 12-item Health Survey. The intention-to-treat principle will be followed for all analyses. Differences between groups will be presented with 95% CIs and will be considered statistically significant at a two-sided p<0.05. Ethics and dissemination Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) is approved by the ethics board at Washington University. Recruitment began in January 2015. Dissemination plans include presentations at scientific conferences, scientific publications, internet-based educational materials and mass media. Trial registration number NCT02241655; Pre-results. PMID:27311914

A predictive index of biomarkers for ictogenesis from tier I safety pharmacology testing that may warrant tier II EEG studies.

PubMed

Gauvin, David V; Zimmermann, Zachary J; Yoder, Joshua; Harter, Marci; Holdsworth, David; Kilgus, Quinn; May, Jonelle; Dalton, Jill; Baird, Theodore J

2018-05-08

Three significant contributions to the field of safety pharmacology were recently published detailing the use of electroencephalography (EEG) by telemetry in a critical role in the successful evaluation of a compound during drug development (1] Authier, Delatte, Kallman, Stevens & Markgraf; JPTM 2016; 81:274-285; 2] Accardi, Pugsley, Forster, Troncy, Huang & Authier; JPTM; 81: 47-59; 3] Bassett, Troncy, Pouliot, Paquette, Ascaha, & Authier; JPTM 2016; 70: 230-240). These authors present a convincing case for monitoring neocortical biopotential waveforms (EEG, ECoG, etc) during preclinical toxicology studies as an opportunity for early identification of a central nervous system (CNS) risk during Investigational New Drug (IND) Enabling Studies. This review is about "ictogenesis" not "epileptogenesis". It is intended to characterize overt behavioral and physiological changes suggestive of drug-induced neurotoxicity/ictogenesis in experimental animals during Tier 1 safety pharmacology testing, prior to first dose administration in man. It is the presence of these predictive or comorbid biomarkers expressed during the requisite conduct of daily clinical or cage side observations, and in early ICH S7A Tier I CNS, pulmonary and cardiovascular safety study designs that should initiate an early conversation regarding Tier II inclusion of EEG monitoring. We conclude that there is no single definitive clinical marker for seizure liability but plasma exposures might add to set proper safety margins when clinical convulsions are observed. Even the observation of a study-related full tonic-clonic convulsion does not establish solid ground to require the financial and temporal investment of a full EEG study under the current regulatory standards. For purposes of this review, we have adopted the FDA term "sponsor" as it refers to any person who takes the responsibility for and initiates a nonclinical investigations of new molecular entities; FDA uses the term "sponsor" primarily in relation to investigational new drug application submissions. Copyright © 2018. Published by Elsevier Inc.

Performance and brain electrical activity during prolonged confinement.

PubMed

Lorenz, B; Lorenz, J; Manzey, D

1996-01-01

A subset of the AGARD-STRES battery including memory search, unstable tracking, and a combination of both tasks (dual-task), was applied repeatedly to the four chamber crew members before, during, and after the 60-day isolation period of EXEMSI. Five ground control group members served as a control group. A subjective state questionnaire was also included. The results were subjected to a quantitative single-subject analysis. Electroencephalograms (EEG) were recorded to permit correlation of changes in task performance with changes in the physiological state. Evaluation of the EEG focused on spectral parameters of spontaneous EEG waves. No physiological data were collected from the control group. Significant decrements in tracking ability were observed in the chamber crew. The time course of these effects followed a triphasic pattern with initial deterioration, intermediate recovery to pre-isolation baseline scores after the first half of the isolation period, and a second deterioration towards the end. None of the control group subjects displayed such an effect. Memory search (speed and accuracy) was only occasionally impaired during isolation, but the control group displayed a similar pattern of changes. It is suggested that a state of decreased alertness causes tracking deterioration, which leads to a reduced efficiency of sustained cue utilization. The assumption of low alertness was further substantiated by higher fatigue ratings by the chamber crew compared to those of the control group. Analysis of the continuous EEG recordings revealed that only two subjects produced reliable alpha wave activity (8-12 Hz) over Pz and, to a much smaller extent, Fz-theta wave activity (5-7 Hz) during task performance. In both subjects Pz-alpha power decreased consistently under task conditions involving single-task and dual-task tracking. Fz-theta activity was increased more by single-task and dual-task memory search than by single-task tracking. The alpha attenuation appears to be associated with an increasing demand on perceptual cue utilization required by the tracking performance. In one subject marked attenuation of alpha power occurred during the first half of the confinement period, where he also scored the highest fatigue ratings. A striking increase in fronto-central theta activity was observed in the same subject after six weeks of isolation. The change was associated with an efficient rather than a degraded task performance, and a high rating of the item "concentrated" and a low rating of the item "fatigued." This finding supports the hypothesis that the activation state associated with increased fronto-central theta activity accompanies efficient performance of demanding mental tasks. The usefulness of standardized laboratory tasks as monitoring instruments is demonstrated by the direct comparability with results of studies obtained from other relevant research applications using the same tasks. The feasibility of a self-administered integrated psychophysiological assessment of the individual state was illustrated by the nearly complete collection of data. The large number of individual data collected over the entire period permitted application of quantitative single-subject analysis, allowing reliable determination of changes in the individual state in the course of time. It thus appears that this assessment technique can be adapted for in-flight monitoring of astronauts during prolonged spaceflights. Parallel EEG recording can provide relevant supplementary information for diagnosing the individual activation state associated with task performance. The existence of large individual differences in the generation of task-sensitive EEG rhythms forms an important issue for further studies.

Recent advances in intravenous anaesthesia.

PubMed

Sneyd, J R

2004-11-01

Efforts to develop new hypnotic compounds continue, although several have recently failed in development. Propofol has been reformulated in various presentations with and without preservatives. Pharmacokinetic and pharmacodynamic differences exist between some of these preparations, and it is currently unclear whether any have substantial advantages over the original presentation. The use of target-controlled infusion (TCI) has been extended to include paediatric anaesthesia and sedation. Application of TCI to remifentanil is now licensed. Linking of electroencephalogram (EEG) monitoring to TCI for closed-loop anaesthesia remains a research tool, although commercial development may follow. The availability of stereoisomer ketamine and improved understanding of its pharmacology have increased non-anaesthetic use of ketamine as an adjunct analgesic. It may be useful in subhypnotic doses for postsurgical patients with pain refractory to morphine administration.

Surgery in temporal lobe epilepsy patients without cranial MRI lateralization.

PubMed

Gomceli, Y B; Erdem, A; Bilir, E; Kutlu, G; Kurt, S; Erden, E; Karatas, A; Erbas, C; Serdaroglu, A

2006-03-01

High resolution MRI is very important in the evaluations of patients with intractable temporal lobe epilepsy in preoperative investigations. Morphologic abnormalities on cranial MRI usually indicate the epileptogenic focus. Intractable TLE patients who have normal cranial MRI or bilateral hippocampal atrophy may have a chance for surgery if a certain epileptogenic focus is determined. We evaluated the patients who were monitorized in Gazi University Medical Faculty Epilepsy Center from October 1997 to April 2004. Seventy three patients, who had a temporal epileptogenic focus, underwent anterior temporal lobectomy at Ankara University Medical Faculty Department of Neurosurgery. Twelve of them (16, 4%), did not have any localizing structural lesion on cranial MRI. Of the 12 patients examined 6 had normal findings and 6 had bilateral hippocampal atrophy. Of these 12 patients, 6 (50%) were women and 6 (50%) were men. The ages of patients ranged from 7 to 37 (mean: 24.5). Preoperatively long-term scalp video-EEG monitoring, cranial MRI, neuropsychological tests, and Wada test were applied in all patients. Five patients, whose investigations resulted in conflicting data, underwent invasive monitoring by the use of subdural strips. The seizure outcome of patients were classified according to Engel with postsurgical follow-up ranging from 11 to 52 (median: 35.7) months. Nine patients (75%) were classified into Engel's Class I and the other 3 patients (25%) were placed into Engel's Class II. One patient who was classified into Engel's Class II had additional psychiatric problems. The other patient had two different epileptogenic foci independent from each other in her ictal EEG. One of them localized in the right anterior temporal area, the other was in the right frontal lobe. She was classified in Engel's Class II and had no seizure originating from temporal epileptic focus, but few seizures originating from the frontal region continued after the surgery. In conclusion, surgery was successful in all 12 patients. We think that patients with no MRI lateralizing or localizing lesion should undergo epilepsy surgery after detailed presurgical evaluations, including invasive monitoring.

Role of EEG background activity, seizure burden and MRI in predicting neurodevelopmental outcome in full-term infants with hypoxic-ischaemic encephalopathy in the era of therapeutic hypothermia.

PubMed

Weeke, Lauren C; Boylan, Geraldine B; Pressler, Ronit M; Hallberg, Boubou; Blennow, Mats; Toet, Mona C; Groenendaal, Floris; de Vries, Linda S

2016-11-01

To investigate the role of EEG background activity, electrographic seizure burden, and MRI in predicting neurodevelopmental outcome in infants with hypoxic-ischaemic encephalopathy (HIE) in the era of therapeutic hypothermia. Twenty-six full-term infants with HIE (September 2011-September 2012), who had video-EEG monitoring during the first 72 h, an MRI performed within the first two weeks and neurodevelopmental assessment at two years were evaluated. EEG background activity at age 24, 36 and 48 h, seizure burden, and severity of brain injury on MRI, were compared and related to neurodevelopmental outcome. EEG background activity was significantly associated with neurodevelopmental outcome at 36 h (p = 0.009) and 48 h after birth (p = 0.029) and with severity of brain injury on MRI at 36 h (p = 0.002) and 48 h (p = 0.018). All infants with a high seizure burden and moderate-severe injury on MRI had an abnormal outcome. The positive predictive value (PPV) of EEG for abnormal outcome was 100% at 36 h and 48 h and the negative predictive value (NPV) was 75% at 36 h and 69% at 48 h. The PPV of MRI was 100% and the NPV 85%. The PPV of seizure burden was 78% and the NPV 71%. Severely abnormal EEG background activity at 36 h and 48 h after birth was associated with severe injury on MRI and abnormal neurodevelopmental outcome. High seizure burden was only associated with abnormal outcome in combination with moderate-severe injury on MRI. Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG

PubMed Central

Mullen, Tim R.; Kothe, Christian A.E.; Chi, Mike; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Jung, Tzyy-Ping; Cauwenberghs, Gert

2015-01-01

Goal We present and evaluate a wearable high-density dry electrode EEG system and an open-source software framework for online neuroimaging and state classification. Methods The system integrates a 64-channel dry EEG form-factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in 9 subjects using the dry EEG system. Results Simulations yielded high accuracy (AUC=0.97±0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity (sdDTF) was significantly above chance with similar performance (AUC) for cLORETA (0.74±0.09) and LCMV (0.72±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74±0.16) but significantly better for LCMV (0.82±0.12). Conclusion We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. Significance This paper is the first validated application of these methods to 64-channel dry EEG. The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes. PMID:26415149

Analysis of absence seizure generation using EEG spatial-temporal regularity measures.

PubMed

Mammone, Nadia; Labate, Domenico; Lay-Ekuakille, Aime; Morabito, Francesco C

2012-12-01

Epileptic seizures are thought to be generated and to evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruitment procedure ending with the crisis can be explored through a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG recordings based on the concept of permutation entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters' setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. According to the results here presented, it seems that the widely accepted model of "jump" transition to absence seizure should be in some cases coupled (or substituted) by a gradual transition model characteristic of self-organizing networks. Indeed, it appears that the transition to the epileptic status is heralded before the preictal state, ever since the interictal stages. As a matter of fact, within the limits of the analyzed database, the frontal-temporal scalp areas appear constantly associated to PE levels higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower PE values. The EEG of healthy subjects neither shows any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index.

PubMed

Babiloni, Claudio; Pennica, Alfredo; Del Percio, Claudio; Noce, Giuseppe; Cordone, Susanna; Muratori, Chiara; Ferracuti, Stefano; Donato, Nicole; Di Campli, Francesco; Gianserra, Laura; Teti, Elisabetta; Aceti, Antonio; Soricelli, Andrea; Viscione, Magdalena; Limatola, Cristina; Andreoni, Massimo; Onorati, Paolo

2016-03-01

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status. Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions. Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05). This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity. This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Action Monitoring Cortical Activity Coupled to Submovements

PubMed Central

Sobolewski, Aleksander

2017-01-01

Numerous studies have examined neural correlates of the human brain’s action-monitoring system during experimentally segmented tasks. However, it remains unknown how such a system operates during continuous motor output when no experimental time marker is available (such as button presses or stimulus onset). We set out to investigate the electrophysiological correlates of action monitoring when hand position has to be repeatedly monitored and corrected. For this, we recorded high-density electroencephalography (EEG) during a visuomotor tracking task during which participants had to follow a target with the mouse cursor along a visible trajectory. By decomposing hand kinematics into naturally occurring periodic submovements, we found an event-related potential (ERP) time-locked to these submovements and localized in a sensorimotor cortical network comprising the supplementary motor area (SMA) and the precentral gyrus. Critically, the amplitude of the ERP correlated with the deviation of the cursor, 110 ms before the submovement. Control analyses showed that this correlation was truly due to the cursor deviation and not to differences in submovement kinematics or to the visual content of the task. The ERP closely resembled those found in response to mismatch events in typical cognitive neuroscience experiments. Our results demonstrate the existence of a cortical process in the SMA, evaluating hand position in synchrony with submovements. These findings suggest a functional role of submovements in a sensorimotor loop of periodic monitoring and correction and generalize previous results from the field of action monitoring to cases where action has to be repeatedly monitored. PMID:29071301

Application of Tsallis Entropy to EEG: Quantifying the Presence of Burst Suppression After Asphyxial Cardiac Arrest in Rats

PubMed Central

Zhang, Dandan; Jia, Xiaofeng; Ding, Haiyan; Ye, Datian; Thakor, Nitish V.

2011-01-01

Burst suppression (BS) activity in EEG is clinically accepted as a marker of brain dysfunction or injury. Experimental studies in a rodent model of brain injury following asphyxial cardiac arrest (CA) show evidence of BS soon after resuscitation, appearing as a transitional recovery pattern between isoelectricity and continuous EEG. The EEG trends in such experiments suggest varying levels of uncertainty or randomness in the signals. To quantify the EEG data, Shannon entropy and Tsallis entropy (TsEn) are examined. More specifically, an entropy-based measure named TsEn area (TsEnA) is proposed to reveal the presence and the extent of development of BS following brain injury. The methodology of TsEnA and the selection of its parameter are elucidated in detail. To test the validity of this measure, 15 rats were subjected to 7 or 9 min of asphyxial CA. EEG recordings immediately after resuscitation from CA were investigated and characterized by TsEnA. The results show that TsEnA correlates well with the outcome assessed by evaluating the rodents after the experiments using a well-established neurological deficit score (Pearson correlation = 0.86, p ⪡ 0.01). This research shows that TsEnA reliably quantifies the complex dynamics in BS EEG, and may be useful as an experimental or clinical tool for objective estimation of the gravity of brain damage after CA. PMID:19695982

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications

PubMed Central

Stone, David B.; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications. PMID:29618975

Self-Adhesive and Capacitive Carbon Nanotube-Based Electrode to Record Electroencephalograph Signals From the Hairy Scalp.

PubMed

Lee, Seung Min; Kim, Jeong Hun; Park, Cheolsoo; Hwang, Ji-Young; Hong, Joung Sook; Lee, Kwang Ho; Lee, Sang Hoon

2016-01-01

We fabricated a carbon nanotube (CNT)/adhesive polydimethylsiloxane (aPDMS) composite-based dry electroencephalograph (EEG) electrode for capacitive measuring of EEG signals. As research related to brain-computer interface applications has advanced, the presence of hairs on a patient's scalp has continued to present an obstacle to recorder EEG signals using dry electrodes. The CNT/aPDMS electrode developed here is elastic, highly conductive, self-adhesive, and capable of making conformal contact with and attaching to a hairy scalp. Onto the conductive disk, hundreds of conductive pillars coated with Parylene C insulation layer were fabricated. A CNT/aPDMS layer was attached on the disk to transmit biosignals to the pillar. The top of disk was designed to be solderable, which enables the electrode to connect with a variety of commercial EEG acquisition systems. The mechanical and electrical characteristics of the electrode were tested, and the performances of the electrodes were evaluated by recording EEGs, including alpha rhythms, auditory-evoked potentials, and steady-state visually-evoked potentials. The results revealed that the electrode provided a high signal-to-noise ratio with good tolerance for motion. Almost no leakage current was observed. Although preamplifiers with ultrahigh input impedance have been essential for previous capacitive electrodes, the EEGs were recorded here by directly connecting a commercially available EEG acquisition system to the electrode to yield high-quality signals comparable to those obtained using conventional wet electrodes.

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications.

PubMed

Stone, David B; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications.

High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection.

PubMed

Ma, Junshui; Bayram, Sevinç; Tao, Peining; Svetnik, Vladimir

2011-03-15

After a review of the ocular artifact reduction literature, a high-throughput method designed to reduce the ocular artifacts in multichannel continuous EEG recordings acquired at clinical EEG laboratories worldwide is proposed. The proposed method belongs to the category of component-based methods, and does not rely on any electrooculography (EOG) signals. Based on a concept that all ocular artifact components exist in a signal component subspace, the method can uniformly handle all types of ocular artifacts, including eye-blinks, saccades, and other eye movements, by automatically identifying ocular components from decomposed signal components. This study also proposes an improved strategy to objectively and quantitatively evaluate artifact reduction methods. The evaluation strategy uses real EEG signals to synthesize realistic simulated datasets with different amounts of ocular artifacts. The simulated datasets enable us to objectively demonstrate that the proposed method outperforms some existing methods when no high-quality EOG signals are available. Moreover, the results of the simulated datasets improve our understanding of the involved signal decomposition algorithms, and provide us with insights into the inconsistency regarding the performance of different methods in the literature. The proposed method was also applied to two independent clinical EEG datasets involving 28 volunteers and over 1000 EEG recordings. This effort further confirms that the proposed method can effectively reduce ocular artifacts in large clinical EEG datasets in a high-throughput fashion. Copyright © 2011 Elsevier B.V. All rights reserved.

Cognitive Technologies for Teams 711HPW/RHCPT

DTIC Science & Technology

2010-09-01

robust physiological indices of team workload, with a particular interest in minimally invasive measures such as EEG, EOG , ECG eye movement data and...cerebral hemodynamics. Current research directions for the CTT program will be discussed. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17...collections of individuals TRACE Monitor 12 Cerebral Hemodynamics • Transcranial Doppler Sonography (TCD) – Utilizes ultrasound signals to monitor

Accuracy of Automatic Polysomnography Scoring Using Frontal Electrodes

PubMed Central

Younes, Magdy; Younes, Mark; Giannouli, Eleni

2016-01-01

Study Objectives: The economic cost of performing sleep monitoring at home is a major deterrent to adding sleep data during home studies for investigation of sleep apnea and to investigating non-respiratory sleep complaints. Michele Sleep Scoring System (MSS) is a validated automatic system that utilizes central electroencephalography (EEG) derivations and requires minimal editing. We wished to determine if MSS' accuracy is maintained if frontal derivations are used instead. If confirmed, home sleep monitoring would not require home setup or lengthy manual scoring by technologists. Methods: One hundred two polysomnograms (PSGs) previously recorded from patients with assorted sleep disorders were scored using MSS once with central and once with frontal derivations. Total sleep time, sleep/stage R sleep onset latencies, awake time, time in different sleep stages, arousal/awakening index and apnea-hypopnea index were compared. In addition, odds ratio product (ORP), a continuous index of sleep depth/quality (Sleep 2015;38:641–54), was generated for every 30-sec epoch in each PSG and epoch-by-epoch comparison of ORP was performed. Results: Intraclass correlation coefficients (ICCs) ranged from 0.89 to 1.0 for the various sleep variables (0.96 ± 0.03). For epoch-by-epoch comparisons of ORP, ICC was > 0.85 in 96 PSGs. Lower values in the other six PSGs were related to signal artifacts in either derivation. ICC for whole-record average ORP was 0.98. Conclusions: MSS is as accurate with frontal as with central EEG derivations. The use of frontal electrodes along with MSS should make it possible to obtain high-quality sleep data without requiring home setup or lengthy scoring time by expert technologists. Citation: Younes M, Younes M, Giannouli E. Accuracy of automatic polysomnography scoring using frontal electrodes. J Clin Sleep Med 2016;12(5):735–746. PMID:26951417

Revised version of quality guidelines for presurgical epilepsy evaluation and surgical epilepsy therapy issued by the Austrian, German, and Swiss working group on presurgical epilepsy diagnosis and operative epilepsy treatment.

PubMed

Rosenow, Felix; Bast, Thomas; Czech, Thomas; Feucht, Martha; Hans, Volkmar H; Helmstaedter, Christoph; Huppertz, Hans-Jürgen; Noachtar, Soheyl; Oltmanns, Frank; Polster, Tilman; Seeck, Margitta; Trinka, Eugen; Wagner, Kathrin; Strzelczyk, Adam

2016-08-01

The definition of minimal standards remains pivotal as a basis for a high standard of care and as a basis for staff allocation or reimbursement. Only limited publications are available regarding the required staffing or methodologic expertise in epilepsy centers. The executive board of the working group (WG) on presurgical epilepsy diagnosis and operative epilepsy treatment published the first guidelines in 2000 for Austria, Germany, and Switzerland. In 2014, revised guidelines were published and the WG decided to publish an unaltered English translation in this report. Because epilepsy surgery is an elective procedure, quality standards are particularly high. As detailed in the first edition of these guidelines, quality control relates to seven different domains: (1) establishing centers with a sufficient number of sufficiently and specifically trained personnel, (2) minimum technical standards and equipment, (3) continuous medical education of employees, (4) surveillance by trained personnel during video electroencephalography (EEG) monitoring (VEM), (5) systematic acquisition of clinical and outcome data, (6) the minimum number of preoperative evaluations and epilepsy surgery procedures, and (7) the cooperation of epilepsy centers. These standards required the certification of the different professions involved and minimum numbers of procedures. In the subsequent decade, quite a number of colleagues were certified by the trinational WG; therefore, the executive board of the WG decided in 2013 to make these standards obligatory. This revised version is particularly relevant given that the German procedure classification explicitly refers to the guidelines of the WG with regard to noninvasive/invasive preoperative video-EEG monitoring and invasive intraoperative diagnostics in epilepsy. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

What it means to be Zen: Marked modulations of local and interareal synchronization during open monitoring meditation

PubMed Central

Hauswald, Anne; Übelacker, Teresa; Leske, Sabine; Weisz, Nathan

2015-01-01

Experienced meditators are able to voluntarily modulate their state of consciousness and attention. In the present study, we took advantage of this ability and studied brain activity related to the shift of mental state. Electrophysiological activity, i.e. EEG, was recorded from 11 subjects with varying degrees of meditation experience during Zen meditation (a form of open monitoring meditation) and during non-meditation rest. On a behavioral level, mindfulness scores were assessed using the Mindfulness Attention and Awareness Scale (MAAS). Analysis of EEG source power revealed the so far unreported finding that MAAS scores significantly correlated with gamma power (30–250 Hz), particularly high-frequency gamma (100–245 Hz), during meditation. High levels of mindfulness were related to increased high-frequency gamma, for example, in the cingulate cortex and somatosensory cortices. Further, we analyzed the relationship between connectivity during meditation and self-reported mindfulness (MAAS). We found a correlation between graph measures in the 160–170 Hz range and MAAS scores. Higher levels of mindfulness were related to lower small worldedness as well as global and local clustering in paracentral, insular, and thalamic regions during meditation. In sum, the present study shows significant relationships of mindfulness and brain activity during meditation indicated by measures of oscillatory power and graph theoretical measures. The most prominent effects occur in brain structures crucially involved in processes of awareness and attention, which also show structural changes in short- and long-term meditators, suggesting continuative alterations in the meditating brain. Overall, our study reveals strong changes in ongoing oscillatory activity as well as connectivity patterns that appear to be sensitive to the psychological state changes induced by Zen meditation. PMID:25562827

What it means to be Zen: marked modulations of local and interareal synchronization during open monitoring meditation.

PubMed

Hauswald, Anne; Übelacker, Teresa; Leske, Sabine; Weisz, Nathan

2015-03-01

Experienced meditators are able to voluntarily modulate their state of consciousness and attention. In the present study, we took advantage of this ability and studied brain activity related to the shift of mental state. Electrophysiological activity, i.e. EEG, was recorded from 11 subjects with varying degrees of meditation experience during Zen meditation (a form of open monitoring meditation) and during non-meditation rest. On a behavioral level, mindfulness scores were assessed using the Mindfulness Attention and Awareness Scale (MAAS). Analysis of EEG source power revealed the so far unreported finding that MAAS scores significantly correlated with gamma power (30-250Hz), particularly high-frequency gamma (100-245Hz), during meditation. High levels of mindfulness were related to increased high-frequency gamma, for example, in the cingulate cortex and somatosensory cortices. Further, we analyzed the relationship between connectivity during meditation and self-reported mindfulness (MAAS). We found a correlation between graph measures in the 160-170Hz range and MAAS scores. Higher levels of mindfulness were related to lower small worldedness as well as global and local clustering in paracentral, insular, and thalamic regions during meditation. In sum, the present study shows significant relationships of mindfulness and brain activity during meditation indicated by measures of oscillatory power and graph theoretical measures. The most prominent effects occur in brain structures crucially involved in processes of awareness and attention, which also show structural changes in short- and long-term meditators, suggesting continuative alterations in the meditating brain. Overall, our study reveals strong changes in ongoing oscillatory activity as well as connectivity patterns that appear to be sensitive to the psychological state changes induced by Zen meditation. Copyright © 2015. Published by Elsevier Inc.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers

PubMed Central

Yücel, Meryem A.; Selb, Juliette; Boas, David A.; Cash, Sydney S.; Cooper, Robert J.

2013-01-01

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90 % and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case. PMID:23796546

Mechanism and Therapy for the Shared Susceptibility to Migraine and Epilepsy after Traumatic Brain Injury (TBI)

DTIC Science & Technology

2013-10-01

injured mice. Nine hours post-injury, one mouse developed status epilepticus (Figure 1) which continued for 3 days resulting in the animal’s death...seizures per day. 6 Figure 1: Electrographic recording of a CCI-injured mouse in status epilepticus . Upper trace is an EEG recording of...4 h of status epilepticus while the lower traces represent portions of the EEG within the dashed boxes at an expanded timescale. The recordings

Scale-Free Music of the Brain

PubMed Central

Wu, Dan; Li, Chao-Yi; Yao, De-Zhong

2009-01-01

Background There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG. Methodology/Principal Findings In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG) waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner's law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS). The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(κ = 0.800, P<0.001). We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners. Conclusions/Significance The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy. PMID:19526057

Effects of tramadol or morphine in dogs undergoing castration on intra-operative electroencephalogram responses and post-operative pain.

PubMed

Kongara, K; Chambers, J P; Johnson, C B; Dukkipati, V S R

2013-11-01

To compare the effects of pre-operatively administered tramadol with those of morphine on electroencephalographic responses to surgery and post-operative pain in dogs undergoing castration. Dogs undergoing castration were treated with either pre-operative morphine (0.5 mg/kg S/C, n = 8) or tramadol (3 mg/kg S/C, n = 8). All dogs also received 0.05 mg/kg acepromazine and 0.04 mg/kg atropine S/C in addition to the test analgesic. Anaesthesia was induced with thiopentone administered I/V to effect and maintained with halothane in oxygen. Respiratory rate, heart rate, end-tidal halothane tension (EtHal) and end-tidal CO2 tension (EtCO2) were monitored throughout surgery. Electroencephalograms (EEG) were recorded continuously using a three electrode montage. Median frequency (F50), total power (Ptot) and 95% spectral edge frequency (F95) derived from EEG power spectra recorded before skin incision (baseline) were compared with those recorded during ligation of the spermatic cords of both testicles. Post-operatively, pain was assessed after 1, 3, 6 and 9 h using the short form of the Glasgow composite measure pain scale (CMPS-SF). Dogs premedicated with tramadol had higher mean F50 (12.2 (SD 0.2) Hz) and lower Ptot (130.39 (SD 12.1) µv(2)) compared with those premedicated with morphine (11.5 (SD 0.2) Hz and 161.8 (SD 15.1) µv(2), respectively; p<0.05) during ligation of testicle 1. There were no differences in EEG responses between the two treatment groups during ligation of testicle 2 (p>0.05). The F95 of the EEG did not differ between the two groups during the ligation of either testicle (p > 0.05). Post-operatively, no significant differences in the CMPS-SF score were found between animals premedicated with tramadol and morphine at any time during the post-operative period. No dog required rescue analgesia. Tramadol and morphine administered pre-operatively provided a similar degree of post-operative analgesia in male dogs at the doses tested.

Dynamic goal states: adjusting cognitive control without conflict monitoring.

PubMed

Scherbaum, Stefan; Dshemuchadse, Maja; Ruge, Hannes; Goschke, Thomas

2012-10-15

A central topic in the cognitive sciences is how cognitive control is adjusted flexibly to changing environmental demands at different time scales to produce goal-oriented behavior. According to an influential account, the context-sensitive recruitment of cognitive control is mediated by a specialized conflict monitoring process that registers current conflict and signals the demand for enhanced control in subsequent trials. This view has been immensely successful not least due to supporting evidence from neuroimaging studies suggesting that the conflict monitoring function is localized within the anterior cingulate cortex (ACC) which, in turn, signals the demand for enhanced control to the prefrontal cortex (PFC). In this article, we propose an alternative model of the adaptive regulation of cognitive control based on multistable goal attractor network dynamics and adjustments of cognitive control within a conflict trial. Without incorporation of an explicit conflict monitoring module, the model mirrors behavior in conflict tasks accounting for effects of response congruency, sequential conflict adaptation, and proportion of incongruent trials. Importantly, the model also mirrors frequency tagged EEG data indicating continuous conflict adaptation and suggests a reinterpretation of the correlation between ACC and the PFC BOLD data reported in previous imaging studies. Together, our simulation data propose an alternative interpretation of both behavioral data as well as imaging data that have previously been interpreted in favor of a specialized conflict monitoring process in the ACC. Copyright © 2012 Elsevier Inc. All rights reserved.

Electroencephalographic inverse localization of brain activity in acute traumatic brain injury as a guide to surgery, monitoring and treatment

PubMed Central

Irimia, Andrei; Goh, S.-Y. Matthew; Torgerson, Carinna M.; Stein, Nathan R.; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.

2013-01-01

Objective To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Methods Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. Results We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Conclusion Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. PMID:24011495

Multichannel wearable system dedicated for simultaneous electroencephalography/near-infrared spectroscopy real-time data acquisitions

NASA Astrophysics Data System (ADS)

Lareau, Etienne; Lesage, Frederic; Pouliot, Philippe; Nguyen, Dang; Le Lan, Jerome; Sawan, Mohamad

2011-09-01

Functional neuroimaging is becoming a valuable tool in cognitive research and clinical applications. The clinical context brings specific constraints that include the requirement of a high channel count to cover the whole head, high sensitivity for single event detection, and portability for long-term bedside monitoring. For epilepsy and stroke monitoring, the combination of electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) is expected to provide useful clinical information, and efforts have been deployed to create prototypes able to simultaneously acquire both measurement modalities. However, to the best of our knowledge, existing systems lack portability, NIRS sensitivity, or have low channel count. We present a battery-powered, portable system with potentially up to 32 EEG channels, 32 NIRS light sources, and 32 detectors. Avalanche photodiodes allow for high NIRS sensitivity and the autonomy of the system is over 24 h. A reduced channel count prototype with 8 EEG channels, 8 sources, and 8 detectors was tested on phantoms. Further validation was done on five healthy adults using a visual stimulation protocol to detect local hemodynamic changes and visually evoked potentials. Results show good concordance with literature regarding functional activations and suggest sufficient performance for clinical use, provided some minor adjustments were made.

Electroencephalographic inverse localization of brain activity in acute traumatic brain injury as a guide to surgery, monitoring and treatment.

PubMed

Irimia, Andrei; Goh, S-Y Matthew; Torgerson, Carinna M; Stein, Nathan R; Chambers, Micah C; Vespa, Paul M; Van Horn, John D

2013-10-01

To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. Published by Elsevier B.V.

Recording of amplitude-integrated electroencephalography, oxygen saturation, pulse rate, and cerebral blood flow during massage of premature infants.

PubMed

Rudnicki, Jacek; Boberski, Marek; Butrymowicz, Ewa; Niedbalski, Paweł; Ogniewski, Paweł; Niedbalski, Marek; Niedbalski, Zbigniew; Podraza, Wojciech; Podraza, Hanna

2012-08-01

Stimulation of the nervous system plays an important role in brain function and psychomotor development of children. Massage can benefit premature infants, but has limitations. The authors conducted a study to verify the direct effects of massage on amplitude-integrated electroencephalography (aEEG), oxygen saturation (SaO(2)), and pulse analyzed by color cerebral function monitor (CCFM) and cerebral blood flow assessed by the Doppler technique. The amplitude of the aEEG trend during massage significantly increased. Massage also impacted the dominant frequency δ waves. Frequency significantly increased during the massage and return to baseline after treatment. SaO(2) significantly decreased during massage. In four premature infants, massage was discontinued due to desaturation below 85%. Pulse frequency during the massage decreased but remained within physiological limits of greater than 100 beats per minute in all infants. Doppler flow values in the anterior cerebral artery measured before and after massage did not show statistically significant changes. Resistance index after massage decreased, which might provide greater perfusion of the brain, but this difference was not statistically significant. Use of the CCFM device allows for monitoring of three basic physiologic functions, namely aEEG, SaO(2), and pulse, and increases the safety of massage in preterm infants. Copyright © 2012 by Thieme Medical Publishers

The study of evolution and depression of the alpha-rhythm in the human brain EEG by means of wavelet-based methods

NASA Astrophysics Data System (ADS)

Runnova, A. E.; Zhuravlev, M. O.; Khramova, M. V.; Pysarchik, A. N.

2017-04-01

We study the appearance, development and depression of the alpha-rhythm in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. The new method based on continuous wavelet transform allows to estimate the energy contribution of various components, including the alpha rhythm, in the general dynamics of the electrical activity of the projections of various areas of the brain. The decision-making process by observe ambiguous images is characterized by specific oscillatory alfa-rhytm patterns in the multi-channel EEG data. We have shown the repeatability of detected principles of the alpha-rhythm evolution in a data of group of 12 healthy male volunteers.

Electroencephalography leads placed by nontechnologists using a template system produce signals equal in quality to technologist-applied, collodion disk leads.

PubMed

Kolls, Brad J; Olson, Daiwai M; Gallentine, William B; Skeen, Mark B; Skidmore, Christopher T; Sinha, Saurabh R

2012-02-01

The purpose of this study was to compare the quality of the electroencephalographic (EEG) data obtained with a BraiNet template in a practical use setting, to that obtained with standard 10/20 spaced, technologist-applied, collodion-based disk leads. Pairs of 8-hour blocks of EEG data were prospectively collected from 32 patients with a Glasgow coma score of ≤9 and clinical concern for underlying nonconvulsive status epilepticus over a 6-month period in the Neurocritical Care Unit at the Duke University Medical Center. The studies were initiated with the BraiNet template system applied by critical care nurse practitioners or physicians, followed by standard, collodion leads applied by registered technologists using the 10/20 system of placement. Impedances were measured at the beginning and end of each block recorded and variance in impedance, mean impedance, and the largest differences in impedances found within a given lead set were compared. Physicians experienced in reading EEG performed a masked review of the EEG segments obtained to assess the subjective quality of the recordings obtained with the templates. We found no clinically significant differences in the impedance measures. There was a 3-hour reduction in the time required to initiate EEG recording using the templates (P < 0.001). There was no difference in the overall subjective quality distributions for template-applied versus technologist-applied EEG leads. The templates were also found to be well accepted by the primary users in the intensive care unit. The findings suggest that the EEG data obtained with this approach are comparable with that obtained by registered technologist-applied leads and represents a possible solution to the growing clinical need for continuous EEG recording availability in the critical care setting.

Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia.

PubMed

Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg

2014-09-01

Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.

Utility of CT-compatible EEG electrodes in critically ill children.

PubMed

Abend, Nicholas S; Dlugos, Dennis J; Zhu, Xiaowei; Schwartz, Erin S

2015-04-01

Electroencephalographic monitoring is being used with increasing frequency in critically ill children who may require frequent and sometimes urgent brain CT scans. Standard metallic disk EEG electrodes commonly produce substantial imaging artifact, and they must be removed and later reapplied when CT scans are indicated. To determine whether conductive plastic electrodes caused artifact that limited CT interpretation. We describe a retrospective cohort of 13 consecutive critically ill children who underwent 17 CT scans with conductive plastic electrodes during 1 year. CT images were evaluated by a pediatric neuroradiologist for artifact presence, type and severity. All CT scans had excellent quality images without artifact that impaired CT interpretation except for one scan in which improper wire placement resulted in artifact. Conductive plastic electrodes do not cause artifact limiting CT scan interpretation and may be used in critically ill children to permit concurrent electroencephalographic monitoring and CT imaging.

Influence of biophase distribution and P-glycoprotein interaction on pharmacokinetic-pharmacodynamic modelling of the effects of morphine on the EEG

PubMed Central

Groenendaal, D; Freijer, J; de Mik, D; Bouw, M R; Danhof, M; de Lange, E C M

2007-01-01

Background and purpose: The aim was to investigate the influence of biophase distribution including P-glycoprotein (Pgp) function on the pharmacokinetic-pharmacodynamic correlations of morphine's actions in rat brain. Experimental approach: Male rats received a 10-min infusion of morphine as 4 mg kg−1, combined with a continuous infusion of the Pgp inhibitor GF120918 or vehicle, 10 or 40 mg kg−1. EEG signals were recorded continuously and blood samples were collected. Key results: Profound hysteresis was observed between morphine blood concentrations and effects on the EEG. Only the termination of the EEG effect was influenced by GF120918. Biophase distribution was best described with an extended catenary biophase distribution model, with a sequential transfer and effect compartment. The rate constant for transport through the transfer compartment (k1e) was 0.038 min−1, being unaffected by GF120918. In contrast, the rate constant for the loss from the effect compartment (keo) decreased 60% after GF120918. The EEG effect was directly related to concentrations in the effect compartment using the sigmoidal Emax model. The values of the pharmacodynamic parameters E0, Emax, EC50 and Hill factor were 45.0 μV, 44.5 μV, 451 ng ml−1 and 2.3, respectively. Conclusions and implications: The effects of GF120918 on the distribution kinetics of morphine in the effect compartment were consistent with the distribution in brain extracellular fluid (ECF) as estimated by intracerebral microdialysis. However, the time-course of morphine concentrations at the site of action in the brain, as deduced from the biophase model, is distinctly different from the brain ECF concentrations. PMID:17471181

[An Electroencephalogram-driven Personalized Affective Music Player System: Algorithms and Preliminary Implementation].

PubMed

Ma, Yong; Li, Juan; Lu, Bin

2016-02-01

In order to monitor the emotional state changes of audience on real-time and to adjust the music playlist, we proposed an algorithm framework of an electroencephalogram (EEG) driven personalized affective music recommendation system based on the portable dry electrode shown in this paper. We also further finished a preliminary implementation on the Android platform. We used a two-dimensional emotional model of arousal and valence as the reference, and mapped the EEG data and the corresponding seed songs to the emotional coordinate quadrant in order to establish the matching relationship. Then, Mel frequency cepstrum coefficients were applied to evaluate the similarity between the seed songs and the songs in music library. In the end, during the music playing state, we used the EEG data to identify the audience's emotional state, and played and adjusted the corresponding song playlist based on the established matching relationship.

Classifying Drivers' Cognitive Load Using EEG Signals.

PubMed

Barua, Shaibal; Ahmed, Mobyen Uddin; Begum, Shahina

2017-01-01

A growing traffic safety issue is the effect of cognitive loading activities on traffic safety and driving performance. To monitor drivers' mental state, understanding cognitive load is important since while driving, performing cognitively loading secondary tasks, for example talking on the phone, can affect the performance in the primary task, i.e. driving. Electroencephalography (EEG) is one of the reliable measures of cognitive load that can detect the changes in instantaneous load and effect of cognitively loading secondary task. In this driving simulator study, 1-back task is carried out while the driver performs three different simulated driving scenarios. This paper presents an EEG based approach to classify a drivers' level of cognitive load using Case-Based Reasoning (CBR). The results show that for each individual scenario as well as using data combined from the different scenarios, CBR based system achieved approximately over 70% of classification accuracy.

The standardization debate: A conflation trap in critical care electroencephalography

PubMed Central

Ng, Marcus C.; Gaspard, Nicolas; Cole, Andrew J.; Hoch, Daniel B.; Cash, Sydney S.; Bianchi, Matt; O’Rourke, Deirdre A.; Rosenthal, Eric S.; Chu, Catherine J.; Westover, M. Brandon

2015-01-01

Purpose Persistent uncertainty over the clinical significance of various pathological continuous electroencephalography (cEEG) findings in the intensive care unit (ICU) has prompted efforts to standardize ICU cEEG terminology and an ensuing debate. We set out to understand the reasons for, and a satisfactory resolution to, this debate. Method We review the positions for and against standardization, and examine their deeper philosophical basis. Results We find that the positions for and against standardization are not fundamentally irreconcilable. Rather, both positions stem from conflating the three cardinal steps in the classic approach to EEG, which we term “description”, “interpretation”, and “prescription”. Using real-world examples we show how this conflation yields muddled clinical reasoning and unproductive debate among electroencephalographers that is translated into confusion among treating clinicians. We propose a middle way that judiciously uses both standardized terminology and clinical reasoning to disentangle these critical steps and apply them in proper sequence. Conclusion The systematic approach to ICU cEEG findings presented herein not only resolves the standardization debate but also clarifies clinical reasoning by helping electroencephalographers assign appropriate weights to cEEG findings in the face of uncertainty. PMID:25457454

Neurophysiological basis of creativity in healthy elderly people: a multiscale entropy approach.

PubMed

Ueno, Kanji; Takahashi, Tetsuya; Takahashi, Koichi; Mizukami, Kimiko; Tanaka, Yuji; Wada, Yuji

2015-03-01

Creativity, which presumably involves various connections within and across different neural networks, reportedly underpins the mental well-being of older adults. Multiscale entropy (MSE) can characterize the complexity inherent in EEG dynamics with multiple temporal scales. It can therefore provide useful insight into neural networks. Given that background, we sought to clarify the neurophysiological bases of creativity in healthy elderly subjects by assessing EEG complexity with MSE, with emphasis on assessment of neural networks. We recorded resting state EEG of 20 healthy elderly subjects. MSE was calculated for each subject for continuous 20-s epochs. Their relevance to individual creativity was examined concurrently with intellectual function. Higher individual creativity was linked closely to increased EEG complexity across higher temporal scales, but no significant relation was found with intellectual function (IQ score). Considering the general "loss of complexity" theory of aging, our finding of increased EEG complexity in elderly people with heightened creativity supports the idea that creativity is associated with activated neural networks. Results reported here underscore the potential usefulness of MSE analysis for characterizing the neurophysiological bases of elderly people with heightened creativity. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The standardization debate: A conflation trap in critical care electroencephalography.

PubMed

Ng, Marcus C; Gaspard, Nicolas; Cole, Andrew J; Hoch, Daniel B; Cash, Sydney S; Bianchi, Matt; O'Rourke, Deirdre A; Rosenthal, Eric S; Chu, Catherine J; Westover, M Brandon

2015-01-01

Persistent uncertainty over the clinical significance of various pathological continuous electroencephalography (cEEG) findings in the intensive care unit (ICU) has prompted efforts to standardize ICU cEEG terminology and an ensuing debate. We set out to understand the reasons for, and a satisfactory resolution to, this debate. We review the positions for and against standardization, and examine their deeper philosophical basis. We find that the positions for and against standardization are not fundamentally irreconcilable. Rather, both positions stem from conflating the three cardinal steps in the classic approach to EEG, which we term "description", "interpretation", and "prescription". Using real-world examples we show how this conflation yields muddled clinical reasoning and unproductive debate among electroencephalographers that is translated into confusion among treating clinicians. We propose a middle way that judiciously uses both standardized terminology and clinical reasoning to disentangle these critical steps and apply them in proper sequence. The systematic approach to ICU cEEG findings presented herein not only resolves the standardization debate but also clarifies clinical reasoning by helping electroencephalographers assign appropriate weights to cEEG findings in the face of uncertainty. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The human brain pacemaker: Synchronized infra-slow neurovascular coupling in patients undergoing non-pulsatile cardiopulmonary bypass.

PubMed

Zanatta, Paolo; Toffolo, Gianna Maria; Sartori, Elisa; Bet, Anna; Baldanzi, Fabrizio; Agarwal, Nivedita; Golanov, Eugene

2013-05-15

In non-pulsatile cardiopulmonary bypass surgery, middle cerebral artery blood flow velocity (BFV) is characterized by infra-slow oscillations of approximately 0.06Hz, which are paralleled by changes in total EEG power variability (EEG-PV), measured in 2s intervals. Since the origin of these BFV oscillations is not known, we explored their possible causative relationships with oscillations in EEG-PV at around 0.06Hz. We monitored 28 patients undergoing non-pulsatile cardiopulmonary bypass using transcranial Doppler sonography and scalp electroencephalography at two levels of anesthesia, deep (prevalence of burst suppression rhythm) and moderate (prevalence of theta rhythm). Under deep anesthesia, the EEG bursts suppression pattern was highly correlative with BFV oscillations. Hence, a detailed quantitative picture of the coupling between electrical brain activity and BFV was derived, both in deep and moderate anesthesia, via linear and non linear processing of EEG-PV and BFV signals, resorting to widely used measures of signal coupling such as frequency of oscillations, coherence, Granger causality and cross-approximate entropy. Results strongly suggest the existence of coupling between EEG-PV and BFV. In moderate anesthesia EEG-PV mean dominant frequency is similar to frequency of BFV oscillations (0.065±0.010Hz vs 0.045±0.019Hz); coherence between the two signals was significant in about 55% of subjects, and the Granger causality suggested an EEG-PV→BFV causal effect direction. The strength of the coupling increased with deepening anesthesia, as EEG-PV oscillations mean dominant frequency virtually coincided with the BFV peak frequency (0.062±0.017Hz vs 0.060±0.024Hz), and coherence became significant in a larger number (65%) of subjects. Cross-approximate entropy decreased significantly from moderate to deep anesthesia, indicating a higher level of synchrony between the two signals. Presence of a subcortical brain pacemaker that drives vascular infra-slow oscillations in the brain is proposed. These findings allow to suggest an original hypothesis explaining the mechanism underlying infra-slow neurovascular coupling. Copyright © 2013 Elsevier Inc. All rights reserved.

Fabrication of a Micro-Needle Array Electrode by Thermal Drawing for Bio-Signals Monitoring

PubMed Central

Ren, Lei; Jiang, Qing; Chen, Keyun; Chen, Zhipeng; Pan, Chengfeng; Jiang, Lelun

2016-01-01

A novel micro-needle array electrode (MAE) fabricated by thermal drawing and coated with Ti/Au film was proposed for bio-signals monitoring. A simple and effective setup was employed to form glassy-state poly (lactic-co-glycolic acid) (PLGA) into a micro-needle array (MA) by the thermal drawing method. The MA was composed of 6 × 6 micro-needles with an average height of about 500 μm. Electrode-skin interface impedance (EII) was recorded as the insertion force was applied on the MAE. The insertion process of the MAE was also simulated by the finite element method. Results showed that MAE could insert into skin with a relatively low compression force and maintain stable contact impedance between the MAE and skin. Bio-signals, including electromyography (EMG), electrocardiography (ECG), and electroencephalograph (EEG) were also collected. Test results showed that the MAE could record EMG, ECG, and EEG signals with good fidelity in shape and amplitude in comparison with the commercial Ag/AgCl electrodes, which proves that MAE is an alternative electrode for bio-signals monitoring. PMID:27322278

Fabrication of a Micro-Needle Array Electrode by Thermal Drawing for Bio-Signals Monitoring.

PubMed

Ren, Lei; Jiang, Qing; Chen, Keyun; Chen, Zhipeng; Pan, Chengfeng; Jiang, Lelun

2016-06-17

A novel micro-needle array electrode (MAE) fabricated by thermal drawing and coated with Ti/Au film was proposed for bio-signals monitoring. A simple and effective setup was employed to form glassy-state poly (lactic-co-glycolic acid) (PLGA) into a micro-needle array (MA) by the thermal drawing method. The MA was composed of 6 × 6 micro-needles with an average height of about 500 μm. Electrode-skin interface impedance (EII) was recorded as the insertion force was applied on the MAE. The insertion process of the MAE was also simulated by the finite element method. Results showed that MAE could insert into skin with a relatively low compression force and maintain stable contact impedance between the MAE and skin. Bio-signals, including electromyography (EMG), electrocardiography (ECG), and electroencephalograph (EEG) were also collected. Test results showed that the MAE could record EMG, ECG, and EEG signals with good fidelity in shape and amplitude in comparison with the commercial Ag/AgCl electrodes, which proves that MAE is an alternative electrode for bio-signals monitoring.

Encephalopathy with status epilepticus during sleep (ESES) induced by oxcarbazepine in idiopathic focal epilepsy in childhood

PubMed Central

Pavlidis, Elena; Rubboli, Guido; Nikanorova, Marina; Kölmel, Margarethe Sophie; Gardella, Elena

2015-01-01

Summary Encephalopathy with status epilepticus during sleep (ESES) is an age-related disorder characterized by neuropsychological regression, epilepsy and a typical EEG pattern of continuous epileptiform activity (> 85%) during NREM sleep. Cases of worsening or induction of ESES with phenytoin, carbamazepine and phenobarbital have been reported. We describe a child with benign epilepsy with centrotemporal spikes (BECTS) in whom treatment with oxcarbazepine (OXC) induced ESES. The patient was studied through repeated clinical-neuropsychological evaluations and 24-hour EEG recordings. He was treated with OXC two months after epilepsy onset. One month after starting OXC, he developed an abrupt and severe cognitive deterioration. A 24-hour EEG and neuropsychological tests showed an electro-clinical picture compatible with ESES. Withdrawal of OXC and introduction of other drugs were followed by a prompt improvement. Five months after ESES onset, a 24-hour EEG was normal. Our report indicates that OXC can induce ESES in BECTS. PMID:26415787

Time-frequency analysis of band-limited EEG with BMFLC and Kalman filter for BCI applications

PubMed Central

2013-01-01

Background Time-Frequency analysis of electroencephalogram (EEG) during different mental tasks received significant attention. As EEG is non-stationary, time-frequency analysis is essential to analyze brain states during different mental tasks. Further, the time-frequency information of EEG signal can be used as a feature for classification in brain-computer interface (BCI) applications. Methods To accurately model the EEG, band-limited multiple Fourier linear combiner (BMFLC), a linear combination of truncated multiple Fourier series models is employed. A state-space model for BMFLC in combination with Kalman filter/smoother is developed to obtain accurate adaptive estimation. By virtue of construction, BMFLC with Kalman filter/smoother provides accurate time-frequency decomposition of the bandlimited signal. Results The proposed method is computationally fast and is suitable for real-time BCI applications. To evaluate the proposed algorithm, a comparison with short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for both synthesized and real EEG data is performed in this paper. The proposed method is applied to BCI Competition data IV for ERD detection in comparison with existing methods. Conclusions Results show that the proposed algorithm can provide optimal time-frequency resolution as compared to STFT and CWT. For ERD detection, BMFLC-KF outperforms STFT and BMFLC-KS in real-time applicability with low computational requirement. PMID:24274109

Continuous detection of the self-initiated walking pre-movement state from EEG correlates without session-to-session recalibration

NASA Astrophysics Data System (ADS)

Ioana Sburlea, Andreea; Montesano, Luis; Minguez, Javier

2015-06-01

Objective. Brain-computer interfaces (BCI) as a rehabilitation tool have been used to restore functions in patients with motor impairments by actively involving the central nervous system and triggering prosthetic devices according to the detected pre-movement state. However, since EEG signals are highly variable between subjects and recording sessions, typically a BCI is calibrated at the beginning of each session. This process is inconvenient especially for patients suffering locomotor disabilities in maintaining a bipedal position for a longer time. This paper presents a continuous EEG decoder of a pre-movement state in self-initiated walking and the usage of this decoder from session to session without recalibrating. Approach. Ten healthy subjects performed a self-initiated walking task during three sessions, with an intersession interval of one week. The implementation of our continuous decoder is based on the combination of movement-related cortical potential (MRCP) and event-related desynchronization (ERD) features with sparse classification models. Main results. During intrasession our technique detects the pre-movement state with 70% accuracy. Moreover this decoder can be applied from session to session without recalibration, with a decrease in performance of about 4% on a one- or two-week intersession interval. Significance. Our detection model operates in a continuous manner, which makes it a straightforward asset for rehabilitation scenarios. By using both temporal and spectral information we attained higher detection rates than the ones obtained with the MRCP and ERD detection models, both during the intrasession and intersession conditions.

Quantitative EEG Metrics Differ Between Outcome Groups and Change Over the First 72 h in Comatose Cardiac Arrest Patients.

PubMed

Wiley, Sara Leingang; Razavi, Babak; Krishnamohan, Prashanth; Mlynash, Michael; Eyngorn, Irina; Meador, Kimford J; Hirsch, Karen G

2018-02-01

Forty to sixty-six percent of patients resuscitated from cardiac arrest remain comatose, and historic outcome predictors are unreliable. Quantitative spectral analysis of continuous electroencephalography (cEEG) may differ between patients with good and poor outcomes. Consecutive patients with post-cardiac arrest hypoxic-ischemic coma undergoing cEEG were enrolled. Spectral analysis was conducted on artifact-free contiguous 5-min cEEG epochs from each hour. Whole band (1-30 Hz), delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (β, 13-30 Hz), α/δ power ratio, percent suppression, and variability were calculated and correlated with outcome. Graphical patterns of quantitative EEG (qEEG) were described and categorized as correlating with outcome. Clinical outcome was dichotomized, with good neurologic outcome being consciousness recovery. Ten subjects with a mean age = 50 yrs (range = 18-65) were analyzed. There were significant differences in total power (3.50 [3.30-4.06] vs. 0.68 [0.52-1.02], p = 0.01), alpha power (1.39 [0.66-1.79] vs 0.27 [0.17-0.48], p < 0.05), delta power (2.78 [2.21-3.01] vs 0.55 [0.38-0.83], p = 0.01), percent suppression (0.66 [0.02-2.42] vs 73.4 [48.0-97.5], p = 0.01), and multiple measures of variability between good and poor outcome patients (all values median [IQR], good vs. poor). qEEG patterns with high or increasing power or large power variability were associated with good outcome (n = 6). Patterns with consistently low or decreasing power or minimal power variability were associated with poor outcome (n = 4). These preliminary results suggest qEEG metrics correlate with outcome. In some patients, qEEG patterns change over the first three days post-arrest.

Intermittency in electric brain activity in the perception of ambiguous images

NASA Astrophysics Data System (ADS)

Kurovskaya, Maria K.; Runnova, Anastasiya E.; Zhuravlev, Maxim O.; Grubov, Vadim V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Pisarchik, Alexander N.

2017-04-01

Present paper is devoted to the study of intermittency during the perception of bistable Necker cube image being a good example of an ambiguous object, with simultaneous measurement of EEG. Distributions of time interval lengths corresponding to the left-oriented and right-oriented cube perception have been obtain. EEG data have been analyzed using continuous wavelet transform and it was shown that the destruction of alpha rhythm with accompanying generation of high frequency oscillations can serve as a marker of Necker cube recognition process.

Mechanism and Therapy for the Shared Susceptibility to Migraine and Epilepsy after Brain Injury (TBI)

DTIC Science & Technology

2015-12-01

30 s). These animals showed 1-8 seizures/day (range). Nine hours after injury, one mouse developed status epilepticus (Figure 2) which continued for...3 days resulting in the animal’s death. Figure 3: Electrographic recording of a CCI-injured mouse in status epilepticus . Upper trace is an EEG...recording of 4 h of status epilepticus while the lower traces represent portions of the EEG within the 10 dashed boxes at an expanded timescale

Electroencephalographic Recordings During Withdrawal of Life-Sustaining Therapy Until 30 Minutes After Declaration of Death.

PubMed

Norton, Loretta; Gibson, Raechelle M; Gofton, Teneille; Benson, Carolyn; Dhanani, Sonny; Shemie, Sam D; Hornby, Laura; Ward, Roxanne; Young, G Bryan

2017-03-01

The timing of the circulatory determination of death for organ donation presents a medical and ethical challenge. Concerns have been raised about the timing of electrocerebral inactivity in relation to the cessation of circulatory function in organ donation after cardio-circulatory death. Nonprocessed electroencephalographic (EEG) measures have not been characterized and may provide insight into neurological function during this process. We assessed electrocortical data in relation to cardiac function after withdrawal of life-sustaining therapy and in the postmortem period after cardiac arrest for four patients in a Canadian intensive care unit. Subhairline EEG and cardio-circulatory monitoring including electrocardiogram, arterial blood pressure (ABP), and oxygen saturation were captured. Electrocerebral inactivity preceded the cessation of the cardiac rhythm and ABP in three patients. In one patient, single delta wave bursts persisted following the cessation of both the cardiac rhythm and ABP. There was a significant difference in EEG amplitude between the 30-minute period before and the 5-minute period following ABP cessation for the group, but we did not observe any well-defined EEG states following the early cardiac arrest period. In a case series of four patients, EEG inactivity preceded electrocardiogram and ABP inactivity during the dying process in three patients. Further study of the electroencephalogram during the withdrawal of life sustaining therapies will add clarity to medical, ethical, and legal concerns for donation after circulatory determined death.