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Sample records for resting ecg analysis

  1. Computational Analysis of ECGs

    NASA Astrophysics Data System (ADS)

    Waters, Kevin

    2013-03-01

    Electrocardiogram is among the most powerful methods at present to diagnose heart conditions. Here we employed Fourier transform to analyze Electrocardiograms. The goal of the project is to find a way to isolate different wave signals in ways that today's technology is not capable of. Our focus was on building on a code that is capable of filtering out P, QRS, T waves and noise from the ECG, so we created frequency filters that omitted selected amount of data. We first deconstructed and then constructed the ECG this way to find an optimal code assembly for each ECG wave (P-wave, QRS-wave, T-wave). By focusing on one patient, we succeeded to disentangle the complicated ECG signal. We plan to extend this method to more patients.

  2. Optimal ECG Electrode Sites and Criteria for Detection of Asymptomatic Coronary Artery Disease - Update 1990. Multilead ECG Changes at Rest, with Exercise, and with Coronary Angioplasty

    DTIC Science & Technology

    1992-02-01

    AD-A248 613 OPTIMAL ECG ELECTRODE SITES AND CRITERIA CORONARY ARTERY DISEASE -UPDATE 1990 MULILEAD ECG CHANGES AT REST, WITH A EXERCISE, AND WITH...5. FUNDING NUMBERS Optimal ECG Electrode Sites and Criteria for Detection of Asymptomatic C - F33615-87-D-0609/0023 Coronary Artery Disease --Update...improve the detection of asymptomatic coronary disease . Three ECG recording systems with signal processing of 30 simultaneous leads (30SL) have been

  3. Noninvasive Fetal ECG analysis

    PubMed Central

    Clifford, Gari D.; Silva, Ikaro; Behar, Joachim; Moody, George B.

    2014-01-01

    Despite the important advances achieved in the field of adult electrocardiography signal processing, the analysis of the non-invasive fetal electrocardiogram (NI-FECG) remains a challenge. Currently no gold standard database exists which provides labelled FECG QRS complexes (and other morphological parameters), and publications rely either on proprietary databases or a very limited set of data recorded from few (or more often, just one) individuals. The PhysioNet/Computing in Cardiology Challenge 2013 enables to tackle some of these limitations by releasing a set of NI-FECG data publicly to the scientific community in order to evaluate signal processing techniques for NI-FECG extraction. The Challenge aim was to encourage development of accurate algorithms for locating QRS complexes and estimating the QT interval in noninvasive FECG signals. Using carefully reviewed reference QRS annotations and QT intervals as a gold standard, based on simultaneous direct FECG when possible, the Challenge was designed to measure and compare the performance of participants’ algorithms objectively. Multiple challenge events were designed to test basic FHR estimation accuracy, as well as accuracy in measurement of inter-beat (RR) and QT intervals needed as a basis for derivation of other FECG features. This editorial reviews the background issues, the design of the Challenge, the key achievements, and the follow-up research generated as a result of the Challenge, published in the concurrent special issue of Physiological Measurement. PMID:25071093

  4. Construction of a Resting High Fidelity ECG "SuperScore" for Management and Screening of Heart Disease

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Delgado, Reynolds; Poulin, Greg; Starc, Vito; Arenare, Brian; Rahman, M. A.

    2006-01-01

    Resting conventional ECG is notoriously insensitive for detecting coronary artery disease (CAD) and only nominally useful in screening for cardiomyopathy (CM). Similarly, conventional exercise stress test ECG is both time- and labor-consuming and its accuracy in identifying CAD is suboptimal for use in population screening. We retrospectively investigated the accuracy of several advanced resting electrocardiographic (ECG) parameters, both alone and in combination, for detecting CAD and cardiomyopathy (CM).

  5. A Mixed Approach Of Automated ECG Analysis

    NASA Astrophysics Data System (ADS)

    De, A. K.; Das, J.; Majumder, D. Dutta

    1982-11-01

    ECG is one of the non-invasive and risk-free technique for collecting data about the functional state of the heart. However, all these data-processing techniques can be classified into two basically different approaches -- the first and second generation ECG computer program. Not the opposition, but simbiosis of these two approaches will lead to systems with the highest accuracy. In our paper we are going to describe a mixed approach which will show higher accuracy with lesser amount of computational work. Key Words : Primary features, Patients' parameter matrix, Screening, Logical comparison technique, Multivariate statistical analysis, Mixed approach.

  6. New Padded Harness for Self-Acquisition of Resting 12-Lead ECGs

    NASA Technical Reports Server (NTRS)

    Schlegel, T. T.; Rood, A. T.

    2011-01-01

    We have developed a dry-electrode harness that permits easy, rapid, and unsupervised self-acquisition of resting 12-lead ECGs without the use of any disposables. Various other advantageous features of the harness include: 1) padded or inflatable cushions at the lateral sides of the torso that function to press the left arm (LA) and right arm (RA) dry electrodes mounted on cushions against sideward (as shown in the Figure below) or downward-rested arms of the subject; 2) sufficient distal placement of the arm electrodes with good abutment and without the need for adhesives, straps, bands, bracelets, or gloves on the arms; 3) padding over the sternum to avoid "tenting" in the V1 through V3 (and V3R, when present) electrode positions; 4) easy-to-don, one-piece design with an adjustable single point of connection and an adjustable shoulder strap; and 5) Lund or "modified Lund" placement of the dry electrodes, the results of which more effectively reproduce results from "standard" 12-lead ECG placements than do results from Mason-Likar lead placements.

  7. Optimal ECG Electrode Sites and Criteria for Detection of Asymptomatic Coronary Artery Disease at Rest and with Exercise.

    DTIC Science & Technology

    1985-12-01

    47 In OPTIMAL ECG ELECTRODE SITES AND CRITERIA to FOR DETECTION OF ASYMPTOMATIC CORONARY to ARTERY DISEASE AT REST AND WITH EXERCISE Ronald H...of Asymptomatic Coronary Artery Disease at Rest and with Exercise 12. PERSONAL AUTHOR(S) Selvester, Ronald H.; and Solomon, Joseph C.13a. TYPE OF...15-30, of all new coronary events in persons with previously unsuspected coronary disease . The prevalence of unrecognized but severe coronary artery

  8. ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Kaur, Inderbir; Rajni, Rajni; Marwaha, Anupma

    2016-12-01

    Electrocardiogram (ECG) is used to record the electrical activity of the heart. The ECG signal being non-stationary in nature, makes the analysis and interpretation of the signal very difficult. Hence accurate analysis of ECG signal with a powerful tool like discrete wavelet transform (DWT) becomes imperative. In this paper, ECG signal is denoised to remove the artifacts and analyzed using Wavelet Transform to detect the QRS complex and arrhythmia. This work is implemented in MATLAB software for MIT/BIH Arrhythmia database and yields the sensitivity of 99.85 %, positive predictivity of 99.92 % and detection error rate of 0.221 % with wavelet transform. It is also inferred that DWT outperforms principle component analysis technique in detection of ECG signal.

  9. Construction and Use of Resting 12-Lead High Fidelity ECG "SuperScores" in Screening for Heart Disease

    NASA Technical Reports Server (NTRS)

    Schlegel, T. T.; Arenare, B.; Greco, E. C.; DePalma, J. L.; Starc, V.; Nunez, T.; Medina, R.; Jugo, D.; Rahman, M.A.; Delgado, R.

    2007-01-01

    We investigated the accuracy of several conventional and advanced resting ECG parameters for identifying obstructive coronary artery disease (CAD) and cardiomyopathy (CM). Advanced high-fidelity 12-lead ECG tests (approx. 5-min supine) were first performed on a "training set" of 99 individuals: 33 with ischemic or dilated CM and low ejection fraction (EF less than 40%); 33 with catheterization-proven obstructive CAD but normal EF; and 33 age-/gender-matched healthy controls. Multiple conventional and advanced ECG parameters were studied for their individual and combined retrospective accuracies in detecting underlying disease, the advanced parameters falling within the following categories: 1) Signal averaged ECG, including 12-lead high frequency QRS (150-250 Hz) plus multiple filtered and unfiltered parameters from the derived Frank leads; 2) 12-lead P, QRS and T-wave morphology via singular value decomposition (SVD) plus signal averaging; 3) Multichannel (12-lead, derived Frank lead, SVD lead) beat-to-beat QT interval variability; 4) Spatial ventricular gradient (and gradient component) variability; and 5) Heart rate variability. Several multiparameter ECG SuperScores were derivable, using stepwise and then generalized additive logistic modeling, that each had 100% retrospective accuracy in detecting underlying CM or CAD. The performance of these same SuperScores was then prospectively evaluated using a test set of another 120 individuals (40 new individuals in each of the CM, CAD and control groups, respectively). All 12-lead ECG SuperScores retrospectively generated for CM continued to perform well in prospectively identifying CM (i.e., areas under the ROC curve greater than 0.95), with one such score (containing just 4 components) maintaining 100% prospective accuracy. SuperScores retrospectively generated for CAD performed somewhat less accurately, with prospective areas under the ROC curve typically in the 0.90-0.95 range. We conclude that resting 12-lead

  10. Optimal ECG (Electrocardiogram) Electrode Sites and Criteria for Detection of Asymptomatic Coronary Artery Disease at Rest and with Exercise.

    DTIC Science & Technology

    1985-12-01

    ASYMPTOMATIC CORONARY < ARTERY DISEASE AT REST AND WITH EXERCISE *Ronald H. Selvester, M.D. D T IC Joseph C. Solomon, M.S. ELECTE S JUL03 98 - University of...imalI ECG L Iec trode 1ites and Lri te ria Tor uJetect1iln of Asymptomatic Coronary Artery Disease at Rest and with Exercise 12. PERSONAL AUTHOR(SI...Coronary Artery 16 Disease , Myocardial Infarction,- iyocardial Ischemia, 19 ABSTRACT eCon inue on reterse if necesam and id’n tifN bv bloch nunberI

  11. Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

    NASA Technical Reports Server (NTRS)

    Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

    2011-01-01

    INTRODUCTION Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. Screening for cardiovascular risk factors is recommended but not always followed in this population. PHASER is a project charged with identifying and prioritizing risk factors in emergency responders. We have deployed an advanced ECG (A-ECG) system developed at NASA for improved sensitivity and specificity in the detection of cardiac risk. METHODS Forty-four professional firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance and laboratory tests for fasting lipid profiles and glucose. Heart rate and conventional 12-lead ECG were obtained at rest and during incremental treadmill exercise testing (XT). In addition, a 5-min resting 12-lead A-ECG was obtained in a subset of firefighters (n=18) and transmitted over a secure networked system to a physician collaborator at NASA for advanced-ECG analysis. This A-ECG system has been proven, using myocardial perfusion and other imaging, to accurately identify a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, non-ischemic cardiomyopathy, and ischemic cardiomyopathy. RESULTS Subjects mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI of 28 (3) kg/square meter. Maximum oxygen uptake (VO2max) was 39 (9) ml/kg/min. This compares with the 45th %ile in healthy reference values and a recommended standard of 42 ml/kg/min for firefighters. The metabolic threshold (VO

  12. Heritability of ECG Biomarkers in the Netherlands Twin Registry Measured from Holter ECGs

    PubMed Central

    Hodkinson, Emily C.; Neijts, Melanie; Sadrieh, Arash; Imtiaz, Mohammad S.; Baumert, Mathias; Subbiah, Rajesh N.; Hayward, Christopher S.; Boomsma, Dorret; Willemsen, Gonneke; Vandenberg, Jamie I.; Hill, Adam P.; De Geus, Eco

    2016-01-01

    Introduction: The resting ECG is the most commonly used tool to assess cardiac electrophysiology. Previous studies have estimated heritability of ECG parameters based on these snapshots of the cardiac electrical activity. In this study we set out to determine whether analysis of heart rate specific data from Holter ECGs allows more complete assessment of the heritability of ECG parameters. Methods and Results: Holter ECGs were recorded from 221 twin pairs and analyzed using a multi-parameter beat binning approach. Heart rate dependent estimates of heritability for QRS duration, QT interval, Tpeak–Tend and Theight were calculated using structural equation modeling. QRS duration is largely determined by environmental factors whereas repolarization is primarily genetically determined. Heritability estimates of both QT interval and Theight were significantly higher when measured from Holter compared to resting ECGs and the heritability estimate of each was heart rate dependent. Analysis of the genetic contribution to correlation between repolarization parameters demonstrated that covariance of individual ECG parameters at different heart rates overlap but at each specific heart rate there was relatively little overlap in the genetic determinants of the different repolarization parameters. Conclusions: Here we present the first study of heritability of repolarization parameters measured from Holter ECGs. Our data demonstrate that higher heritability can be estimated from the Holter than the resting ECG and reveals rate dependence in the genetic—environmental determinants of the ECG that has not previously been tractable. Future applications include deeper dissection of the ECG of participants with inherited cardiac electrical disease. PMID:27199769

  13. Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

    PubMed

    Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G

    2012-10-01

    The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes.

  14. An ECG analysis interactive training system for understanding arrhythmias.

    PubMed

    Lessard, Yvon; Sinteff, Jean-Paul; Siregar, Pridi; Julen, Nathalie; Hannouche, Frédéric; Rio, Stéphane; Le Beux, Pierre

    2009-01-01

    The ECG remains a daily diagnostic tool for the detection of numerous cardiovascular diseases. Our goal was to use a computerized qualitative model (QM) of heart in order to build cases of simple arrhythmias dedicated to initial and more advanced medical teaching. The original QM is able to generate videograms of many cardiac disturbances. A Flash player is used to view ECG, synchronous Lewis diagram and chromatic 2D cardiac animation of a specific case. OAAT is a standardized 18 yes/no answers questionnaire which allows the learner to diagnose five main types of arrhythmias that can be compared with normal sinus rhythm (NSR) analysis. This new tool has been recently used by medical students during practical sessions. Based on medical reasoning learning on NSR video and upon trying to recognize an abnormal cardiac rhythm, all users can reach the 100% winning score since they can perform as many attempts as they like. We believe that unlimited case review with questionnaire answering, ECG and Lewis diagram replay and step-by-step visualization of the abnormal propagation of the cardiac impulse on the 2D heart videos are a highly efficient means to help students understand even complex arrhythmic mechanisms.

  15. Deployment of an Advanced Electrocardiographic Analysis (A-ECG) to Detect Cardiovascular Risk in Career Firefighters

    NASA Technical Reports Server (NTRS)

    Dolezal, B. A.; Storer, T. W.; Abrazado, M.; Watne, R.; Schlegel, T. T.; Batalin, M.; Kaiser, W.; Smith, D. L.; Cooper, C. B.

    2011-01-01

    INTRODUCTION: Sudden cardiac death is the leading cause of line of duty death among firefighters, accounting for approximately 45% of fatalities annually. Firefighters perform strenuous muscular work while wearing heavy, encapsulating personal protective equipment in high ambient temperatures, under chaotic and emotionally stressful conditions. These factors can precipitate sudden cardiac events like myocardial infarction, serious dysrhythmias, or cerebrovascular accidents in firefighters with underlying cardiovascular disease. PURPOSE: The purpose of this study was to deploy and then evaluate the contribution of resting advanced ECG (A-ECG) in addition to other screening tools (family history, lipid profiles, and cardiopulmonary exercise tests, XT) in assessment of an individual fs cardiac risk profile. METHODS: Forty-four career firefighters were recruited to perform comprehensive baseline assessments including tests of aerobic performance, fasting lipids and glucose. Five-min resting 12-lead A-ECGs were obtained in a subset of firefighters (n=21) and transmitted over a secure networked system to a NASA physician collaborator. Using myocardial perfusion and other imaging as the gold standard, A-ECG scoring has been proven useful in accurately identifying a number of cardiac pathologies including coronary artery disease (CAD), left ventricular hypertrophy, hypertrophic cardiomyopathy, and non-ischemic and ischemic cardiomyopathy. RESULTS: Subjects f mean (SD) age was 43 (8) years, weight 91 (13) kg, and BMI 28 (3) kg/m2. Fifty-one percent of subjects had .3 cardiovascular risk factors. One subject had ST depression on XT ECG, at least one positive A-ECG score for CAD, and documented CAD based on cardiology referral. While all other subjects, including those with fewer risk factors, higher aerobic fitness, and normal exercise ECGs, were classified as healthy by A-ECG, there was no trend for association between risk factors and any of 20 A-ECG parameters in the

  16. Principal component analysis of atrial fibrillation: Inclusion of posterior ECG leads does not improve correlation with left atrial activity

    PubMed Central

    Raine, Daniel; Langley, Philip; Shepherd, Ewen; Lord, Stephen; Murray, Stephen; Murray, Alan; Bourke, John P.

    2015-01-01

    Background Lead V1 is routinely analysed due to its large amplitude AF waveform. V1 correlates strongly with right atrial activity but only moderately with left atrial activity. Posterior lead V9 correlates strongest with left atrial activity. Aims (1) To establish whether surface dominant AF frequency (DAF) calculated using principal component analysis (PCA) of a modified 12-lead ECG (including posterior leads) has a stronger correlation with left atrial activity compared to the standard ECG. (2) To assess the contribution of individual ECG leads to the AF principal component in both ECG configurations. Methods Patients were assigned to modified or standard ECG groups. In the modified ECG, posterior leads V8 and V9 replaced V4 and V6. AF waveform was extracted from one-minute surface ECG recordings using PCA. Surface DAF was correlated with intracardiac DAF from the high right atrium (HRA), coronary sinus (CS) and pulmonary veins (PVs). Results 96 patients were studied. Surface DAF from the modified ECG did not have a stronger correlation with left atrial activity compared to the standard ECG. Both ECG configurations correlated strongly with HRA, CS and right PVs but only moderately with left PVs. V1 contributed most to the AF principal component in both ECG configurations. PMID:25619612

  17. A hierarchical method for removal of baseline drift from biomedical signals: application in ECG analysis.

    PubMed

    Luo, Yurong; Hargraves, Rosalyn H; Belle, Ashwin; Bai, Ou; Qi, Xuguang; Ward, Kevin R; Pfaffenberger, Michael Paul; Najarian, Kayvan

    2013-01-01

    Noise can compromise the extraction of some fundamental and important features from biomedical signals and hence prohibit accurate analysis of these signals. Baseline wander in electrocardiogram (ECG) signals is one such example, which can be caused by factors such as respiration, variations in electrode impedance, and excessive body movements. Unless baseline wander is effectively removed, the accuracy of any feature extracted from the ECG, such as timing and duration of the ST-segment, is compromised. This paper approaches this filtering task from a novel standpoint by assuming that the ECG baseline wander comes from an independent and unknown source. The technique utilizes a hierarchical method including a blind source separation (BSS) step, in particular independent component analysis, to eliminate the effect of the baseline wander. We examine the specifics of the components causing the baseline wander and the factors that affect the separation process. Experimental results reveal the superiority of the proposed algorithm in removing the baseline wander.

  18. Comparison of JADE and canonical correlation analysis for ECG de-noising.

    PubMed

    Kuzilek, Jakub; Kremen, Vaclav; Lhotska, Lenka

    2014-01-01

    This paper explores differences between two methods for blind source separation within frame of ECG de-noising. First method is joint approximate diagonalization of eigenmatrices, which is based on estimation of fourth order cross-cummulant tensor and its diagonalization. Second one is the statistical method known as canonical correlation analysis, which is based on estimation of correlation matrices between two multidimensional variables. Both methods were used within method, which combines the blind source separation algorithm with decision tree. The evaluation was made on large database of 382 long-term ECG signals and the results were examined. Biggest difference was found in results of 50 Hz power line interference where the CCA algorithm completely failed. Thus main power of CCA lies in estimation of unstructured noise within ECG. JADE algorithm has larger computational complexity thus the CCA perfomed faster when estimating the components.

  19. Effects of electrocardiography contamination and comparison of ECG removal methods on upper trapezius electromyography recordings.

    PubMed

    Marker, Ryan J; Maluf, Katrina S

    2014-12-01

    Electromyography (EMG) recordings from the trapezius are often contaminated by the electrocardiography (ECG) signal, making it difficult to distinguish low-level muscle activity from muscular rest. This study investigates the influence of ECG contamination on EMG amplitude and frequency estimations in the upper trapezius during muscular rest and low-level contractions. A new method of ECG contamination removal, filtered template subtraction (FTS), is described and compared to 30 Hz high-pass filter (HPF) and averaged template subtraction (ATS) methods. FTS creates a unique template of each ECG artifact using a low-pass filtered copy of the contaminated signal, which is subtracted from contaminated periods in the original signal. ECG contamination results in an over-estimation of EMG amplitude during rest in the upper trapezius, with negligible effects on amplitude and frequency estimations during low-intensity isometric contractions. FTS and HPF successfully removed ECG contamination from periods of muscular rest, yet introduced errors during muscle contraction. Conversely, ATS failed to fully remove ECG contamination during muscular rest, yet did not introduce errors during muscle contraction. The relative advantages and disadvantages of different ECG contamination removal methods should be considered in the context of the specific motor tasks that require analysis.

  20. Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains.

    PubMed

    Vanderlei, L C M; Silva, R A; Pastre, C M; Azevedo, F M; Godoy, M F

    2008-10-01

    The aim of the present study was to compare heart rate variability (HRV) at rest and during exercise using a temporal series obtained with the Polar S810i monitor and a signal from a LYNX(R) signal conditioner (BIO EMG 1000 model) with a channel configured for the acquisition of ECG signals. Fifteen healthy subjects aged 20.9 +/- 1.4 years were analyzed. The subjects remained at rest for 20 min and performed exercise for another 20 min with the workload selected to achieve 60% of submaximal heart rate. RR series were obtained for each individual with a Polar S810i instrument and with an ECG analyzed with a biological signal conditioner. The HRV indices (rMSSD, pNN50, LFnu, HFnu, and LF/HF) were calculated after signal processing and analysis. The unpaired Student t-test and intraclass correlation coefficient were used for data analysis. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV at rest and during exercise. The intraclass correlation coefficient demonstrated satisfactory correlation between the values obtained by the devices at rest (pNN50 = 0.994; rMSSD = 0.995; LFnu = 0.978; HFnu = 0.978; LF/HF = 0.982) and during exercise (pNN50 = 0.869; rMSSD = 0.929; LFnu = 0.973; HFnu = 0.973; LF/HF = 0.942). The calculation of HRV values by means of temporal series obtained from the Polar S810i instrument appears to be as reliable as those obtained by processing the ECG signal captured with a signal conditioner.

  1. Cancelling ECG Artifacts in EEG Using a Modified Independent Component Analysis Approach

    NASA Astrophysics Data System (ADS)

    Devuyst, Stéphanie; Dutoit, Thierry; Stenuit, Patricia; Kerkhofs, Myriam; Stanus, Etienne

    2008-12-01

    We introduce a new automatic method to eliminate electrocardiogram (ECG) noise in an electroencephalogram (EEG) or electrooculogram (EOG). It is based on a modification of the independent component analysis (ICA) algorithm which gives promising results while using only a single-channel electroencephalogram (or electrooculogram) and the ECG. To check the effectiveness of our approach, we compared it with other methods, that is, ensemble average subtraction (EAS) and adaptive filtering (AF). Tests were carried out on simulated data obtained by addition of a filtered ECG on a visually clean original EEG and on real data made up of 10 excerpts of polysomnographic (PSG) sleep recordings containing ECG artifacts and other typical artifacts (e.g., movement, sweat, respiration, etc.). We found that our modified ICA algorithm had the most promising performance on simulated data since it presented the minimal root mean-squared error. Furthermore, using real data, we noted that this algorithm was the most robust to various waveforms of cardiac interference and to the presence of other artifacts, with a correction rate of 91.0%, against 83.5% for EAS and 83.1% for AF.

  2. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  3. Robust human identification using ecg: eigenpulse revisited

    NASA Astrophysics Data System (ADS)

    Jang, Daniel; Wendelken, Suzanne; Irvine, John M.

    2010-04-01

    Biometrics, such as fingerprint, iris scan, and face recognition, offer methods for identifying individuals based on a unique physiological measurement. Recent studies indicate that a person's electrocardiogram (ECG) may also provide a unique biometric signature. Several methods for processing ECG data have appeared in the literature and most approaches rest on an initial detection and segmentation of the heartbeats. Various sources of noise, such as sensor noise, poor sensor placement, or muscle movements, can degrade the ECG signal and introduce errors into the heartbeat segmentation. This paper presents a screening technique for assessing the quality of each segmented heartbeat. Using this technique, a higher quality signal can be extracted to support the identification task. We demonstrate the benefits of this quality screening using a principal component technique known as eigenpulse. The analysis demonstrated the improvement in performance attributable to the quality screening.

  4. Design, fabrication and skin-electrode contact analysis of polymer microneedle-based ECG electrodes

    NASA Astrophysics Data System (ADS)

    O'Mahony, Conor; Grygoryev, Konstantin; Ciarlone, Antonio; Giannoni, Giuseppe; Kenthao, Anan; Galvin, Paul

    2016-08-01

    Microneedle-based ‘dry’ electrodes have immense potential for use in diagnostic procedures such as electrocardiography (ECG) analysis, as they eliminate several of the drawbacks associated with the conventional ‘wet’ electrodes currently used for physiological signal recording. To be commercially successful in such a competitive market, it is essential that dry electrodes are manufacturable in high volumes and at low cost. In addition, the topographical nature of these emerging devices means that electrode performance is likely to be highly dependent on the quality of the skin-electrode contact. This paper presents a low-cost, wafer-level micromoulding technology for the fabrication of polymeric ECG electrodes that use microneedle structures to make a direct electrical contact to the body. The double-sided moulding process can be used to eliminate post-process via creation and wafer dicing steps. In addition, measurement techniques have been developed to characterize the skin-electrode contact force. We perform the first analysis of signal-to-noise ratio dependency on contact force, and show that although microneedle-based electrodes can outperform conventional gel electrodes, the quality of ECG recordings is significantly dependent on temporal and mechanical aspects of the skin-electrode interface.

  5. Continuous digital ECG analysis over accurate R-peak detection using adaptive wavelet technique.

    PubMed

    Gopalakrishnan Nair, T R; Geetha, A P; Asharani, M

    2013-10-01

    Worldwide, health care segment is under a severe challenge to achieve more accurate and intelligent biomedical systems in order to assist healthcare professionals with more accurate and consistent data as well as reliability. The role of ECG in healthcare is one of the paramount importances and it has got a multitude of abnormal relations and anomalies which characterizes intricate cardiovascular performance image. Until the recent past, ECG instruments and analysis played the role of providing the PQRST signal as raw observational output either on paper or on a console or in a file having many diagnostic clues embedded in the signal left to the expert cardiologist to look out for characteristic intervals and to detect the cardiovascular abnormality. Methods and practises are required more and more, to automate this process of cardiac expertise using knowledge engineering and an intelligent systems approach. This paper presents one of the challenging R-peak detections to classify diagnosis and estimate cardio disorders in a fully automated signal processing sequence. This study used an adaptive wavelet approach to generate an appropriate wavelet for R-signal identification under noise, baseband wandering and temporal variations of R-positions. This study designed an adaptive wavelet and successfully detected R- peak variations under various ECG signal conditions. The result and analysis of this method and the ways to use it for further purposes are presented here.

  6. Multiresolution wavelet analysis of the body surface ECG before and after angioplasty.

    PubMed

    Gramatikov, B; Yi-Chun, S; Rix, H; Caminal, P; Thakor, N V

    1995-01-01

    Electrocardiographic recordings of patients with coronary artery stenosis, made before and after angioplasty, were analyzed by the multiresolution wavelet transform (MRWT) technique. The MRWT decomposes the signal of interest into its coarse and detail components at successively finer scales. MRWT was carried out on different leads in order to compare the P-QRS-T complex from recordings made before with those made after percutaneous transluminal coronary angioplasty (PTCA). ECG signals before and after successful PTCA procedures show distinctive changes at certain scales, thus helping to identify whether the procedure has been successful. In six patients who underwent right coronary artery PTCA, varying levels of reperfusion were achieved, and the changes in the detail components of ECG were shown to correlate with the successful reperfusion. The detail components at scales 5 and 6, corresponding approximately to the frequencies in the range of 2.3-8.3 Hz, are shown to be the most sensitive to ischemia-reperfusion changes (p < 0.05). The same conclusion was reached by synthesizing the post-PTCA signals from pre-PTCA signals with the help of these detail components. For on-line monitoring a vector plot, analogous to vector cardiogram, of the two most sensitive MRWT detail components is proposed. Thus, multiresolution analysis of ECG may be useful as a monitoring and diagnostic tool during angioplasty procedures.

  7. Smart ECG Monitoring Patch with Built-in R-Peak Detection for Long-Term HRV Analysis.

    PubMed

    Lee, W K; Yoon, H; Park, K S

    2016-07-01

    Since heart rate variability (HRV) analysis is widely used to evaluate the physiological status of the human body, devices specifically designed for such applications are needed. To this end, we developed a smart electrocardiography (ECG) patch. The smart patch measures ECG using three electrodes integrated into the patch, filters the measured signals to minimize noise, performs analog-to-digital conversion, and detects R-peaks. The measured raw ECG data and the interval between the detected R-peaks can be recorded to enable long-term HRV analysis. Experiments were performed to evaluate the performance of the built-in R-wave detection, robustness of the device under motion, and applicability to the evaluation of mental stress. The R-peak detection results obtained with the device exhibited a sensitivity of 99.29%, a positive predictive value of 100.00%, and an error of 0.71%. The device also exhibited less motional noise than conventional ECG recording, being stable up to a walking speed of 5 km/h. When applied to mental stress analysis, the device evaluated the variation in HRV parameters in the same way as a normal ECG, with very little difference. This device can help users better understand their state of health and provide physicians with more reliable data for objective diagnosis.

  8. A computer program for comprehensive ST-segment depression/heart rate analysis of the exercise ECG test.

    PubMed

    Lehtinen, R; Vänttinen, H; Sievänen, H; Malmivuo, J

    1996-06-01

    The ST-segment depression/heart rate (ST/HR) analysis has been found to improve the diagnostic accuracy of the exercise ECG test in detecting myocardial ischemia. Recently, three different continuous diagnostic variables based on the ST/HR analysis have been introduced; the ST/HR slope, the ST/HR index and the ST/HR hysteresis. The latter utilises both the exercise and recovery phases of the exercise ECG test, whereas the two former are based on the exercise phase only. This present article presents a computer program which not only calculates the above three diagnostic variables but also plots the full diagrams of ST-segment depression against heart rate during both exercise and recovery phases for each ECG lead from given ST/HR data. The program can be used in the exercise ECG diagnosis of daily clinical practice provided that the ST/HR data from the ECG measurement system can be linked to the program. At present, the main purpose of the program is to provide clinical and medical researchers with a practical tool for comprehensive clinical evaluation and development of the ST/HR analysis.

  9. ECG (image)

    MedlinePlus

    ... electrocardiogram (ECG, EKG) is used extensively in the diagnosis of heart disease, ranging from congenital heart disease in infants to myocardial infarction and myocarditis in adults. Several different types of ...

  10. Time-domain ECG signal analysis based on smart-phone.

    PubMed

    Zhou, Shijie; Zhang, Zichen; Gu, Jason

    2011-01-01

    In this paper, a time domain algorithm architecture is presented and implemented on a smart-phone for ECG signal analysis. Using the QRS detection algorithm suggested by Pan-Tompkins and the beat classification method, the heart beats are detected and classified as normal beats and premature ventricular contractions (PVCs). Subsequently, a computationally efficient method is presented to separate ventricular tachycardia (VT) and ventricular fibrillation (VF). This method utilizes Lempel and Ziv complexity analysis combined with K-means algorithm for the coarse-graining process. In addition, a new classification rule is presented to recognize VT and VF in our study. The proposed system provides fairly good performance when applied to the MIT-BIH Database. This algorithm architecture can be efficiently used on the mobile platform.

  11. Language in the brain at rest: new insights from resting state data and graph theoretical analysis

    PubMed Central

    Muller, Angela M.; Meyer, Martin

    2014-01-01

    In humans, the most obvious functional lateralization is the specialization of the left hemisphere for language. Therefore, the involvement of the right hemisphere in language is one of the most remarkable findings during the last two decades of fMRI research. However, the importance of this finding continues to be underestimated. We examined the interaction between the two hemispheres and also the role of the right hemisphere in language. From two seeds representing Broca's area, we conducted a seed correlation analysis (SCA) of resting state fMRI data and could identify a resting state network (RSN) overlapping to significant extent with a language network that was generated by an automated meta-analysis tool. To elucidate the relationship between the clusters of this RSN, we then performed graph theoretical analyses (GTA) using the same resting state dataset. We show that the right hemisphere is clearly involved in language. A modularity analysis revealed that the interaction between the two hemispheres is mediated by three partitions: A bilateral frontal partition consists of nodes representing the classical left sided language regions as well as two right-sided homologs. The second bilateral partition consists of nodes from the right frontal, the left inferior parietal cortex as well as of two nodes within the posterior cerebellum. The third partition is also bilateral and comprises five regions from the posterior midline parts of the brain to the temporal and frontal cortex, two of the nodes are prominent default mode nodes. The involvement of this last partition in a language relevant function is a novel finding. PMID:24808843

  12. Language in the brain at rest: new insights from resting state data and graph theoretical analysis.

    PubMed

    Muller, Angela M; Meyer, Martin

    2014-01-01

    In humans, the most obvious functional lateralization is the specialization of the left hemisphere for language. Therefore, the involvement of the right hemisphere in language is one of the most remarkable findings during the last two decades of fMRI research. However, the importance of this finding continues to be underestimated. We examined the interaction between the two hemispheres and also the role of the right hemisphere in language. From two seeds representing Broca's area, we conducted a seed correlation analysis (SCA) of resting state fMRI data and could identify a resting state network (RSN) overlapping to significant extent with a language network that was generated by an automated meta-analysis tool. To elucidate the relationship between the clusters of this RSN, we then performed graph theoretical analyses (GTA) using the same resting state dataset. We show that the right hemisphere is clearly involved in language. A modularity analysis revealed that the interaction between the two hemispheres is mediated by three partitions: A bilateral frontal partition consists of nodes representing the classical left sided language regions as well as two right-sided homologs. The second bilateral partition consists of nodes from the right frontal, the left inferior parietal cortex as well as of two nodes within the posterior cerebellum. The third partition is also bilateral and comprises five regions from the posterior midline parts of the brain to the temporal and frontal cortex, two of the nodes are prominent default mode nodes. The involvement of this last partition in a language relevant function is a novel finding.

  13. Nonlinear analysis of the ECG during atrial fibrillation in patients for low energy internal cardioversion.

    PubMed

    Diaz, J; Gonzalez, C; Escalona, O; Glover, B M; Manoharan, G

    2008-01-01

    The goal of this study was to investigate the usefulness of nonlinear analysis in determining the success of low energy internal cardioversion (IC) in patients with atrial fibrillation (AF). Nonlinear analysis has previously been used for characterizing AF patterns, and spontaneous termination in its paroxysmal form. However, the relationship between the probability to restore sinus rhythm by IC and quantitative nonlinear analysis based electrocardiographic (ECG) markers has not been explored before. Thirty nine patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in this study. One catheter was positioned in the right atrial appendage and another in the coronary sinus, to deliver a biphasic shock waveform. A voltage step-up protocol (50-300 V) was used for patient cardioversion. Residual atrial fibrillatory signal (RAFS) was derived from 60 seconds of surface ECG from defibrillator pads, prior to shock delivery, by bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The maximal Lyapunov exponent (lambda), correlation dimension (course grained estimation, CDcg) and approximate entropy (ApEn) were extracted from the RAFS. These variables were calculated from 10 s of the RAFS before shock delivery. 26 patients were successfully cardioverted, employing a maximum energy of 11.84 joules. A lower lambda (0.037+/-0.006 vs. 0.044+/-0.008, P=0.01) and CDcg (5.552+/-2.075 vs. 6.592+/-1.130, P=0.049) were found in successfully cardioverted patients than in those non successful ones, with an energy analysis of the RAFS is useful for assessing the prospective efficacy of internal low energy cardioversion of patients with atrial fibrillation.

  14. Object-oriented analysis and design of an ECG storage and retrieval system integrated with an HIS.

    PubMed

    Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S

    1996-03-01

    For a hospital information system, object-oriented methodology plays an increasingly important role, especially for the management of digitized data, e.g., the electrocardiogram, electroencephalogram, electromyogram, spirogram, X-ray, CT and histopathological images, which are not yet computerized in most hospitals. As a first step in an object-oriented approach to hospital information management and storing medical data in an object-oriented database, we connected electrocardiographs to a hospital network and established the integration of ECG storage and retrieval systems with a hospital information system. In this paper, the object-oriented analysis and design of the ECG storage and retrieval systems is reported.

  15. Wavelet analysis and time-frequency distributions of the body surface ECG before and after angioplasty.

    PubMed

    Gramatikov, B; Brinker, J; Yi-chun, S; Thakor, N V

    2000-06-01

    In a pilot study, electrocardiographic (ECG) recordings of patients with left and right coronary stenosis taken before and after angioplasty were analyzed using the continuous wavelet transform. Time-frequency distributions were obtained for different leads in order to examine the dynamics of the QRS-spectrum and establish features specific of ischemia in the time-frequency domain. We found relevant changes in the mid-frequency range, reflecting the ECG's response to percutaneous transluminal coronary angioplasty (PTCA). The changes appeared in ECG leads close to ischemic zones of the myocardium. Time-frequency distributions of the ECG during the QRS may thus become another electrocardiographic indicator of ischemia, alternative to ST-level in standard ECG or body surface mapping. The paper demonstrates the ability of the continuous wavelet transform to detect short lasting events of low amplitude superimposed on large signal deflections.

  16. Left Ventricular Hypertrophy: An allometric comparative analysis of different ECG markers

    NASA Astrophysics Data System (ADS)

    Bonomini, M. P.; Ingallina, F.; Barone, V.; Valentinuzzi, M. E.; Arini, P. D.

    2011-12-01

    Allometry, in general biology, measures the relative growth of a part in relation to the whole living organism. Left ventricular hypertrophy (LVH) is the heart adaptation to excessive load (systolic or diastolic). The increase in left ventricular mass leads to an increase in the electrocardiographic voltages. Based on clinical data, we compared the allometric behavior of three different ECG markers of LVH. To do this, the allometric fit AECG = δ + β (VM) relating left ventricular mass (estimated from ecocardiographic data) and ECG amplitudes (expressed as the Cornell-Voltage, Sokolow and the ECG overall voltage indexes) were compared. Besides, sensitivity and specifity for each index were analyzed. The more sensitive the ECG criteria, the better the allometric fit. In conclusion: The allometric paradigm should be regarded as the way to design new and more sensitive ECG-based LVH markers.

  17. Novel technical solutions for wireless ECG transmission & analysis in the age of the internet cloud.

    PubMed

    Al-Zaiti, Salah S; Shusterman, Vladimir; Carey, Mary G

    2013-01-01

    Current guidelines recommend early reperfusion therapy for ST-elevation myocardial infarction (STEMI) within 90 min of first medical encounter. Telecardiology entails the use of advanced communication technologies to transmit the prehospital 12-lead electrocardiogram (ECG) to offsite cardiologists for early triage to the cath lab; which has been shown to dramatically reduce door-to-balloon time and total mortality. However, hospitals often find adopting ECG transmission technologies very challenging. The current review identifies seven major technical challenges of prehospital ECG transmission, including: paramedics inconvenience and transport delay; signal noise and interpretation errors; equipment malfunction and transmission failure; reliability of mobile phone networks; lack of compliance with the standards of digital ECG formats; poor integration with electronic medical records; and costly hardware and software pre-requisite installation. Current and potential solutions to address each of these technical challenges are discussed in details and include: automated ECG transmission protocols; annotatable waveform-based ECGs; optimal routing solutions; and the use of cloud computing systems rather than vendor-specific processing stations. Nevertheless, strategies to monitor transmission effectiveness and patient outcomes are essential to sustain initial gains of implementing ECG transmission technologies.

  18. An ECG ambulatory system with mobile embedded architecture for ST-segment analysis.

    PubMed

    Miranda-Cid, Alejandro; Alvarado-Serrano, Carlos

    2010-01-01

    A prototype of a ECG ambulatory system for long term monitoring of ST segment of 3 leads, low power, portability and data storage in solid state memory cards has been developed. The solution presented is based in a mobile embedded architecture of a portable entertainment device used as a tool for storage and processing of bioelectric signals, and a mid-range RISC microcontroller, PIC 16F877, which performs the digitalization and transmission of ECG. The ECG amplifier stage is a low power, unipolar voltage and presents minimal distortion of the phase response of high pass filter in the ST segment. We developed an algorithm that manages access to files through an implementation for FAT32, and the ECG display on the device screen. The records are stored in TXT format for further processing. After the acquisition, the system implemented works as a standard USB mass storage device.

  19. Bivariable analysis of ventricular late potentials in high resolution ECG records

    NASA Astrophysics Data System (ADS)

    Orosco, L.; Laciar, E.

    2007-11-01

    In this study the bivariable analysis for ventricular late potentials detection in high-resolution electrocardiographic records is proposed. The standard time-domain analysis and the application of the time-frequency technique to high-resolution ECG records are briefly described as well as their corresponding results. In the proposed technique the time-domain parameter, QRSD and the most significant time-frequency index, ENQRS are used like variables. A bivariable index is defined, that combines the previous parameters. The propose technique allows evaluating the risk of ventricular tachycardia in post-myocardial infarct patients. The results show that the used bivariable index allows discriminating between the patient's population with ventricular tachycardia and the subjects of the control group. Also, it was found that the bivariable technique obtains a good valuation as diagnostic test. It is concluded that comparatively, the valuation of the bivariable technique as diagnostic test is superior to that of the time-domain method and the time-frequency technique evaluated individually.

  20. Mass exponent spectrum analysis of human ECG signals and its application to complexity detection

    NASA Astrophysics Data System (ADS)

    Yang, Xiaodong; Du, Sidan; Ning, Xinbao; Bian, Chunhua

    2008-06-01

    The complexity of electrocardiogram (ECG) signal may reflect the physiological function and healthy status of the heart. In this paper, we introduced two novel intermediate parameters of multifractality, the mass exponent spectrum curvature and area, to characterize the nonlinear complexity of ECG signal. These indicators express the nonlinear superposition of the discrepancies of singularity strengths from all the adjacent points of the spectrum curve and thus overall subsets of original fractal structure. The evaluation of binomial multifractal sets validated these two variables were entirely effective in exploring the complexity of this time series. We then studied the ECG mass exponent spectra taken from the cohorts of healthy, ischemia and myocardial infarction (MI) sufferer based on a large sets of 12 leads’ recordings, and took the statistical averages among each crowd. Experimental results suggest the two values from healthy ECG are apparently larger than those from the heart diseased. While the values from ECG of MI sufferer are much smaller than those from the other two groups. As for the ischemia sufferer, they are almost of moderate magnitude. Afterward, we compared these new indicators with the nonlinear parameters of singularity spectrum. The classification indexes and results of total separating ratios (TSR, defined in the paper) both indicated that our method could achieve a better effect. These conclusions may be of some values in early diagnoses and clinical applications.

  1. Multiple time scale complexity analysis of resting state FMRI.

    PubMed

    Smith, Robert X; Yan, Lirong; Wang, Danny J J

    2014-06-01

    The present study explored multi-scale entropy (MSE) analysis to investigate the entropy of resting state fMRI signals across multiple time scales. MSE analysis was developed to distinguish random noise from complex signals since the entropy of the former decreases with longer time scales while the latter signal maintains its entropy due to a "self-resemblance" across time scales. A long resting state BOLD fMRI (rs-fMRI) scan with 1000 data points was performed on five healthy young volunteers to investigate the spatial and temporal characteristics of entropy across multiple time scales. A shorter rs-fMRI scan with 240 data points was performed on a cohort of subjects consisting of healthy young (age 23 ± 2 years, n = 8) and aged volunteers (age 66 ± 3 years, n = 8) to investigate the effect of healthy aging on the entropy of rs-fMRI. The results showed that MSE of gray matter, rather than white matter, resembles closely that of f (-1) noise over multiple time scales. By filtering out high frequency random fluctuations, MSE analysis is able to reveal enhanced contrast in entropy between gray and white matter, as well as between age groups at longer time scales. Our data support the use of MSE analysis as a validation metric for quantifying the complexity of rs-fMRI signals.

  2. ST/HR hysteresis: exercise and recovery phase ST depression/heart rate analysis of the exercise ECG.

    PubMed

    Lehtinen, R

    1999-01-01

    ST segment depression/heart rate (ST/HR) hysteresis is a recently introduced novel computer method for integrating the exercise and recovery phase ST/HR analysis for improved detection of coronary artery disease (CAD). It is a continuous diagnostic variable that extracts the prevailing direction and average magnitude of the hysteresis in ST depression against HR during the first 3 consecutive minutes of postexercise recovery. This article reviews the development and evaluation of this new method in a clinical population of 347 patients referred for a routine bicycle exercise electrocardiographic (ECG) test at Tampere University Hospital, Finland. Of these patients, 127 had angiographically proven CAD, whereas 13 had no CAD according to angiography, 18 had no perfusion defect according to Tc-99m-sestamibi myocardial imaging and single photon emission computed tomography, and 189 were clinically normal with respect to cardiac diseases. For each patient, the values for ST/HR hysteresis, ST/HR index, end-exercise ST depression, and recovery ST depression were determined for each lead of the Mason-Likar modification of the standard 12-lead exercise ECG and maximum value from the lead system (aVL, aVR, and V1 excluded). The area under the receiver operating characteristics curve (ie, the discriminative capacity) of the ST/HR hysteresis was 89%, which was significantly larger than that of the end-exercise ST depression (76%, P < .0001), recovery ST depression (84%, P = .0063) or ST/HR index (83%, P = .0023), indicating the best diagnostic performance of the ST/HR hysteresis in detection of CAD regardless of the partition value selection. Furthermore, the superior diagnostic performance of the method was relatively insensitive to the ST segment measurement point or to the ECG lead selection. These results suggest that the ST/HR hysteresis improves the clinical utility of the exercise ECG test in detection of CAD.

  3. ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

    ERIC Educational Resources Information Center

    Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

    2015-01-01

    Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

  4. Developing a DICOM Middleware to Implement ECG Conversion and Viewing.

    PubMed

    Ling-Ling, Wang; Ni-Ni, Rao; Li-Xin, Pu; Gang, Wang

    2005-01-01

    Nowadays, medical environment is integrated and complicated, involving large amounts of various medical data, such as images, waveforms and other digital data. For the interoperability of images and waveforms in imaging context, the images and waveforms usually need to be interchanged and stored using one standard. DICOM is the best choice, which is an international standard for the communication and storage of medical information. In this paper, we developed a DICOM middleware with capability of converting SCP-ECG, the European standard for resting ECGs, into DICOM ECGs. Then an ECG viewing component is implemented, which can parse and display SCP-ECG records and DICOM ECGs. The research results show that our work can realize seamless workflows in multi-vendor environment, contribute to the harmonization of ECG standards, and facilitate digital ECG applications.

  5. Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd; Starc, Vito; Leban, Manja; Sinigoj, Petra; Vrhovec, Milos

    2011-01-01

    In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P < 0.001) from a linear combination of 5 independent variables: QRS elevation in the frontal plane (p<0.001), a new repolarization parameter QTcorr (p<0.001), mean high frequency QRS amplitude (p=0.009), the variability parameter % VLF of RRV (p=0.021) and the P-wave width (p=0.10). Here, QTcorr represents the correlation between the calculated QT and the measured QT signal. Conclusions: In apparently healthy subjects with normal conventional ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.

  6. Competency in ECG Interpretation Among Medical Students

    PubMed Central

    Kopeć, Grzegorz; Magoń, Wojciech; Hołda, Mateusz; Podolec, Piotr

    2015-01-01

    Background Electrocardiogram (ECG) is commonly used in diagnosis of heart diseases, including many life-threatening disorders. We aimed to assess skills in ECG interpretation among Polish medical students and to analyze the determinants of these skills. Material/Methods Undergraduates from all Polish medical schools were asked to complete a web-based survey containing 18 ECG strips. Questions concerned primary ECG parameters (rate, rhythm, and axis), emergencies, and common ECG abnormalities. Analysis was restricted to students in their clinical years (4th–6th), and students in their preclinical years (1st–3rd) were used as controls. Results We enrolled 536 medical students (females: n=299; 55.8%), aged 19 to 31 (23±1.6) years from all Polish medical schools. Most (72%) were in their clinical years. The overall rate of good response was better in students in years 4th–5th than those in years 1st–3rd (66% vs. 56%; p<0.0001). Competency in ECG interpretation was higher in students who reported ECG self-learning (69% vs. 62%; p<0.0001) but no difference was found between students who attended or did not attend regular ECG classes (66% vs. 66%; p=0.99). On multivariable analysis (p<0.0001), being in clinical years (OR: 2.45 [1.35–4.46] and self-learning (OR: 2.44 [1.46–4.08]) determined competency in ECG interpretation. Conclusions Polish medical students in their clinical years have a good level of competency in interpreting the primary ECG parameters, but their ability to recognize ECG signs of emergencies and common heart abnormalities is low. ECG interpretation skills are determined by self-education but not by attendance at regular ECG classes. Our results indicate qualitative and quantitative deficiencies in teaching ECG interpretation at medical schools. PMID:26541993

  7. Visualization of multivariate physiological data for cardiorespiratory fitness assessment through ECG (R-peak) analysis.

    PubMed

    Munoz, J E; Bermudez I Badia, S; Rubio, E; Cameirao, M S

    2015-01-01

    The recent rise and popularization of wearable and ubiquitous fitness sensors has increased our ability to generate large amounts of multivariate data for cardiorespiratory fitness (CRF) assessment. Consequently, there is a need to find new methods to visualize and interpret CRF data without overwhelming users. Current visualizations of CRF data are mainly tabular or in the form of stacked univariate plots. Moreover, normative data differs significantly between gender, age and activity, making data interpretation yet more challenging. Here we present a CRF assessment tool based on radar plots that provides a way to represent multivariate cardiorespiratory data from electrocardiographic (ECG) signals within its normative context. To that end, 5 parameters are extracted from raw ECG data using R-peak information: mean HR, SDNN, RMSSD, HRVI and the maximal oxygen uptake, VO2max. Our tool processes ECG data and produces a visualization of the data in a way that it is easy to compare between the performance of the user and normative data. This type of representation can assist both health professionals and non-expert users in the interpretation of CRF data.

  8. High-frequency ECG

    NASA Technical Reports Server (NTRS)

    Tragardh, Elin; Schlegel, Todd T.

    2006-01-01

    The standard ECG is by convention limited to 0.05-150 Hz, but higher frequencies are also present in the ECG signal. With high-resolution technology, it is possible to record and analyze these higher frequencies. The highest amplitudes of the high-frequency components are found within the QRS complex. In past years, the term "high frequency", "high fidelity", and "wideband electrocardiography" have been used by several investigators to refer to the process of recording ECGs with an extended bandwidth of up to 1000 Hz. Several investigators have tried to analyze HF-QRS with the hope that additional features seen in the QRS complex would provide information enhancing the diagnostic value of the ECG. The development of computerized ECG-recording devices that made it possible to record ECG signals with high resolution in both time and amplitude, as well as better possibilities to store and process the signals digitally, offered new methods for analysis. Different techniques to extract the HF-QRS have been described. Several bandwidths and filter types have been applied for the extraction as well as different signal-averaging techniques for noise reduction. There is no standard method for acquiring and quantifying HF-QRS. The physiological mechanisms underlying HF-QRS are still not fully understood. One theory is that HF-QRS are related to the conduction velocity and the fragmentation of the depolarization wave in the myocardium. In a three-dimensional model of the ventricles with a fractal conduction system it was shown that high numbers of splitting branches are associated with HF-QRS. In this experiment, it was also shown that the changes seen in HF-QRS in patients with myocardial ischemia might be due to the slowing of the conduction velocity in the region of ischemia. This mechanism has been tested by Watanabe et al by infusing sodium channel blockers into the left anterior descending artery in dogs. In their study, 60 unipolar ECGs were recorded from the entire

  9. Frequency-phase analysis of resting-state functional MRI

    PubMed Central

    Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

    2017-01-01

    We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

  10. Frequency-phase analysis of resting-state functional MRI.

    PubMed

    Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

    2017-03-08

    We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience.

  11. Frequency Band Analysis of Electrocardiogram (ECG) Signals for Human Emotional State Classification Using Discrete Wavelet Transform (DWT)

    PubMed Central

    Murugappan, Murugappan; Murugappan, Subbulakshmi; Zheng, Bong Siao

    2013-01-01

    [Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions (happiness, disgust, fear, sadness, and neutral) using heart rate variability (HRV) signals derived from an electrocardiogram (ECG). [Subjects] Twenty healthy university students (10 males and 10 females) with a mean age of 23 years participated in this experiment. [Methods] All five emotions were induced by audio-visual stimuli (video clips). ECG signals were acquired using 3 electrodes and were preprocessed using a Butterworth 3rd order filter to remove noise and baseline wander. The Pan-Tompkins algorithm was used to derive the HRV signals from ECG. Discrete wavelet transform (DWT) was used to extract statistical features from the HRV signals using four wavelet functions: Daubechies6 (db6), Daubechies7 (db7), Symmlet8 (sym8), and Coiflet5 (coif5). The k-nearest neighbor (KNN) and linear discriminant analysis (LDA) were used to map the statistical features into corresponding emotions. [Results] KNN provided the maximum average emotion classification rate compared to LDA for five emotions (sadness − 50.28%; happiness − 79.03%; fear − 77.78%; disgust − 88.69%; and neutral − 78.34%). [Conclusion] The results of this study indicate that HRV may be a reliable indicator of changes in the emotional state of subjects and provides an approach to the development of a real-time emotion assessment system with a higher reliability than other systems. PMID:24259846

  12. Frequency Band Analysis of Electrocardiogram (ECG) Signals for Human Emotional State Classification Using Discrete Wavelet Transform (DWT).

    PubMed

    Murugappan, Murugappan; Murugappan, Subbulakshmi; Zheng, Bong Siao

    2013-07-01

    [Purpose] Intelligent emotion assessment systems have been highly successful in a variety of applications, such as e-learning, psychology, and psycho-physiology. This study aimed to assess five different human emotions (happiness, disgust, fear, sadness, and neutral) using heart rate variability (HRV) signals derived from an electrocardiogram (ECG). [Subjects] Twenty healthy university students (10 males and 10 females) with a mean age of 23 years participated in this experiment. [Methods] All five emotions were induced by audio-visual stimuli (video clips). ECG signals were acquired using 3 electrodes and were preprocessed using a Butterworth 3rd order filter to remove noise and baseline wander. The Pan-Tompkins algorithm was used to derive the HRV signals from ECG. Discrete wavelet transform (DWT) was used to extract statistical features from the HRV signals using four wavelet functions: Daubechies6 (db6), Daubechies7 (db7), Symmlet8 (sym8), and Coiflet5 (coif5). The k-nearest neighbor (KNN) and linear discriminant analysis (LDA) were used to map the statistical features into corresponding emotions. [Results] KNN provided the maximum average emotion classification rate compared to LDA for five emotions (sadness - 50.28%; happiness - 79.03%; fear - 77.78%; disgust - 88.69%; and neutral - 78.34%). [Conclusion] The results of this study indicate that HRV may be a reliable indicator of changes in the emotional state of subjects and provides an approach to the development of a real-time emotion assessment system with a higher reliability than other systems.

  13. DSP implementation of wavelet transform for real time ECG wave forms detection and heart rate analysis.

    PubMed

    Bahoura, M; Hassani, M; Hubin, M

    1997-01-01

    An algorithm based on wavelet transform (WTs) suitable for real time implementation has been developed in order to detect ECG characteristics. In particular, QRS complexes, P and T waves may be distinguished from noise, baseline drift or artefacts. This algorithm is implemented in a DSP (SPROC-1400) with a 50 MHz frequency clock. The performance of this algorithm is discussed, its accuracy is evaluated and a comparison is made with a similar algorithm implemented in C language. For the standard MIT/BIH arrhythmia database, this algorithm correctly detects 99.7% of the QRS complexes.

  14. An Improved Method for Discriminating ECG Signals using Typical Nonlinear Dynamic Parameters and Recurrence Quantification Analysis in Cardiac Disease Therapy.

    PubMed

    Tang, M; Chang, C Q; Fung, P C W; Chau, K T; Chan, F H Y

    2005-01-01

    The discrimination of ECG signals using nonlinear dynamic parameters is of crucial importance in the cardiac disease therapy and chaos control for arrhythmia defibrillation in the cardiac system. However, the discrimination results of previous studies using features such as maximal Lyapunov exponent (λmax) and correlation dimension (D2) alone are somewhat limited in recognition rate. In this paper, improved methods for computing λmaxand D2are purposed. Another parameter from recurrence quantification analysis is incorporated to the new multi-feature Bayesian classifier with λmaxand D2so as to improve the discrimination power. Experimental results have verified the prediction using Fisher discriminant that the maximal vertical line length (Vmax) from recurrence quantification analysis is the best to distinguish different ECG classes. Experimental results using the MIT-BIH Arrhythmia Database show improved and excellent overall accuracy (96.3%), average sensitivity (96.3%) and average specificity (98.15%) for discriminating sinus, premature ventricular contraction and ventricular flutter signals.

  15. Functional heart diagnosis by the visualization of time-dependent potential deviation and topologic map-based shape analysis from high-resolution ECG

    NASA Astrophysics Data System (ADS)

    Schulz-Bruenken, Barbara; Pelikan, Erich

    1996-04-01

    Our work focuses on functional heart analysis during acute myocardial infarction based on time-sequence data derived with a high-resolution ECG technique. This data stream can be interpreted as a sequence of potential deviation images. The analysis is performed by both visualizing the potential deviation onto the thorax as well as by shape analysis of the underlying ECG signals using a topologic map. The algorithm deals with the measurement of similarity between different pathological signal types. In contrast to other techniques, the whole ECG signal, coded as a feature vector, is used as input for the self-organizing map. The results show that this approach is suitable for handling unsharp class transitions common to the medical domain.

  16. Comparative Analysis of the Equivital EQ02 Lifemonitor with Holter Ambulatory ECG Device for Continuous Measurement of ECG, Heart Rate, and Heart Rate Variability: A Validation Study for Precision and Accuracy.

    PubMed

    Akintola, Abimbola A; van de Pol, Vera; Bimmel, Daniel; Maan, Arie C; van Heemst, Diana

    2016-01-01

    Background: The Equivital (EQ02) is a multi-parameter telemetric device offering both real-time and/or retrospective, synchronized monitoring of ECG, HR, and HRV, respiration, activity, and temperature. Unlike the Holter, which is the gold standard for continuous ECG measurement, EQO2 continuously monitors ECG via electrodes interwoven in the textile of a wearable belt. Objective: To compare EQ02 with the Holter for continuous home measurement of ECG, heart rate (HR), and heart rate variability (HRV). Methods: Eighteen healthy participants wore, simultaneously for 24 h, the Holter and EQ02 monitors. Per participant, averaged HR, and HRV per 5 min from the two devices were compared using Pearson correlation, paired T-test, and Bland-Altman analyses. Accuracy and precision metrics included mean absolute relative difference (MARD). Results: Artifact content of EQ02 data varied widely between (range 1.93-56.45%) and within (range 0.75-9.61%) participants. Comparing the EQ02 to the Holter, the Pearson correlations were respectively 0.724, 0.955, and 0.997 for datasets containing all data and data with < 50 or < 20% artifacts respectively. For datasets containing respectively all data, data with < 50, or < 20% artifacts, bias estimated by Bland-Altman analysis was -2.8, -1.0, and -0.8 beats per minute and 24 h MARD was 7.08, 3.01, and 1.5. After selecting a 3-h stretch of data containing 1.15% artifacts, Pearson correlation was 0.786 for HRV measured as standard deviation of NN intervals (SDNN). Conclusions: Although the EQ02 can accurately measure ECG and HRV, its accuracy and precision is highly dependent on artifact content. This is a limitation for clinical use in individual patients. However, the advantages of the EQ02 (ability to simultaneously monitor several physiologic parameters) may outweigh its disadvantages (higher artifact load) for research purposes and/ or for home monitoring in larger groups of study participants. Further studies can be aimed at

  17. Comparative Analysis of the Equivital EQ02 Lifemonitor with Holter Ambulatory ECG Device for Continuous Measurement of ECG, Heart Rate, and Heart Rate Variability: A Validation Study for Precision and Accuracy

    PubMed Central

    Akintola, Abimbola A.; van de Pol, Vera; Bimmel, Daniel; Maan, Arie C.; van Heemst, Diana

    2016-01-01

    Background: The Equivital (EQ02) is a multi-parameter telemetric device offering both real-time and/or retrospective, synchronized monitoring of ECG, HR, and HRV, respiration, activity, and temperature. Unlike the Holter, which is the gold standard for continuous ECG measurement, EQO2 continuously monitors ECG via electrodes interwoven in the textile of a wearable belt. Objective: To compare EQ02 with the Holter for continuous home measurement of ECG, heart rate (HR), and heart rate variability (HRV). Methods: Eighteen healthy participants wore, simultaneously for 24 h, the Holter and EQ02 monitors. Per participant, averaged HR, and HRV per 5 min from the two devices were compared using Pearson correlation, paired T-test, and Bland-Altman analyses. Accuracy and precision metrics included mean absolute relative difference (MARD). Results: Artifact content of EQ02 data varied widely between (range 1.93–56.45%) and within (range 0.75–9.61%) participants. Comparing the EQ02 to the Holter, the Pearson correlations were respectively 0.724, 0.955, and 0.997 for datasets containing all data and data with < 50 or < 20% artifacts respectively. For datasets containing respectively all data, data with < 50, or < 20% artifacts, bias estimated by Bland-Altman analysis was −2.8, −1.0, and −0.8 beats per minute and 24 h MARD was 7.08, 3.01, and 1.5. After selecting a 3-h stretch of data containing 1.15% artifacts, Pearson correlation was 0.786 for HRV measured as standard deviation of NN intervals (SDNN). Conclusions: Although the EQ02 can accurately measure ECG and HRV, its accuracy and precision is highly dependent on artifact content. This is a limitation for clinical use in individual patients. However, the advantages of the EQ02 (ability to simultaneously monitor several physiologic parameters) may outweigh its disadvantages (higher artifact load) for research purposes and/ or for home monitoring in larger groups of study participants. Further studies can be aimed

  18. Atropine unmasks bed-rest effect - A spectral analysis of cardiac interbeat intervals

    NASA Technical Reports Server (NTRS)

    Goldberger, Ary L.; Goldwater, Danielle; Bhargava, Valmik

    1986-01-01

    Heart rate spectral data obtained for 10 male subjects between 35-49 years following orthostatic tolerance testing with lower body negative pressure prebed rest and after 7-10 days of bed rest, while on placebo and after intravenous atropine are analyzed. Comparison of the spectral atropine rms for subjects prebed rest and after bed rest reveal a decrease from 63 + or - 24 ms to 40 + or - 23 ms. It is observed that heart rate interval variability for subjects after bed rest and with atropine is reduced; the heart rate at bed rest with atropine is increased from 70.4 + or - 12.4 beats/min prebed rest to 83.7 + or - 18.9 beats/min; and the exercise tolerance time for subjects in the atropine prebed-rest phase (658 + or - 352 s) is higher than the bed-rest phase (505 + or - 252 s). It is noted that bed rest impairs the cardiovascular capacity to adaptively modulate physiological responses, atropine exposes bed-rest deconditioning effects, and spectral analysis is useful for studying the effects of bed-rest deconditioning on cardiac dynamics.

  19. Gender Differences in Bed Rest: Preliminary Analysis of Vascular Function

    NASA Technical Reports Server (NTRS)

    Platts, Steven H.; Stenger, Michael B.; Martin, David S.; Freeman-Perez, Sondra A.; Phillips, Tiffany; Ribeiro, L. Christine

    2008-01-01

    Orthostatic intolerance is a recognized consequence of spaceflight. Numerous studies have shown that women are more susceptible to orthostatic intolerance following spaceflight as well as bed rest, the most commonly used ground-based analog for spaceflight. One of the possible mechanisms proposed to account for this is a difference in vascular responsiveness between genders. We hypothesized that women and men would have differing vascular responses to 90 days of 6-degree head down tilt bed rest. Additionally, we hypothesized that vessels in the upper and lower body would respond differently, as has been shown in the animal literature. Thirteen subjects were placed in bedrest for 90 days (8 men, 5 women) at the Flight Analogs Unit, UTMB. Direct arterial and venous measurements were made with ultrasound to evaluate changes in vascular structure and function. Arterial function was assessed, in the arm and leg, during a reactive hyperemia protocol and during sublingual nitroglycerin administration to gauge the contributions of endothelial dependent and independent dilator function respectively. Venous function was assessed in dorsal hand and foot veins during the administration of pharmaceuticals to assess constrictor and dilator function. Both gender and day effects are seen in arterial dilator function to reactive hyperemia, but none are seen with nitroglycerin. There are also differences in the wall thickness in the arm vs the leg during bed rest, which return toward pre-bed rest levels by day 90. More subjects are required, especially females as there is not sufficient power to properly analyze venous function. Day 90 data are most underpowered.

  20. ECG signal denoising via empirical wavelet transform.

    PubMed

    Singh, Omkar; Sunkaria, Ramesh Kumar

    2016-12-29

    This paper presents new methods for baseline wander correction and powerline interference reduction in electrocardiogram (ECG) signals using empirical wavelet transform (EWT). During data acquisition of ECG signal, various noise sources such as powerline interference, baseline wander and muscle artifacts contaminate the information bearing ECG signal. For better analysis and interpretation, the ECG signal must be free of noise. In the present work, a new approach is used to filter baseline wander and power line interference from the ECG signal. The technique utilized is the empirical wavelet transform, which is a new method used to compute the building modes of a given signal. Its performance as a filter is compared to the standard linear filters and empirical mode decomposition.The results show that EWT delivers a better performance.

  1. Influence of ROI selection on resting state functional connectivity: an individualized approach for resting state fMRI analysis

    PubMed Central

    Sohn, William S.; Yoo, Kwangsun; Lee, Young-Beom; Seo, Sang W.; Na, Duk L.; Jeong, Yong

    2015-01-01

    The differences in how our brain is connected are often thought to reflect the differences in our individual personalities and cognitive abilities. Individual differences in brain connectivity has long been recognized in the neuroscience community however it has yet to manifest itself in the methodology of resting state analysis. This is evident as previous studies use the same region of interest (ROIs) for all subjects. In this paper we demonstrate that the use of ROIs which are standardized across individuals leads to inaccurate calculations of functional connectivity. We also show that this problem can be addressed by taking an individualized approach by using subject-specific ROIs. Finally we show that ROI selection can affect the way we interpret our data by showing different changes in functional connectivity with aging. PMID:26321904

  2. Adaptive spatio-temporal filtering of disturbed ECGs: a multi-channel approach to heartbeat detection in smart clothing.

    PubMed

    Wiklund, Urban; Karlsson, Marcus; Ostlund, Nils; Berglin, Lena; Lindecrantz, Kaj; Karlsson, Stefan; Sandsjö, Leif

    2007-06-01

    Intermittent disturbances are common in ECG signals recorded with smart clothing: this is mainly because of displacement of the electrodes over the skin. We evaluated a novel adaptive method for spatio-temporal filtering for heartbeat detection in noisy multi-channel ECGs including short signal interruptions in single channels. Using multi-channel database recordings (12-channel ECGs from 10 healthy subjects), the results showed that multi-channel spatio-temporal filtering outperformed regular independent component analysis. We also recorded seven channels of ECG using a T-shirt with textile electrodes. Ten healthy subjects performed different sequences during a 10-min recording: resting, standing, flexing breast muscles, walking and pushups. Using adaptive multi-channel filtering, the sensitivity and precision was above 97% in nine subjects. Adaptive multi-channel spatio-temporal filtering can be used to detect heartbeats in ECGs with high noise levels. One application is heartbeat detection in noisy ECG recordings obtained by integrated textile electrodes in smart clothing.

  3. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

    PubMed Central

    Rutter, Lindsay; Nadar, Sreenivasan R.; Holroyd, Tom; Carver, Frederick W.; Apud, Jose; Weinberger, Daniel R.; Coppola, Richard

    2013-01-01

    Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear. PMID:23874288

  4. The Development of a Portable ECG Monitor Based on DSP

    NASA Astrophysics Data System (ADS)

    Nan, CHI Jian; Tao, YAN Yan; Meng Chen, LIU; Li, YANG

    With the advent of global information, researches of Smart Home system are in the ascendant, the ECG real-time detection, and wireless transmission of ECG become more useful. In order to achieve the purpose we developed a portable ECG monitor which achieves the purpose of cardiac disease remote monitoring, and will be used in the physical and psychological disease surveillance in smart home system, we developed this portable ECG Monitor, based on the analysis of existing ECG Monitor, using TMS320F2812 as the core controller, which complete the signal collection, storage, processing, waveform display and transmission.

  5. Robust temporal resolution of MSCT cardiac scan by rotation-time update scheme based on analysis of patient ECG database

    NASA Astrophysics Data System (ADS)

    Glasberg, S.; Farjon, D.; Ankry, M.; Eisenbach, S.; Shnapp, M.; Altman, A.

    2007-03-01

    We have analyzed 144 ECG wave-forms that were taken during cardiac CT exams to determine in retrospect the optimized timing for updating the gantry rotation-time. A score was defined, according to the number of heart beats during X-ray on, which fulfill the temporal resolution (tR)condition, tR<100mSec. The temporal resolution calculation was based on dual-cycle π/2 sector segmentation, where the data required for any image is collected during two heart cycle. The results yield a significant improvement of the tR score with the rotation-time update method relative to using a fixed minimal rotation-time of the gantry. The analysis suggest that full heart scan with better than 100mSec temporal resolution per slice can routinely be achieved in 128 slices MSCT scanner by performing gantry rotation-time -update after patient starts its breath hold. At these conditions the required breath-hold time is expected to be less than 15 seconds.

  6. Resting State Brain Function Analysis Using Concurrent BOLD in ASL Perfusion fMRI

    PubMed Central

    Zhu, Senhua; Fang, Zhuo; Hu, Siyuan; Wang, Ze; Rao, Hengyi

    2013-01-01

    The past decade has seen astounding discoveries about resting-state brain activity patterns in normal brain as well as their alterations in brain diseases. While the vast majority of resting-state studies are based on the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI), arterial spin labeling (ASL) perfusion fMRI can simultaneously capture BOLD and cerebral blood flow (CBF) signals, providing a unique opportunity for assessing resting brain functions with concurrent BOLD (ccBOLD) and CBF signals. Before taking that benefit, it is necessary to validate the utility of ccBOLD signal for resting-state analysis using conventional BOLD (cvBOLD) signal acquired without ASL modulations. To address this technical issue, resting cvBOLD and ASL perfusion MRI were acquired from a large cohort (n = 89) of healthy subjects. Four widely used resting-state brain function analyses were conducted and compared between the two types of BOLD signal, including the posterior cingulate cortex (PCC) seed-based functional connectivity (FC) analysis, independent component analysis (ICA), analysis of amplitude of low frequency fluctuation (ALFF), and analysis of regional homogeneity (ReHo). Consistent default mode network (DMN) as well as other resting-state networks (RSNs) were observed from cvBOLD and ccBOLD using PCC-FC analysis and ICA. ALFF from both modalities were the same for most of brain regions but were different in peripheral regions suffering from the susceptibility gradients induced signal drop. ReHo showed difference in many brain regions, likely reflecting the SNR and resolution differences between the two BOLD modalities. The DMN and auditory networks showed highest CBF values among all RSNs. These results demonstrated the feasibility of ASL perfusion MRI for assessing resting brain functions using its concurrent BOLD in addition to CBF signal, which provides a potentially useful way to maximize the utility of ASL perfusion MRI. PMID:23750275

  7. Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy

    PubMed Central

    Jekova, Irena; Bortolan, Giovanni

    2015-01-01

    Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (rI), II (rII), calculated from them first principal ECG component (rPCA), linear and nonlinear combinations between rI, rII, and rPCA. For the verification task, the one-to-one scenario is applied and threshold values for rI, rII, and rPCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%. PMID:26568954

  8. Resting-State Brain Anomalies in Type 2 Diabetes: A Meta-Analysis

    PubMed Central

    Xia, Wenqing; Chen, Yu-Chen; Ma, Jianhua

    2017-01-01

    Resting-state functional magnetic resonance imaging (fMRI) studies have revealed abnormal neural activity in patients with type 2 diabetes mellitus (T2DM). Nonetheless, these findings are heterogeneous and have not been quantitatively reviewed. Thus, we aimed to conduct a meta-analysis that identified consistent results of existing resting-state fMRI studies to determine concordant resting-state neural brain activity alterations in T2DM patients. A systematic search was conducted for resting-state fMRI studies comparing T2DM patients with healthy controls. Coordinates were extracted from clusters with significant differences. The meta-analysis was performed using the activation likelihood estimation method, and nine studies were included. This meta-analysis identified robustly reduced resting-state brain activity in the whole brain of T2DM patients, including the bilateral lingual gyrus, left postcentral gyrus, right inferior temporal gyrus, right cerebellar culmen, right insula and right posterior cingulate cortex (PCC). The present study demonstrates a characteristic pattern of resting-state brain anomalies that will contribute to the understanding of neuropathophysiological mechanisms underlying T2DM. PMID:28197096

  9. The Moli-sani project: computerized ECG database in a population-based cohort study.

    PubMed

    Iacoviello, Licia; Rago, Livia; Costanzo, Simona; Di Castelnuovo, Augusto; Zito, Francesco; Assanelli, Deodato; Badilini, Fabio; Donati, Maria Benedetta; de Gaetano, Giovanni

    2012-01-01

    Computerized electrocardiogram (ECG) acquisition and interpretation may be extremely useful in handling analysis of data from large cohort studies and exploit research on the use of ECG data as prognostic markers for cardiovascular disease. The Moli-sani project (http://www.moli-sani.org) is a population-based cohort study aiming at evaluating the risk factors linked to chronic-degenerative disease with particular regard to cardiovascular disease and cancer and intermediate metabolic phenotypes such as hypertension, diabetes, dyslipidemia, obesity, and metabolic syndrome. Between March 2005 and April 2010, 24 325 people aged 35 years or older, living in the Molise region (Italy), were randomly recruited. A follow-up based on linkage with hospital discharge records and mortality regional registry and reexamination of the cohort is ongoing and will be repeated at prefixed times. Each subject was administered questionnaires on personal and medical history, food consumption, quality of life (FS36), and psychometry. Plasma serum, cellular pellet, and urinary spots were stored in liquid nitrogen. Subjects were measured blood pressure, weight, height, and waist and hip circumferences, and underwent spirometry to evaluate pulmonary diffusion capacity, gas diffusion, and pulmonary volumes. Standard 12-lead resting ECG was performed by a Cardiette ar2100-view electrocardiograph and tracings stored in digital standard communication protocol format for subsequent analysis. The digital ECG database of the Moli-sani project is currently being used to assess the association between physiologic variables and pathophyiosiologic conditions and parameters derived from the ECG signal. This computerized ECG database represents a unique opportunity to identify and assess prognostic factors associated with cardiovascular and metabolic diseases.

  10. Human ECG signal parameters estimation during controlled physical activity

    NASA Astrophysics Data System (ADS)

    Maciejewski, Marcin; Surtel, Wojciech; Dzida, Grzegorz

    2015-09-01

    ECG signal parameters are commonly used indicators of human health condition. In most cases the patient should remain stationary during the examination to decrease the influence of muscle artifacts. During physical activity, the noise level increases significantly. The ECG signals were acquired during controlled physical activity on a stationary bicycle and during rest. Afterwards, the signals were processed using a method based on Pan-Tompkins algorithms to estimate their parameters and to test the method.

  11. The chaos and order in human ECG under the influence of the external perturbations

    NASA Astrophysics Data System (ADS)

    Ragulskaya, Maria; Valeriy, Pipin

    The results of the many-year telecommunication heliomedical monitoring "Heliomed" show, that space weather and geophysical factor variations serve as a training factor for the adaptation-resistant member of the human population. Here we discuss the specific properties of the human ECG discovered in our experiment. The program "Heliomed" is carried out simultaneously at the different geographical areas that cover the different latitudes. The daily registered param-eters include: the psycho-emotional tests and the 1-st lead ECG, the arterial pressure, the variability cardiac contraction, the electric conduction of bioactive points on skin. The results time series compared with daily values of space weather and geomagnetic parameters. The analysis of ECG signal proceeds as follows. At first step we construct the ECG embedding into 3D phase space using the first 3 Principal Components of the ECG time series. Next, we divide ECG on the separate cycles using the maxima of the ECG's QRS complex. Then, we filter out the non-typical ECG beats by means of the Housdorff distance. Finally, we average the example of the ECG time series along the reference trajectory and study of the dynamical characteristics of the averaged ECG beat. It is found, that the ECG signal embeded in 3D phase space can be considered as a mix of a few states. At the rest, the occurrence of the primary ECG state compare to additional ones is about 8:2. The occurrence of the primary state increases after the stress. The main effect of the external perturbation is observed in structural change of the cardio-cycle and not in the variability of the R-R interval. The num-ber of none-typical cycles increase during an isolated magnetic storm. At the all monitoring centers participating experiment the same type of changes in the cardiac activity parameters is detected to go nearly simultaneously during an isolated magnetic storm. To understand the origin of the standard cardio-cycle changes we use the dynamical

  12. The Cardiac Safety Research Consortium ECG database.

    PubMed

    Kligfield, Paul; Green, Cynthia L

    2012-01-01

    The Cardiac Safety Research Consortium (CSRC) ECG database was initiated to foster research using anonymized, XML-formatted, digitized ECGs with corresponding descriptive variables from placebo- and positive-control arms of thorough QT studies submitted to the US Food and Drug Administration (FDA) by pharmaceutical sponsors. The database can be expanded to other data that are submitted directly to CSRC from other sources, and currently includes digitized ECGs from patients with genotyped varieties of congenital long-QT syndrome; this congenital long-QT database is also linked to ambulatory electrocardiograms stored in the Telemetric and Holter ECG Warehouse (THEW). Thorough QT data sets are available from CSRC for unblinded development of algorithms for analysis of repolarization and for blinded comparative testing of algorithms developed for the identification of moxifloxacin, as used as a positive control in thorough QT studies. Policies and procedures for access to these data sets are available from CSRC, which has developed tools for statistical analysis of blinded new algorithm performance. A recently approved CSRC project will create a data set for blinded analysis of automated ECG interval measurements, whose initial focus will include comparison of four of the major manufacturers of automated electrocardiographs in the United States. CSRC welcomes application for use of the ECG database for clinical investigation.

  13. Wavelets for full reconfigurable ECG acquisition system

    NASA Astrophysics Data System (ADS)

    Morales, D. P.; García, A.; Castillo, E.; Meyer-Baese, U.; Palma, A. J.

    2011-06-01

    This paper presents the use of wavelet cores for a full reconfigurable electrocardiogram signal (ECG) acquisition system. The system is compound by two reconfigurable devices, a FPGA and a FPAA. The FPAA is in charge of the ECG signal acquisition, since this device is a versatile and reconfigurable analog front-end for biosignals. The FPGA is in charge of FPAA configuration, digital signal processing and information extraction such as heart beat rate and others. Wavelet analysis has become a powerful tool for ECG signal processing since it perfectly fits ECG signal shape. The use of these cores has been integrated in the LabVIEW FPGA module development tool that makes possible to employ VHDL cores within the usual LabVIEW graphical programming environment, thus freeing the designer from tedious and time consuming design of communication interfaces. This enables rapid test and graphical representation of results.

  14. Sensitivity- and effort-gain analysis: multilead ECG electrode array selection for activation time imaging.

    PubMed

    Hintermüller, Christoph; Seger, Michael; Pfeifer, Bernhard; Fischer, Gerald; Modre, Robert; Tilg, Bernhard

    2006-10-01

    Methods for noninvasive imaging of electric function of the heart might become clinical standard procedure the next years. Thus, the overall procedure has to meet clinical requirements as an easy and fast application. In this paper, we propose a new electrode array which improves the resolution of methods for activation time imaging considering clinical constraints such as easy to apply and compatibility with routine leads. For identifying the body-surface regions where the body surface potential (BSP) is most sensitive to changes in transmembrane potential (TMP), a virtual array method was used to compute local linear dependency (LLD) maps. The virtual array method computes a measure for the LLD in every point on the body surface. The most suitable number and position of the electrodes within the sensitive body surface regions was selected by constructing effort gain (EG) plots. Such a plot depicts the relative attainable rank of the leadfield matrix in relation to the increase in number of electrodes required to build the electrode array. The attainable rank itself was computed by a detector criterion. Such a criterion estimates the maximum number of source space eigenvectors not covered by noise when being mapped to the electrode space by the leadfield matrix and recorded by a detector. From the sensitivity maps, we found that the BSP is most sensitive to changes in TMP on the upper left frontal and dorsal body surface. These sensitive regions are covered best by an electrode array consisting of two L-shaped parts of approximately 30 cm x 30 cm and approximately 20 cm x 20 cm. The EG analysis revealed that the array meeting clinical requirements best and improving the resolution of activation time imaging consists of 125 electrodes with a regular horizontal and vertical spacing of 2-3 cm.

  15. Sparse dictionary learning for resting-state fMRI analysis

    NASA Astrophysics Data System (ADS)

    Lee, Kangjoo; Han, Paul Kyu; Ye, Jong Chul

    2011-09-01

    Recently, there has been increased interest in the usage of neuroimaging techniques to investigate what happens in the brain at rest. Functional imaging studies have revealed that the default-mode network activity is disrupted in Alzheimer's disease (AD). However, there is no consensus, as yet, on the choice of analysis method for the application of resting-state analysis for disease classification. This paper proposes a novel compressed sensing based resting-state fMRI analysis tool called Sparse-SPM. As the brain's functional systems has shown to have features of complex networks according to graph theoretical analysis, we apply a graph model to represent a sparse combination of information flows in complex network perspectives. In particular, a new concept of spatially adaptive design matrix has been proposed by implementing sparse dictionary learning based on sparsity. The proposed approach shows better performance compared to other conventional methods, such as independent component analysis (ICA) and seed-based approach, in classifying the AD patients from normal using resting-state analysis.

  16. Cross coherence independent component analysis in resting and action states EEG discrimination

    NASA Astrophysics Data System (ADS)

    Almurshedi, A.; Ismail, A. K.

    2014-11-01

    Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition.

  17. Resting-State Brain Abnormalities in Chronic Subjective Tinnitus: A Meta-Analysis

    PubMed Central

    Chen, Yu-Chen; Wang, Fang; Wang, Jie; Bo, Fan; Xia, Wenqing; Gu, Jian-Ping; Yin, Xindao

    2017-01-01

    Purpose: The neural mechanisms that give rise to the phantom sound of tinnitus have not been fully elucidated. Neuroimaging studies have revealed abnormalities in resting-state activity that could represent the neural signature of tinnitus, but there is considerable heterogeneity in the data. To address this issue, we conducted a meta-analysis of published neuroimaging studies aimed at identifying a common core of resting-state brain abnormalities in tinnitus patients. Methods: A systematic search was conducted for whole-brain resting-state neuroimaging studies with SPECT, PET and functional MRI that compared chronic tinnitus patients with healthy controls. The authors searched PubMed, Science Direct, Web of Knowledge and Embase databases for neuroimaging studies on tinnitus published up to September 2016. From each study, coordinates were extracted from clusters with significant differences between tinnitus subjects and controls. Meta-analysis was performed using the activation likelihood estimation (ALE) method. Results: Data were included from nine resting-state neuroimaging studies that reported a total of 51 distinct foci. The meta-analysis identified consistent regions of increased resting-state brain activity in tinnitus patients relative to controls that included, bilaterally, the insula, middle temporal gyrus (MTG), inferior frontal gyrus (IFG), parahippocampal gyrus, cerebellum posterior lobe and right superior frontal gyrus. Moreover, decreased brain activity was only observed in the left cuneus and right thalamus. Conclusions: The current meta-analysis is, to our knowledge, the first to demonstrate a characteristic pattern of resting-state brain abnormalities that may serve as neuroimaging markers and contribute to the understanding of neuropathophysiological mechanisms for chronic tinnitus. PMID:28174532

  18. Resting-State Brain Abnormalities in Chronic Subjective Tinnitus: A Meta-Analysis.

    PubMed

    Chen, Yu-Chen; Wang, Fang; Wang, Jie; Bo, Fan; Xia, Wenqing; Gu, Jian-Ping; Yin, Xindao

    2017-01-01

    Purpose: The neural mechanisms that give rise to the phantom sound of tinnitus have not been fully elucidated. Neuroimaging studies have revealed abnormalities in resting-state activity that could represent the neural signature of tinnitus, but there is considerable heterogeneity in the data. To address this issue, we conducted a meta-analysis of published neuroimaging studies aimed at identifying a common core of resting-state brain abnormalities in tinnitus patients. Methods: A systematic search was conducted for whole-brain resting-state neuroimaging studies with SPECT, PET and functional MRI that compared chronic tinnitus patients with healthy controls. The authors searched PubMed, Science Direct, Web of Knowledge and Embase databases for neuroimaging studies on tinnitus published up to September 2016. From each study, coordinates were extracted from clusters with significant differences between tinnitus subjects and controls. Meta-analysis was performed using the activation likelihood estimation (ALE) method. Results: Data were included from nine resting-state neuroimaging studies that reported a total of 51 distinct foci. The meta-analysis identified consistent regions of increased resting-state brain activity in tinnitus patients relative to controls that included, bilaterally, the insula, middle temporal gyrus (MTG), inferior frontal gyrus (IFG), parahippocampal gyrus, cerebellum posterior lobe and right superior frontal gyrus. Moreover, decreased brain activity was only observed in the left cuneus and right thalamus. Conclusions: The current meta-analysis is, to our knowledge, the first to demonstrate a characteristic pattern of resting-state brain abnormalities that may serve as neuroimaging markers and contribute to the understanding of neuropathophysiological mechanisms for chronic tinnitus.

  19. Tissue Doppler Imaging Combined with Advanced 12-Lead ECG Analysis Might Improve Early Diagnosis of Hypertrophic Cardiomyopathy in Childhood

    NASA Technical Reports Server (NTRS)

    Femlund, E.; Schlegel, T.; Liuba, P.

    2011-01-01

    Optimization of early diagnosis of childhood hypertrophic cardiomyopathy (HCM) is essential in lowering the risk of HCM complications. Standard echocardiography (ECHO) has shown to be less sensitive in this regard. In this study, we sought to assess whether spatial QRS-T angle deviation, which has shown to predict HCM in adults with high sensitivity, and myocardial Tissue Doppler Imaging (TDI) could be additional tools in early diagnosis of HCM in childhood. Methods: Children and adolescents with familial HCM (n=10, median age 16, range 5-27 years), and without obvious hypertrophy but with heredity for HCM (n=12, median age 16, range 4-25 years, HCM or sudden death with autopsy-verified HCM in greater than or equal to 1 first-degree relative, HCM-risk) were additionally investigated with TDI and advanced 12-lead ECG analysis using Cardiax(Registered trademark) (IMED Co Ltd, Budapest, Hungary and Houston). Spatial QRS-T angle (SA) was derived from Kors regression-related transformation. Healthy age-matched controls (n=21) were also studied. All participants underwent thorough clinical examination. Results: Spatial QRS-T angle (Figure/ Panel A) and septal E/Ea ratio (Figure/Panel B) were most increased in HCM group as compared to the HCM-risk and control groups (p less than 0.05). Of note, these 2 variables showed a trend toward higher levels in HCM-risk group than in control group (p=0.05 for E/Ea and 0.06 for QRS/T by ANOVA). In a logistic regression model, increased SA and septal E/Ea ratio appeared to significantly predict both the disease (Chi-square in HCM group: 9 and 5, respectively, p less than 0.05 for both) and the risk for HCM (Chi-square in HCM-risk group: 5 and 4 respectively, p less than 0.05 for both), with further increased predictability level when these 2 variables were combined (Chi-square 10 in HCM group, and 7 in HCM-risk group, p less than 0.01 for both). Conclusions: In this small material, Tissue Doppler Imaging and spatial mean QRS-T angle

  20. Brugada ECG Pattern Unmasked by IV Flecainide in an Individual with Idiopathic Fascicular Ventricular Tachycardia.

    PubMed

    Gavin, Andrew R; Young, Glenn D; McGavigan, Andrew D

    2013-01-01

    A 45-year old man presents with stable monomorphic ventricular tachycardia. He had previously been diagnosed with idiopathic fascicular ventricular tachycardia. Intravenous flecainide results in termination of his tachycardia but unmasks a latent type 1 Brugada ECG pattern not seen on his resting ECG. We discuss his subsequent management and the need to consider an alternative diagnosis in individuals with a Brugada type ECG pattern who present with stable monomorphic ventricular tachycardia.

  1. Accuracy of advanced versus strictly conventional 12-lead ECG for detection and screening of coronary artery disease, left ventricular hypertrophy and left ventricular systolic dysfunction

    PubMed Central

    2010-01-01

    Background Resting conventional 12-lead ECG has low sensitivity for detection of coronary artery disease (CAD) and left ventricular hypertrophy (LVH) and low positive predictive value (PPV) for prediction of left ventricular systolic dysfunction (LVSD). We hypothesized that a ~5-min resting 12-lead advanced ECG test ("A-ECG") that combined results from both the advanced and conventional ECG could more accurately screen for these conditions than strictly conventional ECG. Methods Results from nearly every conventional and advanced resting ECG parameter known from the literature to have diagnostic or predictive value were first retrospectively evaluated in 418 healthy controls and 290 patients with imaging-proven CAD, LVH and/or LVSD. Each ECG parameter was examined for potential inclusion within multi-parameter A-ECG scores derived from multivariate regression models that were designed to optimally screen for disease in general or LVSD in particular. The performance of the best retrospectively-validated A-ECG scores was then compared against that of optimized pooled criteria from the strictly conventional ECG in a test set of 315 additional individuals. Results Compared to optimized pooled criteria from the strictly conventional ECG, a 7-parameter A-ECG score validated in the training set increased the sensitivity of resting ECG for identifying disease in the test set from 78% (72-84%) to 92% (88-96%) (P < 0.0001) while also increasing specificity from 85% (77-91%) to 94% (88-98%) (P < 0.05). In diseased patients, another 5-parameter A-ECG score increased the PPV of ECG for LVSD from 53% (41-65%) to 92% (78-98%) (P < 0.0001) without compromising related negative predictive value. Conclusion Resting 12-lead A-ECG scoring is more accurate than strictly conventional ECG in screening for CAD, LVH and LVSD. PMID:20565702

  2. Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals

    NASA Astrophysics Data System (ADS)

    Sameni, Reza; Clifford, Gari D.; Jutten, Christian; Shamsollahi, Mohammad B.

    2007-12-01

    A three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.

  3. Denoising of ECG signal during spaceflight using singular value decomposition

    NASA Astrophysics Data System (ADS)

    Li, Zhuo; Wang, Li

    2009-12-01

    The Singular Value Decomposition (SVD) method is introduced to denoise the ECG signal during spaceflight. The theory base of SVD method is given briefly. The denoising process of the strategy is presented combining a segment of real ECG signal. We improve the algorithm of calculating Singular Value Ratio (SVR) spectrum, and propose a constructive approach of analysis characteristic patterns. We reproduce the ECG signal very well and compress the noise effectively. The SVD method is proved to be suitable for denoising the ECG signal.

  4. Hybrid ECG signal conditioner

    NASA Technical Reports Server (NTRS)

    Rinard, G. A.; Steffen, D. A.; Sturm, R. E.

    1979-01-01

    Circuit with high common-mode rejection has ability to filter and amplify accepted analog electrocardiogram (ECG) signals of varying amplitude, shape, and polarity. In addition, low power circuit develops standardized pulses that can be counted and averaged by heart/breath rate processor.

  5. Energy landscape analysis of the subcortical brain network unravels system properties beneath resting state dynamics.

    PubMed

    Kang, Jiyoung; Pae, Chongwon; Park, Hae-Jeong

    2017-04-01

    The configuration of the human brain system at rest, which is in a transitory phase among multistable states, remains unknown. To investigate the dynamic systems properties of the human brain at rest, we constructed an energy landscape for the state dynamics of the subcortical brain network, a critical center that modulates whole brain states, using resting state fMRI. We evaluated alterations in energy landscapes following perturbation in network parameters, which revealed characteristics of the state dynamics in the subcortical brain system, such as maximal number of attractors, unequal temporal occupations, and readiness for reconfiguration of the system. Perturbation in the network parameters, even those as small as the ones in individual nodes or edges, caused a significant shift in the energy landscape of brain systems. The effect of the perturbation on the energy landscape depended on the network properties of the perturbed nodes and edges, with greater effects on hub nodes and hubs-connecting edges in the subcortical brain system. Two simultaneously perturbed nodes produced perturbation effects showing low sensitivity in the interhemispheric homologous nodes and strong dependency on the more primary node among the two. This study demonstrated that energy landscape analysis could be an important tool to investigate alterations in brain networks that may underlie certain brain diseases, or diverse brain functions that may emerge due to the reconfiguration of the default brain network at rest.

  6. Disturbed resting state EEG synchronization in bipolar disorder: A graph-theoretic analysis.

    PubMed

    Kim, Dae-Jin; Bolbecker, Amanda R; Howell, Josselyn; Rass, Olga; Sporns, Olaf; Hetrick, William P; Breier, Alan; O'Donnell, Brian F

    2013-01-01

    Disruption of functional connectivity may be a key feature of bipolar disorder (BD) which reflects disturbances of synchronization and oscillations within brain networks. We investigated whether the resting electroencephalogram (EEG) in patients with BD showed altered synchronization or network properties. Resting-state EEG was recorded in 57 BD type-I patients and 87 healthy control subjects. Functional connectivity between pairs of EEG channels was measured using synchronization likelihood (SL) for 5 frequency bands (δ, θ, α, β, and γ). Graph-theoretic analysis was applied to SL over the electrode array to assess network properties. BD patients showed a decrease of mean synchronization in the alpha band, and the decreases were greatest in fronto-central and centro-parietal connections. In addition, the clustering coefficient and global efficiency were decreased in BD patients, whereas the characteristic path length increased. We also found that the normalized characteristic path length and small-worldness were significantly correlated with depression scores in BD patients. These results suggest that BD patients show impaired neural synchronization at rest and a disruption of resting-state functional connectivity.

  7. Cluster analysis of resting-state fMRI time series.

    PubMed

    Mezer, Aviv; Yovel, Yossi; Pasternak, Ofer; Gorfine, Tali; Assaf, Yaniv

    2009-05-01

    Functional MRI (fMRI) has become one of the leading methods for brain mapping in neuroscience. Recent advances in fMRI analysis were used to define the default state of brain activity, functional connectivity and basal activity. Basal activity measured with fMRI raised tremendous interest among neuroscientists since synchronized brain activity pattern could be retrieved while the subject rests (resting state fMRI). During recent years, a few signal processing schemes have been suggested to analyze the resting state blood oxygenation level dependent (BOLD) signal from simple correlations to spectral decomposition. In most of these analysis schemes, the question asked was which brain areas "behave" in the time domain similarly to a pre-specified ROI. In this work we applied short time frequency analysis and clustering to study the spatial signal characteristics of resting state fMRI time series. Such analysis revealed that clusters of similar BOLD fluctuations are found in the cortex but also in the white matter and sub-cortical gray matter regions (thalamus). We found high similarities between the BOLD clusters and the neuro-anatomical appearance of brain regions. Additional analysis of the BOLD time series revealed a strong correlation between head movements and clustering quality. Experiments performed with T1-weighted time series also provided similar quality of clustering. These observations led us to the conclusion that non-functional contributions to the BOLD time series can also account for symmetric appearance of signal fluctuations. These contributions may include head motions, the underling microvasculature anatomy and cellular morphology.

  8. Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping

    PubMed Central

    Meszlényi, Regina J.; Hermann, Petra; Buza, Krisztian; Gál, Viktor; Vidnyánszky, Zoltán

    2017-01-01

    Traditional resting-state network concept is based on calculating linear dependence of spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which assumes temporally stable zero-lag synchrony across regions. However, growing amount of experimental findings suggest that functional connectivity exhibits dynamic changes and a complex time-lag structure, which cannot be captured by the static zero-lag correlation analysis. Here we propose a new approach applying Dynamic Time Warping (DTW) distance to evaluate functional connectivity strength that accounts for non-stationarity and phase-lags between the observed signals. Using simulated fMRI data we found that DTW captures dynamic interactions and it is less sensitive to linearly combined global noise in the data as compared to traditional correlation analysis. We tested our method using resting-state fMRI data from repeated measurements of an individual subject and showed that DTW analysis results in more stable connectivity patterns by reducing the within-subject variability and increasing robustness for preprocessing strategies. Classification results on a public dataset revealed a superior sensitivity of the DTW analysis to group differences by showing that DTW based classifiers outperform the zero-lag correlation and maximal lag cross-correlation based classifiers significantly. Our findings suggest that analysing resting-state functional connectivity using DTW provides an efficient new way for characterizing functional networks. PMID:28261052

  9. High Resolution ECG for Evaluation of Heart Function During Exposure to Subacute Hypobaric Hypoxia

    NASA Technical Reports Server (NTRS)

    Zupet, Petra; Finderle, Zarko; Schlegel, Todd T.; Princi, Tanja; Starc, Vito

    2010-01-01

    High altitude climbing presents a wide spectrum of health risks, including exposure to hypobaric hypoxia. Risks are also typically exacerbated by the difficulty in appropriately monitoring for early signs of organ dysfunction in remote areas. We investigated whether high resolution advanced ECG analysis might be helpful as a non-invasive and easy-to-use tool (e.g., instead of Doppler echocardiography) for evaluating early signs of heart overload in hypobaric hypoxia. Nine non-acclimatized healthy trained alpine rescuers (age 43.7 plus or minus 7.3 years) climbed in four days to the altitude of 4,200 m on Mount Ararat. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position on different days but at the same time of day at four different altitudes: 400 m (reference altitude), 1,700 m, 3,200 m and 4,200 m. Changes in conventional and advanced resting ECG parameters, including in beat-to-beat QT and RR variability, waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG was estimated by calculation of the regression coefficients in independent linear regression models. A p-value of less than 0.05 was adopted as statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with trends k = -96 ms/1000 m with p = 0.000 and k = -9 ms/1000 m with p = 0.001, respectively. Significant changes were found in P-wave amplitude, which nearly doubled from the lowest to the highest altitude (k = 41.6 microvolt/1000 m with p = 0.000), and nearly significant changes in P-wave duration (k = 2.9 ms/1000 m with p = 0.059). Changes were less significant or non-significant in other studied parameters including those of waveform complexity, signal-averaged, high-frequency and spatial/spatiotemporal ECG. High resolution ECG analysis, particularly of the P wave, shows promise as a tool for monitoring early changes in heart function

  10. Quantitative analysis of arterial flow properties for detection of non-calcified plaques in ECG-gated coronary CT angiography

    NASA Astrophysics Data System (ADS)

    Wei, Jun; Zhou, Chuan; Chan, Heang-Ping; Chughtai, Aamer; Agarwal, Prachi; Kuriakose, Jean; Hadjiiski, Lubomir; Patel, Smita; Kazerooni, Ella

    2015-03-01

    We are developing a computer-aided detection system to assist radiologists in detection of non-calcified plaques (NCPs) in coronary CT angiograms (cCTA). In this study, we performed quantitative analysis of arterial flow properties in each vessel branch and extracted flow information to differentiate the presence and absence of stenosis in a vessel segment. Under rest conditions, blood flow in a single vessel branch was assumed to follow Poiseuille's law. For a uniform pressure distribution, two quantitative flow features, the normalized arterial compliance per unit length (Cu) and the normalized volumetric flow (Q) along the vessel centerline, were calculated based on the parabolic Poiseuille solution. The flow features were evaluated for a two-class classification task to differentiate NCP candidates obtained by prescreening as true NCPs and false positives (FPs) in cCTA. For evaluation, a data set of 83 cCTA scans was retrospectively collected from 83 patient files with IRB approval. A total of 118 NCPs were identified by experienced cardiothoracic radiologists. The correlation between the two flow features was 0.32. The discriminatory ability of the flow features evaluated as the area under the ROC curve (AUC) was 0.65 for Cu and 0.63 for Q in comparison with AUCs of 0.56-0.69 from our previous luminal features. With stepwise LDA feature selection, volumetric flow (Q) was selected in addition to three other luminal features. With FROC analysis, the test results indicated a reduction of the FP rates to 3.14, 1.98, and 1.32 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively. The study indicated that quantitative blood flow analysis has the potential to provide useful features for the detection of NCPs in cCTA.

  11. Graph network analysis of immediate motor-learning induced changes in resting state BOLD.

    PubMed

    Sami, S; Miall, R C

    2013-01-01

    Recent studies have demonstrated that following learning tasks, changes in the resting state activity of the brain shape regional connections in functionally specific circuits. Here we expand on these findings by comparing changes induced in the resting state immediately following four motor tasks. Two groups of participants performed a visuo-motor joystick task with one group adapting to a transformed relationship between joystick and cursor. Two other groups were trained in either explicit or implicit procedural sequence learning. Resting state BOLD data were collected immediately before and after the tasks. We then used graph theory-based approaches that include statistical measures of functional integration and segregation to characterize changes in biologically plausible brain connectivity networks within each group. Our results demonstrate that motor learning reorganizes resting brain networks with an increase in local information transfer, as indicated by local efficiency measures that affect the brain's small world network architecture. This was particularly apparent when comparing two distinct forms of explicit motor learning: procedural learning and the joystick learning task. Both groups showed notable increases in local efficiency. However, a change in local efficiency in the inferior frontal and cerebellar regions also distinguishes between the two learning tasks. Additional graph analytic measures on the "non-learning" visuo-motor performance task revealed reversed topological patterns in comparison with the three learning tasks. These findings underscore the utility of graph-based network analysis as a novel means to compare both regional and global changes in functional brain connectivity in the resting state following motor learning tasks.

  12. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism

    PubMed Central

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms. PMID:27695408

  13. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism.

    PubMed

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

  14. Singular spectrum analysis and adaptive filtering enhance the functional connectivity analysis of resting state fMRI data.

    PubMed

    Piaggi, Paolo; Menicucci, Danilo; Gentili, Claudio; Handjaras, Giacomo; Gemignani, Angelo; Landi, Alberto

    2014-05-01

    Sources of noise in resting-state fMRI experiments include instrumental and physiological noises, which need to be filtered before a functional connectivity analysis of brain regions is performed. These noisy components show autocorrelated and nonstationary properties that limit the efficacy of standard techniques (i.e. time filtering and general linear model). Herein we describe a novel approach based on the combination of singular spectrum analysis and adaptive filtering, which allows a greater noise reduction and yields better connectivity estimates between regions at rest, providing a new feasible procedure to analyze fMRI data.

  15. The programmable ECG simulator.

    PubMed

    Caner, Candan; Engin, Mehmet; Engin, Erkan Zeki

    2008-08-01

    This paper reports the design and development of Digital Signal Controller (DSPIC)-based ECG simulator intended to use in testing, calibration and maintenance of electrocardiographic equipment, and to support biomedical engineering students' education. It generates all 12 healthy ECG derivation signals having a profile that varies with heart rate, amplitude, and different noise contamination in a manner which reflects true in vivo conditions. The heart rate can be set at the range of 30 to 120 beats/minute in four steps. The noise and power line interference effects can be set at the range of 0 to 20 dB in three steps. Since standard commercially available electronic components were used to construct the prototype simulator, the proposed design was also relatively inexpensive to produce.

  16. Large-scale Granger causality analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  17. Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data.

    PubMed

    Ramkumar, Pavan; Parkkonen, Lauri; Hyvärinen, Aapo

    2014-02-01

    We developed a data-driven method to spatiotemporally and spectrally characterize the dynamics of brain oscillations in resting-state magnetoencephalography (MEG) data. The method, called envelope spatial Fourier independent component analysis (eSFICA), maximizes the spatial and spectral sparseness of Fourier energies of a cortically constrained source current estimate. We compared this method using a simulated data set against 5 other variants of independent component analysis and found that eSFICA performed on par with its temporal variant, eTFICA, and better than other ICA variants, in characterizing dynamics at time scales of the order of minutes. We then applied eSFICA to real MEG data obtained from 9 subjects during rest. The method identified several networks showing within- and cross-frequency inter-areal functional connectivity profiles which resemble previously reported resting-state networks, such as the bilateral sensorimotor network at ~20Hz, the lateral and medial parieto-occipital sources at ~10Hz, a subset of the default-mode network at ~8 and ~15Hz, and lateralized temporal lobe sources at ~8Hz. Finally, we interpreted the estimated networks as spatiospectral filters and applied the filters to obtain the dynamics during a natural stimulus sequence presented to the same 9 subjects. We observed occipital alpha modulation to visual stimuli, bilateral rolandic mu modulation to tactile stimuli and video clips of hands, and the temporal lobe network modulation to speech stimuli, but no modulation of the sources in the default-mode network. We conclude that (1) the proposed method robustly detects inter-areal cross-frequency networks at long time scales, (2) the functional relevance of the resting-state networks can be probed by applying the obtained spatiospectral filters to data from measurements with controlled external stimulation.

  18. Reduction of resting heart rate with antianginal drugs: review and meta-analysis.

    PubMed

    Cucherat, Michel; Borer, Jeffrey S

    2012-07-01

    The benefit of heart rate (HR) reduction in patients with stable coronary artery disease is well demonstrated for symptom prevention and relief, and benefits on outcomes are being actively investigated. We aimed to quantify the reduction in resting HR induced by 5 antianginal drugs frequently used for symptom prevention (diltiazem, verapamil, atenolol, metoprolol, and ivabradine) in stable angina pectoris. We identified studies published between 1966 and 2007 in PubMed, Embase, and the Cochrane database and reviewed the bibliographies to locate additional studies. Eligible studies were double-blind, randomized, placebo-controlled trials in patients with stable angina. Trials were combined using weighted mean difference and fixed-effect model meta-analysis. The main outcome measure was resting HR at the study end. For diltiazem, resting HR reduction versus placebo ranged from -0.08 beats per minute (bpm) [95% confidence interval (CI) -1.5 to +1.4] for 120 mg/d to -8.0 bpm (95% CI, -11.1 to -5.0) with 360 mg/d. For sustained-release diltiazem, there was a reduction in resting HR of -4.5 bpm (95% CI, -6.4 to -2.5), with no dose-response relationship (heterogeneity P = 0.62). Resting HR reductions for the other agents were -3.2 bpm (95% CI, -5.1 to -1.3) for verapamil (with no dose-response relationship, heterogeneity P = 0.87); -19.0 bpm (95% CI, -20.4 to -17.6) for atenolol; -13.2 bpm (95% CI, -14.7 to -11.7) for metoprolol (with greater reductions for 150 mg/d and long-acting 190 mg/d); and between -9.3 bpm (95% CI, -13.8 to -4.8) and -19.6 bpm (95% CI, -23.8 to -15.4) for ivabradine. Ivabradine, atenolol, and metoprolol give similar reductions in resting HR (-10 to -20 bpm), whereas verapamil and diltiazem produce only marginal reductions (<10 bpm).

  19. Frequency Clustering Analysis for Resting State Functional Magnetic Resonance Imaging Based on Hilbert-Huang Transform

    PubMed Central

    Wu, Xia; Wu, Tong; Liu, Chenghua; Wen, Xiaotong; Yao, Li

    2017-01-01

    Objective: Exploring resting-state functional networks using functional magnetic resonance imaging (fMRI) is a hot topic in the field of brain functions. Previous studies suggested that the frequency dependence between blood oxygen level dependent (BOLD) signals may convey meaningful information regarding interactions between brain regions. Methods: In this article, we introduced a novel frequency clustering analysis method based on Hilbert-Huang Transform (HHT) and a label-replacement procedure. First, the time series from multiple predefined regions of interest (ROIs) were extracted. Second, each time series was decomposed into several intrinsic mode functions (IMFs) by using HHT. Third, the improved k-means clustering method using a label-replacement method was applied to the data of each subject to classify the ROIs into different classes. Results: Two independent resting-state fMRI dataset of healthy subjects were analyzed to test the efficacy of method. The results show almost identical clusters when applied to different runs of a dataset or to different datasets, indicating a stable performance of our framework. Conclusions and Significance: Our framework provided a novel measure for functional segregation of the brain according to time-frequency characteristics of resting state BOLD activities. PMID:28261074

  20. Independent component analysis of localized resting-state functional magnetic resonance imaging reveals specific motor subnetworks.

    PubMed

    Sohn, William Seunghyun; Yoo, Kwangsun; Jeong, Yong

    2012-01-01

    Recent studies have shown that blood oxygen level-dependent low-frequency (<0.1 Hz) fluctuations (LFFs) during a resting-state exhibit a high degree of correlation with other regions that share cognitive function. Initial studies of resting-state network mapping have focused primarily on major networks such as the default mode network, primary motor, somatosensory, visual, and auditory networks. However, more specific or subnetworks, including those associated with specific motor functions, have yet to be properly addressed. We performed independent component analysis (ICA) in a specific target region of the brain, a process we name, "localized ICA." We demonstrated that when ICA is applied to localized fMRI data, it can be used to distinguish resting-state LFFs associated with specific motor functions (e.g., finger tapping, foot movement, or bilateral lip pulsing) in the primary motor cortex. These ICA components generated from localized data can then be used as functional regions of interest to map whole-brain connectivity. In addition, this method can be used to visualize inter-regional connectivity by expanding the localized region and identifying components that show connectivity between the two regions.

  1. Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis.

    PubMed

    Gopal, Shruti; Miller, Robyn L; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R; Cahill, Nathan; Baum, Stefi A; Calhoun, Vince D

    2016-01-01

    Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects.

  2. Independent component analysis of EEG dipole source localization in resting and action state of brain

    NASA Astrophysics Data System (ADS)

    Almurshedi, Ahmed; Ismail, Abd Khamim

    2015-04-01

    EEG source localization was studied in order to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes using EEGLAB with Independent Component Analysis (ICA) algorithm. Neuron source locations are responsible in generating current dipoles in different states of brain through the measured potentials. The current dipole sources localization are measured by fitting an equivalent current dipole model using a non-linear optimization technique with the implementation of standardized boundary element head model. To fit dipole models to ICA components in an EEGLAB dataset, ICA decomposition is performed and appropriate components to be fitted are selected. The topographical scalp distributions of delta, theta, alpha, and beta power spectrum and cross coherence of EEG signals are observed. In close eyes condition it shows that during resting and action states of brain, alpha band was activated from occipital (O1, O2) and partial (P3, P4) area. Therefore, parieto-occipital area of brain are active in both resting and action state of brain. However cross coherence tells that there is more coherence between right and left hemisphere in action state of brain than that in the resting state. The preliminary result indicates that these potentials arise from the same generators in the brain.

  3. A method of ECG template extraction for biometrics applications.

    PubMed

    Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

    2014-01-01

    ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

  4. Analysis of Arterial Mechanics During Head-down Tilt Bed Rest

    NASA Technical Reports Server (NTRS)

    Elliot, Morgan; Martin, David S.; Westby, Christian M.; Stenger, Michael B.; Platts, Steve

    2014-01-01

    Arterial health may be affected by microgravity or ground based analogs of spaceflight, as shown by an increase in thoracic aorta stiffness1. Head-down tilt bed rest (HDTBR) is often used as a ground-based simulation of spaceflight because it induces physiological changes similar to those that occur in space2, 3. This abstract details an analysis of arterial stiffness (a subclinical measure of atherosclerosis), the distensibility coefficient (DC), and the pressure-strain elastic modulus (PSE) of the arterial walls during HDTBR. This project may help determine how spaceflight differentially affects arterial function in the upper vs. lower body.

  5. Digitalis toxicity: ECG vignette.

    PubMed

    Vyas, Aniruddha; Bachani, Neeta; Thakur, Hrishikesh; Lokhandwala, Yash

    2016-09-01

    "Digitalis toxicity, often candidly indexed as poisoning, has plagued the medical profession for over 200 years. The situation qualifies as a professional disgrace on the basis of three items: the situation persists, physicians are often slow to recognize it and, over the decades, writers have been harsh in their denunciation of fellow physicians when toxicity has occurred…." These are the opening remarks of an essay published in 1983 on the 2nd centenary of William Withering's 'magic potion from foxglove's extract for dropsy.' Even today, after many decades, these words appear relevant! We present and discuss an interesting ECG of digitalis toxicity.

  6. Multi-level bootstrap analysis of stable clusters in resting-state fMRI.

    PubMed

    Bellec, Pierre; Rosa-Neto, Pedro; Lyttelton, Oliver C; Benali, Habib; Evans, Alan C

    2010-07-01

    A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features across all replications. This bootstrap analysis of stable clusters (BASC) has several benefits: (1) it can be implemented in a multi-level fashion to investigate stable RSNs at the level of individual subjects and at the level of a group; (2) it provides a principled measure of RSN stability; and (3) the maximization of the stability measure can be used as a natural criterion to select the number of RSNs. A simulation study validated the good performance of the multi-level BASC on purely synthetic data. Stable networks were also derived from a real resting-state study for 43 subjects. At the group level, seven RSNs were identified which exhibited a good agreement with the previous findings from the literature. The comparison between the individual and group-level stability maps demonstrated the capacity of BASC to establish successful correspondences between these two levels of analysis and at the same time retain some interesting subject-specific characteristics, e.g. the specific involvement of subcortical regions in the visual and fronto-parietal networks for some subjects.

  7. Brugada ECG patterns in athletes.

    PubMed

    Chung, Eugene H

    2015-01-01

    Brugada syndrome is responsible for up to 4% of all sudden cardiac deaths worldwide and up to 20% of sudden cardiac deaths in patients with structurally normal hearts. Heterogeneity of repolarization and depolarization, particularly over the right ventricle and the outflow tract, is responsible for the arrhythmogenic substrate. The coved Type I ECG pattern is considered diagnostic of the syndrome but its prevalence is very low. Distinguishing between a saddle back Type 2 Brugada pattern and one of many "Brugada-like" patterns presents challenges especially in athletes. A number of criteria have been proposed to assess Brugada ECG patterns. Proper precordial ECG lead placement is paramount. This paper reviews Brugada syndrome, Brugada ECG patterns, and recently proposed criteria. Recommendations for evaluating a Brugada ECG pattern are provided.

  8. Wavelet-based regularity analysis reveals Recurrent Spatiotemporal Behavior in Resting-state fMRI

    PubMed Central

    Smith, Robert X.; Jann, Kay; Ances, Beau; Wang, Danny J.J.

    2015-01-01

    One of the major findings from multi-modal neuroimaging studies in the past decade is that the human brain is anatomically and functionally organized into large-scale networks. In resting state fMRI (rs-fMRI), spatial patterns emerge when temporal correlations between various brain regions are tallied, evidencing networks of ongoing intercortical cooperation. However, the dynamic structure governing the brain’s spontaneous activity is far less understood due to the short and noisy nature of the rs-fMRI signal. Here we develop a wavelet-based regularity analysis based on noise estimation capabilities of the wavelet transform to measure recurrent temporal pattern stability within the rs-fMRI signal across multiple temporal scales. The method consists of performing a stationary wavelet transform (SWT) to preserve signal structure, followed by construction of “lagged” subsequences to adjust for correlated features, and finally the calculation of sample entropy across wavelet scales based on an “objective” estimate of noise level at each scale. We found that the brain’s default mode network (DMN) areas manifest a higher level of irregularity in rs-fMRI time series than rest of the brain. In 25 aged subjects with mild cognitive impairment and 25 matched healthy controls, wavelet based regularity analysis showed improved sensitivity in detecting changes in the regularity of rs-fMRI signals between the two groups within the DMN and executive control networks, compared to standard multiscale entropy analysis. Wavelet based regularity analysis based on noise estimation capabilities of the wavelet transform is a promising technique to characterize the dynamic structure of rs-fMRI as well as other biological signals. PMID:26096080

  9. Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

    NASA Astrophysics Data System (ADS)

    Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

    2016-03-01

    Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

  10. Localized connectivity in depression: a meta-analysis of resting state functional imaging studies.

    PubMed

    Iwabuchi, Sarina J; Krishnadas, Rajeev; Li, Chunbo; Auer, Dorothee P; Radua, Joaquim; Palaniyappan, Lena

    2015-04-01

    Resting-state fMRI studies investigating the pathophysiology of depression have identified prominent abnormalities in large-scale brain networks. However, it is unclear if localized dysfunction of specialized brain regions contribute to network-level abnormalities. We employed a meta-analytical procedure and reviewed studies conducted in China investigating changes in regional homogeneity (ReHo), a measure of localized intraregional connectivity, from resting-state fMRI in depression. Exploiting the statistical power gained from pooled analysis, we also investigated the effects of age, gender, illness duration and treatment on ReHo. The medial prefrontal cortex (MPFC) showed the most robust and reliable increase in ReHo in depression, with greater abnormality in medication-free patients with multiple episodes. Brain networks that relate to this region have been identified previously to show aberrant connectivity in depression, and we propose that the localized neuronal inefficiency of MPFC exists alongside wider network level disruptions involving this region.

  11. ECG parameters and exposure to carbon ultrafine particles in young healthy subjects.

    PubMed

    Zareba, Wojciech; Couderc, Jean Philippe; Oberdörster, Günter; Chalupa, David; Cox, Christopher; Huang, Li-Shan; Peters, Annette; Utell, Mark J; Frampton, Mark W

    2009-02-01

    The mechanisms underlying the association between air pollution and cardiovascular morbidity and mortality are unknown. This study aimed to determine whether controlled exposure to elemental carbon ultrafine particles (UFP) affects electrocardiogram (ECG) parameters describing heart rate variability; repolarization duration, morphology, and variability; and changes in the ST segment. Two separate controlled studies (12 subjects each) were performed using a crossover design, in which each subject was exposed to filtered air and carbon UFP for 2 hours. The first protocol involved 2 exposures to air and 10 microg/m(3) (approximately 2 x 10(6) particles/cm(3), count median diameter approximately 25 nm, geometric standard deviation approximately 1.6), at rest. The second protocol included 3 exposures to air, 10, and 25 microg/m(3) UFP (approximately 7 x 10(6) particles/cm(3)), with repeated exercise. Each subject underwent a continuous digital 12-lead ECG Holter recording to analyze the above ECG parameters. Repeated measures analysis of variance (ANOVA) was used to compare tested parameters between exposures. The observed responses to UFP exposure were small and generally not significant, although there were trends indicating an increase in parasympathetic tone, which is most likely also responsible for trends toward ST elevation, blunted QTc shortening, and increased variability of T-wave complexity after exposure to UFP. Recovery from exercise showed a blunted response of the parasympathetic system after exposure to UFP in comparison to air exposure. In conclusion, transient exposure to 10-25 microg/m(3) ultrafine carbon particles does not cause marked changes in ECG-derived parameters in young healthy subjects. However, trends are observed indicating that some subjects might be susceptible to air pollution, with a response involving autonomic modulation of the heart and repolarization of the ventricular myocardium.

  12. The prevalence of abnormal ECG in trained sportsmen

    PubMed Central

    Malhotra, V.K.; Singh, Navreet; Bishnoi, R.S.; Chadha, D.S.; Bhardwaj, P.; Madan, H.; Dutta, R.; Ghosh, A.K.; Sengupta, S.; Perumal, P.

    2015-01-01

    Background Competitive sports training causes structural and conductive system changes manifesting by various electrocardiographic alterations. We undertook this study to assess the prevalence of abnormal ECG in trained Indian athletes and correlate it with the nature of sports training, that is endurance or strength training. Methods We evaluated a standard resting, lying 12 lead Electrocardiogram (ECG) in 66 actively training Indian athletes. Standard diagnostic criteria were used to define various morphological ECG abnormalities. Results 33/66 (50%) of the athletes were undertaking endurance training while the other 33 (50%) were involved in a strength-training regimen. Overall 54/66 (81%) sportsmen had significant ECG changes. 68% of these changes were considered as normal training related features, while the remaining 32% were considered abnormal. There were seven common training related ECG changes–Sinus Bradycardia (21%), Sinus Arrhythmia (16%), 1st degree Atrioventricular Heart Block (6%), Type 1 2nd-degree Atrioventicular Heart Block (3%), Incomplete Right bundle branch block (RBBB) (24%), Early Repolarization (42%), Left Ventricular Hypertrophy (LVH) (14%); while three abnormal ECG changes--T-wave inversion (13%), RBBB(4%), Right ventricular hypertrophy (RVH) with strain (29%) were noted. Early repolarization (commonest change), sinus bradycardia, and incomplete RBBB were the commoner features noticed, with a significantly higher presence in the endurance trained athletes. Conclusion A high proportion of athletes undergoing competitive level sports training are likely to have abnormal ECG recordings. Majority of these are benign, and related to the physiological adaptation to the extreme levels of exertion. These changes are commoner during endurance training (running) than strength training (weightlifting). PMID:26663958

  13. A controlled study of a new ECG electrode system.

    PubMed

    Sheffield, L T; Roitman, D I; Kansal, S

    1978-07-01

    A newly marketed resting ECG electrode system was compared with conventional metal suction and plate electrodes, electrode cream and patient cable. Two experienced technicians were given special training in the use of the new electrode, electrolyte and patient cable system and alternated daily in using new and conventional equipment. Nearly equal numbers of perfect-scoring ECGs were recorded with each system, attesting to the impartiality of the technicians. A total of 1,062 ECGs were evaluated, 554 with the new system and 508 with the conventional one. ECG tracings were evaluated by electrocardiographers unaware of which system was used for each. A quantitative scoring system was used to measure the technical quality of each tracing in terms of baseline drift, powerline artifact and myographic plus miscellaneous artifacts. The new system received mean scores of 2.33, 3.08, and 2.72, respectively, while the conventional electrodes received scores of 2.56, 3.03 and 2.79. We concluded that the two types of electrodes produced ECGs of essentially equal quality.

  14. A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis

    PubMed Central

    Guardia, Gabriela D. A.; Pires, Luís Ferreira; Vêncio, Ricardo Z. N.; Malmegrim, Kelen C. R.; de Farias, Cléver R. G.

    2015-01-01

    Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis. PMID:26207740

  15. A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

    PubMed

    Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

    2015-01-01

    Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

  16. Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode.

    PubMed

    Maldjian, Joseph A; Davenport, Elizabeth M; Whitlow, Christopher T

    2014-08-01

    Interhemispheric connectivity with resting state MEG has been elusive, and demonstration of the default mode network (DMN) yet more challenging. Recent seed-based MEG analyses have shown interhemispheric connectivity using power envelope correlations. The purpose of this study is to compare graph theoretic maps of brain connectivity generated using MEG with and without signal leakage correction to evaluate for the presence of interhemispheric connectivity. Eight minutes of resting state eyes-open MEG data were obtained in 22 normal male subjects enrolled in an IRB-approved study (ages 16-18). Data were processed using an in-house automated MEG processing pipeline and projected into standard (MNI) source space at 7mm resolution using a scalar beamformer. Mean beta-band amplitude was sampled at 2.5second epochs from the source space time series. Leakage correction was performed in the time domain of the source space beam formed signal prior to amplitude transformation. Graph theoretic voxel-wise source space correlation connectivity analysis was performed for leakage corrected and uncorrected data. Degree maps were thresholded across subjects for the top 20% of connected nodes to identify hubs. Additional degree maps for sensory, visual, motor, and temporal regions were generated to identify interhemispheric connectivity using laterality indices. Hubs for the uncorrected MEG networks were predominantly symmetric and midline, bearing some resemblance to fMRI networks. These included the cingulate cortex, bilateral inferior frontal lobes, bilateral hippocampal formations and bilateral cerebellar hemispheres. These uncorrected networks however, demonstrated little to no interhemispheric connectivity using the ROI-based degree maps. Leakage corrected MEG data identified the DMN, with hubs in the posterior cingulate and biparietal areas. These corrected networks demonstrated robust interhemispheric connectivity for the ROI-based degree maps. Graph theoretic analysis of

  17. Vibrational analysis of rectangular sandwich plates resting on some elastic point supports

    SciTech Connect

    Ichinomiya, Osamu; Maruyama, Koichi; Sekine, Kouji

    1995-11-01

    An approximate solution of forced-vibration for rectangular sandwich plate resting on some elastic point supports is presented. The sandwich plate has thin, anisotropic composite laminated faces and a thick orthotropic core. The simplified sandwich plate model is used in the analysis. The governing equation of elastically point supported rectangular sandwich plate is obtained by using the Lagrange equation. The steady state response solution to a sinusoidally varying point force is also derived. The response curves of rectangular sandwich plates having CFRP laminated faces and aluminum honeycomb core is calculated. Application examples illustrate the effects of laminate lay-up of face sheets, core material properties and core thickness ratio on the vibration characteristics of rectangular sandwich plate.

  18. Fetal ECG extraction by extended state Kalman filtering based on single-channel recordings.

    PubMed

    Niknazar, Mohammad; Rivet, Bertrand; Jutten, Christian

    2013-05-01

    In this paper, we present an extended nonlinear Bayesian filtering framework for extracting electrocardiograms (ECGs) from a single channel as encountered in the fetal ECG extraction from abdominal sensor. The recorded signals are modeled as the summation of several ECGs. Each of them is described by a nonlinear dynamic model, previously presented for the generation of a highly realistic synthetic ECG. Consequently, each ECG has a corresponding term in this model and can thus be efficiently discriminated even if the waves overlap in time. The parameter sensitivity analysis for different values of noise level, amplitude, and heart rate ratios between fetal and maternal ECGs shows its effectiveness for a large set of values of these parameters. This framework is also validated on the extractions of fetal ECG from actual abdominal recordings, as well as of actual twin magnetocardiograms.

  19. Anatomical sector analysis of load-bearing tibial bone structure during 90-day bed rest and 1-year recovery.

    PubMed

    Cervinka, Tomas; Rittweger, Jörn; Hyttinen, Jari; Felsenberg, Dieter; Sievänen, Harri

    2011-07-01

    The aim of this study was to investigate whether the bone response to long bed rest-related immobility and during subsequent recovery differed at anatomically different sectors of tibial epiphysis and diaphysis. For this study, peripheral quantitative tomographic (pQCT) scans obtained from a previous 90-day 'Long Term Bed Rest' intervention were preprocessed with a new method based on statistical approach and re-analysed sector-wise. The pQCT was performed on 25 young healthy males twice before the bed rest, after the bed rest and after 1-year follow-up. All men underwent a strict bed rest intervention, and in addition, seven of them received pamidronate treatment and nine did flywheel exercises as countermeasures against disuse-related bone loss. Clearly, 3-9% sector-specific losses in trabecular density were observed at the tibial epiphysis on average. Similarly, cortical density decreased in a sector-specific way being the largest at the anterior sector of tibial diaphysis. During recovery, the bed rest-induced bone losses were practically restored and no consistent sector-specific modulation was observed in any subgroup. It is concluded that the sector-specific analysis of bone cross-sections has potential to reveal skeletal responses to various interventions that cannot be inferred from the average analysis of the whole bone cross-section. This approach is considered also useful for evaluating the bone responses from the biomechanical point of view.

  20. Some regularity on how to locate electrodes for higher fECG SNRs

    NASA Astrophysics Data System (ADS)

    Zhang, Jie-Min; Huang, Xiao-Lin; Guan, Qun; Liu, Tie-Bing; Li, Ping; Zhao, Ying; Liu, Hong-Xing

    2015-03-01

    The electrocardiogram (ECG) recorded from the abdominal surface of a pregnant woman is a composite of maternal ECG, fetal ECG (fECG) and other noises, while only the fECG component is always needed by us. With different locations of electrode pairs on the maternal abdominal surface to measure fECGs, the signal-to-noise ratios (SNRs) of the recorded abdominal ECGs are also correspondingly different. Some regularity on how to locate electrodes to obtain higher fECG SNRs is needed practically. In this paper, 343 groups of abdominal ECG records were acquired from 78 pregnant women with different electrode pairs locating, and an appropriate extended research database is formed. Then the regularity on fECG SNRs corresponding to different electrode pairs locating was studied. Based on statistical analysis, it is shown that the fECG SNRs are significantly higher in certain locations than others. Reasonable explanation is also provided to the statistical result using the theories of the fetal cardiac electrical axis and the signal phase delay. Project supported by the National Natural Science Foundation of China (Grant No. 61271079) and the Supporting Plan Project of Jiangsu Province, China (Grant No. BE2010720).

  1. The ISCE ECG genome pilot challenge: a 2004 progress report.

    PubMed

    Kligfield, Paul; Badilini, Fabio; Brown, Barry; Helfenbein, Erich; Kohls, Mark

    2004-01-01

    The International Society for Computerized Electrocardiography (ISCE) "genome project" began in 2000 as an open-ended discussion of ECG database needs and opportunities. Cooperation within ISCE led to a "pilot challenge" of the database concept, which called for establishment of methodology for transmission, storage, and integrated re-analysis of digitized waveforms of three different ECG manufacturers. The present report documents the early implementation of that goal.

  2. Connectivity graph analysis of the auditory resting state network in tinnitus.

    PubMed

    Maudoux, A; Lefebvre, Ph; Cabay, J-E; Demertzi, A; Vanhaudenhuyse, A; Laureys, S; Soddu, A

    2012-11-16

    Thirteen chronic tinnitus patients and fifteen age-matched healthy controls were studied on a 3T magnetic resonance imaging (MRI) scanner during resting condition (i.e. eyes closed, no task performance). The auditory resting-state component was selected using an automatic component selection approach. Functional connectivity (correlations/anti-correlations) in the extracted network was portrayed by integrating the independent component analysis (ICA) approach with a graph theory method. Tinnitus and control groups showed different graph connectivity patterns. In the control group, the connectivity graph was divided into two distinct anti-correlated networks. The first one encompassed the auditory cortices and the insula. The second one encompassed frontoparietal and anterior cingulate cortices, brainstem, amygdala, basal ganglia/nucleus accumbens and parahippocampal regions. In the tinnitus group, only one of the two previously described networks was observed, encompassing the auditory cortices and the insula. Direct group comparison showed, in the tinnitus group, an increased functional connectivity between auditory cortices and the left parahippocampal region surviving multiple comparisons. We investigated a possible correlation between four tinnitus relevant measures (tinnitus handicap inventory (THI) and tinnitus questionnaire (TQ) scores, tinnitus duration and tinnitus intensity during the scanning session) and the connectivity pattern in the tinnitus population. We observed a significant positive correlation between the beta values of the posterior cingulate/precuneus region and the THI score. Our results show a modified functional connectivity pattern in tinnitus sufferers and highlight the role of the parahippocampal region in tinnitus physiopathology. They also point out the importance of the activity and connectivity pattern of the posterior cingulate cortex/precuneus region to the development of the tinnitus associated distress. This article is part of a

  3. Piezoelectric extraction of ECG signal.

    PubMed

    Ahmad, Mahmoud Al

    2016-11-17

    The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other.

  4. Piezoelectric extraction of ECG signal

    NASA Astrophysics Data System (ADS)

    Ahmad, Mahmoud Al

    2016-11-01

    The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other.

  5. Altered resting-state functional activity in posttraumatic stress disorder: A quantitative meta-analysis

    PubMed Central

    Wang, Ting; Liu, Jia; Zhang, Junran; Zhan, Wang; Li, Lei; Wu, Min; Huang, Hua; Zhu, Hongyan; Kemp, Graham J.; Gong, Qiyong

    2016-01-01

    Many functional neuroimaging studies have reported differential patterns of spontaneous brain activity in posttraumatic stress disorder (PTSD), but the findings are inconsistent and have not so far been quantitatively reviewed. The present study set out to determine consistent, specific regional brain activity alterations in PTSD, using the Effect Size Signed Differential Mapping technique to conduct a quantitative meta-analysis of resting-state functional neuroimaging studies of PTSD that used either a non-trauma (NTC) or a trauma-exposed (TEC) comparison control group. Fifteen functional neuroimaging studies were included, comparing 286 PTSDs, 203 TECs and 155 NTCs. Compared with NTC, PTSD patients showed hyperactivity in the right anterior insula and bilateral cerebellum, and hypoactivity in the dorsal medial prefrontal cortex (mPFC); compared with TEC, PTSD showed hyperactivity in the ventral mPFC. The pooled meta-analysis showed hypoactivity in the posterior insula, superior temporal, and Heschl’s gyrus in PTSD. Additionally, subgroup meta-analysis (non-medicated subjects vs. NTC) identified abnormal activation in the prefrontal-limbic system. In meta-regression analyses, mean illness duration was positively associated with activity in the right cerebellum (PTSD vs. NTC), and illness severity was negatively associated with activity in the right lingual gyrus (PTSD vs. TEC). PMID:27251865

  6. Comparison of Resting Energy Expenditure Between Cancer Subjects and Healthy Controls: A Meta-Analysis.

    PubMed

    Nguyen, Thi Yen Vi; Batterham, Marijka J; Edwards, Cheree

    2016-01-01

    There is conflicting evidence surrounding the extent of changes in resting energy expenditure (REE) in cancer. This meta-analysis aimed to establish the mean difference in REE, as kilojoules per kilogram fat-free mass, among cancer patients when compared to healthy control subjects. The secondary aim was to determine differences among different cancer types. PubMed, Cochrane Library, Medline, Science Direct, Scopus, Web of Science, Wiley Online Library, and ProQuest Central were searched from the earliest records until March 2014. Studies were included if measured REE was reported as kilojoules or kilocalories per kilogram fat-free mass (FFM) in adult subjects with cancer. Twenty-seven studies were included in the meta-analysis. Fourteen studies included both cancer (n = 1453) and control (n = 1145) groups. The meta-analysis shows an average increase in REE of 9.66 (95% confidence interval: 3.34, 15.98) kJ/kgFFM/day in cancer patients when compared to control subjects. Heterogeneity was detected (P < 0.001) which suggest variations in REE among cancer types. Elevations are most noticeable in patients with cancers of metabolically demanding organs.

  7. Nonlinear analysis of electroencephalogram at rest and during cognitive tasks in patients with schizophrenia

    PubMed Central

    Carlino, Elisa; Sigaudo, Monica; Pollo, Antonella; Benedetti, Fabrizio; Mongini, Tullia; Castagna, Filomena; Vighetti, Sergio; Rocca, Paola

    2012-01-01

    Background In spite of the large number of studies on schizophrenia, a full understanding of its core pathology still eludes us. The application of the nonlinear theory of electroencephalography (EEG) analysis provides an interesting tool to differentiate between physiologic conditions (e.g., resting state and mathematical task) and normal and pathologic brain activities. The aim of the present study was to investigate nonlinear EEG activity in patients with schizophrenia. Methods We recorded 19-lead EEGs in patients with stable schizophrenia and healthy controls under 4 different conditions: eyes closed, eyes open, forward counting and backward counting. A nonlinear measure of complexity was calculated by means of correlation dimension (D2). Results We included 17 patients and 17 controls in our analysis. Comparing the 2 populations, we observed greater D2 values in the patient group. In controls, increased D2 values were observed during active states (eyes open and the 2 cognitive tasks) compared with baseline conditions. This increase of brain complexity, which can be interpreted as an increase of information processing and integration, was not preserved in the patient population. Limitations Patients with schizophrenia were taking antipsychotic medications, so the presence of medication effects cannot be excluded. Conclusion Our results suggest that patients with schizophrenia present changes in brain activity compared with healthy controls, and this pathologic alteration can be successfully studied with nonlinear EEG analysis. PMID:22353633

  8. Multiscale entropy analysis of resting-state magnetoencephalogram with tensor factorisations in Alzheimer's disease.

    PubMed

    Escudero, Javier; Acar, Evrim; Fernández, Alberto; Bro, Rasmus

    2015-10-01

    Tensor factorisations have proven useful to model amplitude and spectral information of brain recordings. Here, we assess the usefulness of tensor factorisations in the multiway analysis of other brain signal features in the context of complexity measures recently proposed to inspect multiscale dynamics. We consider the "refined composite multiscale entropy" (rcMSE), which computes entropy "profiles" showing levels of physiological complexity over temporal scales for individual signals. We compute the rcMSE of resting-state magnetoencephalogram (MEG) recordings from 36 patients with Alzheimer's disease and 26 control subjects. Instead of traditional simple visual examinations, we organise the entropy profiles as a three-way tensor to inspect relationships across temporal and spatial scales and subjects with multiway data analysis techniques based on PARAFAC and PARAFAC2 factorisations. A PARAFAC2 model with two factors was appropriate to account for the interactions in the entropy tensor between temporal scales and MEG channels for all subjects. Moreover, the PARAFAC2 factors had information related to the subjects' diagnosis, achieving a cross-validated area under the ROC curve of 0.77. This confirms the suitability of tensor factorisations to represent electrophysiological brain data efficiently despite the unsupervised nature of these techniques. This article is part of a Special Issue entitled 'Neural data analysis'.

  9. The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI.

    PubMed

    Khalili-Mahani, Najmeh; Chang, Catie; van Osch, Matthias J; Veer, Ilya M; van Buchem, Mark A; Dahan, Albert; Beckmann, Christian F; van Gerven, Joop M A; Rombouts, Serge A R B

    2013-01-15

    Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical

  10. Creep rupture analysis of a beam resting on high temperature foundation

    NASA Technical Reports Server (NTRS)

    Gu, Randy J.; Cozzarelli, Francis A.

    1988-01-01

    A simplified uniaxial strain controlled creep damage law is deduced with the use of experimental observation from a more complex strain dependent law. This creep damage law correlates the creep damage, which is interpreted as the density variation in the material, directly with the accumulated creep strain. Based on the deduced uniaxial strain controlled creep damage law, a continuum mechanical creep rupture analysis is carried out for a beam resting on a high temperature elastic (Winkler) foundation. The analysis includes the determination of the nondimensional time for initial rupture, the propagation of the rupture front with the associated thinning of the beam, and the influence of creep damage on the deflection of the beam. Creep damage starts accumulating in the beam as soon as the load is applied, and a creep rupture front develops at and propagates from the point at which the creep damage first reaches its critical value. By introducing a series of fundamental assumptions within the framework of technical Euler-Bernoulli type beam theory, a governing set of integro-differential equations is derived in terms of the nondimensional bending moment and the deflection. These governing equations are subjected to a set of interface conditions at the propagating rupture front. A numerical technique is developed to solve the governing equations together with the interface equations, and the computed results are presented and discussed in detail.

  11. Human ECG indicators for fast screening and evaluation

    NASA Astrophysics Data System (ADS)

    Maciejewski, Marcin; DzierŻak, RóŻa; Surtel, Wojciech; Saran, Tomasz

    2016-09-01

    Telemedical system design and implementation requires numerous steps. It is necessary to evaluate the operation of algorithms responsible for analysis and detection of life-threatening situations. By performing ECG analysis it is possible to obtain information about the overall patient health condition as well as detailed information about the circulatory system condition. To achieve that goal one must gather, filter and process data. Data was gathered using a purposely built device from a group of four volunteers. Available data set was processed to obtain information about the patients condition. Pan-Tompkins algorithm was used to detect R peaks and calculate heart rhythm. Afterward the rest of parameters were extracted in time domain using windowed peak detection and polynomial estimation. The parameters were calculated as delays between appropriate points in the signal. The method proved to be able to extract parameters in some of the cases, and proved limited effectiveness in situations where physical activity was significant. It was nevertheless possible to eliminate noise from the mains, the trend and higher frequency noise Further improvements need to be introduced to increase the method's robustness in the presence of significant muscle noise.

  12. Analysis of Arterial Mechanics During Head-Down-Tilt Bed Rest

    NASA Technical Reports Server (NTRS)

    Elliott, Morgan B.; Martin, David S.; Westby, Christian M.; Stenger, Michael B.; Platts, Steven H.

    2014-01-01

    Carotid, brachial, and tibial arteries reacted differently to HDTBR. Previous studies have not analyzed the mechanical properties of the human brachial or anterior tibial arteries. After slight variations during bed-rest, arterial mechanical properties and IMT returned to pre-bed rest values, with the exception of tibial stiffness and PSE, which continued to be reduced post-bed rest while the DC remained elevated. The tibial artery remodeling was probably due to decreased pressure and volume. Resulting implications for longer duration spaceflight are unclear. Arterial health may be affected by microgravity, as shown by increased thoracic aorta stiffness in other ground based simulations (Aubert).

  13. The future of remote ECG monitoring systems

    PubMed Central

    Guo, Shu-Li; Han, Li-Na; Liu, Hong-Wei; Si, Quan-Jin; Kong, De-Feng; Guo, Fu-Su

    2016-01-01

    Remote ECG monitoring systems are becoming commonplace medical devices for remote heart monitoring. In recent years, remote ECG monitoring systems have been applied in the monitoring of various kinds of heart diseases, and the quality of the transmission and reception of the ECG signals during remote process kept advancing. However, there remains accompanying challenges. This report focuses on the three components of the remote ECG monitoring system: patient (the end user), the doctor workstation, and the remote server, reviewing and evaluating the imminent challenges on the wearable systems, packet loss in remote transmission, portable ECG monitoring system, patient ECG data collection system, and ECG signals transmission including real-time processing ST segment, R wave, RR interval and QRS wave, etc. This paper tries to clarify the future developmental strategies of the ECG remote monitoring, which can be helpful in guiding the research and development of remote ECG monitoring. PMID:27582770

  14. Complexity analysis of resting-state MEG activity in early-stage Parkinson's disease patients.

    PubMed

    Gómez, Carlos; Olde Dubbelink, Kim T E; Stam, Cornelis J; Abásolo, Daniel; Berendse, Henk W; Hornero, Roberto

    2011-12-01

    The aim of the present study was to analyze resting-state brain activity in patients with Parkinson's disease (PD), a degenerative disorder of the nervous system. Magnetoencephalography (MEG) signals were recorded with a 151-channel whole-head radial gradiometer MEG system in 18 early-stage untreated PD patients and 20 age-matched control subjects. Artifact-free epochs of 4 s (1250 samples) were analyzed with Lempel-Ziv complexity (LZC), applying two- and three-symbol sequence conversion methods. The results showed that MEG signals from PD patients are less complex than control subjects' recordings. We found significant group differences (p-values <0.01) for the 10 major cortical areas analyzed (e.g., bilateral frontal, central, temporal, parietal, and occipital regions). In addition, using receiver-operating characteristic curves with a leave-one-out cross-validation procedure, a classification accuracy of 81.58% was obtained. In order to investigate the best combination of LZC results for classification purposes, a forward stepwise linear discriminant analysis with leave-one out cross-validation was employed. LZC results (three-symbol sequence conversion) from right parietal and temporal brain regions were automatically selected by the model. With this procedure, an accuracy of 84.21% (77.78% sensitivity, 90.0% specificity) was achieved. Our findings demonstrate the usefulness of LZC to detect an abnormal type of dynamics associated with PD.

  15. Creativity and the default network: A functional connectivity analysis of the creative brain at rest.

    PubMed

    Beaty, Roger E; Benedek, Mathias; Wilkins, Robin W; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J; Hodges, Donald A; Koschutnig, Karl; Neubauer, Aljoscha C

    2014-11-01

    The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes.

  16. Blink-related delta oscillations in the resting-state EEG: a wavelet analysis.

    PubMed

    Bonfiglio, Luca; Sello, Stefano; Andre, Paolo; Carboncini, Maria Chiara; Arrighi, Pieranna; Rossi, Bruno

    2009-01-02

    Over the past decades, many studies have linked the variations in frequency of spontaneous blinking with certain aspects of information processing and in particular with attention and working memory functions. On the other hand, according to the theory postulated by Crick and Koch, the actual function of primary consciousness is based on the reciprocal interaction between attention and working memory in the automatic and serial mode. The purpose of this study was to investigate for electrophysiological correlates compatible with the cognitive nature of spontaneous blinking, by using the EEG recordings obtained in a group of seven healthy volunteers while they rested quietly though awake, with their eyes open, but not actively engaged in attention-demanding goal-directed behaviours. The global wavelet analysis - at total of 189 three-second EEG epochs time-locked to the blink - revealed an increase in the delta band signal corresponding to the blink. In particular, a reconstruction of the EEG signal by means of inverse-wavelet transform (IWT) showed a blink-related P300-like wave at mid-parietal site. We assumed this phenomenon to represent an electrophysiological sign of the automatic processing of contextual environmental information. This might play a role in maintaining perceptive awareness of the environment at a low level of processing, while the subject is not engaged in attention-demanding tasks but rather introspectively oriented mental activities or free association(s).

  17. Comparative analysis of the diagnostic and prognostic value of exercise ECG and thallium-201 scintigraphic markers of myocardial ischemia in asymptomatic and symptomatic patients

    SciTech Connect

    Gibson, R.S. )

    1989-08-01

    A considerable amount of data now exists that indicates that exercise ECG--due to its suboptimal sensitivity and specificity--has limited diagnostic and prognostic value in asymptomatic subjects, patients with chest pain of unclear etiology or those with chronic stable angina pectoris, and in patients recovering from acute myocardial infarction. Because of this and the well-recognized advantages of thallium-201 scintigraphy, there appears to be a strong rationale for recommending exercise perfusion imaging, rather than exercise ECG alone, as the preferred method for detecting CAD and staging its severity. This recommendation seems justified given the fact that (1) thallium-201 scintigraphy is far more sensitive and specific in detecting myocardial ischemia than exercise testing; (2) unlike stress ECG, thallium-201 scintigraphy can localize ischemia to a specific area of areas subtended by a specific coronary artery; and (3) thallium-201 scintigraphy has been shown to be more reliable to risk stratification of individual patients than exercise testing alone. The more optimal prognostic efficiency of thallium-201 scintigraphy is due, in part, to the fact that the error rate in falsely classifying patients as low-risk is substantially and significantly smaller with thallium-201 scintigraphy than with stress ECG. 52 references.

  18. Resting Orientations of Dinosaur Scapulae and Forelimbs: A Numerical Analysis, with Implications for Reconstructions and Museum Mounts.

    PubMed

    Senter, Phil; Robins, James H

    2015-01-01

    The inclination of the scapular blade and the resting pose of the forelimb in dinosaurs differ among reconstructions and among skeletal mounts. For most dinosaurian taxa, no attempt has previously been made to quantify the correct resting positions of these elements. Here, we used data from skeletons preserved in articulation to quantify the resting orientations of the scapula and forelimb in dinosaurs. Specimens were included in the study only if they were preserved lying on their sides; for each specimen the angle between forelimb bones at a given joint was included in the analysis only if the joint was preserved in articulation. Using correlation analyses of the angles between the long axis of the sacrum, the first dorsal centrum, and the scapular blade in theropods and Eoraptor, we found that vertebral hyperextension does not influence scapular orientation in saurischians. Among examined taxa, the long axis of the scapular blade was found to be most horizontal in bipedal saurischians, most vertical in basal ornithopods, and intermediate in hadrosauroids. We found that in bipedal dinosaurs other than theropods with semilunate carpals, the resting orientation of the elbow is close to a right angle and the resting orientation of the wrist is such that the hand exhibits only slight ulnar deviation from the antebrachium. In theropods with semilunate carpals the elbow and wrist are more flexed at rest, with the elbow at a strongly acute angle and with the wrist approximately at a right angle. The results of our study have important implications for correct orientations of bones in reconstructions and skeletal mounts. Here, we provide recommendations on bone orientations based on our results.

  19. Resting Orientations of Dinosaur Scapulae and Forelimbs: A Numerical Analysis, with Implications for Reconstructions and Museum Mounts

    PubMed Central

    Senter, Phil; Robins, James H.

    2015-01-01

    The inclination of the scapular blade and the resting pose of the forelimb in dinosaurs differ among reconstructions and among skeletal mounts. For most dinosaurian taxa, no attempt has previously been made to quantify the correct resting positions of these elements. Here, we used data from skeletons preserved in articulation to quantify the resting orientations of the scapula and forelimb in dinosaurs. Specimens were included in the study only if they were preserved lying on their sides; for each specimen the angle between forelimb bones at a given joint was included in the analysis only if the joint was preserved in articulation. Using correlation analyses of the angles between the long axis of the sacrum, the first dorsal centrum, and the scapular blade in theropods and Eoraptor, we found that vertebral hyperextension does not influence scapular orientation in saurischians. Among examined taxa, the long axis of the scapular blade was found to be most horizontal in bipedal saurischians, most vertical in basal ornithopods, and intermediate in hadrosauroids. We found that in bipedal dinosaurs other than theropods with semilunate carpals, the resting orientation of the elbow is close to a right angle and the resting orientation of the wrist is such that the hand exhibits only slight ulnar deviation from the antebrachium. In theropods with semilunate carpals the elbow and wrist are more flexed at rest, with the elbow at a strongly acute angle and with the wrist approximately at a right angle. The results of our study have important implications for correct orientations of bones in reconstructions and skeletal mounts. Here, we provide recommendations on bone orientations based on our results. PMID:26675035

  20. Resting motor threshold in idiopathic generalized epilepsies: a systematic review with meta-analysis.

    PubMed

    Brigo, Francesco; Storti, Monica; Benedetti, Maria Donata; Rossini, Fabio; Nardone, Raffaele; Tezzon, Frediano; Fiaschi, Antonio; Bongiovanni, Luigi Giuseppe; Manganotti, Paolo

    2012-08-01

    Resting motor threshold (rMT) assessed by means of Transcranial Magnetic Stimulation (TMS) is thought to reflect trans-synaptic excitability of cortico-spinal neurons. TMS studies reporting rMT in idiopathic generalized epilepsies (IGEs) yielded discrepant results, so that it is difficult to draw a definitive conclusion on cortico-spinal excitability in IGEs by simple summation of previous results regarding this measure. Our purpose was to carry out a systematic review and a meta-analysis of studies evaluating rMT values obtained during single-pulse TMS in patients with IGEs. Controlled studies measuring rMT by single-pulse TMS in drug-naive patients older than 12 years affected by IGEs were systematically reviewed. rMT values were assessed calculating mean difference and odds ratio with 95% confidence intervals (CI). Fourteen trials (265 epileptic patients and 424 controls) were included. Patients with juvenile myoclonic epilepsy (JME) have a statistically significant lower rMT compared with controls (mean difference: -6.78; 95% CI -10.55 to -3.00); when considering all subtypes of IGEs and IGEs other than JME no statistically significant differences were found. Overall considered, the results are indicative of a cortico-spinal hyper-excitability in JME, providing not enough evidence for motor hyper-excitability in other subtypes of IGE. The considerable variability across studies probably reflects the presence of relevant clinical and methodological heterogeneity, and higher temporal variability among rMT measurements over time, related to unstable cortical excitability in these patients.

  1. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    PubMed

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  2. Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

    PubMed Central

    Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

    2013-01-01

    Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID

  3. Assessing validity and reliability of resting metabolic rate in six gas analysis systems.

    PubMed

    Cooper, Jamie A; Watras, Abigail C; O'Brien, Matthew J; Luke, Amy; Dobratz, Jennifer R; Earthman, Carrie P; Schoeller, Dale A

    2009-01-01

    The Deltatrac Metabolic Monitor (DTC) (VIASYS Healthcare Inc, SensorMedics, Yorba Linda, CA), one of the most popular indirect calorimetry systems for measuring resting metabolic rate (RMR) in human subjects, is no longer being manufactured. This study compared five different gas analysis systems to the DTC. RMR was measured by the DTC and at least one other instrument at three study sites for a total of 38 participants. The five indirect calorimetry systems included the MedGraphics CPX Ultima (Medical Graphics Corp, St Paul, MN), the MedGem (Microlife USA, Golden, CO), Vmax Encore 29 System (VIASYS Healthcare Inc, Yorba Linda, CA), the TrueOne 2400 (Parvo Medics, Sandy, UT), and the Korr ReeVue (Korr Medical Technologies, Salt Lake City, UT). Validity was assessed using paired t tests to compare means; reliability was assessed by using both paired t tests and root mean square calculations with F tests for significance. Within-subject comparisons for validity of RMR revealed a significant difference between the DTC and the Ultima system. Bland-Altman plot analysis showed significant bias with increasing RMR values for the Korr and MedGem systems. Respiratory exchange ratio (RER) analysis showed a significant difference between the DTC and the Ultima system and a trend for a difference with the Vmax system (P=0.09). Reliability assessment for RMR revealed that all instruments had a significantly larger coefficient of variation (CV) (ranging from 4.8% to 10.9%) for RMR compared to the 3.0% CV for the DTC. Reliability assessment for RER data showed none of the instrument CVs was significantly larger than the DTC CV. The results were quite disappointing because none of the instruments equaled the within-person reliability of the DTC. The TrueOne and Vmax systems were the most valid instruments in comparison with the DTC for both RMR and RER assessment. Further testing is needed to identify an instrument with the reliability and validity of the DTC.

  4. A Practical and Cheap Circuit for ECG Sensing and Heart Frequency Alarm

    NASA Astrophysics Data System (ADS)

    Aviña-Cervantes, J. G.; González-García, A. E.; Alvarado-Méndez, E.; Trejo-Durán, M.; Torres-Cisneros, M.; Sánchez-Yáñez, R.; Ayala-Ramírez, V.

    2006-09-01

    A practical electronic circuit for ECG sensing, using high gain instrumentation amplifiers, a PIC microcontroller and two electrodes is presented. It allows to identify and to amplify a well-delimited ECG signal for a further wave analysis, and using a zero crossing detector a heart frequency detector is also implemented. By the moment, the conventional electrocardiogram (ECG) configurations making use of separate electrical connections to the arms and legs (bipolar limb lead 1) is exploited. This device is a practical and cheap way to monitoring ECG signal and some heart anomalies (e.g., arrhythmias, tachycardia) that can be used in a network to communicate anytime with a far health supervisor.

  5. Interactomic analysis of REST/NRSF and implications of its functional links with the transcription suppressor TRIM28 during neuronal differentiation

    PubMed Central

    Lee, Namgyu; Park, Sung Jin; Haddad, Ghazal; Kim, Dae-Kyum; Park, Seon-Min; Park, Sang Ki; Choi, Kwan Yong

    2016-01-01

    RE-1 silencing transcription factor (REST) is a transcriptional repressor that regulates gene expression by binding to repressor element 1. However, despite its critical function in physiology, little is known about its interaction proteins. Here we identified 204 REST-interacting proteins using affinity purification and mass spectrometry. The interactome included proteins associated with mRNA processing/splicing, chromatin organization, and transcription. The interactions of these REST-interacting proteins, which included TRIM28, were confirmed by co-immunoprecipitation and immunocytochemistry, respectively. Gene Ontology (GO) analysis revealed that neuronal differentiation-related GO terms were enriched among target genes that were co-regulated by REST and TRIM28, while the level of CTNND2 was increased by the knockdown of REST and TRIM28. Consistently, the level of CTNND2 increased while those of REST and TRIM28 decreased during neuronal differentiation in the primary neurons, suggesting that CTNND2 expression may be co-regulated by both. Furthermore, neurite outgrowth was increased by depletion of REST or TRIM28, implying that reduction of both REST and TRIM28 could promote neuronal differentiation via induction of CTNND2 expression. In conclusion, our study of REST reveals novel interacting proteins which could be a valuable resource for investigating unidentified functions of REST and also suggested functional links between REST and TRIM28 during neuronal development. PMID:27976729

  6. High Resolution ECG for Evaluation of QT Interval Variability during Exposure to Acute Hypoxia

    NASA Technical Reports Server (NTRS)

    Zupet, P.; Finderle, Z.; Schlegel, Todd T.; Starc, V.

    2010-01-01

    Ventricular repolarization instability as quantified by the index of QT interval variability (QTVI) is one of the best predictors for risk of malignant ventricular arrhythmias and sudden cardiac death. Because it is difficult to appropriately monitor early signs of organ dysfunction at high altitude, we investigated whether high resolution advanced ECG (HR-ECG) analysis might be helpful as a non-invasive and easy-to-use tool for evaluating the risk of cardiac arrhythmias during exposure to acute hypoxia. 19 non-acclimatized healthy trained alpinists (age 37, 8 plus or minus 4,7 years) participated in the study. Five-minute high-resolution 12-lead electrocardiograms (ECGs) were recorded (Cardiosoft) in each subject at rest in the supine position breathing room air and then after breathing 12.5% oxygen for 30 min. For beat-to-beat RR and QT variability, the program of Starc was utilized to derive standard time domain measures such as root mean square of the successive interval difference (rMSSD) of RRV and QTV, the corrected QT interval (QTc) and the QTVI in lead II. Changes were evaluated with paired-samples t-test with p-values less than 0.05 considered statistically significant. As expected, the RR interval and its variability both decreased with increasing altitude, with p = 0.000 and p = 0.005, respectively. Significant increases were found in both the rMSSDQT and the QTVI in lead II, with p = 0.002 and p = 0.003, respectively. There was no change in QTc interval length (p = non significant). QT variability parameters may be useful for evaluating changes in ventricular repolarization caused by hypoxia. These changes might be driven by increases in sympathetic nervous system activity at ventricular level.

  7. Non-contact ECG monitoring

    NASA Astrophysics Data System (ADS)

    Smirnov, Alexey S.; Erlikh, Vadim V.; Kodkin, Vladimir L.; Keller, Andrei V.; Epishev, Vitaly V.

    2016-03-01

    The research is dedicated to non-contact methods of electrocardiography. The authors describe the routine of experimental procedure and suggest the approach to solving the problems which arise at indirect signal recording. The paper presents the results of experiments conducted by the authors, covers the flow charts of ECG recorders and reviews the drawbacks of filtering methods used in foreign equivalents.

  8. Piezoelectric extraction of ECG signal

    PubMed Central

    Ahmad, Mahmoud Al

    2016-01-01

    The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other. PMID:27853180

  9. Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.

    PubMed

    Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert; Angstadt, Michael; Liberzon, Israel; Phan, K Luan; Scott, Clayton

    2013-11-01

    Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning.

  10. Integrity of central nervous function in diabetes mellitus assessed by resting state EEG frequency analysis and source localization.

    PubMed

    Frøkjær, Jens B; Graversen, Carina; Brock, Christina; Khodayari-Rostamabad, Ahmad; Olesen, Søren S; Hansen, Tine M; Søfteland, Eirik; Simrén, Magnus; Drewes, Asbjørn M

    2017-02-01

    Diabetes mellitus (DM) is associated with structural and functional changes of the central nervous system. We used electroencephalography (EEG) to assess resting state cortical activity and explored associations to relevant clinical features. Multichannel resting state EEG was recorded in 27 healthy controls and 24 patients with longstanding DM and signs of autonomic dysfunction. The power distribution based on wavelet analysis was summarized into frequency bands with corresponding topographic mapping. Source localization analysis was applied to explore the electrical cortical sources underlying the EEG. Compared to controls, DM patients had an overall decreased EEG power in the delta (1-4Hz) and gamma (30-45Hz) bands. Topographic analysis revealed that these changes were confined to the frontal region for the delta band and to central cortical areas for the gamma band. Source localization analysis identified sources with reduced activity in the left postcentral gyrus for the gamma band and in right superior parietal lobule for the alpha1 (8-10Hz) band. DM patients with clinical signs of autonomic dysfunction and gastrointestinal symptoms had evidence of altered resting state cortical processing. This may reflect metabolic, vascular or neuronal changes associated with diabetes.

  11. Advanced ECG in 2016: is there more than just a tracing?

    PubMed

    Reichlin, Tobias; Abächerli, Roger; Twerenbold, Raphael; Kühne, Michael; Schaer, Beat; Müller, Christian; Sticherling, Christian; Osswald, Stefan

    2016-01-01

    The 12-lead electrocardiogram (ECG) is the most frequently used technology in clinical cardiology. It is critical for evidence-based management of patients with most cardiovascular conditions, including patients with acute myocardial infarction, suspected chronic cardiac ischaemia, cardiac arrhythmias, heart failure and implantable cardiac devices. In contrast to many other techniques in cardiology, the ECG is simple, small, mobile, universally available and cheap, and therefore particularly attractive. Standard ECG interpretation mainly relies on direct visual assessment. The progress in biomedical computing and signal processing, and the available computational power offer fascinating new options for ECG analysis relevant to all fields of cardiology. Several digital ECG markers and advanced ECG technologies have shown promise in preliminary studies. This article reviews promising novel surface ECG technologies in three different fields. (1) For the detection of myocardial ischaemia and infarction, QRS morphology feature analysis, the analysis of high frequency QRS components (HF-QRS) and methods using vectorcardiography as well as ECG imaging are discussed. (2) For the identification and management of patients with cardiac arrhythmias, methods of advanced P-wave analysis are discussed and the concept of ECG imaging for noninvasive localisation of cardiac arrhythmias is presented. (3) For risk stratification of sudden cardiac death and the selection of patients for medical device therapy, several novel markers including an automated QRS-score for scar quantification, the QRS-T angle or the T-wave peak-to-end-interval are discussed. Despite the existing preliminary data, none of the advanced ECG markers and technologies has yet accomplished the transition into clinical practice. Further refinement of these technologies and broader validation in large unselected patient cohorts are the critical next step needed to facilitate translation of advanced ECG technologies

  12. Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

    PubMed Central

    Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

    2016-01-01

    Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596

  13. The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital.

    PubMed

    Harris, Patricia R E

    2016-09-01

    The electrocardiogram (ECG) is a well-established diagnostic tool extensively used in clinical settings. Knowledge of cardiac rhythm and mastery of cardiac waveform interpretation are fundamental for intensive care nurses. Recognition of the normal findings for the 12-lead ECG and understanding the significance of changes from baseline in continuous cardiac monitoring are essential steps toward ensuring safe patient care. This article highlights historical developments in electrocardiography, describes the normal resting 12-lead ECG, and discusses the need for continuous cardiac monitoring. In addition, future directions for the ECG are explored briefly.

  14. Shannon's Energy Based Algorithm in ECG Signal Processing.

    PubMed

    Beyramienanlou, Hamed; Lotfivand, Nasser

    2017-01-01

    Physikalisch-Technische Bundesanstalt (PTB) database is electrocardiograms (ECGs) set from healthy volunteers and patients with different heart diseases. PTB is provided for research and teaching purposes by National Metrology Institute of Germany. The analysis method of complex QRS in ECG signals for diagnosis of heart disease is extremely important. In this article, a method on Shannon energy (SE) in order to detect QRS complex in 12 leads of ECG signal is provided. At first, this algorithm computes the Shannon energy (SE) and then makes an envelope of Shannon energy (SE) by using the defined threshold. Then, the signal peaks are determined. The efficiency of the algorithm is tested on 70 cases. Of all 12 standard leads, ECG signals include 840 leads of the PTB Diagnostic ECG Database (PTBDB). The algorithm shows that the Shannon energy (SE) sensitivity is equal to 99.924%, the detection error rate (DER) is equal to 0.155%, Positive Predictivity (+P) is equal to 99.922%, and Classification Accuracy (Acc) is equal to 99.846%.

  15. Shannon's Energy Based Algorithm in ECG Signal Processing

    PubMed Central

    2017-01-01

    Physikalisch-Technische Bundesanstalt (PTB) database is electrocardiograms (ECGs) set from healthy volunteers and patients with different heart diseases. PTB is provided for research and teaching purposes by National Metrology Institute of Germany. The analysis method of complex QRS in ECG signals for diagnosis of heart disease is extremely important. In this article, a method on Shannon energy (SE) in order to detect QRS complex in 12 leads of ECG signal is provided. At first, this algorithm computes the Shannon energy (SE) and then makes an envelope of Shannon energy (SE) by using the defined threshold. Then, the signal peaks are determined. The efficiency of the algorithm is tested on 70 cases. Of all 12 standard leads, ECG signals include 840 leads of the PTB Diagnostic ECG Database (PTBDB). The algorithm shows that the Shannon energy (SE) sensitivity is equal to 99.924%, the detection error rate (DER) is equal to 0.155%, Positive Predictivity (+P) is equal to 99.922%, and Classification Accuracy (Acc) is equal to 99.846%. PMID:28197213

  16. A system for intelligent home care ECG upload and priorisation.

    PubMed

    D'Angelo, Lorenzo T; Tarita, Eugeniu; Zywietz, Tosja K; Lueth, Tim C

    2010-01-01

    In this contribution, a system for internet based, automated home care ECG upload and priorisation is presented for the first time. It unifies the advantages of existing telemonitoring ECG systems adding functionalities such as automated priorisation and usability for home care. Chronic cardiac diseases are a big group in the geriatric field. Most of them can be easily diagnosed with help of an electrocardiogram. A frequent or long-term ECG analysis allows early diagnosis of e.g. a cardiac infarction. Nevertheless, patients often aren't willing to visit a doctor for prophylactic purposes. Possible solutions of this problem are home care devices, which are used to investigate patients at home without the presence of a doctor on site. As the diffusion of such systems leads to a huge amount of data which has to be managed and evaluated, the presented approach focuses on an easy to use software for ECG upload from home, a web based management application and an algorithm for ECG preanalysis and priorisation.

  17. [Dynamics of ECG voltage in changing gravity].

    PubMed

    Saltykova, M M; At'kov, O Iu; Capderou, A; Morgun, V V; Gusakov, V A; Kheĭmets, G I; Konovalov, G A; Kondratiuk, L L; Kataev, Iu V; Voronin, L I; Kaspranskiĭ, R R; Vaida, P

    2006-01-01

    Comparative analysis of the QRS voltage response to gravity variations was made using the data about 26 normal human subjects collected in parabolic flights (CNERS-AIRBUS A300 Zero-G, n=23; IL-76MD, n=3) and during the tilt test (head-up tilt at 70 degrees for a min and head-down tilt at-15 degrees for 5 min, n=14). Both the parabolic flights and provocative tilt tests affected R-amplitude in the Z lead. During the hypergravity episodes it was observed in 95% of cases with the mean gain of 16% and maximal--56%. On transition to the horizontal position, the Rz-amplitude showed a rise in each subject (16% on the average). In microgravity, the Rz-amplitude reduced in 95% of the observations. The voltage decline averaged 18% and reached 49% at the maximum. The head-down tilt was conducive to Rz reduction in 78% of observations averaging 2%. Analysis of the ECG records under changing gravity when blood redistribution developed within few seconds not enough for serious metabolic shifts still revealed QRS deviations associated exclusively with the physical factors, i.e., alteration in tissue conduction and distance to electrodes. Our findings can stand in good stead in evaluation of the dynamics of predictive ECG parameters during long-term experiments leading to changes as in tissue conduction, so metabolism.

  18. Noninvasive fetal ECG estimation using adaptive comb filter.

    PubMed

    Wei, Zheng; Xueyun, Wei; Jian jian, Zhong; Hongxing, Liu

    2013-10-01

    This paper describes a robust and simple algorithm for fetal electrocardiogram (FECG) estimation from abdominal signal using adaptive comb filter (ACF). The ACF can adjust itself to the temporal variations in fundamental frequency, which makes it qualified for the estimation of quasi-periodic component from physiologic signal, such as ECG. The validity and performance of the described method are confirmed through experiments on real fetal ECG data. A comparison with the well-known independent component analysis (ICA) method has also been presented.

  19. Graph-based network analysis of resting-state functional MRI.

    PubMed

    Wang, Jinhui; Zuo, Xinian; He, Yong

    2010-01-01

    In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

  20. Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state.

    PubMed

    Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

    2014-01-01

    Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states.

  1. Sleep stage and obstructive apneaic epoch classification using single-lead ECG

    PubMed Central

    2010-01-01

    Background Polysomnography (PSG) is used to define physiological sleep and different physiological sleep stages, to assess sleep quality and diagnose many types of sleep disorders such as obstructive sleep apnea. However, PSG requires not only the connection of various sensors and electrodes to the subject but also spending the night in a bed that is different from the subject's own bed. This study is designed to investigate the feasibility of automatic classification of sleep stages and obstructive apneaic epochs using only the features derived from a single-lead electrocardiography (ECG) signal. Methods For this purpose, PSG recordings (ECG included) were obtained during the night's sleep (mean duration 7 hours) of 17 subjects (5 men) with ages between 26 and 67. Based on these recordings, sleep experts performed sleep scoring for each subject. This study consisted of the following steps: (1) Visual inspection of ECG data corresponding to each 30-second epoch, and selection of epochs with relatively clean signals, (2) beat-to-beat interval (RR interval) computation using an R-peak detection algorithm, (3) feature extraction from RR interval values, and (4) classification of sleep stages (or obstructive apneaic periods) using one-versus-rest approach. The features used in the study were the median value, the difference between the 75 and 25 percentile values, and mean absolute deviations of the RR intervals computed for each epoch. The k-nearest-neighbor (kNN), quadratic discriminant analysis (QDA), and support vector machines (SVM) methods were used as the classification tools. In the testing procedure 10-fold cross-validation was employed. Results QDA and SVM performed similarly well and significantly better than kNN for both sleep stage and apneaic epoch classification studies. The classification accuracy rates were between 80 and 90% for the stages other than non-rapid-eye-movement stage 2. The accuracies were 60 or 70% for that specific stage. In five

  2. The Effect of Exercise Training on Resting Concentrations of Peripheral Brain-Derived Neurotrophic Factor (BDNF): A Meta-Analysis

    PubMed Central

    Dinoff, Adam; Herrmann, Nathan; Swardfager, Walter; Liu, Celina S.; Sherman, Chelsea; Chan, Sarah; Lanctôt, Krista L.

    2016-01-01

    Background The mechanisms through which physical activity supports healthy brain function remain to be elucidated. One hypothesis suggests that increased brain-derived neurotrophic factor (BDNF) mediates some cognitive and mood benefits. This meta-analysis sought to determine the effect of exercise training on resting concentrations of BDNF in peripheral blood. Methods MEDLINE, Embase, PsycINFO, SPORTDiscus, Rehabilitation & Sports Medicine Source, and CINAHL databases were searched for original, peer-reviewed reports of peripheral blood BDNF concentrations before and after exercise interventions ≥ 2 weeks. Risk of bias was assessed using standardized criteria. Standardized mean differences (SMDs) were generated from random effects models. Risk of publication bias was assessed using funnel plots and Egger’s test. Potential sources of heterogeneity were explored in subgroup analyses. Results In 29 studies that met inclusion criteria, resting concentrations of peripheral blood BDNF were higher after intervention (SMD = 0.39, 95% CI: 0.17–0.60, p < 0.001). Subgroup analyses suggested a significant effect in aerobic (SMD = 0.66, 95% CI: 0.33–0.99, p < 0.001) but not resistance training (SMD = 0.07, 95% CI: -0.15–0.30, p = 0.52) interventions. No significant difference in effect was observed between males and females, nor in serum vs plasma. Conclusion Aerobic but not resistance training interventions increased resting BDNF concentrations in peripheral blood. PMID:27658238

  3. Resting anal pressure, not outlet obstruction or transit, predicts healthcare utilization in chronic constipation: a retrospective cohort analysis

    PubMed Central

    Staller, Kyle; Barshop, Kenneth; Kuo, Braden; Ananthakrishnan, Ashwin N

    2015-01-01

    Background Chronic constipation is common and exerts a considerable burden on health-related quality of life and healthcare resource utilization. Anorectal manometry (ARM) and colonic transit testing have allowed classification of subtypes of constipation, raising promise of targeted treatments. There has been limited study of the correlation between physiological parameters and healthcare utilization. Methods All patients undergoing ARM and colonic transit testing for chronic constipation at two tertiary care centers from 2000 to 2014 were included in this retrospective study. Our primary outcomes included number of constipation-related and gastroenterology visits per year. Multivariate linear regression adjusting for confounders defined independent effect of measures of colonic and anorectal function on healthcare utilization. Key Results Our study included 612 patients with chronic constipation. More than 50% (n=333) of patients had outlet obstruction by means of balloon expulsion testing and 43.5% (n=266) had slow colonic transit. On unadjusted analysis, outlet obstruction (1.98 vs. 1.68), slow transit (2.40 vs 2.07) and high resting anal pressure (2.16 vs. 1.76) were all associated with greater constipation-related visits/year compared to patients without each of those parameters (P<0.05 for all). Outlet obstruction and high resting anal pressure were also associated with greater number of gastroenterology visits/year. After multivariate adjustment, high resting anal pressure was the only independent predictor of increased constipation-related visits/year (P=0.02) and gastroenterology visits/year (P=0.04). Conclusions and Inferences Among patients with chronic constipation, high resting anal pressure, rather than outlet obstruction or slow transit, predicts healthcare resource utilization. PMID:26172284

  4. A Multi-Methodological MR Resting State Network Analysis to Assess the Changes in Brain Physiology of Children with ADHD

    PubMed Central

    de Celis Alonso, Benito; Hidalgo Tobón, Silvia; Dies Suarez, Pilar; García Flores, Julio; de Celis Carrillo, Benito; Barragán Pérez, Eduardo

    2014-01-01

    The purpose of this work was to highlight the neurological differences between the MR resting state networks of a group of children with ADHD (pre-treatment) and an age-matched healthy group. Results were obtained using different image analysis techniques. A sample of n = 46 children with ages between 6 and 12 years were included in this study (23 per cohort). Resting state image analysis was performed using ReHo, ALFF and ICA techniques. ReHo and ICA represent connectivity analyses calculated with different mathematical approaches. ALFF represents an indirect measurement of brain activity. The ReHo and ICA analyses suggested differences between the two groups, while the ALFF analysis did not. The ReHo and ALFF analyses presented differences with respect to the results previously reported in the literature. ICA analysis showed that the same resting state networks that appear in healthy volunteers of adult age were obtained for both groups. In contrast, these networks were not identical when comparing the healthy and ADHD groups. These differences affected areas for all the networks except the Right Memory Function network. All techniques employed in this study were used to monitor different cerebral regions which participate in the phenomenological characterization of ADHD patients when compared to healthy controls. Results from our three analyses indicated that the cerebellum and mid-frontal lobe bilaterally for ReHo, the executive function regions in ICA, and the precuneus, cuneus and the clacarine fissure for ALFF, were the “hubs” in which the main inter-group differences were found. These results do not just help to explain the physiology underlying the disorder but open the door to future uses of these methodologies to monitor and evaluate patients with ADHD. PMID:24945408

  5. The evolution of ambulatory ECG monitoring.

    PubMed

    Kennedy, Harold L

    2013-01-01

    Ambulatory Holter electrocardiographic (ECG) monitoring has undergone continuous technological evolution since its invention and development in the 1950s era. With commercial introduction in 1963, there has been an evolution of Holter recorders from 1 channel to 12 channel recorders with increasingly smaller storage media, and there has evolved Holter analysis systems employing increasingly technologically advanced electronics providing a myriad of data displays. This evolution of smaller physical instruments with increasing technological capacity has characterized the development of electronics over the past 50 years. Currently the technology has been focused upon the conventional continuous 24 to 48 hour ambulatory ECG examination, and conventional extended ambulatory monitoring strategies for infrequent to rare arrhythmic events. However, the emergence of the Internet, Wi-Fi, cellular networks, and broad-band transmission has positioned these modalities at the doorway of the digital world. This has led to an adoption of more cost-effective strategies to these conventional methods of performing the examination. As a result, the emergence of the mobile smartphone coupled with this digital capacity is leading to the recent development of Holter smartphone applications. The potential of point-of-care applications utilizing the Holter smartphone and a vast array of new non-invasive sensors is evident in the not too distant future. The Holter smartphone is anticipated to contribute significantly in the future to the field of global health.

  6. Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems.

    PubMed

    Ibaida, Ayman; Khalil, Ibrahim

    2013-12-01

    With the growing number of aging population and a significant portion of that suffering from cardiac diseases, it is conceivable that remote ECG patient monitoring systems are expected to be widely used as point-of-care (PoC) applications in hospitals around the world. Therefore, huge amount of ECG signal collected by body sensor networks from remote patients at homes will be transmitted along with other physiological readings such as blood pressure, temperature, glucose level, etc., and diagnosed by those remote patient monitoring systems. It is utterly important that patient confidentiality is protected while data are being transmitted over the public network as well as when they are stored in hospital servers used by remote monitoring systems. In this paper, a wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data. The proposed method allows ECG signal to hide its corresponding patient confidential data and other physiological information thus guaranteeing the integration between ECG and the rest. To evaluate the effectiveness of the proposed technique on the ECG signal, two distortion measurement metrics have been used: the percentage residual difference and the wavelet weighted PRD. It is found that the proposed technique provides high-security protection for patients data with low (less than 1%) distortion and ECG data remain diagnosable after watermarking (i.e., hiding patient confidential data) and as well as after watermarks (i.e., hidden data) are removed from the watermarked data.

  7. Analysis of short single rest/activation epoch fMRI by self-organizing map neural network

    NASA Astrophysics Data System (ADS)

    Erberich, Stephan G.; Dietrich, Thomas; Kemeny, Stefan; Krings, Timo; Willmes, Klaus; Thron, Armin; Oberschelp, Walter

    2000-04-01

    Functional magnet resonance imaging (fMRI) has become a standard non invasive brain imaging technique delivering high spatial resolution. Brain activation is determined by magnetic susceptibility of the blood oxygen level (BOLD effect) during an activation task, e.g. motor, auditory and visual tasks. Usually box-car paradigms have 2 - 4 rest/activation epochs with at least an overall of 50 volumes per scan in the time domain. Statistical test based analysis methods need a large amount of repetitively acquired brain volumes to gain statistical power, like Student's t-test. The introduced technique based on a self-organizing neural network (SOM) makes use of the intrinsic features of the condition change between rest and activation epoch and demonstrated to differentiate between the conditions with less time points having only one rest and one activation epoch. The method reduces scan and analysis time and the probability of possible motion artifacts from the relaxation of the patients head. Functional magnet resonance imaging (fMRI) of patients for pre-surgical evaluation and volunteers were acquired with motor (hand clenching and finger tapping), sensory (ice application), auditory (phonological and semantic word recognition task) and visual paradigms (mental rotation). For imaging we used different BOLD contrast sensitive Gradient Echo Planar Imaging (GE-EPI) single-shot pulse sequences (TR 2000 and 4000, 64 X 64 and 128 X 128, 15 - 40 slices) on a Philips Gyroscan NT 1.5 Tesla MR imager. All paradigms were RARARA (R equals rest, A equals activation) with an epoch width of 11 time points each. We used the self-organizing neural network implementation described by T. Kohonen with a 4 X 2 2D neuron map. The presented time course vectors were clustered by similar features in the 2D neuron map. Three neural networks were trained and used for labeling with the time course vectors of one, two and all three on/off epochs. The results were also compared by using a

  8. Adaptive Fourier decomposition based ECG denoising.

    PubMed

    Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

    2016-10-01

    A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition.

  9. Simple electrocardiogram (ECG) signal analyzer for homecare system among the elderly.

    PubMed

    Lin, Liuh-Chii; Yeh, Yun-Chi; Ho, Kuei-Jung

    2015-09-10

    This study presents a simple electrocardiogram (ECG) signal analyzer for homecare system among the elderly. It can transmit ECG signals of patient around his/her house through Bluetooth to computers in house. ECG signals are analyzed by the computer. If abnormal case of heartbeat is found, the emergency call is automatically dialed. Meanwhile, the determined heartbeat case of ECG signals will be forwarded to patient's MD through internet. Therefore, the patient can do whatever he/she wants around his/her house with our proposed simple cardiac arrhythmias signal analyzer. The proposed consists of five major processing stages: (i) preprocessing stage for enlarging ECG signals' amplitude and eliminating noises; (ii) ECG signal transmitter/receiver stage, ECG signals are transmitted through Bluetooth to the signal receiver in patient's house; (iii) QRS extraction stage for detecting QRS waveform using the Difference Operation Method (DOM) method; (iv) qualitative features stage for qualitative feature selection on ECG signals; and (v) classification stage for determining patient's heartbeat cases using the Principal Component Analysis (PCA) method. In the experiment, the total classification accuracy (TCA) was approximately 93.19% in average.

  10. Simple electrocardiogram (ECG) signal analyzer for homecare system among the elderly.

    PubMed

    Lin, Liuh-Chii; Yeh, Yun-Chi; Ho, Kuei-Jung

    2015-01-01

    This study presents a simple electrocardiogram (ECG) signal analyzer for homecare system among the elderly. It can transmit ECG signals of patient around his/her house through Bluetooth to computers in house. ECG signals are analyzed by the computer. If abnormal case of heartbeat is found, the emergency call is automatically dialed. Meanwhile, the determined heartbeat case of ECG signals will be forwarded to patient's MD through internet. Therefore, the patient can do whatever he/she wants around his/her house with our proposed simple cardiac arrhythmias signal analyzer. The proposed consists of five major processing stages: (i) preprocessing stage for enlarging ECG signals' amplitude and eliminating noises; (ii) ECG signal transmitter/receiver stage, ECG signals are transmitted through Bluetooth to the signal receiver in patient's house; (iii) QRS extraction stage for detecting QRS waveform using the Difference Operation Method (DOM) method; (iv) qualitative features stage for qualitative feature selection on ECG signals; and (v) classification stage for determining patient's heartbeat cases using the Principal Component Analysis (PCA) method. In the experiment, the total classification accuracy (TCA) was approximately 93.19% in average.

  11. Resting state functional connectivity analysis for addiction medicine: From individual loci to complex networks.

    PubMed

    Pariyadath, Vani; Gowin, Joshua L; Stein, Elliot A

    2016-01-01

    Resting state functional connectivity (rsFC) has provided a new and valuable tool for investigating network-level dysfunction in addiction. Following the recent development of a framework of large scale network disruptions, we have been able to arrive at unique insights into craving-related aspects of addiction using rsFC. However, such network-level advancement has thus far eluded our understanding of mesocorticolimbic involvement in addiction. Given the importance of this system in vulnerability and resilience to addiction, understanding mesocorticolimbic dynamics to the same extent could provide critical insights into the disease. To this end, we review here recent studies on addiction that employ rsfC and suggest a new approach, one that combines a novel model for addiction with new experimental techniques as well as participant groups, to accelerate progress in this arena.

  12. The association and predictive value analysis of metabolic syndrome combined with resting heart rate on cardiovascular autonomic neuropathy in the general Chinese population

    PubMed Central

    2013-01-01

    Background The purpose of this study was to explore the extent of associations of cardiovascular autonomic neuropathy (CAN) with metabolic syndrome (MetS) and resting heart reate (HR), and to evaluate the predictive value of MetS combined with HR on CAN in a large sample derived from a Chinese population. Materials and methods We conducted a large-scale, population-based, cross-sectional study to explore the relationships of CAN with MetS and resting HR. This study included 2092 participants aged 30–80 years, and a total of 387 subjects were diagnosed with CAN in our dataset. The associations of CAN with MetS and resting HR were assessed by a multivariate logistic regression (MLR) analysis (using subjects without CAN as a reference group) after controlling for potential confounding factors. The predictive performance of resting HR and MetS was evaluated using the area under the receiver-operating characteristic curve (AUC). Results A tendency toward increased CAN prevalence with increasing resting HR was reported (p for trend < 0.001). MLR analysis showed that MetS and resting HR were very significantly and independently associated with CAN (β = 0.495 for MetS and β = 0.952 for HR, P < 0.001 for both). Resting HR alone and combined with MetS (MetS-HR) strongly predicted CAN (AUC = 0.719, P < 0.001 for resting HR and AUC = 0.735, P < 0.001 for MetS-HR). Conclusion Our findings signify that MetS and resting HR were very significantly and independently associated with CAN in the general Chinese population. Resting HR and MetS-HR both have a high value in predicting CAN in the general population. PMID:24238358

  13. A Study on the Optimal Positions of ECG Electrodes in a Garment for the Design of ECG-Monitoring Clothing for Male.

    PubMed

    Cho, Hakyung; Lee, Joo Hyeon

    2015-09-01

    Smart clothing is a sort of wearable device used for ubiquitous health monitoring. It provides comfort and efficiency in vital sign measurements and has been studied and developed in various types of monitoring platforms such as T-shirt and sports bra. However, despite these previous approaches, smart clothing for electrocardiography (ECG) monitoring has encountered a serious shortcoming relevant to motion artifacts caused by wearer movement. In effect, motion artifacts are one of the major problems in practical implementation of most wearable health-monitoring devices. In the ECG measurements collected by a garment, motion artifacts are usually caused by improper location of the electrode, leading to lack of contact between the electrode and skin with body motion. The aim of this study was to suggest a design for ECG-monitoring clothing contributing to reduction of motion artifacts. Based on the clothing science theory, it was assumed in this study that the stability of the electrode in a dynamic state differed depending on the electrode location in an ECG-monitoring garment. Founded on this assumption, effects of 56 electrode positions were determined by sectioning the surface of the garment into grids with 6 cm intervals in the front and back of the bodice. In order to determine the optimal locations of the ECG electrodes from the 56 positions, ECG measurements were collected from 10 participants at every electrode position in the garment while the wearer was in motion. The electrode locations indicating both an ECG measurement rate higher than 80.0 % and a large amplitude during motion were selected as the optimal electrode locations. The results of this analysis show four electrode locations with consistently higher ECG measurement rates and larger amplitudes amongst the 56 locations. These four locations were abstracted to be least affected by wearer movement in this research. Based on this result, a design of the garment-formed ECG monitoring platform

  14. Weighted phase lag index and graph analysis: preliminary investigation of functional connectivity during resting state in children.

    PubMed

    Ortiz, Erick; Stingl, Krunoslav; Münssinger, Jana; Braun, Christoph; Preissl, Hubert; Belardinelli, Paolo

    2012-01-01

    Resting state functional connectivity of MEG data was studied in 29 children (9-10 years old). The weighted phase lag index (WPLI) was employed for estimating connectivity and compared to coherence. To further evaluate the network structure, a graph analysis based on WPLI was used to determine clustering coefficient (C) and betweenness centrality (BC) as local coefficients as well as the characteristic path length (L) as a parameter for global interconnectedness. The network's modular structure was also calculated to estimate functional segregation. A seed region was identified in the central occipital area based on the power distribution at the sensor level in the alpha band. WPLI reveals a specific connectivity map different from power and coherence. BC and modularity show a strong level of connectedness in the occipital area between lateral and central sensors. C shows different isolated areas of occipital sensors. Globally, a network with the shortest L is detected in the alpha band, consistently with the local results. Our results are in agreement with findings in adults, indicating a similar functional network in children at this age in the alpha band. The integrated use of WPLI and graph analysis can help to gain a better description of resting state networks.

  15. Bed Rest versus Early Ambulation with Standard Anticoagulation in The Management of Deep Vein Thrombosis: A Meta-Analysis

    PubMed Central

    Chen, Yuexin; Fan, Zhongjie; Li, Yongjun

    2015-01-01

    Introduction Bed rest has been considered as the cornerstone of management of deep vein thrombosis (DVT) for a long time, though it is not evidence-base, and there is growing evidence favoring early ambulation. Methods Electronic databases including Medline, PubMed, Cochrane Library and three Chinese databases were searched with key words of “deep vein thrombosis”, “pulmonary embolism”, “venous thrombosis”, “bed rest”, “immobilization”, “mobilization” and “ambulation”. We considered randomized controlled trials, prospective or retrospective cohort studies that compared the outcomes of acute DVT patients managed with early ambulation versus bed rest, in addition to standard anticoagulation. Meta-analysis pertaining to the incidence of new pulmonary embolism (PE), progression of DVT, and DVT related deaths were conducted, as well as the extent of remission of pain and edema. Results 13 studies were included with a total of 3269 patients. Compared to bed rest, early ambulation was not associated with a higher incidence of new PE, progression of DVT, or DVT related deaths (RD −0.03, 95% CI −0.05∼ −0.02; Z = 1.24, p = 0.22; random effect model, Tau2 = 0.01). Moreover, if the patients suffered moderate or severe pain initially, early ambulation was related to a better outcome, with respect to remission of acute pain in the affected limb (SMD 0.42, 95%CI 0.09∼0.74; Z = 2.52, p = 0.01; random effect model, Tau2 = 0.04). Meta-analysis of alleviation of edema cannot elicit a solid conclusion because of significant heterogeneity among the few studies. Conclusions Compared to bed rest, early ambulation of acute DVT patients with anticoagulation was not associated with a higher incidence of new PE, progression of DVT, and DVT related deaths. Furthermore, for the patients suffered moderate or severe pain initially, a better outcome can be seen in early ambulation group, regarding to the remission of acute pain in the affected limb. PMID

  16. Time-Varying Network Measures in Resting and Task States Using Graph Theoretical Analysis.

    PubMed

    Yang, Chia-Yen; Lin, Ching-Po

    2015-07-01

    Recent studies have shown the importance of graph theory in analyzing characteristic features of functional networks of the human brain. However, many of these explorations have focused on static patterns of a representative graph that describe the relatively long-term brain activity. Therefore, this study established and characterized functional networks based on the synchronization likelihood and graph theory. Quasidynamic graphs were constructed simply by dividing a long-term static graph into a sequence of subgraphs that each had a timescale of 1 s. Irregular changes were then used to investigate differences in human brain networks between resting and math-operation states using magnetoencephalography, which may provide insights into the functional substrates underlying logical reasoning. We found that graph properties could differ from brain frequency rhythms, with a higher frequency indicating a lower small-worldness, while changes in human brain state altered the functional networks into more-centralized and segregated distributions according to the task requirements. Time-varying connectivity maps could provide detailed information about the structure distribution. The frontal theta activity represents the essential foundation and may subsequently interact with high-frequency activity in cognitive processing.

  17. Analysis by NASA's VESGEN Software of Retinal Blood Vessels Before and After 70-Day Bed Rest: A Retrospective Study

    NASA Technical Reports Server (NTRS)

    Raghunandan, Sneha; Vyas, Ruchi J.; Vizzeri, Gianmarco; Taibbi, Giovanni; Zanello, Susana B.; Ploutz-Snyder, Robert; Parsons-Wingerter, Patricia A.

    2016-01-01

    Significant risks for visual impairment associated with increased intracranial pressure (VIIP) are incurred by microgravity spaceflight, especially long-duration missions. Impairments include decreased near visual acuity, posterior globe flattening, choroidal folds, optic disc edema and cotton wool spots. We hypothesize that microgravity-induced fluid shifts result in pathological changes within the retinal blood vessels that precede development of visual and other ocular impairments. Potential contributions of retinal vascular remodeling to VIIP etiology are therefore being investigated by NASAs innovative VESsel GENeration Analysis (VESGEN) software for two studies: (1) head-down tilt in human subjects before and after 70 days of bed rest, and (2) U.S. crew members before and after ISS missions. VESGEN analysis in previous research supported by the US National Institutes of Health identified surprising new opportunities to regenerate retinal vessels during early-stage, potentially reversible progression of the visually impairing and blinding disease, diabetic retinopathy.

  18. [A wireless ECG monitor based on ARM].

    PubMed

    Fan, Ai-Hua; Bian, Chun-Hua; Ning, Xin-Bao; He, Ai-Jun; Zhuang, Jian-Jun; Wu, Xu-Hui

    2008-11-01

    This paper presents a novel monitor which uses ARM controller AT91SAM7S64 as its main processor, LCM (Liquid Crystal Display Module) for displaying ECG waves, SD (Secure Digital memory) card for data storage and RF module PTR8000 for radio data transmission. This portable monitor boasts alarm function for abnormality and can provide dynamic ECG monitoring for patients.

  19. A novel algorithm for Bluetooth ECG.

    PubMed

    Pandya, Utpal T; Desai, Uday B

    2012-11-01

    In wireless transmission of ECG, data latency will be significant when battery power level and data transmission distance are not maintained. In applications like home monitoring or personalized care, to overcome the joint effect of previous issues of wireless transmission and other ECG measurement noises, a novel filtering strategy is required. Here, a novel algorithm, identified as peak rejection adaptive sampling modified moving average (PRASMMA) algorithm for wireless ECG is introduced. This algorithm first removes error in bit pattern of received data if occurred in wireless transmission and then removes baseline drift. Afterward, a modified moving average is implemented except in the region of each QRS complexes. The algorithm also sets its filtering parameters according to different sampling rate selected for acquisition of signals. To demonstrate the work, a prototyped Bluetooth-based ECG module is used to capture ECG with different sampling rate and in different position of patient. This module transmits ECG wirelessly to Bluetooth-enabled devices where the PRASMMA algorithm is applied on captured ECG. The performance of PRASMMA algorithm is compared with moving average and S-Golay algorithms visually as well as numerically. The results show that the PRASMMA algorithm can significantly improve the ECG reconstruction by efficiently removing the noise and its use can be extended to any parameters where peaks are importance for diagnostic purpose.

  20. Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span.

    PubMed

    Sokunbi, Moses O; Cameron, George G; Ahearn, Trevor S; Murray, Alison D; Staff, Roger T

    2015-11-01

    In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI dataset of 86 healthy adults (41 males) with age ranging from 19 to 85 years. We expect the complexity of the resting state fMRI signals measured to be consistent with the Goldberger/Lipsitz model for robustness where healthier (younger) and more robust systems exhibit more complexity in their physiological output and system complexity decrease with age. The mean whole brain fApEn demonstrated significant negative correlation (r = -0.472, p<0.001) with age. In comparison, SampEn produced a non-significant negative correlation (r = -0.099, p = 0.367). fApEn also demonstrated a significant (p < 0.05) negative correlation with age regionally (frontal, parietal, limbic, temporal and cerebellum parietal lobes). There was no significant correlation regionally between the SampEn maps and age. These results support the Goldberger/Lipsitz model for robustness and have shown that fApEn is potentially a sensitive new method for the complexity analysis of fMRI data.

  1. III Lead ECG Pulse Measurement Sensor

    NASA Astrophysics Data System (ADS)

    Thangaraju, S. K.; Munisamy, K.

    2015-09-01

    Heart rate sensing is very important. Method of measuring heart pulse by using an electrocardiogram (ECG) technique is described. Electrocardiogram is a measurement of the potential difference (the electrical pulse) generated by a cardiac tissue, mainly the heart. This paper also reports the development of a three lead ECG hardware system that would be the basis of developing a more cost efficient, portable and easy to use ECG machine. Einthoven's Three Lead method [1] is used for ECG signal extraction. Using amplifiers such as the instrumentation amplifier AD620BN and the conventional operational amplifier Ua741 that would be used to amplify the ECG signal extracted develop this system. The signal would then be filtered from noise using Butterworth filter techniques to obtain optimum output. Also a right leg guard was implemented as a safety feature to this system. Simulation was carried out for development of the system using P-spice Program.

  2. A Review of Fetal ECG Signal Processing; Issues and Promising Directions

    PubMed Central

    Sameni, Reza; Clifford, Gari D.

    2010-01-01

    The field of electrocardiography has been in existence for over a century, yet despite significant advances in adult clinical electrocardiography, signal processing techniques and fast digital processors, the analysis of fetal ECGs is still in its infancy. This is, partly due to a lack of availability of gold standard databases, partly due to the relatively low signal-to-noise ratio of the fetal ECG compared to the maternal ECG (caused by the various media between the fetal heart and the measuring electrodes, and the fact that the fetal heart is simply smaller), and in part, due to the less complete clinical knowledge concerning fetal cardiac function and development. In this paper we review a range of promising recording and signal processing techniques for fetal ECG analysis that have been developed over the last forty years, and discuss both their shortcomings and advantages. Before doing so, however, we review fetal cardiac development, and the etiology of the fetal ECG. A selection of relevant models for the fetal/maternal ECG mixture is also discussed. In light of current understanding of the fetal ECG, we then attempt to justify recommendations for promising future directions in signal processing, and database creation. PMID:21614148

  3. Association between resting heart rate and cardiovascular mortality: evidence from a meta-analysis of prospective studies

    PubMed Central

    Li, Yuechun

    2015-01-01

    The results from published studies on resting heart rate (RHR) and risk of cardiovascular mortality are not consistent. We therefore conducted a meta-analysis to quantitatively summarize the evidence from prospective studies about the association of RHR with risk cardiovascular mortality. Pertinent studies were identified by a search of Pubmed and Web of Knowledge to January 2015. The random effect model was used. Sensitivity analysis and publication bias were conducted. Dose-response relationship was assessed by restricted cubic spline and variance-weighted least squares regression analysis. Twenty prospective articles were included in this meta-analysis. Pooled results suggested that highest RHR level versus lowest levels was significantly associated with the risk of cardiovascular mortality [summary relative risk (RR) = 1.69, 95% CI = 1.42-2.00, I2 = 87.5%]. Subjects with RHR levels of > 80 bites per minute (bpm) had a RR of 1.49 (1.24-1.79) for cardiovascular mortality. The results for subgroups analysis of geographic locations, sex and duration of follow-up are consistent with the overall results. The linear dose-response analysis indicated that an increase in RHR of 10 bpm was statistically significantly associated with a 6% increase in the risk of developing cardiovascular mortality (summary RR = 1.06, 95% CI = 1.04-1.08). Thus, we conclude that elevated RHR was significantly associated with an increased risk of cardiovascular mortality. PMID:26629022

  4. Low-frequency fluctuation amplitude analysis of resting-state fMRI in sickle cell disease

    NASA Astrophysics Data System (ADS)

    Coloigner, Julie; Kim, Yeun; Bush, Adam; Borzage, Matt; Rajagopalan, Vidya; Lepore, Natasha; Wood, John

    2015-12-01

    Sickle cell disease may result in neurological damage and strokes, leading to morbidity and mortality. Currently, there are no dependable biomarkers to predict impending strokes. In this study, we analyzed neuronal processes at resting state and more particularly how this disease affects the default mode network. The amplitude of low frequency fluctuations was used to reflect areas of spontaneous BOLD signal across brain regions. We compared the activations of sickle cell disease patients to a control group using variance analysis and t-test. Significant regional differences among the two groups were observed, especially in the default mode network areas and cortical regions near large cerebral arteries. These findings suggest that sickle cell disease causes activation modifications near vessels, and these changes could be used as a biomarker of the disease.

  5. Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal.

    PubMed

    Panigrahy, D; Sahu, P K

    2017-02-16

    This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.

  6. An Investigation on the Effect of Extremely Low Frequency Pulsed Electromagnetic Fields on Human Electrocardiograms (ECGs)

    PubMed Central

    Fang, Qiang; Mahmoud, Seedahmed S.; Yan, Jiayong; Li, Hui

    2016-01-01

    For this investigation, we studied the effects of extremely low frequency pulse electromagnetic fields (ELF-PEMF) on the human cardiac signal. Electrocardiograms (ECGs) of 22 healthy volunteers before and after a short duration of ELF-PEMF exposure were recorded. The experiment was conducted under single-blind conditions. The root mean square (RMS) value of the recorded data was considered as comparison criteria. We also measured and analysed four important ECG time intervals before and after ELF-PEMF exposure. Results revealed that the RMS value of the ECG recordings from 18 participants (81.8% of the total participants) increased with a mean value of 3.72%. The increase in ECG voltage levels was then verified by a second experimental protocol with a control exposure. In addition to this, we used hyperbolic T-distributions (HTD) in the analysis of ECG signals to verify the change in the RR interval. It was found that there were small shifts in the frequency-domain signal before and after EMF exposure. This shift has an influence on all frequency components of the ECG signals, as all spectrums were shifted. It is shown from this investigation that a short time exposure to ELF-PEMF can affect the properties of ECG signals. Further study is needed to consolidate this finding and discover more on the biological effects of ELF-PEMF on human physiological processes. PMID:27886102

  7. Improving ECG Services at a Children's Hospital: Implementation of a Digital ECG System

    PubMed Central

    Osei, Frank A.; Gates, Gregory J.; Choi, Steven J.; Hsu, Daphne T.; Pass, Robert H.; Ceresnak, Scott R.

    2015-01-01

    Background. The use of digital ECG software and services is becoming common. We hypothesized that the introduction of a completely digital ECG system would increase the volume of ECGs interpreted at our children's hospital. Methods. As part of a hospital wide quality improvement initiative, a digital ECG service (MUSE, GE) was implemented at the Children's Hospital at Montefiore in June 2012. The total volume of ECGs performed in the first 6 months of the digital ECG era was compared to 18 months of the predigital era. Predigital and postdigital data were compared via t-tests. Results. The mean ECGs interpreted per month were 53 ± 16 in the predigital era and 216 ± 37 in the postdigital era (p < 0.001), a fourfold increase in ECG volume after introduction of the digital system. There was no significant change in inpatient or outpatient service volume during that time. The mean billing time decreased from 21 ± 27 days in the postdigital era to 12 ± 5 days in the postdigital era (p < 0.001). Conclusion. Implementation of a digital ECG system increased the volume of ECGs officially interpreted and reported. PMID:26451150

  8. Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography.

    PubMed

    Penzel, Thomas; Kantelhardt, Jan W; Bartsch, Ronny P; Riedl, Maik; Kraemer, Jan F; Wessel, Niels; Garcia, Carmen; Glos, Martin; Fietze, Ingo; Schöbel, Christoph

    2016-01-01

    The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

  9. Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography

    PubMed Central

    Penzel, Thomas; Kantelhardt, Jan W.; Bartsch, Ronny P.; Riedl, Maik; Kraemer, Jan F.; Wessel, Niels; Garcia, Carmen; Glos, Martin; Fietze, Ingo; Schöbel, Christoph

    2016-01-01

    The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave). PMID:27826247

  10. Characterization of the Resting MscS: Modeling and Analysis of the Closed Bacterial Mechanosensitive Channel of Small Conductance

    PubMed Central

    Anishkin, Andriy; Akitake, Bradley; Sukharev, Sergei

    2008-01-01

    Channels from the MscS family are adaptive tension-activated osmolyte release valves that regulate turgor in prokaryotes and volume in plant chloroplasts. The crystal structure of Escherichia coli MscS has provided a starting point for detailed descriptions of its mechanism. However, solved in the absence of the lipid bilayer, this structure may deviate from a native conformation. In this study, we utilized molecular dynamics simulations and a new iterative extrapolated-motion protocol to pack the splayed peripheral TM1 and TM2 transmembrane helices along the central TM3 shaft. This modification restored the tension transmission route between the membrane and the channel gate. We also modeled the structure of the 26-amino acid N-terminal segments that were unresolved in the crystals. The resulting compact conformation, which we believe approximates the closed resting state of MscS, matches the hydrophobic thickness of the lipid bilayer with arginines 46, 54, and 74 facing the polar lipid headgroups. The pore-lining helices in this resting state feature alternative kinks near the conserved G121 instead of the G113 kinks observed in the crystal structure and the transmembrane barrel remains stable in extended molecular dynamics simulations. Further analysis of the dynamics of the pore constriction revealed several moderately asymmetric and largely dehydrated states. Biochemical and patch-clamp experiments with engineered double-cysteine mutants demonstrated cross-linking between predicted adjacent residue pairs, which formed either spontaneously or under moderate oxidation. The L72C-V99C bridge linking more peripheral TM2 to TM3 caused a shift of channel activation to higher pressures. TM3 to TM3 cross-links through the A84C-T93C, S95C-I97C, and A106C-G108C cysteine pairs were shown to lock MscS in a nonconductive state. Normal channel activity in these mutants could be recovered upon disulfide reduction with dithiothreitol. These results confirmed our modeling

  11. [A USB-Based Digital ECG Sensor].

    PubMed

    Shi Bol; Kong, Xiangyong; Ma, Xiaozhi; Zhang, Genxuan

    2016-01-01

    Based on the ECG-specific BMD 101 integrated circun chip, this study designed a digital ECG sensor. In practical application, users just need to connect the ECG sensor 'o upper computer (such as PC or mobile phone) through USB interface, to realize the functions including display, alarm, saving, transfer etc. After tests, They demonstrate that the sensor can be applied to the detection of arrhythmia, such as bigeminy coupled rhythm, proiosystole etc. Besides, the sensor has various advantages in monitoring an managing the heart health of people out of hospital, including low cost, small volume, usableness, simplicity of operation etc.

  12. Detection of Cardiac Abnormalities from Multilead ECG using Multiscale Phase Alternation Features.

    PubMed

    Tripathy, R K; Dandapat, S

    2016-06-01

    The cardiac activities such as the depolarization and the relaxation of atria and ventricles are observed in electrocardiogram (ECG). The changes in the morphological features of ECG are the symptoms of particular heart pathology. It is a cumbersome task for medical experts to visually identify any subtle changes in the morphological features during 24 hours of ECG recording. Therefore, the automated analysis of ECG signal is a need for accurate detection of cardiac abnormalities. In this paper, a novel method for automated detection of cardiac abnormalities from multilead ECG is proposed. The method uses multiscale phase alternation (PA) features of multilead ECG and two classifiers, k-nearest neighbor (KNN) and fuzzy KNN for classification of bundle branch block (BBB), myocardial infarction (MI), heart muscle defect (HMD) and healthy control (HC). The dual tree complex wavelet transform (DTCWT) is used to decompose the ECG signal of each lead into complex wavelet coefficients at different scales. The phase of the complex wavelet coefficients is computed and the PA values at each wavelet scale are used as features for detection and classification of cardiac abnormalities. A publicly available multilead ECG database (PTB database) is used for testing of the proposed method. The experimental results show that, the proposed multiscale PA features and the fuzzy KNN classifier have better performance for detection of cardiac abnormalities with sensitivity values of 78.12 %, 80.90 % and 94.31 % for BBB, HMD and MI classes. The sensitivity value of proposed method for MI class is compared with the state-of-art techniques from multilead ECG.

  13. A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition

    PubMed Central

    Zhao, Zhidong; Yang, Lei; Chen, Diandian; Luo, Yi

    2013-01-01

    In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness. PMID:23698274

  14. Spatiotemporal analysis of the appearance of gamma-band Microstates in resting state MEG.

    PubMed

    Kelsey, Matthew; Prior, Fred W; Larson-Prior, Linda J

    2015-01-01

    Spatiotemporal analysis of EEG signal has revealed a rich set of methods to quantify neuronal activity using spatially global topographic templates, called Microstates. These methods complement more traditional spectral analysis, which uses band limited source data to determine defining differences in band power and peak characteristics. The high sampling rate and increased resistance to high frequency noise of MEG data offers an opportunity to explore the utility of spatiotemporal analysis over a wider spectrum than in EEG. In this work, we explore the utility of representing band limited MEG source data using established microstate techniques, especially in gamma frequency bands - a range yet unexplored using these techniques. We develop methods for gauging the goodness-of-fit achieved by resultant microstate templates and demonstrate sensor-level dispersion characteristics across wide-band signals as well as across signals filtered by canonical bands. These analyses reveal that, while high-frequency-band derived microstate templates are visually lawful, they fail to exhibit important explained variance and dispersion characteristics present in low- and full-band data necessary to meet the requirements of a microstate model.

  15. Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

    NASA Astrophysics Data System (ADS)

    Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

    2010-03-01

    The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

  16. Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

    PubMed Central

    Miller, Robyn L.; Yaesoubi, Maziar; Turner, Jessica A.; Mathalon, Daniel; Preda, Adrian; Pearlson, Godfrey; Adali, Tulay; Calhoun, Vince D.

    2016-01-01

    Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject’s trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is

  17. Heredity characteristics of schizophrenia shown by dynamic functional connectivity analysis of resting-state functional MRI scans of unaffected siblings.

    PubMed

    Su, Jianpo; Shen, Hui; Zeng, Ling-Li; Qin, Jian; Liu, Zhening; Hu, Dewen

    2016-08-03

    Previous static resting-state functional connectivity (FC) MRI (rs-fcMRI) studies have suggested certain heredity characteristics of schizophrenia. Recently, dynamic rs-fcMRI analysis, which can better characterize the time-varying nature of intrinsic activity and connectivity and may therefore unveil the special connectivity patterns that are always lost in static FC analysis, has shown a potential neuroendophenotype of schizophrenia. In this study, we have extended previous static rs-fcMRI studies to a dynamic study by exploring whether healthy siblings share aberrant dynamic FC patterns with schizophrenic patients, which may imply a potential risk for siblings to develop schizophrenia. We utilized the dynamic rs-fcMRI method using a sliding window approach to evaluate FC discrepancies within transient states across schizophrenic patients, unaffected siblings, and matched healthy controls. Statistical analysis showed five trait-related connections that are related to cingulo-opercular, occipital, and default mode networks, reflecting the shared connectivity alterations between schizophrenic patients and their unaffected siblings. The findings suggested that schizophrenic patients and their unaffected siblings shared common transient functional disconnectivity, implying a potential risk for the healthy siblings of developing schizophrenia.

  18. Differences in hemispherical thalamo-cortical causality analysis during resting-state fMRI.

    PubMed

    Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Wolff, Stephan; Deuschl, Guunther; Heute, Ulrich; Muthuraman, Muthuraman

    2014-01-01

    Thalamus is a very important part of the human brain. It has been reported to act as a relay for the messaging taking place between the cortical and sub-cortical regions of the brain. In the present study, we analyze the functional network between both hemispheres of the brain with the focus on thalamus. We used conditional Granger causality (CGC) and time-resolved partial directed coherence (tPDC) to investigate the functional connectivity. Results of CGC analysis revealed the asymmetry between connection strengths of the bilateral thalamus. Upon testing the functional connectivity of the default-mode network (DMN) at low-frequency fluctuations (LFF) and comparing coherence vectors using Spearman's rank correlation, we found that thalamus is a better source for the signals directed towards the contralateral regions of the brain, however, when thalamus acts as sink, it is a better sink for signals generated from ipsilateral regions of the brain.

  19. Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals.

    PubMed

    Elhaj, Fatin A; Salim, Naomie; Harris, Arief R; Swee, Tan Tian; Ahmed, Taqwa

    2016-04-01

    Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support

  20. Smartphone home monitoring of ECG

    NASA Astrophysics Data System (ADS)

    Szu, Harold; Hsu, Charles; Moon, Gyu; Landa, Joseph; Nakajima, Hiroshi; Hata, Yutaka

    2012-06-01

    A system of ambulatory, halter, electrocardiography (ECG) monitoring system has already been commercially available for recording and transmitting heartbeats data by the Internet. However, it enjoys the confidence with a reservation and thus a limited market penetration, our system was targeting at aging global villagers having an increasingly biomedical wellness (BMW) homecare needs, not hospital related BMI (biomedical illness). It was designed within SWaP-C (Size, Weight, and Power, Cost) using 3 innovative modules: (i) Smart Electrode (lowpower mixed signal embedded with modern compressive sensing and nanotechnology to improve the electrodes' contact impedance); (ii) Learnable Database (in terms of adaptive wavelets transform QRST feature extraction, Sequential Query Relational database allowing home care monitoring retrievable Aided Target Recognition); (iii) Smartphone (touch screen interface, powerful computation capability, caretaker reporting with GPI, ID, and patient panic button for programmable emergence procedure). It can provide a supplementary home screening system for the post or the pre-diagnosis care at home with a build-in database searchable with the time, the place, and the degree of urgency happened, using in-situ screening.

  1. Highly Reliable Key Generation from Electrocardiogram (ECG).

    PubMed

    Karimian, Nima; Guo, Zimu; Tehranipoor, Mark; Forte, Domenic

    2016-09-08

    Traditional passwords are inadequate as cryptographic keys, as they are easy to forge and are vulnerable to guessing. Human biometrics have been proposed as a promising alternative due to their intrinsic nature. Electrocardiogram (ECG) is an emerging biometric that is extremely difficult to forge and circumvent, but has not yet been heavily investigated for cryptographic key generation. ECG has challenges with respect to immunity to noise, abnormalities, etc. In this paper, we propose a novel key generation approach that extracts keys from real valued ECG features with high reliability and entropy in mind. Our technique, called interval optimized mapping bit allocation (IOMBA), is applied to normal and abnormal ECG signals under multiple session conditions. We also investigate IOMBA in the context of different feature extraction methods, such as wavelet, discrete cosine transform, etc. to find the best method for feature extraction. Experiments of IOMBA show that 217-bit, 38-bit, and 100-bit keys with 99.9%, 97.4%, and 95% average reliability and high entropy can be extracted from normal, abnormal, and multiple session ECG signals, respectively. By allowing more errors or lowering entropy, key lengths can be further increased by tunable parameters of IOMBA which can be useful in other applications. While IOMBA is demonstrated on ECG, it should be useful for other biometrics as well.

  2. CinC Challenge 2013: comparing three algorithms to extract fetal ECG

    NASA Astrophysics Data System (ADS)

    Loja, Juan; Velecela, Esteban; Palacio-Baus, Kenneth; Astudillo, Darwin; Medina, Rubén.; Wong, Sara

    2015-12-01

    This paper reports a comparison between three fetal ECG (fECG) detectors developed during the CinC 2013 challenge for fECG detection. Algorithm A1 is based on Independent Component Analysis, A2 is based on fECG detection of RS Slope and A3 is based on Expectation-Weighted Estimation of Fiducial Points. The proposed methodology was validated using the annotated database available for the challenge. Each detector was characterized in terms of its performance by using measures of sensitivity, (Se), positive predictive value (P+) and delay time (td). Additionally, the database was contaminated with white noise for two SNR conditions. Decision fusion was tested considering the most common types of combination of detectors. Results show that the decision fusion of A1 and A2 improves fQRS detection, maintaining high Se and P+ even under low SNR conditions without a significant td increase.

  3. Segmentation of ECG from Surface EMG Using DWT and EMD: A Comparison Study

    NASA Astrophysics Data System (ADS)

    Shahbakhti, Mohammad; Heydari, Elnaz; Luu, Gia Thien

    2014-10-01

    The electrocardiographic (ECG) signal is a major artifact during recording the surface electromyography (SEMG). Removal of this artifact is one of the important tasks before SEMG analysis for biomedical goals. In this paper, the application of discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for elimination of ECG artifact from SEMG is investigated. The focus of this research is to reach the optimized number of decomposed levels using mean power frequency (MPF) by both techniques. In order to implement the proposed methods, ten simulated and three real ECG contaminated SEMG signals have been tested. Signal-to-noise ratio (SNR) and mean square error (MSE) between the filtered and the pure signals are applied as the performance indexes of this research. The obtained results suggest both techniques could remove ECG artifact from SEMG signals fair enough, however, DWT performs much better and faster in real data.

  4. ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

    NASA Astrophysics Data System (ADS)

    Kora, Padmavathi; Sri Rama Krishna, K.

    2016-12-01

    Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

  5. ECG contamination of EEG signals: effect on entropy.

    PubMed

    Chakrabarti, Dhritiman; Bansal, Sonia

    2016-02-01

    Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.

  6. Prolonged corrected QT interval is predictive of future stroke events even in subjects without ECG-diagnosed left ventricular hypertrophy.

    PubMed

    Ishikawa, Joji; Ishikawa, Shizukiyo; Kario, Kazuomi

    2015-03-01

    We attempted to evaluate whether subjects who exhibit prolonged corrected QT (QTc) interval (≥440 ms in men and ≥460 ms in women) on ECG, with and without ECG-diagnosed left ventricular hypertrophy (ECG-LVH; Cornell product, ≥244 mV×ms), are at increased risk of stroke. Among the 10 643 subjects, there were a total of 375 stroke events during the follow-up period (128.7±28.1 months; 114 142 person-years). The subjects with prolonged QTc interval (hazard ratio, 2.13; 95% confidence interval, 1.22-3.73) had an increased risk of stroke even after adjustment for ECG-LVH (hazard ratio, 1.71; 95% confidence interval, 1.22-2.40). When we stratified the subjects into those with neither a prolonged QTc interval nor ECG-LVH, those with a prolonged QTc interval but without ECG-LVH, and those with ECG-LVH, multivariate-adjusted Cox proportional hazards analysis demonstrated that the subjects with prolonged QTc intervals but not ECG-LVH (1.2% of all subjects; incidence, 10.7%; hazard ratio, 2.70, 95% confidence interval, 1.48-4.94) and those with ECG-LVH (incidence, 7.9%; hazard ratio, 1.83; 95% confidence interval, 1.31-2.57) had an increased risk of stroke events, compared with those with neither a prolonged QTc interval nor ECG-LVH. In conclusion, prolonged QTc interval was associated with stroke risk even among patients without ECG-LVH in the general population.

  7. Resting heart rate and risk of metabolic syndrome in adults: a dose-response meta-analysis of observational studies.

    PubMed

    Liu, Xuejiao; Luo, Xinping; Liu, Yu; Sun, Xizhuo; Han, Chengyi; Zhang, Lu; Wang, Bingyuan; Ren, Yongcheng; Zhao, Yang; Zhang, Dongdong; Hu, Dongsheng; Zhang, Ming

    2017-03-01

    The magnitude of the risk of metabolic syndrome (MetS) with increased resting heart rate (RHR) has been inconsistently reported in some observational studies, and whether a dose-response relationship exists between RHR and MetS is unclear. We performed a meta-analysis including dose-response analysis to quantitatively evaluate this association in adults. We searched PubMed, Web of Knowledge, China National Knowledge Infrastructure, and WanFang databases for articles published up to April 2, 2016. A random-effects model was used to pool relative risks (RRs) and 95% confidence intervals (CIs); restricted cubic spline function was used to assess the dose-response relationship. Seven prospective cohort studies and 10 cross-sectional studies with a total of 169,786 participants were included. The pooled RR was 2.10 (95% CI 1.80-2.46, I (2) = 79.8%, n = 13) for the highest versus reference RHR category and 1.28 (95% CI 1.23-1.34, I (2) = 87.7%, n = 15) for each 10 beats per minute (bpm) increment in RHR. We found no evidence of a nonlinear dose-response association between RHR and MetS (P nonlinearity = 0.201). The relationship was consistent in most subgroup analyses and robust on sensitivity analysis. No significant publication bias was observed. This meta-analysis suggests that risk of MetS may be increased with elevated RHR.

  8. Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity.

    PubMed

    Dong, Debo; Wang, Yulin; Chang, Xuebin; Luo, Cheng; Yao, Dezhong

    2017-03-11

    Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).

  9. An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

    PubMed

    Varanini, M; Tartarisco, G; Billeci, L; Macerata, A; Pioggia, G; Balocchi, R

    2014-08-01

    Non-invasive fetal heart rate is of great relevance in clinical practice to monitor fetal health state during pregnancy. To date, however, despite significant advances in the field of electrocardiography, the analysis of abdominal fetal ECG is considered a challenging problem for biomedical and signal processing communities. This is mainly due to the low signal-to-noise ratio of fetal ECG and difficulties in cancellation of maternal QRS complexes, motion and electromyographic artefacts. In this paper we present an efficient unsupervised algorithm for fetal QRS complex detection from abdominal multichannel signal recordings combining ICA and maternal ECG cancelling, which outperforms each single method. The signal is first pre-processed to remove impulsive artefacts, baseline wandering and power line interference. The following steps are then applied: maternal ECG extraction through independent component analysis (ICA); maternal QRS detection; maternal ECG cancelling through weighted singular value decomposition; enhancing of fetal ECG through ICA and fetal QRS detection. We participated in the Physionet/Computing in Cardiology Challenge 2013, obtaining the top official scores of the challenge (among 53 teams of participants) of event 1 and event 2 concerning fetal heart rate and fetal interbeat intervals estimation section. The developed algorithms are released as open-source on the Physionet website.

  10. Depression and resting state heart rate variability in children and adolescents - A systematic review and meta-analysis.

    PubMed

    Koenig, Julian; Kemp, Andrew H; Beauchaine, Theodore P; Thayer, Julian F; Kaess, Michael

    2016-06-01

    Among adults, depression is associated with reduced vagal activity, as indexed by high frequency heart rate variability [HF-HRV]), which correlates inversely with depression severity. Available evidence in depressed children and adolescents remains to be reviewed systematically. A search of the literature was performed to identify studies reporting (i) HF-HRV in clinically depressed children/adolescents relative to controls (k=4, n=259) and (ii) the association between HF-HRV and depressive symptoms as measured by standardized psychometric instruments in children and adolescents (k=6, n=2625). Random-effects meta-analysis on group differences revealed significant effects that were associated with a moderate effect size (Hedges' g=-0.59; 95% CI [-1.05; -0.13]), indicating lower resting state HF-HRV among clinically depressed children/adolescents (n=99) compared to healthy controls (n=160), consistent with findings among adults. While no correlation between HF-HRV and depressive symptom severity was observed (r=-.041 [-0.143; 0.062]), these additional correlational findings are limited to non-clinical samples. Findings have important clinical implications including a potentially increased risk for future physical ill health and also the identification of potential new treatment targets in child and adolescent depression.

  11. Electromyography-based analysis of human upper limbs during 45-day head-down bed-rest

    NASA Astrophysics Data System (ADS)

    Fu, Anshuang; Wang, Chunhui; Qi, Hongzhi; Li, Fan; Wang, Zheng; He, Feng; Zhou, Peng; Chen, Shanguang; Ming, Dong

    2016-03-01

    Muscle deconditioning occurs in response to simulated or actual microgravity. In spaceflight, astronauts become monkey-like for mainly using their upper limbs to control the operating system and to complete corresponding tasks. The changes of upper limbs' athletic ability will directly affect astronauts' working performance. This study investigated the variation trend of surface electromyography (sEMG) during prolonged simulated microgravity. Eight healthy males participating in this study performed strict 45-day head-down bed-rest (HDBR). On the 5th day of pre-HDBR, and the 15th, the 30th and the 45th days of HDBR, the subjects performed maximum pushing task and maximum pulling task, and sEMG was collected from upper limbs synchronously. Each subject's maximum volunteer contractions of both the tasks during these days were compared, showing no significant change. However, changes were detected by sEMG-based analysis. It was found that integrated EMG, root mean square, mean frequency, fuzzy entropy of deltoid, and fuzzy entropy of triceps brachii changed significantly when comparing pre-HDBR with HDBR. The variation trend showed a recovery tendency after significant decline, which is inconsistent with the monotonic variation of lower limbs that was proved by previous research. These findings suggest that EMG changes in upper limbs during prolonged simulated microgravity, but has different variation trend from lower limbs.

  12. Effects of exercise on resting blood pressure in obese children: a meta-analysis of randomized controlled trials.

    PubMed

    García-Hermoso, A; Saavedra, J M; Escalante, Y

    2013-11-01

    The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on the resting blood pressure (systolic and diastolic) of obese children. A computerized search was made of seven databases using keywords. Effect sizes (ES) and 95% confidence intervals were calculated, and the heterogeneity of the studies was estimated using Cochran's Q-statistic applied to the effect size means. Nine randomized controlled trial (RCT) studies were selected for review as satisfying the inclusion criteria (n = 205 exercise, 205 control). The main cumulative evidence indicates that the exercise programmes with a frequency of three sessions weekly lasting longer than 60 min had a moderate effect on systolic blood pressure (ES = -0.46, I(2)  = 27%), and programmes of under 12 weeks with more than three sessions weekly were beneficial in terms of reduction of diastolic blood pressure (ES = -0.35, I(2)  = 78%).

  13. Quality assessment of digital annotated ECG data from clinical trials by the FDA ECG Warehouse.

    PubMed

    Sarapa, Nenad

    2007-09-01

    The FDA mandates that digital electrocardiograms (ECGs) from 'thorough' QTc trials be submitted into the ECG Warehouse in Health Level 7 extended markup language format with annotated onset and offset points of waveforms. The FDA did not disclose the exact Warehouse metrics and minimal acceptable quality standards. The author describes the Warehouse scoring algorithms and metrics used by FDA, points out ways to improve FDA review and suggests Warehouse benefits for pharmaceutical sponsors. The Warehouse ranks individual ECGs according to their score for each quality metric and produces histogram distributions with Warehouse-specific thresholds that identify ECGs of questionable quality. Automatic Warehouse algorithms assess the quality of QT annotation and duration of manual QT measurement by the central ECG laboratory.

  14. Clinical disease presentation and ECG characteristics of LMNA mutation carriers

    PubMed Central

    Ollila, Laura; Nikus, Kjell; Holmström, Miia; Jalanko, Mikko; Jurkko, Raija; Kaartinen, Maija; Koskenvuo, Juha; Kuusisto, Johanna; Kärkkäinen, Satu; Palojoki, Eeva; Reissell, Eeva; Piirilä, Päivi; Heliö, Tiina

    2017-01-01

    Objective Mutations in the LMNA gene encoding lamins A and C of the nuclear lamina are a frequent cause of cardiomyopathy accounting for 5–8% of familial dilated cardiomyopathy (DCM). Our aim was to study disease onset, presentation and progression among LMNA mutation carriers. Methods Clinical follow-up data from 27 LMNA mutation carriers and 78 patients with idiopathic DCM without an LMNA mutation were collected. In addition, ECG data were collected and analysed systematically from 20 healthy controls. Results Kaplan-Meier analysis revealed no difference in event-free survival (death, heart transplant, resuscitation and appropriate implantable cardioverter-defibrillator therapy included as events) between LMNA mutation carriers and DCM controls (p=0.5). LMNA mutation carriers presented with atrial fibrillation at a younger age than the DCM controls (47 vs 57 years, p=0.003). Male LMNA mutation carriers presented with clinical manifestations roughly a decade earlier than females. In close follow-up non-sustained ventricular tachycardia was detected in 78% of LMNA mutation carriers. ECG signs of septal remodelling were present in 81% of the LMNA mutation carriers, 21% of the DCM controls and none of the healthy controls giving a high sensitivity and specificity for the standard ECG in distinguishing LMNA mutation carriers from patients with DCM and healthy controls. Conclusions Male LMNA mutation carriers present clinical manifestations at a younger age than females. ECG septal remodelling appears to distinguish LMNA mutation carriers from healthy controls and patients with DCM without LMNA mutations. PMID:28123761

  15. Robust electrocardiogram (ECG) beat classification using discrete wavelet transform.

    PubMed

    Minhas, Fayyaz-ul-Amir Afsar; Arif, Muhammad

    2008-05-01

    This paper presents a robust technique for the classification of six types of heartbeats through an electrocardiogram (ECG). Features extracted from the QRS complex of the ECG using a wavelet transform along with the instantaneous RR-interval are used for beat classification. The wavelet transform utilized for feature extraction in this paper can also be employed for QRS delineation, leading to reduction in overall system complexity as no separate feature extraction stage would be required in the practical implementation of the system. Only 11 features are used for beat classification with the classification accuracy of approximately 99.5% through a KNN classifier. Another main advantage of this method is its robustness to noise, which is illustrated in this paper through experimental results. Furthermore, principal component analysis (PCA) has been used for feature reduction, which reduces the number of features from 11 to 6 while retaining the high beat classification accuracy. Due to reduction in computational complexity (using six features, the time required is approximately 4 ms per beat), a simple classifier and noise robustness (at 10 dB signal-to-noise ratio, accuracy is 95%), this method offers substantial advantages over previous techniques for implementation in a practical ECG analyzer.

  16. Motion artifact removal algorithm by ICA for e-bra: a women ECG measurement system

    NASA Astrophysics Data System (ADS)

    Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

    2013-04-01

    Wearable ECG(ElectroCardioGram) measurement systems have increasingly been developing for people who suffer from CVD(CardioVascular Disease) and have very active lifestyles. Especially, in the case of female CVD patients, several abnormal CVD symptoms are accompanied with CVDs. Therefore, monitoring women's ECG signal is a significant diagnostic method to prevent from sudden heart attack. The E-bra ECG measurement system from our previous work provides more convenient option for women than Holter monitor system. The e-bra system was developed with a motion artifact removal algorithm by using an adaptive filter with LMS(least mean square) and a wandering noise baseline detection algorithm. In this paper, ICA(independent component analysis) algorithms are suggested to remove motion artifact factor for the e-bra system. Firstly, the ICA algorithms are developed with two kinds of statistical theories: Kurtosis, Endropy and evaluated by performing simulations with a ECG signal created by sgolayfilt function of MATLAB, a noise signal including 0.4Hz, 1.1Hz and 1.9Hz, and a weighed vector W estimated by kurtosis or entropy. A correlation value is shown as the degree of similarity between the created ECG signal and the estimated new ECG signal. In the real time E-Bra system, two pseudo signals are extracted by multiplying with a random weighted vector W, the measured ECG signal from E-bra system, and the noise component signal by noise extraction algorithm from our previous work. The suggested ICA algorithm basing on kurtosis or entropy is used to estimate the new ECG signal Y without noise component.

  17. Real-time CHF detection from ECG signals using a novel discretization method.

    PubMed

    Orhan, Umut

    2013-10-01

    This study proposes a new method, equal frequency in amplitude and equal width in time (EFiA-EWiT) discretization, to discriminate between congestive heart failure (CHF) and normal sinus rhythm (NSR) patterns in ECG signals. The ECG unit pattern concept was introduced to represent the standard RR interval, and our method extracted certain features from the unit patterns to classify by a primitive classifier. The proposed method was tested on two classification experiments by using ECG records in Physiobank databases and the results were compared to those from several previous studies. In the first experiment, an off-line classification was performed with unit patterns selected from long ECG segments. The method was also used to detect CHF by real-time ECG waveform analysis. In addition to demonstrating the success of the proposed method, the results showed that some unit patterns in a long ECG segment from a heart patient were more suggestive of disease than the others. These results indicate that the proposed approach merits additional research.

  18. Artificial neural network-based classification of body movements in ambulatory ECG signal.

    PubMed

    Darji, Sachin T; Kher, Rahul K

    2013-11-01

    Abstract Ambulatory ECG monitoring provides electrical activity of the heart when a person is involved in doing normal routine activities. Thus, the recorded ECG signal consists of cardiac signal along with motion artifacts introduced due to a person's body movements during routine activities. Detection of motion artifacts due to different physical activities might help in further cardiac diagnosis. Ambulatory ECG signal analysis for detection of various motion artifacts using adaptive filtering approach is addressed in this paper. We have used BIOPAC MP 36 system for acquiring ECG signal. The ECG signals of five healthy subjects (aged between 22-30 years) were recorded while the person performed various body movements like up and down movement of the left hand, up and down movement of the right hand, waist twisting movement while standing and change from sitting down on a chair to standing up movement in lead I configuration. An adaptive filter-based approach has been used to extract the motion artifact component from the ambulatory ECG signal. The features of motion artifact signal, extracted using Gabor transform, have been used to train the artificial neural network (ANN) for classifying body movements.

  19. Self-organized neural network for the quality control of 12-lead ECG signals.

    PubMed

    Chen, Yun; Yang, Hui

    2012-09-01

    Telemedicine is very important for the timely delivery of health care to cardiovascular patients, especially those who live in the rural areas of developing countries. However, there are a number of uncertainty factors inherent to the mobile-phone-based recording of electrocardiogram (ECG) signals such as personnel with minimal training and other extraneous noises. PhysioNet organized a challenge in 2011 to develop efficient algorithms that can assess the ECG signal quality in telemedicine settings. This paper presents our efforts in this challenge to integrate multiscale recurrence analysis with a self-organizing map for controlling the ECG signal quality. As opposed to directly evaluating the 12-lead ECG, we utilize an information-preserving transform, i.e. Dower transform, to derive the 3-lead vectorcardiogram (VCG) from the 12-lead ECG in the first place. Secondly, we delineate the nonlinear and nonstationary characteristics underlying the 3-lead VCG signals into multiple time-frequency scales. Furthermore, a self-organizing map is trained, in both supervised and unsupervised ways, to identify the correlations between signal quality and multiscale recurrence features. The efficacy and robustness of this approach are validated using real-world ECG recordings available from PhysioNet. The average performance was demonstrated to be 95.25% for the training dataset and 90.0% for the independent test dataset with unknown labels.

  20. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia

    PubMed Central

    Meda, Shashwath A.; Ruaño, Gualberto; Windemuth, Andreas; O’Neil, Kasey; Berwise, Clifton; Dunn, Sabra M.; Boccaccio, Leah E.; Narayanan, Balaji; Kocherla, Mohan; Sprooten, Emma; Keshavan, Matcheri S.; Tamminga, Carol A.; Sweeney, John A.; Clementz, Brett A.; Calhoun, Vince D.; Pearlson, Godfrey D.

    2014-01-01

    The brain’s default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging–genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases. PMID:24778245

  1. Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

    PubMed

    Meda, Shashwath A; Ruaño, Gualberto; Windemuth, Andreas; O'Neil, Kasey; Berwise, Clifton; Dunn, Sabra M; Boccaccio, Leah E; Narayanan, Balaji; Kocherla, Mohan; Sprooten, Emma; Keshavan, Matcheri S; Tamminga, Carol A; Sweeney, John A; Clementz, Brett A; Calhoun, Vince D; Pearlson, Godfrey D

    2014-05-13

    The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

  2. Brain complex network analysis by means of resting state fMRI and graph analysis: will it be helpful in clinical epilepsy?

    PubMed

    Onias, Heloisa; Viol, Aline; Palhano-Fontes, Fernanda; Andrade, Katia C; Sturzbecher, Marcio; Viswanathan, Gandhimohan; de Araujo, Draulio B

    2014-09-01

    Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy.

  3. Effect of Head-Down Bed Rest and Artificial Gravity Countermeasure on Cardiac Autonomic and Advanced Electrocardiographic Function

    NASA Technical Reports Server (NTRS)

    Schlegel, T. T.; Platts, S.; Stenger, M.; Ribeiro, C.; Natapoff, A.; Howarth, M.; Evans, J.

    2007-01-01

    To study the effects of 21 days of head-down bed rest (HDBR), with versus without an artificial gravity (AG) countermeasure, on cardiac autonomic and advanced electrocardiographic function. Fourteen healthy men participated in the study: seven experienced 21 days of HDBR alone ("HDBR controls") and seven the same degree and duration of HDBR but with approximately 1hr daily short-arm centrifugation as an AG countermeasure ("AG-treated"). Five minute supine high-fidelity 12-lead ECGs were obtained in all subjects: 1) 4 days before HDBR; 2) on the last day of HDBR; and 3) 7 days after HDBR. Besides conventional 12-lead ECG intervals and voltages, all of the following advanced ECG parameters were studied: 1) both stochastic (time and frequency domain) and deterministic heart rate variability (HRV); 2) beat-to-beat QT interval variability (QTV); 3) T-wave morphology, including signal-averaged T-wave residua (TWR) and principal component analysis ratios; 4) other SAECG-related parameters including high frequency QRS ECG and late potentials; and 5) several advanced ECG estimates of left ventricular (LV) mass. The most important results by repeated measures ANOVA were that: 1) Heart rates, Bazett-corrected QTc intervals, TWR, LF/HF power and the alpha 1 of HRV were significantly increased in both groups (i.e., by HDBR), but with no relevant HDBR*group differences; 2) All purely "vagally-mediated" parameters of HRV (e.g., RMSSD, HF power, Poincare SD1, etc.), PR intervals, and also several parameters of LV mass (Cornell and Sokolow-Lyon voltages, spatial ventricular activation times, ventricular gradients) were all significantly decreased in both groups (i.e., by HDBR), but again with no relevant HDBR*group differences); 3) All "generalized" or "vagal plus sympathetic" parameters of stochastic HRV (i.e., SDNN, total power, LF power) were significantly more decreased in the AG-treated group than in the HDBR-only group (i.e., here there was a relevant HDBR*group difference

  4. ECG monitoring of heart failure and pilot load/overload by the Vesla seat pad.

    PubMed

    Sem-Jacobsen, C W

    1976-04-01

    Heart failure has caused sudden incapacitation of pilots in command of commerical airliners. These fatal episodes have occurred in connection with takeoffs and landings, and have resulted in incidents as well as major accidents in which more than 300 people have been killed. Coronary attack may be verified later at autopsy. Sudden cardiac arrest or serious episodes, such as ventricular tachycardia, usually cannot be detected at autopsy. A number of accidents due to unknown reasons or to "pilot error" can be due to, and some probably are, cardiac breakdown. It is today possible, with the Vesla Seat Pad, to monitor the pilot's ECG. The Vesla Seat Pad is a device for biomedical monitoring of ECG signals from human subjects without attachment to the subjects of any leads or sensor devices. The Vesla pad on which a human subject may rest, requires no power source. It is capable of obtaining appropriate ECG signals, transmitted to the pad through the medium of the subject's perspiration, for monitoring the subject's heart action. ECG signals, together with other data, can be electronically processed and used to warn the co-pilot and tower of impending hazard. The "dead man's button" with an OVERLOAD warning system could greatly, when taken into use, improve flying safety.

  5. Identification and Expression Analysis of Upregulated Genes in the Resting Egg-Producing Water Flea (Daphnia pulex).

    PubMed

    Takahashi, Tomoko; Ohnuma, Masaaki

    2016-02-01

    Water fleas (Daphnia pulex) normally produce subitaneous eggs that initiate development immediately after oviposition. However, in response to habitat degradation, resting eggs are produced, which are enclosed in a sturdy outer envelope (ephippium) and can survive in harsh environments for an extended time. To understand the molecular mechanism underlying resting egg production in D. pulex, we investigated the genes whose expression patterns played a role in the production and identified the following six candidate genes: Dpfa-1, Dpfa-2, Dpep-1, Dpep-2, Dpep-3, and Dpep-4. These six genes displayed > 40-fold higher expression levels in resting egg-producing animals compared with those in subitaneous egg-producing animals at the period when the ovaries were mature. Dpfa-1 and Dpfa-2 were expressed in the fat cells, and their expression patterns were synchronized with the development of resting egg oocytes in the ovary. In contrast, Dpep-1-4 were expressed in the morphologically altered epidermal cells of the brood chamber with the formation of the ephippium, and their expression patterns were also related to ephippium formation. Our results suggest that the former two genes encode the resting egg-specific components produced by fat cells and that the latter four genes encode the components related to the ephippium formation synthesized by epidermal cells.

  6. Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis

    PubMed Central

    Jung, Wi Hoon; Kim, Sung Nyun; Lee, Tae Young; Jang, Joon Hwan; Choi, Chi-Hoon; Kang, Do-Hyung; Kwon, Jun Soo

    2013-01-01

    One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC) in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts (BEs) compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry (VBM) and FC analyses in BEs to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis (GTA) to explore the topological organization of whole-brain functional networks. Compared to novices, BEs exhibited decreased and increased gray matter volume (GMV) in the amygdala and nucleus accumbens (NA), respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex (mOFC) and decreased FC between the NA and medial prefrontal cortex (mPFC). Further GTA revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in BEs. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing. PMID:24106471

  7. Exploring the brains of Baduk (Go) experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis.

    PubMed

    Jung, Wi Hoon; Kim, Sung Nyun; Lee, Tae Young; Jang, Joon Hwan; Choi, Chi-Hoon; Kang, Do-Hyung; Kwon, Jun Soo

    2013-01-01

    One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC) in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts (BEs) compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry (VBM) and FC analyses in BEs to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis (GTA) to explore the topological organization of whole-brain functional networks. Compared to novices, BEs exhibited decreased and increased gray matter volume (GMV) in the amygdala and nucleus accumbens (NA), respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex (mOFC) and decreased FC between the NA and medial prefrontal cortex (mPFC). Further GTA revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in BEs. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing.

  8. ECG Response of Koalas to Tourists Proximity: A Preliminary Study

    PubMed Central

    Ropert-Coudert, Yan; Brooks, Lisa; Yamamoto, Maki; Kato, Akiko

    2009-01-01

    Koalas operate on a tight energy budget and, thus, may not always display behavioral avoidance reaction when placed in a stressful condition. We investigated the physiological response of captive koalas Phascolarctos cinereus in a conservation centre to the presence of tourists walking through their habitat. We compared, using animal-attached data-recorders, the electrocardiogram activity of female koalas in contact with tourists and in a human-free area. One of the koalas in the tourist zone presented elevated heart rate values and variability throughout the recording period. The remaining female in the exhibit area showed a higher field resting heart rates during the daytime than that in the isolated area. In the evening, heart rate profiles changed drastically and both the koalas in the exhibit and in the tourist-free zones displayed similar field resting heart rates, which were lower than those during the day. In parallel, the autonomic nervous systems of these two individuals evolved from sympathetic-dominant during the day to parasympathetic-dominant in the evening. Our results report ECG of free-living koalas for the first time. Although they are preliminary due to the difficulty of having sufficient samples of animals of the same sex and age, our results stress out the importance of studies investigating the physiological reaction of animals to tourists. PMID:19823679

  9. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    PubMed Central

    Xu, Tingting; Cullen, Kathryn R.; Mueller, Bryon; Schreiner, Mindy W.; Lim, Kelvin O.; Schulz, S. Charles; Parhi, Keshab K.

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new

  10. Bed rest during pregnancy

    MedlinePlus

    ... on the inferior vena cava. How Can I Deal with Discomfort from Bed Rest? Bed rest can ... Group Health Cooperative, Bellevue, WA. Also reviewed by David Zieve, MD, MHA, Isla Ogilvie, PhD, and the ...

  11. [Implementation of ECG Monitoring System Based on Internet of Things].

    PubMed

    Lu, Liangliang; Chen, Minya

    2015-11-01

    In order to expand the capabilities of hospital's traditional ECG device and enhance medical staff's work efficiency, an ECG monitoring system based on internet of things is introduced. The system can monitor ECG signals in real time and analyze data using ECG sensor, PDA, Web servers, which embeds C language, Android systems, .NET, wireless network and other technologies. After experiments, it can be showed that the system has high reliability and stability and can bring the convenience to medical staffs.

  12. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Radiographic ECG/respirator synchronizer. 892.1970... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic ECG/respirator synchronizer. (a) Identification. A radiographic ECG/respirator synchronizer is a device intended to be used...

  13. [Research of DICOM-ECG implementation based on DCMTK].

    PubMed

    Wang, Xiang; Wu, Jian; Ma, Yaquanz; Peng, Cheng

    2013-11-01

    Parsed the ECG descriptions in DICOM 3.0 standard and accomplished a DICOM-ECG file which conforms to the DICOM standard by a toolkit DCMTK. The DICOM-ECG file can communicate with systems which support DICOM standard directly.

  14. ECG Beats Classification Using Mixture of Features

    PubMed Central

    Ari, Samit

    2014-01-01

    Classification of electrocardiogram (ECG) signals plays an important role in clinical diagnosis of heart disease. This paper proposes the design of an efficient system for classification of the normal beat (N), ventricular ectopic beat (V), supraventricular ectopic beat (S), fusion beat (F), and unknown beat (Q) using a mixture of features. In this paper, two different feature extraction methods are proposed for classification of ECG beats: (i) S-transform based features along with temporal features and (ii) mixture of ST and WT based features along with temporal features. The extracted feature set is independently classified using multilayer perceptron neural network (MLPNN). The performances are evaluated on several normal and abnormal ECG signals from 44 recordings of the MIT-BIH arrhythmia database. In this work, the performances of three feature extraction techniques with MLP-NN classifier are compared using five classes of ECG beat recommended by AAMI (Association for the Advancement of Medical Instrumentation) standards. The average sensitivity performances of the proposed feature extraction technique for N, S, F, V, and Q are 95.70%, 78.05%, 49.60%, 89.68%, and 33.89%, respectively. The experimental results demonstrate that the proposed feature extraction techniques show better performances compared to other existing features extraction techniques. PMID:27350985

  15. Exploring the "what if?" in geology through a RESTful open-source framework for cloud-based simulation and analysis

    NASA Astrophysics Data System (ADS)

    Klump, Jens; Robertson, Jess

    2016-04-01

    The spatial and temporal extent of geological phenomena makes experiments in geology difficult to conduct, if not entirely impossible and collection of data is laborious and expensive - so expensive that most of the time we cannot test a hypothesis. The aim, in many cases, is to gather enough data to build a predictive geological model. Even in a mine, where data are abundant, a model remains incomplete because the information at the level of a blasting block is two orders of magnitude larger than the sample from a drill core, and we have to take measurement errors into account. So, what confidence can we have in a model based on sparse data, uncertainties and measurement error? Our framework consist of two layers: (a) a ground-truth layer that contains geological models, which can be statistically based on historical operations data, and (b) a network of RESTful synthetic sensor microservices which can query the ground-truth for underlying properties and produce a simulated measurement to a control layer, which could be a database or LIMS, a machine learner or a companies' existing data infrastructure. Ground truth data are generated by an implicit geological model which serves as a host for nested models of geological processes as smaller scales. Our two layers are implemented using Flask and Gunicorn, which are open source Python web application framework and server, the PyData stack (numpy, scipy etc) and Rabbit MQ (an open-source queuing library). Sensor data is encoded using a JSON-LD version of the SensorML and Observations and Measurements standards. Containerisation of the synthetic sensors using Docker and CoreOS allows rapid and scalable deployment of large numbers of sensors, as well as sensor discovery to form a self-organized dynamic network of sensors. Real-time simulation of data sources can be used to investigate crucial questions such as the potential information gain from future sensing capabilities, or from new sampling strategies, or the

  16. Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

    PubMed

    Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

    2016-01-01

    Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

  17. Electromyographic analysis of upper and lower fascicles of the orbicularis oris muscle in deaf individuals, in mandibular rest position, compared to hearers.

    PubMed

    Regalo, S C H; Vitti, M; Hallak, J E C; Siéssere, S; Pagnano, V O; Semprini, M

    2006-01-01

    This study had the aim to analyze electromyographically, the upper and lower fascicles of the orbicularis oris muscle in bilingual, oralist deaf individuals, comparing them with clinically healthy volunteers in mandibular rest position. This was performed in 50 patients of both sexes with an average age of 18.5 years, divided into 4 groups. 1. Ten deaf bilingual, nasal-breathing patients; 2. Ten deaf bilingual, buccal-breathing patients; 3. Ten deaf oralist, nasal-breathing patients; 4. Twenty healthy volunteers, nasal-breathing patients. An electromyograph K6-I EMG Light Channel Surface Electromyography (Myo-tronics Co. Seattle, WA, EUA) of eight channels was used. The electrodes applied were duotrodes, silver-chloride surface, disposable. Statistical analysis was performed using the SPSS software version 10.0 (Chicago, IL). Continuos data with normal distribution were analyzed by univariate analysis of variance (ANOVA). The level of significance was set at alpha= 0.01. Comparing the EMG activity of the orbicularis oris muscle made it possible to verify that, during clinical mandibular rest position, all four groups presented various levels of electromyographic (EMG) activity with statistically significant differences (F = 8.81, p < 0.01). Based this study's data, it was possible to conclude that the electromyography analysis of the orbicularis oris muscle in deaf individuals showed that deaf individuals presented higher levels of EMG activity of the orbicularis oris muscle than normal controls during mandibular rest position.

  18. Sparse Matrix for ECG Identification with Two-Lead Features

    PubMed Central

    Tseng, Kuo-Kun; Luo, Jiao; Wang, Wenmin; Haiting, Dong

    2015-01-01

    Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods. PMID:25961074

  19. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  20. Hyperkalemia Induced Brugada Phenocopy: A Rare ECG Manifestation

    PubMed Central

    Akbar, Ghulam; Mirrani, Ghazi

    2017-01-01

    Brugada syndrome (BrS) is an inherited disorder of cardiac ion channels characterized by peculiar ECG findings predisposing individuals to ventricular arrhythmias, syncope, and sudden cardiac death (SCD). Various electrolyte disturbances and ion channels blocking drugs could also provoke BrS ECG findings without genetic BrS. Clinical differentiation and recognition are essential for guiding the legitimate action. Hyperkalemia is well known to cause a wide variety of ECG manifestations. Severe hyperkalemia can even cause life threatening ventricular arrhythmias and cardiac conduction abnormalities. Most common ECG findings include peaked tall T waves with short PR interval and wide QRS complex. Since it is very commonly encountered disorder, physicians need to be aware of even its rare ECG manifestations, which include ST segment elevation and Brugada pattern ECG (BrP). We are adding a case to the limited literature about hyperkalemia induced reversible Brugada pattern ECG changes. PMID:28326201

  1. Identifying UMLS concepts from ECG Impressions using KnowledgeMap.

    PubMed

    Denny, Joshua C; Spickard, Anderson; Miller, Randolph A; Schildcrout, Jonathan; Darbar, Dawood; Rosenbloom, S Trent; Peterson, Josh F

    2005-01-01

    Electrocardiogram (ECG) impressions represent a wealth of medical information for potential decision support and drug-effect discovery. Much of this information is inaccessible to automated methods in the free-text portion of the ECG report. We studied the application of the KnowledgeMap concept identifier (KMCI) to map Unified Medical Language System (UMLS) concepts from ECG impressions. ECGs were processed by KMCI and the results scored for accuracy by multiple raters. Reviewers also recorded unidentified concepts through the scoring interface. Overall, KMCI correctly identified 1059 out of 1171 concepts for a recall of 0.90. Precision, indicating the proportion of ECG concepts correctly identified, was 0.94. KMCI was particularly effective at identifying ECG rhythms (330/333), perfusion changes (65/66), and noncardiac medical concepts (11/11). In conclusion, KMCI is an effective method for mapping ECG impressions to UMLS concepts.

  2. Resting cerebral blood flow

    PubMed Central

    Ances, B M.; Sisti, D; Vaida, F; Liang, C L.; Leontiev, O; Perthen, J E.; Buxton, R B.; Benson, D; Smith, D M.; Little, S J.; Richman, D D.; Moore, D J.; Ellis, R J.

    2009-01-01

    Objective: HIV enters the brain soon after infection causing neuronal damage and microglial/astrocyte dysfunction leading to neuropsychological impairment. We examined the impact of HIV on resting cerebral blood flow (rCBF) within the lenticular nuclei (LN) and visual cortex (VC). Methods: This cross-sectional study used arterial spin labeling MRI (ASL-MRI) to measure rCBF within 33 HIV+ and 26 HIV− subjects. Nonparametric Wilcoxon rank sum test assessed rCBF differences due to HIV serostatus. Classification and regression tree (CART) analysis determined optimal rCBF cutoffs for differentiating HIV serostatus. The effects of neuropsychological impairment and infection duration on rCBF were evaluated. Results: rCBF within the LN and VC were significantly reduced for HIV+ compared to HIV− subjects. A 2-tiered CART approach using either LN rCBF ≤50.09 mL/100 mL/min or LN rCBF >50.09 mL/100 mL/min but VC rCBF ≤37.05 mL/100 mL/min yielded an 88% (29/33) sensitivity and an 88% (23/26) specificity for differentiating by HIV serostatus. HIV+ subjects, including neuropsychologically unimpaired, had reduced rCBF within the LN (p = 0.02) and VC (p = 0.001) compared to HIV− controls. A temporal progression of brain involvement occurred with LN rCBF significantly reduced for both acute/early (<1 year of seroconversion) and chronic HIV-infected subjects, whereas rCBF in the VC was diminished for only chronic HIV-infected subjects. Conclusion: Resting cerebral blood flow (rCBF) using arterial spin labeling MRI has the potential to be a noninvasive neuroimaging biomarker for assessing HIV in the brain. rCBF reductions that occur soon after seroconversion possibly reflect neuronal or vascular injury among HIV+ individuals not yet expressing neuropsychological impairment. GLOSSARY AEH = acute/early HIV infection; ANOVA = analysis of variance; ASL-MRI = arterial spin labeling MRI; CART = classification and regression tree; CBF = cerebral blood flow; CH = chronic HIV

  3. Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.

    PubMed

    Oster, Julien; Behar, Joachim; Sayadi, Omid; Nemati, Shamim; Johnson, Alistair E W; Clifford, Gari D

    2015-09-01

    Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. F1 scores of 98.3% and 99.5% were found on each database, respectively, which are superior to other published algorithms' results reported on the same databases. Only 3% of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.

  4. An ECG storage and retrieval system embedded in client server HIS utilizing object-oriented DB.

    PubMed

    Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S

    1996-02-01

    In the University of Tokyo Hospital, the improved client server HIS has been applied to clinical practice and physicians can order prescription, laboratory examination, ECG examination and radiographic examination, etc. directly by themselves and read results of these examinations, except medical signal waves, schema and image, on UNIX workstations. Recently, we designed and developed an ECG storage and retrieval system embedded in the client server HIS utilizing object-oriented database to take the first step in dealing with digitized signal, schema and image data and show waves, graphics, and images directly to physicians by the client server HIS. The system was developed based on object-oriented analysis and design, and implemented with object-oriented database management system (OODMS) and C++ programming language. In this paper, we describe the ECG data model, functions of the storage and retrieval system, features of user interface and the result of its implementation in the HIS.

  5. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach.

    PubMed

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-04-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD.

  6. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach

    PubMed Central

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-01-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD. PMID:24098860

  7. Single frequency RF powered ECG telemetry system

    NASA Technical Reports Server (NTRS)

    Ko, W. H.; Hynecek, J.; Homa, J.

    1979-01-01

    It has been demonstrated that a radio frequency magnetic field can be used to power implanted electronic circuitry for short range telemetry to replace batteries. A substantial reduction in implanted volume can be achieved by using only one RF tank circuit for receiving the RF power and transmitting the telemetered information. A single channel telemetry system of this type, using time sharing techniques, was developed and employed to transmit the ECG signal from Rhesus monkeys in primate chairs. The signal from the implant is received during the period when the RF powering radiation is interrupted. The ECG signal is carried by 20-microsec pulse position modulated pulses, referred to the trailing edge of the RF powering pulse. Satisfactory results have been obtained with this single frequency system. The concept and the design presented may be useful for short-range long-term implant telemetry systems.

  8. Simulation methods for the online extraction of ECG parameters under Matlab/Simulink.

    PubMed

    von Wagner, G; Kunzmann, U; Schöchlin, J; Bolz, A

    2002-01-01

    The classification of cardiac pathologies in the human ECG greatly depends on the reliable extraction of characteristic features. This work presents a complete simulation environment for testing ECG classification algorithms under Matlab/Simulink. Evaluation of algorithm performance is undertaken in full compliance with the ANSI/AAMI standards EC38 and EC57, and ranges from beat-to-beat analysis to the comparison of episode markers (e.g., for VT/VF detection algorithms). For testing the quality of waveform boundary detection, our own testing methods have been implemented in compliance with existing literature.

  9. Improving the quality of the ECG signal by filtering in wavelet transform domain

    NASA Astrophysics Data System (ADS)

    DzierŻak, RóŻa; Surtel, Wojciech; Dzida, Grzegorz; Maciejewski, Marcin

    2016-09-01

    The article concerns the research methods of noise reduction occurring in the ECG signals. The method is based on the use of filtration in wavelet transform domain. The study was conducted on two types of signal - received during the rest of the patient and obtained during physical activity. For each of the signals 3 types of filtration were used. The study was designed to determine the effectiveness of various wavelets for de-noising signals obtained in both cases. The results confirm the suitability of the method for improving the quality of the electrocardiogram in case of both types of signals.

  10. Abnormal functional resting-state networks in ADHD: graph theory and pattern recognition analysis of fMRI data.

    PubMed

    dos Santos Siqueira, Anderson; Biazoli Junior, Claudinei Eduardo; Comfort, William Edgar; Rohde, Luis Augusto; Sato, João Ricardo

    2014-01-01

    The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors.

  11. Bridging the Gap: Dynamic Causal Modeling and Granger Causality Analysis of Resting State Functional Magnetic Resonance Imaging.

    PubMed

    Bajaj, Sahil; Adhikari, Bhim M; Friston, Karl J; Dhamala, Mukesh

    2016-09-16

    Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitative) in-degree of key nodes of the default mode. Our simulation results suggested a (qualitative) consistency between GC and DCM. Furthermore, by applying nonparametric GC and stochastic DCM to resting-state fMRI data, we confirmed that both GC and DCM infer similar (quantitative) directionality between the posterior cingulate cortex (PCC), the medial prefrontal cortex, the left middle temporal cortex, and the left angular gyrus. These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.

  12. Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data

    PubMed Central

    dos Santos Siqueira, Anderson; Biazoli Junior, Claudinei Eduardo; Comfort, William Edgar; Rohde, Luis Augusto; Sato, João Ricardo

    2014-01-01

    The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors. PMID:25309910

  13. ECG Sensor Card with Evolving RBP Algorithms for Human Verification

    PubMed Central

    Tseng, Kuo-Kun; Huang, Huang-Nan; Zeng, Fufu; Tu, Shu-Yi

    2015-01-01

    It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack—the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals. PMID:26307995

  14. ECG Sensor Card with Evolving RBP Algorithms for Human Verification.

    PubMed

    Tseng, Kuo-Kun; Huang, Huang-Nan; Zeng, Fufu; Tu, Shu-Yi

    2015-08-21

    It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack-the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals.

  15. An independent components and functional connectivity analysis of resting state fMRI data points to neural network dysregulation in adult ADHD.

    PubMed

    Hoekzema, Elseline; Carmona, Susana; Ramos-Quiroga, J Antoni; Richarte Fernández, Vanesa; Bosch, Rosa; Soliva, Juan Carlos; Rovira, Mariana; Bulbena, Antonio; Tobeña, Adolf; Casas, Miguel; Vilarroya, Oscar

    2014-04-01

    Spontaneous fluctuations can be measured in the brain that reflect dissociable functional networks oscillating at synchronized frequencies, such as the default mode network (DMN). In contrast to its diametrically opposed task-positive counterpart, the DMN predominantly signals during a state of rest, and inappropriate regulation of this network has been associated with inattention, a core characteristic of attention-deficit/hyperactivity disorder (ADHD). To examine whether abnormalities can be identified in the DMN component of patients with ADHD, we applied an independent components analysis to resting state functional magnetic resonance imaging data acquired from 22 male medication-naïve adults with ADHD and 23 neurotypical individuals. We observed a stronger coherence of the left dorsolateral prefrontal cortex (dlPFC) with the DMN component in patients with ADHD which correlated with measures of selective attention. The increased left dlPFC-DMN coherence also surfaced in a whole-brain replication analysis involving an independent sample of 9 medication-naïve adult patients and 9 controls. In addition, a post hoc seed-to-voxel functional connectivity analysis using the dlPFC as a seed region to further examine this region's suggested connectivity differences uncovered a higher temporal coherence with various other neural networks and confirmed a reduced anticorrelation with the DMN. These results point to a more diffuse connectivity between functional networks in patients with ADHD. Moreover, our findings suggest that state-inappropriate neural activity in ADHD is not confined to DMN intrusion during attention-demanding contexts, but also surfaces as an insufficient suppression of dlPFC signaling in relation to DMN activity during rest. Together with previous findings, these results point to a general dysfunction in the orthogonality of functional networks.

  16. Evaluation of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Large-Scale Network Analysis Using Network-Based Statistic.

    PubMed

    Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, B Douglas; Kalinosky, Benjamin; Budde, Matthew D; Schmit, Brian D; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar N

    2017-03-15

    Large-scale network analysis characterizes the brain as a complex network of nodes and edges to evaluate functional connectivity patterns. The utility of graph-based techniques has been demonstrated in an increasing number of resting-state functional MRI (rs-fMRI) studies in the normal and diseased brain. However, to our knowledge, graph theory has not been used to study the reorganization pattern of resting-state brain networks in patients with traumatic complete spinal cord injury (SCI). In the present analysis, we applied a graph-theoretical approach to explore changes to global brain network architecture as a result of SCI. Fifteen subjects with chronic (> 2 years) complete (American Spinal Injury Association [ASIA] A) cervical SCI and 15 neurologically intact controls were scanned using rs-fMRI. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI) or nodes. The average time series was extracted at each node, and correlation analysis was performed between every pair of nodes. A functional connectivity matrix for each subject was then generated. Subsequently, the matrices were averaged across groups, and network changes were evaluated between groups using the network-based statistic (NBS) method. Our results showed decreased connectivity in a subnetwork of the whole brain in SCI compared with control subjects. Upon further examination, increased connectivity was observed in a subnetwork of the sensorimotor cortex and cerebellum network in SCI. In conclusion, our findings emphasize the applicability of NBS to study functional connectivity architecture in diseased brain states. Further, we show reorganization of large-scale resting-state brain networks in traumatic SCI, with potential prognostic and therapeutic implications.

  17. ECG denoising and fiducial point extraction using an extended Kalman filtering framework with linear and nonlinear phase observations.

    PubMed

    Akhbari, Mahsa; Shamsollahi, Mohammad B; Jutten, Christian; Armoundas, Antonis A; Sayadi, Omid

    2016-02-01

    In this paper we propose an efficient method for denoising and extracting fiducial point (FP) of ECG signals. The method is based on a nonlinear dynamic model which uses Gaussian functions to model ECG waveforms. For estimating the model parameters, we use an extended Kalman filter (EKF). In this framework called EKF25, all the parameters of Gaussian functions as well as the ECG waveforms (P-wave, QRS complex and T-wave) in the ECG dynamical model, are considered as state variables. In this paper, the dynamic time warping method is used to estimate the nonlinear ECG phase observation. We compare this new approach with linear phase observation models. Using linear and nonlinear EKF25 for ECG denoising and nonlinear EKF25 for fiducial point extraction and ECG interval analysis are the main contributions of this paper. Performance comparison with other EKF-based techniques shows that the proposed method results in higher output SNR with an average SNR improvement of 12 dB for an input SNR of -8 dB. To evaluate the FP extraction performance, we compare the proposed method with a method based on partially collapsed Gibbs sampler and an established EKF-based method. The mean absolute error and the root mean square error of all FPs, across all databases are 14 ms and 22 ms, respectively, for our proposed method, with an advantage when using a nonlinear phase observation. These errors are significantly smaller than errors obtained with other methods. For ECG interval analysis, with an absolute mean error and a root mean square error of about 22 ms and 29 ms, the proposed method achieves better accuracy and smaller variability with respect to other methods.

  18. Cost-effectiveness of pre-participation screening of athletes with ECG in Europe and Algeria.

    PubMed

    Assanelli, Deodato; Levaggi, Rosella; Carré, François; Sharma, Sanjay; Deligiannis, Asterios; Mellwig, Klaus Peter; Tahmi, Mohamed; Vinetti, Giovanni; Aliverti, Paola

    2015-03-01

    The aim of this study is to evaluate the cost-effectiveness of ECG in combination with family and personal history and physical examination in order to detect cardiovascular diseases that might cause sudden death in athletes. The study was conducted on a cohort of 6,634, mainly young professional and recreational athletes, 1,071 from Algeria and 5,563 from Europe (France, Germany and Greece). Each athlete underwent medical history, physical examination, and resting 12-lead ECG. 293 athletes (4.4 %), 149 in Europe (2.7 %) and 144 in Algeria (13.4 %) required further tests, and 56 were diagnosed with cardiovascular disease and thus disqualified. The cost-effectiveness ratio (CER) was calculated as the ratio between the cost of screening and the number of statistical life-years saved by the intervention. The estimated reduced risk of death deriving from treatment or disqualification resulted in the saving of 79.1 statistical life-years in Europe and 136.3 in Algeria. CER of screening was 4,071 purchasing-power-parity-adjusted US dollars ($PPP) in Europe and 582 $PPP in Algeria. The results of this study strongly support the utilisation of 12-lead ECG in the pre-participation screening of young athletes, especially in countries where secondary preventive care is not highly developed.

  19. Normal mode analysis of a rotating group of lashed turbine blades by substructures. [calculations for blades at rest and at operating speed

    NASA Technical Reports Server (NTRS)

    Filstrup, A. W.

    1973-01-01

    A group of 5 lashed identical stream turbine blades is studied through the use of single level substructuring using NASTRAN level 15.1. An altered version, similar to DMAP Program Number 3 of the NASTRAN Newsletter, of Rigid Format 13.0 was used. Steady-state displacements and stresses due to centrifugal loads are obtained both without and with consideration of differential stiffness. The normal mode calculations were performed for blades at rest and at operating speed. Substructuring lowered the computation costs of the analysis by a factor of four.

  20. Analysis of EEG Signals Related to Artists and Nonartists during Visual Perception, Mental Imagery, and Rest Using Approximate Entropy

    PubMed Central

    Shourie, Nasrin; Firoozabadi, Mohammad; Badie, Kambiz

    2014-01-01

    In this paper, differences between multichannel EEG signals of artists and nonartists were analyzed during visual perception and mental imagery of some paintings and at resting condition using approximate entropy (ApEn). It was found that ApEn is significantly higher for artists during the visual perception and the mental imagery in the frontal lobe, suggesting that artists process more information during these conditions. It was also observed that ApEn decreases for the two groups during the visual perception due to increasing mental load; however, their variation patterns are different. This difference may be used for measuring progress in novice artists. In addition, it was found that ApEn is significantly lower during the visual perception than the mental imagery in some of the channels, suggesting that visual perception task requires more cerebral efforts. PMID:25133180

  1. Changes of Functional Brain Networks in Major Depressive Disorder: A Graph Theoretical Analysis of Resting-State fMRI.

    PubMed

    Ye, Ming; Yang, Tianliang; Qing, Peng; Lei, Xu; Qiu, Jiang; Liu, Guangyuan

    2015-01-01

    Recent developments in graph theory have heightened the need for investigating the disruptions in the topological structure of functional brain network in major depressive disorder (MDD). In this study, we employed resting-state functional magnetic resonance imaging (fMRI) and graph theory to examine the whole-brain functional networks among 42 MDD patients and 42 healthy controls. Our results showed that compared with healthy controls, MDD patients showed higher local efficiency and modularity. Furthermore, MDD patients showed altered nodal centralities of many brain regions, including hippocampus, temporal cortex, anterior cingulate gyrus and dorsolateral prefrontal gyrus, mainly located in default mode network and cognitive control network. Together, our results suggested that MDD was associated with disruptions in the topological structure of functional brain networks, and provided new insights concerning the pathophysiological mechanisms of MDD.

  2. Resting Heart Rate and Auditory Evoked Potential

    PubMed Central

    Fiuza Regaçone, Simone; Baptista de Lima, Daiane Damaris; Engrácia Valenti, Vitor; Figueiredo Frizzo, Ana Cláudia

    2015-01-01

    The objective of this study was to evaluate the association between rest heart rate (HR) and the components of the auditory evoked-related potentials (ERPs) at rest in women. We investigated 21 healthy female university students between 18 and 24 years old. We performed complete audiological evaluation and measurement of heart rate for 10 minutes at rest (heart rate monitor Polar RS800CX) and performed ERPs analysis (discrepancy in frequency and duration). There was a moderate negative correlation of the N1 and P3a with rest HR and a strong positive correlation of the P2 and N2 components with rest HR. Larger components of the ERP are associated with higher rest HR. PMID:26504838

  3. An in silico analysis of oxygen uptake of a mild COPD patient during rest and exercise using a portable oxygen concentrator

    PubMed Central

    Katz, Ira; Pichelin, Marine; Montesantos, Spyridon; Kang, Min-Yeong; Sapoval, Bernard; Zhu, Kaixian; Thevenin, Charles-Philippe; McCoy, Robert; Martin, Andrew R; Caillibotte, Georges

    2016-01-01

    Oxygen treatment based on intermittent-flow devices with pulse delivery modes available from portable oxygen concentrators (POCs) depends on the characteristics of the delivered pulse such as volume, pulse width (the time of the pulse to be delivered), and pulse delay (the time for the pulse to be initiated from the start of inhalation) as well as a patient’s breathing characteristics, disease state, and respiratory morphology. This article presents a physiological-based analysis of the performance, in terms of blood oxygenation, of a commercial POC at different settings using an in silico model of a COPD patient at rest and during exercise. The analysis encompasses experimental measurements of pulse volume, width, and time delay of the POC at three different settings and two breathing rates related to rest and exercise. These experimental data of device performance are inputs to a physiological-based model of oxygen uptake that takes into account the real dynamic nature of gas exchange to illustrate how device- and patient-specific factors can affect patient oxygenation. This type of physiological analysis that considers the true effectiveness of oxygen transfer to the blood, as opposed to delivery to the nose (or mouth), can be instructive in applying therapies and designing new devices. PMID:27729783

  4. Wireless Self-Acquistion of 12-Lead ECG via Android Smart Phone

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.

    2012-01-01

    Researchers at NASA s Johnson Space Center and at Orbital Research, Inc. (a NASA SBIR grant recipient) have recently developed a dry-electrode harness that allows for self-acquisition of resting 12-lead ECGs by minimally trained laypersons. When used in conjunction with commercial wireless (e.g., Bluetooth(TM) or 802.11-enabled) 12-lead ECG devices and custom smart phone-based software, the collected 12-lead ECG data can also immediately be forwarded from any geographic location within cellular range to the user s physician(s) of choice. The system can also be used to immediately forward to central receiving stations 12-lead ECG data collected during space flight or during activities in any remote terrestrial location supported by an internet or cellular phone infrastructure. The main novel aspects of the system are first, the dry-electrode 12-lead ECG harness itself, and second, an accompanying Android(TM) smart phone-based wireless 12-lead ECG capability. The ECG harness nominally employs dry electrodes manufactured by Orbital Research, Inc, recently cleared through the Food and Drug Administration (FDA). However, other dry electrodes that are not yet FDA cleared, for example those recently developed by Nanosonic, Inc as part of another NASA SBIR grant, can also be used. The various advantageous features of the harness include: 1) laypersons can be quickly instructed on its correct use, remotely if necessary; 2) all tangled "leadwire spaghetti" is eliminated, as is the common clinical problem of "leadwire reversal"; 3) all adhesives and disposables are also eliminated, the harness being fully reusable; if multiple individuals intend to use use the same harness, then standard antimicrobial wipes can be employed to sterilize the dry electrodes (and harness surface if needed) between users; 5) padded cushions at the lateral sides of the torso function to press the left arm (LA) and right arm (RA) dry electrodes mounted on the cushions against sideward or downward-rested

  5. A model-based approach to human identification using ECG

    NASA Astrophysics Data System (ADS)

    Homer, Mark; Irvine, John M.; Wendelken, Suzanne

    2009-05-01

    Biometrics, such as fingerprint, iris scan, and face recognition, offer methods for identifying individuals based on a unique physiological measurement. Recent studies indicate that a person's electrocardiogram (ECG) may also provide a unique biometric signature. Current techniques for identification using ECG rely on empirical methods for extracting features from the ECG signal. This paper presents an alternative approach based on a time-domain model of the ECG trace. Because Auto-Regressive Integrated Moving Average (ARIMA) models form a rich class of descriptors for representing the structure of periodic time series data, they are well-suited to characterizing the ECG signal. We present a method for modeling the ECG, extracting features from the model representation, and identifying individuals using these features.

  6. Investigating the use of mutual information and non-metric clustering for functional connectivity analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    Wang, Xixi; Nagarajan, Mahesh B.; Abidin, Anas Z.; DSouza, Adora; Hobbs, Susan K.; Wismüller, Axel

    2015-03-01

    Functional MRI (fMRI) is currently used to investigate structural and functional connectivity in human brain networks. To this end, previous studies have proposed computational methods that involve assumptions that can induce information loss, such as assumed linear coupling of the fMRI signals or requiring dimension reduction. This study presents a new computational framework for investigating the functional connectivity in the brain and recovering network structure while reducing the information loss inherent in previous methods. For this purpose, pair-wise mutual information (MI) was extracted from all pixel time series within the brain on resting-state fMRI data. Non-metric topographic mapping of proximity (TMP) data was subsequently applied to recover network structure from the pair-wise MI analysis. Our computational framework is demonstrated in the task of identifying regions of the primary motor cortex network on resting state fMRI data. For ground truth comparison, we also localized regions of the primary motor cortex associated with hand movement in a task-based fMRI sequence with a finger-tapping stimulus function. The similarity between our pair-wise MI clustering results and the ground truth is evaluated using the dice coefficient. Our results show that non-metric clustering with the TMP algorithm, as performed on pair-wise MI analysis, was able to detect the primary motor cortex network and achieved a dice coefficient of 0.53 in terms of overlap with the ground truth. Thus, we conclude that our computational framework can extract and visualize valuable information concerning the underlying network structure between different regions of the brain in resting state fMRI.

  7. Compressed domain ECG biometric with two-lead features

    NASA Astrophysics Data System (ADS)

    Lee, Wan-Jou; Chang, Wen-Whei

    2016-07-01

    This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. We target the two-lead ECG configuration that is routinely used in long-term heart monitoring. Incorporation of compressed-domain biometric techniques enables faster person identification as it by-passes the full decompression. Experiments on public ECG databases demonstrate the validity of the proposed method for biometric identification with high accuracies on both healthy and diseased subjects.

  8. A new method for QRS complex detection in multichannel ECG: Application to self-monitoring of fetal health.

    PubMed

    Varanini, Maurizio; Tartarisco, Gennaro; Balocchi, Rita; Macerata, Alberto; Pioggia, Giovanni; Billeci, Lucia

    2016-04-13

    This paper proposes a new approach for QRS complex detection in multichannel ECG and presents its application to fetal QRS (fQRS) detection in signals acquired from maternal abdominal leads. The method exploits the characteristics of pseudo-periodicity and time shape of QRS, it consists of devising a quality index (QI) which synthesizes these characteristics and of finding the linear combination of the acquired ECGs, which maximizes this QI. In the application for fQRS detection two QIs are devised, one QI (mQI) for maternal ECG (mECG) and one QI (fQI) for fetal ECG (fECG). The method is completely unsupervised and based on the following steps: signal pre-processing; maternal QRS-enhanced signal extraction by finding the linear combination that maximize the mQI; detection of maternal QRSs; mECG component approximation and canceling by weighted Singular Value Decomposition (SVD); fQRS-enhanced signal extraction by finding the linear combination that maximize the fQI and fQRS detection. The proposed method was compared with our previously developed Independent Component Analysis (ICA) based method as well as with simple mECG canceling and simple ICA methods. The comparison was carried out by evaluating the performances of the procedures in fQRS detection. The new method outperformed the results of the other approaches on the annotated open set of the Computing in Cardiology Challenge 2013 database. The proposed method seems to be promising for its implementation on portable device and for use in self-monitoring of fetal health in pregnant women.

  9. A nonlinear Bayesian filtering framework for ECG denoising.

    PubMed

    Sameni, Reza; Shamsollahi, Mohammad B; Jutten, Christian; Clifford, Gari D

    2007-12-01

    In this paper, a nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings. The necessary dynamic models of the ECG are based on a modified nonlinear dynamic model, previously suggested for the generation of a highly realistic synthetic ECG. A modified version of this model is used in several Bayesian filters, including the Extended Kalman Filter, Extended Kalman Smoother, and Unscented Kalman Filter. An automatic parameter selection method is also introduced, to facilitate the adaptation of the model parameters to a vast variety of ECGs. This approach is evaluated on several normal ECGs, by artificially adding white and colored Gaussian noises to visually inspected clean ECG recordings, and studying the SNR and morphology of the filter outputs. The results of the study demonstrate superior results compared with conventional ECG denoising approaches such as bandpass filtering, adaptive filtering, and wavelet denoising, over a wide range of ECG SNRs. The method is also successfully evaluated on real nonstationary muscle artifact. This method may therefore serve as an effective framework for the model-based filtering of noisy ECG recordings.

  10. Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition

    PubMed Central

    Chang, Kang-Ming

    2010-01-01

    A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces. Three noise patterns with different power—50 Hz, EMG, and base line wander – were embedded into simulated and real ECG signals. Traditional IIR filter, Wiener filter, empirical mode decomposition (EMD) and EEMD were used to compare filtering performance. Mean square error between clean and filtered ECGs was used as filtering performance indexes. Results showed that high noise reduction is the major advantage of the EEMD based filter, especially on arrhythmia ECGs. PMID:22219702

  11. An awareness approach to analyze ECG streaming data.

    PubMed

    Don, S; Chung, Duckwon; Choi, Eunmi; Min, Dugki

    2013-04-01

    Real-time remote health monitoring systems are experiencing tremendous advancement resulting from improvements in low power, reliable sensors; yet they are still constrained to low-level interpretation. Automatic data analysis continues to be a tedious task due to a lack of efficient, reliable platforms for data analysis. In this paper, we present a system for monitoring patients remotely by emphasizing the strength of Complex Event Processing (CEP) and Situation Awareness. In this approach, the system makes decisions in a declarative way, which helps medical experts to understand the situation in a more realistic manner. The primary objective of this paper is to explicate the different components inside the system. To verify the technical feasibility of each component, the proposed system is implemented and tested using ECG data.

  12. 3-lead acquisition using single channel ECG device developed on AD8232 analog front end for wireless ECG application

    NASA Astrophysics Data System (ADS)

    Agung, Mochammad Anugrah; Basari

    2017-02-01

    Electrocardiogram (ECG) devices measure electrical activity of the heart muscle to determine heart conditions. ECG signal quality is the key factor in determining the diseases of the heart. This paper presents the design of 3-lead acquistion on single channel wireless ECG device developed on AD8232 chip platform using microcontroller. To make the system different from others, monopole antenna 2.4 GHz is used in order to send and receive ECG signal. The results show that the system still can receive ECG signal up to 15 meters by line of sight (LOS) condition. The shape of ECG signals is precisely similar with the expected signal, although some delays occur between two consecutive pulses. For further step, the system will be applied with on-body antenna in order to investigate body to body communication that will give variation in connectivity from the others.

  13. Exploring the effective connectivity of resting state networks in mild cognitive impairment: an fMRI study combining ICA and multivariate Granger causality analysis.

    PubMed

    Liu, Zhenyu; Bai, Lijun; Dai, Ruwei; Zhong, Chongguang; Wang, Hu; You, Youbo; Wei, Wenjuan; Tian, Jie

    2012-01-01

    Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent neuroimaging studies have shown that the cognitive and memory decline in AD and MCI patients is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses of small-world attributes. However, the causal interactions among the spatially isolated but function-related resting state networks (RSNs) are still largely unexplored in MCI patients. In this study, we first identified eight RSNs by independent components analysis (ICA) from resting state functional MRI data of 16 MCI patients and 18 age-matched healthy subjects respectively. Then, we performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that MCI patients exhibited decreased causal interactions among the RSNs in both intensity and quantity compared with normal controls. Results from mGCA indicated that the causal interactions involving the default mode network (DMN) became weaker in MCI patients, while stronger causal connectivity emerged related to the memory network and executive control network. Our findings suggested that the DMN played a less important role in MCI patients. Increased causal connectivity of the memory network and executive control network may elucidate the dysfunctional and compensatory processes in the brain networks of MCI patients. These preliminary findings may be helpful for further understanding the pathological mechanisms of MCI and provide a new clue to explore the neurophysiological mechanisms of MCI.

  14. FRS REST Services

    EPA Pesticide Factsheets

    FRS exposes several REST services that allows developers to utilize a live feed of data from the FRS database. This web page is intended for a technical audience and describes the content and purpose of each service available.

  15. High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

    NASA Technical Reports Server (NTRS)

    Rahman, Atiar

    2006-01-01

    Background: Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). Methods and Results: 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P<0.001). Conclusions: Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

  16. High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

    NASA Technical Reports Server (NTRS)

    2004-01-01

    Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P less than 0.00l). Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

  17. Application of computerized exercise ECG digitization. Interpretation in large clinical trials.

    PubMed

    Caralis, D G; Shaw, L; Bilgere, B; Younis, L; Stocke, K; Wiens, R D; Chaitman, B R

    1992-04-01

    The authors report on a semiautomated program that incorporates both visual identification of fiducial points and digital determination of the ST-segment at 60 ms and 80 ms from the J point, ST slope, changes in R wave, and baseline drift. The off-line program can enhance the accuracy of detecting electrocardiographic (ECG) changes, as well as reproducibility of the exercise and postexercise ECG, as a marker of myocardial ischemia. The analysis program is written in Microsoft QuickBASIC 2.0 for an IBM personal computer interfaced to a Summagraphics mm1201 microgrid II digitizer. The program consists of the following components: (1) alphanumeric data entry, (2) ECG wave form digitization, (2) calculation of test results, (4) physician overread, and (5) editor function for remeasurements. This computerized exercise ECG digitization-interpretation program is accurate and reproducible for the quantitative assessment of ST changes and requires minimal time allotment for physician overread. The program is suitable for analysis and interpretation of large volumes of exercise tests in multicenter clinical trials and is currently utilized in the TIMI II, TIMI III, and BARI studies sponsored by the National Institutes of Health.

  18. Wireless Sensor-Based Smart-Clothing Platform for ECG Monitoring.

    PubMed

    Wang, Jie; Lin, Chung-Chih; Yu, Yan-Shuo; Yu, Tsang-Chu

    2015-01-01

    The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and positive prediction is above 99.5%. Power-saving transmission is reduced by nearly 1980 times the power consumption in the best-case analysis.

  19. Wireless Sensor-Based Smart-Clothing Platform for ECG Monitoring

    PubMed Central

    Wang, Jie; Lin, Chung-Chih; Yu, Yan-Shuo; Yu, Tsang-Chu

    2015-01-01

    The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the “very good signal” interval. The average of the QRS sensitivity and positive prediction is above 99.5%. Power-saving transmission is reduced by nearly 1980 times the power consumption in the best-case analysis. PMID:26640512

  20. Plasma electrolytes, pH, and ECG during and after exhaustive exercise.

    NASA Technical Reports Server (NTRS)

    Coester, N.; Elliott, J. C.; Luft, U. C.

    1973-01-01

    Ten men worked on a bicycle ergometer at increasing work loads to exhaustion in 15 min. Each performed one test breathing air and another with added CO2 in random sequence. ECG was recorded during exercise and for 30 min of recovery. Arterial samples for blood gases, pH, and electrolytes were drawn at rest, in the last minute of exercise and at 1, 4, 10, 20, and 30 min thereafter. A striking increase in the amplitude of T and P waves was observed reaching a maximum in the first 2 min after exercise. All electrolytes measured were increased at the end of exercise, most markedly potassium (60%) and phosphorus (53%). Potassium dropped faster than all others to below resting values in 4 min coinciding with the lowest levels in plasma bicarbonate. ECG alterations were not closely related in time with any single factor such as potassium, but appeared to reflect an interaction of the transient mineral and acid-base imbalance during and immediately following exhaustive exercise.

  1. Bed rest and immunity

    NASA Astrophysics Data System (ADS)

    Sonnenfeld, Gerald; Aviles, Hernan; Butel, Janet S.; Shearer, William T.; Niesel, David; Pandya, Utpal; Allen, Christopher; Ochs, Hans D.; Blancher, Antoine; Abbal, Michel

    2007-02-01

    Space flight has been shown to result in altered immune responses. The current study was designed to investigate this possibility by using the bed rest model of some space flight conditions. A large number of women are included as subjects in the study. The hypothesis being tested is: 60 days head-down tilt bed rest of humans will affect the immune system and resistance to infection. Blood, urine and saliva samples will be obtained from bed rest subjects prior to, at intervals during, and after completion of 60 days of head-down tilt bed rest. Leukocyte blastogenesis, cytokine production and virus reactivation will be assessed. The ability of the subjects to respond appropriately to immunization with the neoantigen bacteriophage φX-174 will also be determined. Bed rest is being carried out at MEDES, Toulouse France, and the University of Texas Medical Branch, Galveston, TX. The studies to be carried out in France will also allow assessment of the effects of muscle/bone exercise and nutritional countermeasures on the immune system in addition to the effects of bed rest.

  2. ECG derived respiration: comparison of time-domain approaches and application to altered breathing patterns of patients with schizophrenia.

    PubMed

    Schmidt, Marcus; Schumann, Andy; Müller, Jonas; Bär, Karl-Jürgen; Rose, Georg

    2017-04-01

    In life-threatening diseases and in several clinical interventions, monitoring of vital parameters is essential to guarantee the safety of patients. Besides monitoring the electrocardiogram (ECG), it is helpful to assess respiratory activity. If the respiration signal itself is not recorded, it can be extracted from the ECG (i.e. ECG derived respiration, EDR). In the present paper, we compared six EDR approaches, namely RS-decline quantified by central moments, respiratory sinus arrhythmia (RSA), R-wave amplitude, QRS area, RS-distance and maximum RS-slope. In order to evaluate the performance of each approach, we applied each method to a database of ECGs and reference respiration signals of 41 healthy subjects. All considered methods revealed relatively small absolute mean errors of the breathing rate (BR) at rest (0.75-1.3 Bpm). The method based on higher order central moments revealed a minimum mean absolute error of 0.75 Bpm (4.40%) and a maximum correlation and concordance with the reference BR (r p  =  0.97, r c  =  0.97). Using this technique, we analyzed changes of respiration in patients suffering from acute schizophrenia. An increased respiration rate of about 4 Bpm was found. Additionally, alteration of respiratory ratio and reduced respiratory sinus arrhythmia was demonstrated. We conclude that a precise dynamic monitoring of breathing and the investigation of changes in breathing patterns is possible without recording respiration per se.

  3. Reliability analysis of visual ranking of coronary artery calcification on low-dose CT of the thorax for lung cancer screening: comparison with ECG-gated calcium scoring CT.

    PubMed

    Kim, Yoon Kyung; Sung, Yon Mi; Cho, So Hyun; Park, Young Nam; Choi, Hye-Young

    2014-12-01

    Coronary artery calcification (CAC) is frequently detected on low-dose CT (LDCT) of the thorax. Concurrent assessment of CAC and lung cancer screening using LDCT is beneficial in terms of cost and radiation dose reduction. The aim of our study was to evaluate the reliability of visual ranking of positive CAC on LDCT compared to Agatston score (AS) on electrocardiogram (ECG)-gated calcium scoring CT. We studied 576 patients who were consecutively registered for health screening and undergoing both LDCT and ECG-gated calcium scoring CT. We excluded subjects with an AS of zero. The final study cohort included 117 patients with CAC (97 men; mean age, 53.4 ± 8.5). AS was used as the gold standard (mean score 166.0; range 0.4-3,719.3). Two board-certified radiologists and two radiology residents participated in an observer performance study. Visual ranking of CAC was performed according to four categories (1-10, 11-100, 101-400, and 401 or higher) for coronary artery disease risk stratification. Weighted kappa statistics were used to measure the degree of reliability on visual ranking of CAC on LDCT. The degree of reliability on visual ranking of CAC on LDCT compared to ECG-gated calcium scoring CT was excellent for board-certified radiologists and good for radiology residents. A high degree of association was observed with 71.6% of visual rankings in the same category as the Agatston category and 98.9% varying by no more than one category. Visual ranking of positive CAC on LDCT is reliable for predicting AS rank categorization.

  4. A novel biometric authentication approach using ECG and EMG signals.

    PubMed

    Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

    2015-05-01

    Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

  5. Reliability of graph analysis of resting state fMRI using test-retest dataset from the Human Connectome Project.

    PubMed

    Termenon, M; Jaillard, A; Delon-Martin, C; Achard, S

    2016-11-15

    The exploration of brain networks with resting-state fMRI (rs-fMRI) combined with graph theoretical approaches has become popular, with the perspective of finding network graph metrics as biomarkers in the context of clinical studies. A preliminary requirement for such findings is to assess the reliability of the graph based connectivity metrics. In previous test-retest (TRT) studies, this reliability has been explored using intraclass correlation coefficient (ICC) with heterogeneous results. But the issue of sample size has not been addressed. Using the large TRT rs-fMRI dataset from the Human Connectome Project (HCP), we computed ICCs and their corresponding p-values (applying permutation and bootstrap techniques) and varied the number of subjects (from 20 to 100), the scan duration (from 400 to 1200 time points), the cost and the graph metrics, using the Anatomic-Automatic Labelling (AAL) parcellation scheme. We quantified the reliability of the graph metrics computed both at global and regional level depending, at optimal cost, on two key parameters, the sample size and the number of time points or scan duration. In the cost range between 20% to 35%, most of the global graph metrics are reliable with 40 subjects or more with long scan duration (14min 24s). In large samples (for instance, 100 subjects), most global and regional graph metrics are reliable for a minimum scan duration of 7min 14s. Finally, for 40 subjects and long scan duration (14min 24s), the reliable regions are located in the main areas of the default mode network (DMN), the motor and the visual networks.

  6. Comparing consistency of R2* and T2*-weighted BOLD analysis of resting state fetal fMRI

    NASA Astrophysics Data System (ADS)

    Seshamani, Sharmishtaa; Blazejewska, Anna I.; Gatenby, Christopher; Mckown, Susan; Caucutt, Jason; Dighe, Manjiri; Studholme, Colin

    2015-03-01

    Understanding when and how resting state brain functional activity begins in the human brain is an increasing area of interest in both basic neuroscience and in the clinical evaluation of the brain during pregnancy and after premature birth. Although fMRI studies have been carried out on pregnant women since the 1990's, reliable mapping of brain function in utero is an extremely challenging problem due to the unconstrained fetal head motion. Recent studies have employed scrubbing to exclude parts of the time series and whole subjects from studies in order to control the confounds of motion. Fundamentally, even after correction of the location of signals due to motion, signal intensity variations are a fundamental limitation, due to coil sensitivity and spin history effects. An alternative technique is to use a more parametric MRI signal derived from multiple echoes that provides a level of independence from basic MRI signal variation. Here we examine the use of R2* mapping combined with slice based multi echo geometric distortion correction for in-utero studies. The challenges for R2* mapping arise from the relatively low signal strength of in-utero data. In this paper we focus on comparing activation detection in-utero using T2W and R2* approaches. We make use a subset of studies with relatively limited motion to compare the activation patterns without the additional confound of significant motion. Results at different gestational ages indicate comparable agreement in many activation patterns when limited motion is present, and the detection of some additional networks in the R2* data, not seen in the T2W results.

  7. Comparison of Polar® RS800G3™ heart rate monitor with Polar® S810i™ and electrocardiogram to obtain the series of RR intervals and analysis of heart rate variability at rest.

    PubMed

    Barbosa, Marianne Penachini da Costa de Rezende; da Silva, Natália Turri; de Azevedo, Fábio Mícolis; Pastre, Carlos Marcelo; Vanderlei, Luiz Carlos Marques

    2016-03-01

    The Polar® RS800G3™ rate monitor was released in the market to replace the Polar® S810i™, and few studies have assessed that the RR series obtained by this equipment is reliable for analysis of heart rate variability (HRV). We compared HRV indexes among the devices Polar® RS800G3™, Polar® S810i™ and eletrocardiogram (ECG) to know whether the series of Polar® RS800G3™ are as reliable as those devices already validated. We analysed data from 30 healthy young adults, male, with an average age of 20·66 ± 1·40 years, which had captured the heart rate beat to beat in the three devices simultaneously with spontaneously breathing, first in the supine position and subsequently sit both for 30 min. The obtained series of RR intervals was used to calculate the indexes of HRV in the time domain (SDNN and RMSSD) and in the frequency domain (LF, HF and LF/HF). There were no significant differences in HRV indexes calculated from series obtained by the three devices, regardless of the position analysed, and a high correlation coefficient was observed. The results suggest that the Polar® RS800G3™ is able to capture series of RR intervals for analysis of HRV indexes as reliable as those obtained by ECG and Polar® S810i™.

  8. Heterogeneous Aging Effects on Functional Connectivity in Different Cortical Regions: A Resting-State Functional MRI Study Using Functional Data Analysis.

    PubMed

    Chen, Pin-Yu; Chiou, Jeng-Min; Yang, Ya-Fang; Chen, Yu-Ting; Hsieh, Hsin-Long; Chang, Yu-Ling; Tseng, Wen-Yih I

    Brain aging is a complex and heterogeneous process characterized by the selective loss and preservation of brain functions. This study examines the normal aging effects on the cerebral cortex by characterizing changes in functional connectivity using resting-state fMRI data. Previous resting-state fMRI studies on normal aging have examined specific networks of the brain, whereas few studies have examined cortical-cortical connectivities across the entire brain. To characterize the effects of normal aging on the cerebral cortex, we proposed the Pearson functional product-moment correlation coefficient for measuring functional connectivity, which has advantages over the traditional correlation coefficient. The distinct patterns of changes in functional connectivity within and among the four cerebral lobes clarified the effects of normal aging on cortical function. Besides, the advantages of the proposed approach over other methods considered were demonstrated through simulation comparisons. The results showed heterogeneous changes in functional connectivity in normal aging. Specifically, the elderly group exhibited enhanced inter-lobe connectivity between the frontal lobe and the other lobes. Inter-lobe connectivity decreased between the temporal and parietal lobes. The results support the frontal aging hypothesis proposed in behavioral and structural MRI studies. In conclusion, functional correlation analysis enables differentiation of changes in functional connectivities and characterizes the heterogeneous aging effects in different cortical regions.

  9. Whole brain high-resolution functional imaging at ultra high magnetic fields: an application to the analysis of resting state networks.

    PubMed

    De Martino, Federico; Esposito, Fabrizio; van de Moortele, Pierre-Francois; Harel, Noam; Formisano, Elia; Goebel, Rainer; Ugurbil, Kamil; Yacoub, Essa

    2011-08-01

    Whole-brain functional magnetic resonance imaging (fMRI) allows measuring brain dynamics at all brain regions simultaneously and is widely used in research and clinical neuroscience to observe both stimulus-related and spontaneous neural activity. Ultrahigh magnetic fields (7T and above) allow functional imaging with high contrast-to-noise ratios and improved spatial resolution and specificity compared to clinical fields (1.5T and 3T). High-resolution 7T fMRI, however, has been mostly limited to partial brain coverage with previous whole-brain applications sacrificing either the spatial or temporal resolution. Here we present whole-brain high-resolution (1, 1.5 and 2mm isotropic voxels) resting state fMRI at 7T, obtained with parallel imaging technology, without sacrificing temporal resolution or brain coverage, over what is typically achieved at 3T with several fold larger voxel volumes. Using Independent Component Analysis we demonstrate that high resolution images acquired at 7T retain enough sensitivity for the reliable extraction of typical resting state brain networks and illustrate the added value of obtaining both single subject and group maps, using cortex based alignment, of the default-mode network (DMN) with high native resolution. By comparing results between multiple resolutions we show that smaller voxels volumes (1 and 1.5mm isotropic) data result in reduced partial volume effects, permitting separations of detailed spatial features within the DMN patterns as well as a better function to anatomy correspondence.

  10. Heterogeneous Aging Effects on Functional Connectivity in Different Cortical Regions: A Resting-State Functional MRI Study Using Functional Data Analysis

    PubMed Central

    Chen, Pin-Yu; Chiou, Jeng-Min; Yang, Ya-Fang; Chen, Yu-Ting; Hsieh, Hsin-Long; Chang, Yu-Ling; Tseng, Wen-Yih I.

    2016-01-01

    Brain aging is a complex and heterogeneous process characterized by the selective loss and preservation of brain functions. This study examines the normal aging effects on the cerebral cortex by characterizing changes in functional connectivity using resting-state fMRI data. Previous resting-state fMRI studies on normal aging have examined specific networks of the brain, whereas few studies have examined cortical-cortical connectivities across the entire brain. To characterize the effects of normal aging on the cerebral cortex, we proposed the Pearson functional product-moment correlation coefficient for measuring functional connectivity, which has advantages over the traditional correlation coefficient. The distinct patterns of changes in functional connectivity within and among the four cerebral lobes clarified the effects of normal aging on cortical function. Besides, the advantages of the proposed approach over other methods considered were demonstrated through simulation comparisons. The results showed heterogeneous changes in functional connectivity in normal aging. Specifically, the elderly group exhibited enhanced inter-lobe connectivity between the frontal lobe and the other lobes. Inter-lobe connectivity decreased between the temporal and parietal lobes. The results support the frontal aging hypothesis proposed in behavioral and structural MRI studies. In conclusion, functional correlation analysis enables differentiation of changes in functional connectivities and characterizes the heterogeneous aging effects in different cortical regions. PMID:27658309

  11. 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

  12. Microcontroller-based underwater acoustic ECG telemetry system.

    PubMed

    Istepanian, R S; Woodward, B

    1997-06-01

    This paper presents a microcontroller-based underwater acoustic telemetry system for digital transmission of the electrocardiogram (ECG). The system is designed for the real time, through-water transmission of data representing any parameter, and it was used initially for transmitting in multiplexed format the heart rate, breathing rate and depth of a diver using self-contained underwater breathing apparatus (SCUBA). Here, it is used to monitor cardiovascular reflexes during diving and swimming. The programmable capability of the system provides an effective solution to the problem of transmitting data in the presence of multipath interference. An important feature of the paper is a comparative performance analysis of two encoding methods, Pulse Code Modulation (PCM) and Pulse Position Modulation (PPM).

  13. Reversible ischemia in severe stress Tc-99m-Sestamibi perfusion defects: Assessment with gated tomographic polar map Fourier amplitude and amplitude/perfusion ratio images and correlation with resting images

    SciTech Connect

    Williams, K.A.; Taillon, L.A.

    1994-05-01

    Reversible ischemia in myocardial segments with severe hypoperfusion ({le}50% of normal activity) on stress Tc-99m-Sestamibi (MIBI) images was assessed with ECG-gated tomographic (GSPECT) indices of myocardial thickening, as reflected by an increase in regional count density during systole. GSPECT bullseye plots were generated for each of 8 frames acquired after stress MIBI injection in 39 patients with coronary artery disease and at least one severe perfusion defect on summed SPECT images. Using first harmonic Fourier amplitude (AMP) and AMP to perfusion ratio (APR) images, regional myocardial systolic thickening was assessed using a 5-segment model, scored 0 to 3, for absent, minimal, mildly reduced or normal thickening. These data were regionally compared with defect reversibility assessed using a separate-day or a preceding same-day resting MIBI injection images, in which these segments were scored from 0 to 3 for absent, minimal, partial or complete defect reversibility. Of 91 severe stress defects, 16 showed absent, 18 minimal, 43 partial, and 14 complete reversibility on resting images. Both AMP and APR scores were in statistically significant agreement (p=.0218 and .0006) with resting image reversibility grades, with 79% (p=.0324) and 86% (p=.0001) agreement on the presence of reversibility on resting imaging, respectively. AMP correctly identified 89% of the reversibility defects on rest images, while the APR identified 99% (p=.0248 vs. AMP). On analysis of segment scores, the AMP slightly underestimated the degree of rest image reversibility (p=.0235), while APR images indicated more reversibility thin did resting images (p=.0092). In conclusion, GSPECT MIBI bullseye Fourier AMP images correlate well with the pattern of reversibility on resting MIBI in severe stress perfusion defects. When indexed for the degree of hypoperfusion, the Fourier images depict a greater degree of defect reversibility than resting MIBI images.

  14. Stability of computer ECG amplitude measurements in the presence of noise. The CSE Working Party.

    PubMed

    Zywietz, C; Willems, J L; Arnaud, P; van Bemmel, J H; Degani, R; Macfarlane, P W

    1990-02-01

    An important feature of an ECG analysis program is its ability to provide reliable measurements under various operating conditions, e.g., on noise-free and noisy ECGs. Therefore, within the European cooperative project "Common Standards For Quantitative Electrocardiography" (CSE), the accuracy and stability of ECG measurements obtained by several computer programs has been compared. To investigate the stability of measurements two sets of 10 ECGs with and without seven different high- and low-frequency types of noise--altogether 160 electrocardiograms and 160 vectorcardiograms--have been analyzed by eight electrocardiographic and five vectorcardiographic computer programs. The stability of measurement was tested with respect to results obtained for the noise-free recordings. In a previous paper, the influence of noise on wave boundary recognition has been reported. In the present paper, the effect of noise on amplitude measurements and on problems of waveform definitions within the QRS complex are described. The results indicate that programs analyzing an averaged beat exhibit less variability than programs which measure every complex or a selected beat. Comparability and stability of measurements could be improved if a standardized procedure for amplitude references were to be introduced. In addition, the stability of QRS waveform labelling could be improved if waveforms' minimum amplitude and duration were to be validated against the noise level which itself should be determined by a standardized procedure.

  15. Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI

    PubMed Central

    Spisák, Tamás; Jakab, András; Kis, Sándor A.; Opposits, Gábor; Aranyi, Csaba; Berényi, Ervin; Emri, Miklós

    2014-01-01

    Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that “resting-state” fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group

  16. Reliability and Reproducibility of Advanced ECG Parameters in Month-to-Month and Year-to-Year Recordings in Healthy Subjects

    NASA Technical Reports Server (NTRS)

    Starc, Vito; Abughazaleh, Ahmed S.; Schlegel, Todd T.

    2014-01-01

    Advanced resting ECG parameters such the spatial mean QRS-T angle and the QT variability index (QTVI) have important diagnostic and prognostic utility, but their reliability and reproducibility (R&R) are not well characterized. We hypothesized that the spatial QRS-T angle would have relatively higher R&R than parameters such as QTVI that are more responsive to transient changes in the autonomic nervous system. The R&R of several conventional and advanced ECG para-meters were studied via intraclass correlation coefficients (ICCs) and coefficients of variation (CVs) in: (1) 15 supine healthy subjects from month-to-month; (2) 27 supine healthy subjects from year-to-year; and (3) 25 subjects after transition from the supine to the seated posture. As hypothesized, for the spatial mean QRS-T angle and many conventional ECG parameters, ICCs we-re higher, and CVs lower than QTVI, suggesting that the former parameters are more reliable and reproducible.

  17. A novel similarity comparison approach for dynamic ECG series.

    PubMed

    Yin, Hong; Zhu, Xiaoqian; Ma, Shaodong; Yang, Shuqiang; Chen, Liqian

    2015-01-01

    The heart sound signal is a reflection of heart and vascular system motion. Long-term continuous electrocardiogram (ECG) contains important information which can be helpful to prevent heart failure. A single piece of a long-term ECG recording usually consists of more than one hundred thousand data points in length, making it difficult to derive hidden features that may be reflected through dynamic ECG monitoring, which is also very time-consuming to analyze. In this paper, a Dynamic Time Warping based on MapReduce (MRDTW) is proposed to make prognoses of possible lesions in patients. Through comparison of a real-time ECG of a patient with the reference sets of normal and problematic cardiac waveforms, the experimental results reveal that our approach not only retains high accuracy, but also greatly improves the efficiency of the similarity measure in dynamic ECG series.

  18. Comparison of three mobile devices for measuring R-R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system.

    PubMed

    Weippert, Matthias; Kumar, Mohit; Kreuzfeld, Steffi; Arndt, Dagmar; Rieger, Annika; Stoll, Regina

    2010-07-01

    The first aim of this study was to compare an ambulatory five-lead ECG system with the commercially available breast belt measuring devices; Polar S810i and Suunto t6, in terms of R-R interval measures and heart rate variability (HRV) indices. The second aim was to compare different HRV spectral analysis methods. Nineteen young males (aged between 22 and 31 years, median 24 years) underwent simultaneous R-R interval recordings with the three instruments during supine and sitting rest, moderate dynamic, and moderate to vigorous static exercise of the upper and lower limb. For each subject, 17 R-R interval series of 3-min length were extracted from the whole recordings and then analyzed in frequency domain using (1) a fast Fourier transform (FFT), (2) an autoregressive model (AR), (3) a Welch periodogram (WP) and (4) a continuous wavelet transform (CWT). Intra-class correlation coefficients (ICC) and Bland-Altman limits of agreement (LoA) method served as criteria for measurement agreement. Regarding the R-R interval recordings, ICC (lower ICC 95% confidence interval >0.99) as well as LoA (maximum LoA: -15.1 to 14.3 ms for ECG vs. Polar) showed an excellent agreement between all devices. Therefore, the three instruments may be used interchangeably in recording and interpolation of R-R intervals. ICCs for HRV frequency parameters were also high, but in most cases LoA analysis revealed unacceptable discrepancies between the instruments. The agreement among the different frequency transform methods can be taken for granted when analyzing the normalized power in low and high frequency ranges; however, not when analyzing the absolute values.

  19. Analysis by NASA's VESGEN Software of Retinal Blood Vessels in Human Subjects Undergoing Head-Down Tilt During 70-Day Bed Rest

    NASA Technical Reports Server (NTRS)

    Vyas, Ruchi J.; Murray, Matthew C.; Predovic, Marina; Lim, Shiyin; Askin, Kayleigh N.; Vizzeri, Gianmarco; Taibbi, Giovanni; Mason, Sara Stroble; Zanello, Susana B.; Young, Millenia; Parsons-Wingerter, Patricia

    2017-01-01

    Significant risks for visual impairment associated with increased intracranial pressure (VIIP) are incurred by microgravity spaceflight, especially long-duration missions [1]. We hypothesize that microgravity-induced fluid shifts result in pathological changes within blood vessels of the retina that precede development of visual and other ocular impairments. Potential contributions of retinal vascular remodeling to VIIP etiology are therefore being investigated for two studies in 30deg infrared (IR) Heidelberg Spectralis(Registered Trademark) images with NASA's innovative VESsel GENeration Analysis (VESGEN) software [2,3]. The retrospective studies include: (1) before, during and after (pre, mid and post) 6º head-down tilt (HDT) in human subjects during 70 days of bed rest, and (2) before and after missions to the International Space Station (ISS) by U.S. crew members. Results for both studies are almost complete. A preliminary example for HDT is described below.

  20. Sequential Total Variation Denoising for the Extraction of Fetal ECG from Single-Channel Maternal Abdominal ECG

    PubMed Central

    Lee, Kwang Jin; Lee, Boreom

    2016-01-01

    Fetal heart rate (FHR) is an important determinant of fetal health. Cardiotocography (CTG) is widely used for measuring the FHR in the clinical field. However, fetal movement and blood flow through the maternal blood vessels can critically influence Doppler ultrasound signals. Moreover, CTG is not suitable for long-term monitoring. Therefore, researchers have been developing algorithms to estimate the FHR using electrocardiograms (ECGs) from the abdomen of pregnant women. However, separating the weak fetal ECG signal from the abdominal ECG signal is a challenging problem. In this paper, we propose a method for estimating the FHR using sequential total variation denoising and compare its performance with that of other single-channel fetal ECG extraction methods via simulation using the Fetal ECG Synthetic Database (FECGSYNDB). Moreover, we used real data from PhysioNet fetal ECG databases for the evaluation of the algorithm performance. The R-peak detection rate is calculated to evaluate the performance of our algorithm. Our approach could not only separate the fetal ECG signals from the abdominal ECG signals but also accurately estimate the FHR. PMID:27376296

  1. Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

    NASA Astrophysics Data System (ADS)

    Wismüller, Axel; DSouza, Adora M.; Abidin, Anas Z.; Wang, Xixi; Hobbs, Susan K.; Nagarajan, Mahesh B.

    2015-03-01

    Echo state networks (ESN) are recurrent neural networks where the hidden layer is replaced with a fixed reservoir of neurons. Unlike feed-forward networks, neuron training in ESN is restricted to the output neurons alone thereby providing a computational advantage. We demonstrate the use of such ESNs in our mutual connectivity analysis (MCA) framework for recovering the primary motor cortex network associated with hand movement from resting state functional MRI (fMRI) data. Such a framework consists of two steps - (1) defining a pair-wise affinity matrix between different pixel time series within the brain to characterize network activity and (2) recovering network components from the affinity matrix with non-metric clustering. Here, ESNs are used to evaluate pair-wise cross-estimation performance between pixel time series to create the affinity matrix, which is subsequently subject to non-metric clustering with the Louvain method. For comparison, the ground truth of the motor cortex network structure is established with a task-based fMRI sequence. Overlap between the primary motor cortex network recovered with our model free MCA approach and the ground truth was measured with the Dice coefficient. Our results show that network recovery with our proposed MCA approach is in close agreement with the ground truth. Such network recovery is achieved without requiring low-pass filtering of the time series ensembles prior to analysis, an fMRI preprocessing step that has courted controversy in recent years. Thus, we conclude our MCA framework can allow recovery and visualization of the underlying functionally connected networks in the brain on resting state fMRI.

  2. Coping with anger-provoking situations, psychosocial working conditions, and ECG-detected signs of coronary heart disease.

    PubMed

    Härenstam, A; Theorell, T; Kaijser, L

    2000-01-01

    This study explored the association among coping, psychosocial work factors, and signs of coronary heart disease (CHD) among prison staff (777 men, 345 women). Electrocardiogram (ECG) recordings at rest, health examinations, and a questionnaire were used. A high level of covert coping in men and a low level of open coping in women showed the strongest association with signs of CHD. Among several traditional biological and lifestyle risk factors, only age and systolic blood pressure in men and none in the case of women were significantly associated with CHD signs in the final multivariate regression analyses. A coping style of repressed emotions and actions in anger-provoking situations, independent of traditional risk factors, seems to be associated with a prevalence of ECG signs in male and female prison staff.

  3. Comparison of baroreceptor cardiac reflex sensitivity estimates from inter-systolic and ECG R-R intervals.

    PubMed

    del Paso, Gustavo A Reyes; González, M Isabel; Hernández, José A

    2010-11-01

    Baroreceptor reflex sensitivity (BRS) is frequently evaluated using the spontaneous sequence method. Many of these studies use the inter-systolic interval (ISI) derived from a blood pressure monitor (e.g., Finapres) as interbeat interval measure instead of the traditionally recommended R-R series derived from the ECG. In this study, we examine possible differences between estimates of BRS from ISI and ECG R-R intervals. BRS was evaluated in 35 participants under three conditions: rest, mental arithmetic, and recovery periods. Although correlations between the two estimates are very high (all rs>.9), small but significant differences were found: the measures from ISI systematically yield higher BRS values and result in the detection of a greater number of reflex sequences. The higher BRS values from measures of ISI are due to the effects of pulse transit time fluctuations associated with the sequences of change in blood pressure.

  4. Wavelet-based low-delay ECG compression algorithm for continuous ECG transmission.

    PubMed

    Kim, Byung S; Yoo, Sun K; Lee, Moon H

    2006-01-01

    The delay performance of compression algorithms is particularly important when time-critical data transmission is required. In this paper, we propose a wavelet-based electrocardiogram (ECG) compression algorithm with a low delay property for instantaneous, continuous ECG transmission suitable for telecardiology applications over a wireless network. The proposed algorithm reduces the frame size as much as possible to achieve a low delay, while maintaining reconstructed signal quality. To attain both low delay and high quality, it employs waveform partitioning, adaptive frame size adjustment, wavelet compression, flexible bit allocation, and header compression. The performances of the proposed algorithm in terms of reconstructed signal quality, processing delay, and error resilience were evaluated using the Massachusetts Institute of Technology University and Beth Israel Hospital (MIT-BIH) and Creighton University Ventricular Tachyarrhythmia (CU) databases and a code division multiple access-based simulation model with mobile channel noise.

  5. In vivo bone remodeling rates determination and compressive stiffness variations before, during 60 days bed rest and two years follow up: A micro-FE-analysis from HR-pQCT measurements of the berlin Bed Rest Study-2

    NASA Astrophysics Data System (ADS)

    Ritter, Zully; Belavy, Daniel; Baumann, Wolfgang W.; Felsenberg, Dieter

    2017-03-01

    Bed rest studies are used for simulation and study of physiological changes as observed in unloading/non-gravity environments. Amongst others, bone mass reduction, similar as occurring due to aging osteoporosis, combined with bio-fluids redistribution and muscle atrophy have been observed and analyzed. Advanced radiological methods of high resolution such as HR-pQCT (XtremeCT) allow 3D-visualizing in vivo bone remodeling processes occurring during absence/reduction of mechanical stimuli (0 to <1 g) as simulated by bed rest. Induced bone micro-structure (e.g. trabecular number, cortical thickness, porosity) and density variations can be quantified. However, these parameters are average values of each sample and important information regarding bone mass distribution and within bone mechanical behaviour is lost. Finite element models with hexa-elements of identical size as the HR-pQCT measurements (0.082 mm×0.082 mm×0.082 mm, ca. 7E6 elements/sample) can be used for subject-specific in vivo stiffness calculation. This technique also allows quantifying if bone microstructural changes represent a risk of mechanical bone collapse (fracture).

  6. Agreement between clinical and portable EMG/ECG diagnosis of sleep bruxism.

    PubMed

    Castroflorio, T; Bargellini, A; Rossini, G; Cugliari, G; Deregibus, A; Manfredini, D

    2015-10-01

    The aim of this study was to compare clinical sleep bruxism (SB) diagnosis with an instrumental diagnosis obtained with a device providing electromyography/electrocardiography (EMG/ECG) recordings. Forty-five (N = 45) subjects (19 males and 26 females, mean age 28 ± 11 years) were selected among patients referring to the Gnathology Unit of the Dental School of the University of Torino. An expert clinician assessed the presence of SB based on the presence of one or more signs/symptoms (i.e., transient jaw muscle pain in the morning, muscle fatigue at awakening, presence of tooth wear, masseter hypertrophy). Furthermore, all participants underwent an instrumental recording at home with a portable device (Bruxoff; OT Bioelettronica, Torino, Italy) allowing a simultaneous recording of EMG signals from both the masseter muscles as well as heart frequency. Statistical procedures were performed with the software Statistical Package for the Social Science v. 20.0 (SPSS 20.0; IBM, Milan, Italy). Based on the EMG/ECG analysis, 26 subjects (11 males, 15 females, mean age 28 ± 10 years) were diagnosed as sleep bruxers, whilst 19 subjects (7 males, 12 females, mean age 30 ± 10 years) were diagnosed as non-bruxers. The correlation between the clinical and EMG/ECG SB diagnoses was low (ϕ value = 0.250), with a 62.2% agreement (28/45 subjects) between the two approaches (kappa = 0.248). Assuming instrumental EMG/ECG diagnosis as the standard of reference for definite SB diagnosis in this investigation, the false-positive and false-negative rates were unacceptable for all clinical signs/symptoms. In conclusion, findings from clinical assessment are not related with SB diagnosis performed with a portable EMG/ECG recorder.

  7. ECG manifestations in acute organophosphorus poisoning.

    PubMed

    Paul, Uttam Kumar; Bhattacharyya, Anup Kumar

    2012-02-01

    A cross-sectional study was conducted to evaluate the electrocardiographic changes in 107 patients of acute organophosphorus poisoning admitted at casuality ward of MGM Medical College, Kisanganj from June 2007 to June 2010. Electrocardiographic changes were recorded before the administration of atropine. Prolonged Q-Tc interval was the commonest ECG abnormality, found in 67 patients (62.6%), followed by sinus tachycardia in 36 patients (33.6%). Sinus bradycardia was found in 33 patients (30.8%). Elevation of ST segment was seen in 27 patients (25.2%). T wave inversion was seen in 21 patients (19.6%). First-degree heart block (P-R interval >0.20 seconds) occurred in 9 cases (8.4%). Atrial fibrillation was seen in 5 patients (4.6%). Ventricular tachycardia was seen in 6 cases (5.6%) and ventricular premature complexes in 3 patients (2.8%). Of these 6 cases of ventricular tachycardia 1 responded to intravenous lignocaine, and the other 5 developed ventricular fibrillation leading to death despite other resuscitative measures. All the electrocardiographical abnormalities returned to normal before the patients were discharged. Seventeen patients died. The cause of death was ventricular fibrillation in 5 patients and non-cardiogenic pulmonary oedema in others. In conclusion it can be said that ECG should be carefully recorded and analysed in all patients of acute organophosphorus poisoning, and depending upon these changes and other clinical and biochemical parameters, the patients should immediately be shifted to well equipped ICU for better care which will reduce the mortality rate caused by these highly lethal poisons.

  8. Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals.

    PubMed

    Sudarshan, Vidya K; Acharya, U Rajendra; Oh, Shu Lih; Adam, Muhammad; Tan, Jen Hong; Chua, Chua Kuang; Chua, Kok Poo; Tan, Ru San

    2017-04-01

    Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments.

  9. Diagnostic Role of ECG Recording Simultaneously With EEG Testing.

    PubMed

    Kendirli, Mustafa Tansel; Aparci, Mustafa; Kendirli, Nurten; Tekeli, Hakan; Karaoglan, Mustafa; Senol, Mehmet Guney; Togrol, Erdem

    2015-07-01

    Arrhythmia is not uncommon in the etiology of syncope which mimics epilepsy. Data about the epilepsy induced vagal tonus abnormalities have being increasingly reported. So we aimed to evaluate what a neurologist may gain by a simultaneous electrocardiogram (ECG) and electroencephalogram (EEG) recording in the patients who underwent EEG testing due to prediagnosis of epilepsy. We retrospectively evaluated and detected ECG abnormalities in 68 (18%) of 376 patients who underwent EEG testing. A minimum of 20 of minutes artifact-free recording were required for each patient. Standard 1-channel ECG was simultaneously recorded in conjunction with the EEG. In all, 28% of females and 14% of males had ECG abnormalities. Females (mean age 49 years, range 18-88 years) were older compared with the male group (mean age 28 years, range 16-83 years). Atrial fibrillation was more frequent in female group whereas bradycardia and respiratory sinus arrhythmia was higher in male group. One case had been detected a critical asystole indicating sick sinus syndrome in the female group and treated with a pacemaker implantation in the following period. Simultaneous ECG recording in conjunction with EEG testing is a clinical prerequisite to detect and to clarify the coexisting ECG and EEG abnormalities and their clinical relevance. Potentially rare lethal causes of syncope that mimic seizure or those that could cause resistance to antiepileptic therapy could effectively be distinguished by detecting ECG abnormalities coinciding with the signs and abnormalities during EEG recording.

  10. Flexible Graphene Electrodes for Prolonged Dynamic ECG Monitoring

    PubMed Central

    Lou, Cunguang; Li, Ruikai; Li, Zhaopeng; Liang, Tie; Wei, Zihui; Run, Mingtao; Yan, Xiaobing; Liu, Xiuling

    2016-01-01

    This paper describes the development of a graphene-based dry flexible electrocardiography (ECG) electrode and a portable wireless ECG measurement system. First, graphene films on polyethylene terephthalate (PET) substrates and graphene paper were used to construct the ECG electrode. Then, a graphene textile was synthesized for the fabrication of a wearable ECG monitoring system. The structure and the electrical properties of the graphene electrodes were evaluated using Raman spectroscopy, scanning electron microscopy (SEM), and alternating current impedance spectroscopy. ECG signals were then collected from healthy subjects using the developed graphene electrode and portable measurement system. The results show that the graphene electrode was able to acquire the typical characteristics and features of human ECG signals with a high signal-to-noise (SNR) ratio in different states of motion. A week-long continuous wearability test showed no degradation in the ECG signal quality over time. The graphene-based flexible electrode demonstrates comfortability, good biocompatibility, and high electrophysiological detection sensitivity. The graphene electrode also combines the potential for use in long-term wearable dynamic cardiac activity monitoring systems with convenience and comfort for use in home health care of elderly and high-risk adults. PMID:27809270

  11. Altered Effective Connectivity of the Primary Motor Cortex in Stroke: A Resting-State fMRI Study with Granger Causality Analysis

    PubMed Central

    Fan, Mingxia; Yin, Dazhi; Sun, Limin; Jia, Jie; Tang, Chaozheng; Zheng, Xiaohui; Jiang, Yuwei; Wu, Jie; Gong, Jiayu

    2016-01-01

    The primary motor cortex (M1) is often abnormally recruited in stroke patients with motor disabilities. However, little is known about the alterations in the causal connectivity of M1 following stroke. The purpose of the present study was to investigate whether the effective connectivity of the ipsilesional M1 is disturbed in stroke patients who show different outcomes in hand motor function. 23 patients with left-hemisphere subcortical stroke were selected and divided into two subgroups: partially paralyzed hands (PPH) and completely paralyzed hands (CPH). Further, 24 matched healthy controls (HCs) were recruited. A voxel-wise Granger causality analysis (GCA) on the resting-state fMRI data between the ipsilesional M1 and the whole brain was performed to explore differences between the three groups. Our results showed that the influence from the frontoparietal cortices to ipsilesional M1 was diminished in both stroke subgroups and the influence from ipsilesional M1 to the sensorimotor cortices decreased greater in the CPH group than in the PPH group. Moreover, compared with the PPH group, the decreased influence from ipsilesional M1 to the contralesional cerebellum and from the contralesional superior parietal lobe to ipsilesional M1 were observed in the CPH group, and their GCA values were positively correlated with the FMA scores; Conversely, the increased influence from ipsilesional M1 to the ipsilesional middle frontal gyrus and middle temporal gyrus were observed, whose GCA values were negatively correlated with the FMA scores. This study suggests that the abnormalities of casual flow in the ipsilesional M1 are related to the severity of stroke-hand dysfunction, providing valuable information to understand the deficits in resting-state effective connectivity of motor execution and the frontoparietal motor control network during brain plasticity following stroke. PMID:27846290

  12. Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

    NASA Astrophysics Data System (ADS)

    Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

    2015-03-01

    Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

  13. Abnormalities of localized connectivity in schizophrenia patients and their unaffected relatives: a meta-analysis of resting-state functional magnetic resonance imaging studies

    PubMed Central

    Xiao, Bo; Wang, Shuai; Liu, Jianbo; Meng, Tiantian; He, Yuqiong; Luo, Xuerong

    2017-01-01

    Objective The localized dysfunction of specialized brain regions in schizophrenia patients and their unaffected relatives has been identified in a large-scale brain network; however, evidence is inconsistent. We aimed to identify abnormalities in the localized connectivity in schizophrenia patients and their relatives by conducting a meta-analysis of regional homogeneity (ReHo) studies. Methods Fourteen studies on resting-state functional magnetic resonance imaging, with 316 schizophrenia patients, 342 healthy controls, and 66 unaffected relatives, were included in the meta-analysis. This analysis was performed using anisotropic effect-size-based signed differential mapping software. Results Schizophrenia patients showed increased ReHo in right superior frontal gyrus and right superior temporal gyrus, as well as decreased ReHo in left fusiform gyrus, left superior temporal gyrus, left postcentral gyrus, and right precentral gyrus. Unaffected relatives showed decreased ReHo in right insula and right superior temporal gyrus. These results remained widely unchanged in both sensitivity and subgroup analyses. Conclusion Schizophrenia patients and their unaffected relatives had extensive abnormal localized connectivity in cerebrum, especially in superior temporal gyrus, which were the potential diagnostic markers and expounded the pathophysiological hypothesis for the disorder. PMID:28243099

  14. Resting state functional magnetic resonance imaging reveals distinct brain activity in heavy cannabis users – a multi-voxel pattern analysis

    PubMed Central

    Cheng, H; Skosnik, PD; Pruce, BJ; Brumbaugh, MS; Vollmer, JM; Fridberg, DJ; O’Donnell, BF; Hetrick, WP; Newman, SD

    2015-01-01

    Chronic cannabis use can cause cognitive, perceptual and personality alterations, which are believed to be associated with regional brain changes and possible changes in connectivity between functional regions. This study aims to identify the changes from resting state functional magnetic resonance imaging scans. A two-level multi-voxel pattern analysis was proposed to classify male cannabis users from normal controls. The first level analysis works on a voxel basis and identifies clusters for the input of a second level analysis, which works on the functional connectivity between these regions. We found distinct clusters for male cannabis users in the middle frontal gyrus, precentral gyrus, superior frontal gyrus, posterior cingulate cortex, cerebellum and some other regions. Based on the functional connectivity of these clusters, a high overall accuracy rate of 84–88% in classification accuracy was achieved. High correlations were also found between the overall classification accuracy and Barrett Barrett Impulsiveness Scale factor scores of attention and motor. Our result suggests regional differences in the brains of male cannabis users that span from the cerebellum to the prefrontal cortex, which are associated with differences in functional connectivity. PMID:25237118

  15. Statistical performance evaluation of ECG transmission using wireless networks.

    PubMed

    Shakhatreh, Walid; Gharaibeh, Khaled; Al-Zaben, Awad

    2013-07-01

    This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.

  16. Comparison of heart rate variability between resting state and external-cuff-inflation-and-deflation state: a pilot study.

    PubMed

    Ji, Lizhen; Liu, Chengyu; Li, Peng; Wang, Xinpei; Yan, Chang; Liu, Changchun

    2015-10-01

    Heart rate variability (HRV) has been widely used in clinical research to provide an insight into the autonomic control of the cardiovascular system. Measurement of HRV is generally performed under a relaxed resting state. The effects of other conditions on HRV measurement, such as running, mountaineering, head-up tilt, etc, have also been investigated. This study aimed to explore whether an inflation-and-deflation process applied to a unilateral upper arm cuff would influence the HRV measurement. Fifty healthy young volunteers aged between 21 and 30 were enrolled in this study. Electrocardiogram (ECG) signals were recorded for each subject over a five minute resting state followed by a five minute external-cuff-inflation-and-deflation state (ECID state). A one minute gap was scheduled between the two measurements. Consecutive RR intervals in the ECG were extracted automatically to form the HRV data for each of the two states. Time domain (SDNN, RMSSD and PNN50), frequency domain (LFn, HFn and LF/HF) and nonlinear (VLI, VAI and SampEn) HRV indices were analyzed and compared between the two states. In addition, the effects of mean artery pressure (MAP) and heart rate (HR) on the aforementioned HRV indices were assessed for the two states, respectively, by Pearson correlation analysis. The results showed no significant difference in all aforementioned HRV indices between the resting and the ECID states (all p  >  0.05). The corresponding HRV indices had significant positive correlation (all p  <  0.01) between the two states. None of the indices showed MAP-related change (all p  >  0.05) for either state. Besides, none of the indices showed HR-related change (all p  >  0.05) for either state except the index of VLI in the resting state. To conclude, this pilot study suggested that the applied ECID process hardly influenced those commonly used HRV indices. It would thus be applicable to simultaneously measure both blood pressure and HRV

  17. Implementation of a Data Packet Generator Using Pattern Matching for Wearable ECG Monitoring Systems

    PubMed Central

    Noh, Yun Hong; Jeong, Do Un

    2014-01-01

    In this paper, a packet generator using a pattern matching algorithm for real-time abnormal heartbeat detection is proposed. The packet generator creates a very small data packet which conveys sufficient crucial information for health condition analysis. The data packet envelopes real time ECG signals and transmits them to a smartphone via Bluetooth. An Android application was developed specifically to decode the packet and extract ECG information for health condition analysis. Several graphical presentations are displayed and shown on the smartphone. We evaluate the performance of abnormal heartbeat detection accuracy using the MIT/BIH Arrhythmia Database and real time experiments. The experimental result confirm our finding that abnormal heart beat detection is practically possible. We also performed data compression ratio and signal restoration performance evaluations to establish the usefulness of the proposed packet generator and the results were excellent. PMID:25029280

  18. Administration of eCG on Day 6 postpartum could enhance reproductive performance of Holstein dairy cows.

    PubMed

    Vojgani, M; Akbarinejad, V; Niasari-Naslaji, A

    2013-05-01

    Injection of eCG on Day 6 postpartum could enhance early resumption of ovarian activity in Holstein dairy cows. The present study was conducted to investigate the effects of eCG treatment on Day 6 postpartum on reproductive performance of Holstein dairy cows. Holstein dairy cows (n=420) were randomly assigned to two groups. Cows in eCG-treated group (n=220) received an intramuscular injection of eCG (500IU Folligon®) on Day 6 postpartum, while cows in the Control group (n=200) received no treatment. Estrus expression was observed thrice daily, and AI was carried out 12 hours after standing estrus. Data were analyzed using GLM and Genmod procedures, and survival analysis. Days to first service decreased in the eCG-treated (74.4±1.76 days) compared to the Control (84.2±2.79 days) group (P=0.008). Calving to conception interval was shorter in eCG-treated (103.9±3.14 days) vs Control (130.3±5.70 days) group (P=0.0006). Cows treated with eCG were inseminated and conceived earlier than untreated cows (P<0.05). In conclusion, injection of eCG on Day 6 postpartum improved reproductive performance in Holstein dairy cows.

  19. Degree Of Diminution In Vagal-Cardiac Activity Predicts Sudden Death In Familial Dysautonomia When Resting Tachycardia Is Absent

    NASA Technical Reports Server (NTRS)

    Schlegel, T. T.; Marthol, H.; Bucchner, S.; Tutaj, M.; Berlin, D.; Axelrod, F. B.; Hilz, M. J.

    2004-01-01

    Patients with familial dysautonomia (FD) have an increased risk of sudden death, but sensitive and specific predictors of sudden death in FD are lacking. Methods. We recorded 10-min resting high-fidelity 12-lead ECGs in 14 FD patients and in 14 age/gender-matched healthy subjects and studied 25+ different heart rate variability (HRV) indices for their ability to predict sudden death in the FD patients. Indices studied included those from 4 "nonlinear" HRV techniques (detrended fluctuation analysis, approximate entropy, correlation dimension, and PoincarC analyses). The predictive value of PR, QRS, QTc and JTc intervals, QT dispersion (QTd), beat-to-beat QT and PR interval variability indices (QTVI and PRVI) and 12- lead high frequency QRS ECG (150-250 Hz) were also studied. FD patients and controls (C) differed (Pless than 0.0l) with respect to 20+ of the HRV indices (FD less than C) and with respect to QTVI and PRVI (FDBC) and HF QRS- related root mean squared voltages (FDBC) and reduced amplitude zone counts (FD less than C). They differed less with respect to PR intervals (FD less than C) and JTc intervals (FD greater than C) (P less than 0.05 for both) and did not differ at all with respect to QRS and QTc intervals and to QTd. Within 12 months after study, 2 of the 14 patients succumbed to sudden cardiac arrest. The best predictor of sudden death was the degree of diminution in HRV vagal-cardiac (parasympathetic) parameters such as RMSSD, the SDl of Poincare plots, and HF spectral power. Excluding the two FD patients who had resting tachycardia (HR greater than 100, which confounds traditional HRV analyses), the following criteria were independently 100% sensitive and 100% specific for predicting sudden death in the remaining 12 FD patients during spontaneous breathing: RMSSD less than 13 ms and/or PoincarC SD1 less than 9 ms. In FD patients without supine tachycardia, the degree of diminution in parasympathetic HRV parameters (by high-fidelity ECG) predicts

  20. The 24-lead ECG display for enhanced recognition of STEMI-equivalent patterns in the 12-lead ECG.

    PubMed

    Pahlm, Ulrika; Pahlm, Olle; Wagner, Galen S

    2014-01-01

    In a patient with chest pain and suspected acute coronary syndrome, the electrocardiogram (ECG) is the only readily available diagnostic tool. It is important to maximize its usefulness to detect acute myocardial ischemia that may evolve to myocardial infarction unless the patient is treated expediently with reperfusion therapy. Since diagnostic guidelines have usually included only ST-elevation myocardial infarction (STEMI) as the entity that should be diagnosed and treated urgently, a patient with coronary occlusion represented on ECG as ST depression is likely not to be considered a candidate for receiving immediate coronary angiography and coronary intervention. ECG criteria for STEMI detection require that ST elevation meet predetermined millivolt thresholds and appear in at least two spatially contiguous ECG leads. The typical ECG reader recognizes only three contiguous pairs: aVL and I; II and aVF; aVF and III. However, viewing the "orderly sequenced" 12-lead ECG display, two more contiguous pairs become obvious in the frontal plane: +I and -aVR; -aVR and +II. The 24-lead ECG is a display of the standard 12-lead ECG as both the classical positive leads and their negative (inverted) counterparts. Leads +V1, +V2, +V3, +V4, +V5, and +V6 and their inverted counterparts are used to generate a "clock-face display" for the transverse plane. Similarly, +aVL, +I, -aVR, +II, +aVF, +III in the frontal plane and their inverted counterparts are used to generate a clock-face display for the frontal plane. Optimum results, 78% sensitivity and 93% specificity, were obtained using the following 19 ECG leads: frontal plane: +aVR, -III, +aVL, +I, -aVR, +II, +aVF, +III, -aVL; transverse plane: +V1, +V2, +V3, +V4, +V5, +V6, -V1, -V2, -V3.

  1. Genome‐wide analysis reveals conserved transcriptional responses downstream of resting potential change in Xenopus embryos, axolotl regeneration, and human mesenchymal cell differentiation

    PubMed Central

    Pai, Vaibhav P.; Martyniuk, Christopher J.; Echeverri, Karen; Sundelacruz, Sarah; Kaplan, David L.

    2015-01-01

    Abstract Endogenous bioelectric signaling via changes in cellular resting potential (V mem) is a key regulator of patterning during regeneration and embryogenesis in numerous model systems. Depolarization of V mem has been functionally implicated in dedifferentiation, tumorigenesis, anatomical re‐specification, and appendage regeneration. However, no unbiased analyses have been performed to understand genome‐wide transcriptional responses to V mem change in vivo. Moreover, it is unknown which genes or gene networks represent conserved targets of bioelectrical signaling across different patterning contexts and species. Here, we use microarray analysis to comparatively analyze transcriptional responses to V mem depolarization. We compare the response of the transcriptome during embryogenesis (Xenopus development), regeneration (axolotl regeneration), and stem cell differentiation (human mesenchymal stem cells in culture) to identify common networks across model species that are associated with depolarization. Both subnetwork enrichment and PANTHER analyses identified a number of key genetic modules as targets of V mem change, and also revealed important (well‐conserved) commonalities in bioelectric signal transduction, despite highly diverse experimental contexts and species. Depolarization regulates specific transcriptional networks across all three germ layers (ectoderm, mesoderm, and endoderm) such as cell differentiation and apoptosis, and this information will be used for developing mechanistic models of bioelectric regulation of patterning. Moreover, our analysis reveals that V mem change regulates transcripts related to important disease pathways such as cancer and neurodegeneration, which may represent novel targets for emerging electroceutical therapies. PMID:27499876

  2. Genome-wide analysis reveals conserved transcriptional responses downstream of resting potential change in Xenopus embryos, axolotl regeneration, and human mesenchymal cell differentiation.

    PubMed

    Pai, Vaibhav P; Martyniuk, Christopher J; Echeverri, Karen; Sundelacruz, Sarah; Kaplan, David L; Levin, Michael

    2016-02-01

    Endogenous bioelectric signaling via changes in cellular resting potential (V mem) is a key regulator of patterning during regeneration and embryogenesis in numerous model systems. Depolarization of V mem has been functionally implicated in dedifferentiation, tumorigenesis, anatomical re-specification, and appendage regeneration. However, no unbiased analyses have been performed to understand genome-wide transcriptional responses to V mem change in vivo. Moreover, it is unknown which genes or gene networks represent conserved targets of bioelectrical signaling across different patterning contexts and species. Here, we use microarray analysis to comparatively analyze transcriptional responses to V mem depolarization. We compare the response of the transcriptome during embryogenesis (Xenopus development), regeneration (axolotl regeneration), and stem cell differentiation (human mesenchymal stem cells in culture) to identify common networks across model species that are associated with depolarization. Both subnetwork enrichment and PANTHER analyses identified a number of key genetic modules as targets of V mem change, and also revealed important (well-conserved) commonalities in bioelectric signal transduction, despite highly diverse experimental contexts and species. Depolarization regulates specific transcriptional networks across all three germ layers (ectoderm, mesoderm, and endoderm) such as cell differentiation and apoptosis, and this information will be used for developing mechanistic models of bioelectric regulation of patterning. Moreover, our analysis reveals that V mem change regulates transcripts related to important disease pathways such as cancer and neurodegeneration, which may represent novel targets for emerging electroceutical therapies.

  3. A Differential ECG Amplifier with Single-Ended Output

    NASA Technical Reports Server (NTRS)

    Katchis, L.

    1972-01-01

    Three-stage amplifier is used for ECG measurements which require conversion of differential input to single-ended output. Circuit may be useful in biological telemetry for amplification of signals from specimen-implanted sensors.

  4. Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients.

    PubMed

    Corsi, Cristiana; Cortesi, Marilisa; Callisesi, Giulia; De Bie, Johan; Napolitano, Carlo; Santoro, Antonio; Mortara, David; Severi, Stefano

    2017-02-15

    Blood potassium concentration ([K(+)]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K(+)] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K(+)] varies significantly during the therapy. To elucidate the mechanism linking [K(+)] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K(+)] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (TS/A) was used as starting point for an ECG-based [K(+)] estimate (KECG). Leave-one-out cross-validation was performed. Agreement between KECG and reference [K(+)] from blood samples was promising (error: -0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of KECG correlation to blood [K(+)]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.

  5. mREST Interface Specification

    NASA Technical Reports Server (NTRS)

    McCartney, Patrick; MacLean, John

    2012-01-01

    mREST is an implementation of the REST architecture specific to the management and sharing of data in a system of logical elements. The purpose of this document is to clearly define the mREST interface protocol. The interface protocol covers all of the interaction between mREST clients and mREST servers. System-level requirements are not specifically addressed. In an mREST system, there are typically some backend interfaces between a Logical System Element (LSE) and the associated hardware/software system. For example, a network camera LSE would have a backend interface to the camera itself. These interfaces are specific to each type of LSE and are not covered in this document. There are also frontend interfaces that may exist in certain mREST manager applications. For example, an electronic procedure execution application may have a specialized interface for configuring the procedures. This interface would be application specific and outside of this document scope. mREST is intended to be a generic protocol which can be used in a wide variety of applications. A few scenarios are discussed to provide additional clarity but, in general, application-specific implementations of mREST are not specifically addressed. In short, this document is intended to provide all of the information necessary for an application developer to create mREST interface agents. This includes both mREST clients (mREST manager applications) and mREST servers (logical system elements, or LSEs).

  6. A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings.

    PubMed

    Vullings, R; Peters, C H L; Hermans, M J M; Wijn, P F F; Oei, S G; Bergmans, J W M

    2010-07-01

    The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications.

  7. Chest conduction properties and ECG equalization.

    PubMed

    Delle Cave, G; Fabricatore, G; Nolfe, G; Petrosino, M; Pizzuti, G P

    2000-01-01

    In common practice of detecting and recording biomedical signals, it is often implicitly assumed that the propagation, through the whole circuit human body-electrodes recording devices, is frequency and voltage independent. As a consequence, clinicians are not aware that recorded signals do not correspond faithfully to the original electrical activity of organs under investigation. We have studied the transmission of electrical signals in human body at various voltages and frequencies to understand if and to which extent the most diffused stimulating and recording techniques used in medicine are affected by global body conduction properties. Our results show that, in order to obtain a more faithful detection of electrical activity produced or evoked by human organs (e.g. EGG, electromyography, etc.), it is convenient to 'equalize'' recorded signals. To this purpose, two equalization techniques are proposed, based, respectively, on a simple hardware filtering during acquisition, or FFT post-processing of the acquired signals. As an application, we have studied the transmission of electrical signal in human chest and have compared equalized high frequency ECG signals with raw (original) recordings.

  8. Variability in surface ECG morphology: signal or noise?

    NASA Technical Reports Server (NTRS)

    Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

    1988-01-01

    Using data collected from canine models of acute myocardial ischemia, we investigated two issues of major relevance to electrocardiographic signal averaging: ECG epoch alignment, and the spectral characteristics of the beat-to-beat variability in ECG morphology. With initial digitization rates of 1 kHz, an iterative a posteriori matched filtering alignment scheme, and linear interpolation, we demonstrated that there is sufficient information in the body surface ECG to merit alignment to a precision of 0.1 msecs. Applying this technique to align QRS complexes and atrial pacing artifacts independently, we demonstrated that the conduction delay from atrial stimulus to ventricular activation may be so variable as to preclude using atrial pacing as an alignment mechanism, and that this variability in conduction time be modulated at the frequency of respiration and at a much lower frequency (0.02-0.03Hz). Using a multidimensional spectral technique, we investigated the beat-to-beat variability in ECG morphology, demonstrating that the frequency spectrum of ECG morphological variation reveals a readily discernable modulation at the frequency of respiration. In addition, this technique detects a subtle beat-to-beat alternation in surface ECG morphology which accompanies transient coronary artery occlusion. We conclude that physiologically important information may be stored in the variability in the surface electrocardiogram, and that this information is lost by conventional averaging techniques.

  9. Unveiling the Biometric Potential of Finger-Based ECG Signals

    PubMed Central

    Lourenço, André; Silva, Hugo; Fred, Ana

    2011-01-01

    The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications. PMID:21837235

  10. Live ECG readings using Google Glass in emergency situations.

    PubMed

    Schaer, Roger; Salamin, Fanny; Jimenez Del Toro, Oscar Alfonso; Atzori, Manfredo; Muller, Henning; Widmer, Antoine

    2015-01-01

    Most sudden cardiac problems require rapid treatment to preserve life. In this regard, electrocardiograms (ECG) shown on vital parameter monitoring systems help medical staff to detect problems. In some situations, such monitoring systems may display information in a less than convenient way for medical staff. For example, vital parameters are displayed on large screens outside the field of view of a surgeon during cardiac surgery. This may lead to losing time and to mistakes when problems occur during cardiac operations. In this paper we present a novel approach to display vital parameters such as the second derivative of the ECG rhythm and heart rate close to the field of view of a surgeon using Google Glass. As a preliminary assessment, we run an experimental study to verify the possibility for medical staff to identify abnormal ECG rhythms from Google Glass. This study compares 6 ECG rhythms readings from a 13.3 inch laptop screen and from the prism of Google Glass. Seven medical residents in internal medicine participated in the study. The preliminary results show that there is no difference between identifying these 6 ECG rhythms from the laptop screen versus Google Glass. Both allow close to perfect identification of the 6 common ECG rhythms. This shows the potential of connected glasses such as Google Glass to be useful in selected medical applications.

  11. Embroidered Electrode with Silver/Titanium Coating for Long-Term ECG Monitoring

    PubMed Central

    Weder, Markus; Hegemann, Dirk; Amberg, Martin; Hess, Markus; Boesel, Luciano F.; Abächerli, Roger; Meyer, Veronika R.; Rossi, René M.

    2015-01-01

    For the long-time monitoring of electrocardiograms, electrodes must be skin-friendly and non-irritating, but in addition they must deliver leads without artifacts even if the skin is dry and the body is moving. Today's adhesive conducting gel electrodes are not suitable for such applications. We have developed an embroidered textile electrode from polyethylene terephthalate yarn which is plasma-coated with silver for electrical conductivity and with an ultra-thin titanium layer on top for passivation. Two of these electrodes are embedded into a breast belt. They are moisturized with a very low amount of water vapor from an integrated reservoir. The combination of silver, titanium and water vapor results in an excellent electrode chemistry. With this belt the long-time monitoring of electrocardiography (ECG) is possible at rest as well as when the patient is moving. PMID:25599424

  12. Free vibration and biaxial buckling analysis of magneto-electro-elastic microplate resting on visco-Pasternak substrate via modified strain gradient theory

    NASA Astrophysics Data System (ADS)

    Jamalpoor, A.; Ahmadi-Savadkoohi, A.; Hosseini-Hashemi, Sh

    2016-10-01

    This paper deals with the theoretical analysis of free vibration and biaxial buckling of magneto-electro-elastic (MEE) microplate resting on Kelvin-Voigt visco-Pasternak foundation and subjected to initial external electric and magnetic potentials, using modified strain gradient theory (MSGT). Kirchhoff plate model and Hamilton’s principle are employed to extract the governing equations of motion. Governing equations were analytically solved to obtain clear closed-form expression for complex natural frequencies and buckling loads using Navier’s approach. Numerical results are presented to reveal variations of natural frequency and buckling load ratio of MEE microplate against different amounts of the length scale parameter, initial external electric and magnetic potentials, aspect ratio, damping and transverse and shear stiffness parameters of the visco-Pasternak foundation, length to thickness ratio, microplate thickness and higher modes. Numerical results of this study illustrate that by increasing thickness-to-material length scale parameter ratio, both natural frequency and buckling load ratio predicted by MSGT and modified couple stress theory are reduced because the non-dimensional length scale parameter tends to decrease the stiffness of structures and make them more flexible. In addition, results show that initial external electric and initial external magnetic potentials have no considerable influence on the buckling load ratio and frequency of MEE microplate as the microplate thickness increases.

  13. Abnormalities of regional brain function in Parkinson’s disease: a meta-analysis of resting state functional magnetic resonance imaging studies

    PubMed Central

    Pan, PingLei; Zhang, Yang; Liu, Yi; Zhang, He; Guan, DeNing; Xu, Yun

    2017-01-01

    There is convincing evidence that abnormalities of regional brain function exist in Parkinson’s disease (PD). However, many resting-state functional magnetic resonance imaging (rs-fMRI) studies using amplitude of low-frequency fluctuations (ALFF) have reported inconsistent results about regional spontaneous neuronal activity in PD. Therefore, we conducted a comprehensive meta-analysis using the Seed-based d Mapping and several complementary analyses. We searched PubMed, Embase, and Web of Science databases for eligible whole-brain rs-fMRI studies that measured ALFF differences between patients with PD and healthy controls published from January 1st, 2000 until June 24, 2016. Eleven studies reporting 14 comparisons, comparing 421 patients and 381 healthy controls, were included. The most consistent and replicable findings in patients with PD compared with healthy controls were identified, including the decreased ALFFs in the bilateral supplementary motor areas, left putamen, left premotor cortex, and left inferior parietal gyrus, and increased ALFFs in the right inferior parietal gyrus. The altered ALFFs in these brain regions are related to motor deficits and compensation in PD, which contribute to understanding its neurobiological underpinnings and could serve as specific regions of interest for further studies. PMID:28079169

  14. Alterations of functional connectivities from early to middle adulthood: Clues from multivariate pattern analysis of resting-state fMRI data.

    PubMed

    Tian, Lixia; Ma, Lin; Wang, Linlin

    2016-04-01

    In contrast to extended research interests in the maturation and aging of human brain, alterations of brain structure and function from early to middle adulthood have been much less studied. The aim of the present study was to investigate the extent and pattern of the alterations of functional interactions between brain regions from early to middle adulthood. We carried out the study by multivariate pattern analysis of resting-state fMRI (RS-fMRI) data of 63 adults aged 18 to 45 years. Specifically, using elastic net, we performed brain age estimation and age-group classification (young adults aged 18-28 years vs. middle-aged adults aged 35-45 years) based on the resting-state functional connectivities (RSFCs) between 160 regions of interest (ROIs) evaluated on the RS-fMRI data of each subject. The results indicate that the estimated brain ages were significantly correlated with the chronological age (R=0.78, MAE=4.81), and a classification rate of 94.44% and area under the receiver operating characteristic curve (AUC) of 0.99 were obtained when classifying the young and middle-aged adults. These results provide strong evidence that functional interactions between brain regions undergo notable alterations from early to middle adulthood. By analyzing the RSFCs that contribute to brain age estimation/age-group classification, we found that a majority of the RSFCs were inter-network, and we speculate that inter-network RSFCs might mature late but age early as compared to intra-network ones. In addition, the strengthening/weakening of the RSFCs associated with the left/right hemispheric ROIs, the weakening of cortico-cerebellar RSFCs and the strengthening of the RSFCs between the default mode network and other networks contributed much to both brain age estimation and age-group classification. All these alterations might reflect that aging of brain function is already in progress in middle adulthood. Overall, the present study indicated that the RSFCs undergo notable

  15. Cardiac Autonomic Alteration and Metabolic Syndrome: An Ambulatory ECG-based Study in A General Population

    PubMed Central

    Ma, Yan; Tseng, Ping-Huei; Ahn, Andrew; Wu, Ming-Shiang; Ho, Yi-Lwun; Chen, Ming-Fong; Peng, Chung-Kang

    2017-01-01

    Metabolic syndrome (MetS) has been associated with chronic damage to the cardiovascular system. This study aimed to evaluate early stage cardiac autonomic dysfunction with electrocardiography (ECG)-based measures in MetS subjects. During 2012–2013, 175 subjects with MetS and 226 healthy controls underwent ECG recordings of at least 4 hours starting in the morning with ambulatory one-lead ECG monitors. MetS was diagnosed using the criteria defined in the Adult Treatment Panel III, with a modification of waist circumference for Asians. Conventional heart rate variability (HRV) analysis, and complexity index (CI1–20) calculated from 20 scales of entropy (multiscale entropy, MSE), were compared between subjects with MetS and controls. Compared with the healthy controls, subjects with MetS had significantly reduced HRV, including SDNN and pNN20 in time domain, VLF, LF and HF in frequency domain, as well as SD2 in Poincaré analysis. MetS subjects have significantly lower complexity index (CI1–20) than healthy subjects (1.69 ± 0.18 vs. 1.77 ± 0.12, p < 0.001). MetS severity was inversely associated with the CI1–20 (r = −0.27, p < 0.001). MetS is associated with significant alterations in heart rate dynamics, including HRV and complexity. PMID:28290487

  16. How can computerized interpretation algorithms adapt to gender/age differences in ECG measurements?

    PubMed

    Xue, Joel; Farrell, Robert M

    2014-01-01

    It is well known that there are gender differences in 12 lead ECG measurements, some of which can be statistically significant. It is also an accepted practice that we should consider those differences when we interpret ECGs, by either a human overreader or a computerized algorithm. There are some major gender differences in 12 lead ECG measurements based on automatic algorithms, including global measurements such as heart rate, QRS duration, QT interval, and lead-by-lead measurements like QRS amplitude, ST level, etc. The interpretation criteria used in the automatic algorithms can be adapted to the gender differences in the measurements. The analysis of a group of 1339 patients with acute inferior MI showed that for patients under age 60, women had lower ST elevations at the J point in lead II than men (57±91μV vs. 86±117μV, p<0.02). This trend was reversed for patients over age 60 (lead aVF: 102±126μV vs. 84±117μV, p<0.04; lead III: 130±146μV vs. 103±131μV, p<0.007). Therefore, the ST elevation thresholds were set based on available gender and age information, which resulted in 25% relative sensitivity improvement for women under age 60, while maintaining a high specificity of 98%. Similar analyses were done for prolonged QT interval and LVH cases. The paper uses several design examples to demonstrate (1) how to design a gender-specific algorithm, and (2) how to design a robust ECG interpretation algorithm which relies less on absolute threshold-based criteria and is instead more reliant on overall morphology features, which are especially important when gender information is unavailable for automatic analysis.

  17. Association Between Resting-State Microstates and Ratings on the Amsterdam Resting-State Questionnaire.

    PubMed

    Pipinis, Evaldas; Melynyte, Sigita; Koenig, Thomas; Jarutyte, Lina; Linkenkaer-Hansen, Klaus; Ruksenas, Osvaldas; Griskova-Bulanova, Inga

    2017-03-01

    There is a gap in understanding on how physiologically observed activity is related to the subjective, internally oriented experience during resting state. Microstate analysis is a frequent approach to evaluate resting-state EEG. But the relationship of commonly observed resting-state microstates to psychological domains of resting is not clear. The Amsterdam Resting-State Questionnaire (ARSQ) was recently introduced, offering an effective way to quantify subjective states after a period of resting and associate these quantifiers to psychological and physiological variables. In a sample of 94 healthy volunteers who participated in closed-eyes 5 min resting session with concurrent EEG recording and subsequent filling of the ARSQ we evaluated parameters of microstate Classes A, B, C, D. We showed a moderate negative association between contribution (r = -0.40) of Class C and experienced somatic awareness (SA). The negative correlation between Class C and SA seems reasonable as Class C becomes more dominant when connections to contextual information (and bodily sensations as assessed with SA) are loosened (in reduced attention states, during sleep, hypnosis, or psychosis). We suggest that the use of questionnaires such as the ARSQ is helpful in exploring the variation of resting-state EEG parameters and its relationship to variation in sensory and non-sensory experiences.

  18. Standard-compliant real-time transmission of ECGs: harmonization of ISO/IEEE 11073-PHD and SCP-ECG.

    PubMed

    Trigo, Jesús D; Chiarugi, Franco; Alesanco, Alvaro; Martínez-Espronceda, Miguel; Chronaki, Catherine E; Escayola, Javier; Martínez, Ignacio; García, José

    2009-01-01

    Ambient assisted living and integrated care in an aging society is based on the vision of the lifelong Electronic Health Record calling for HealthCare Information Systems and medical device interoperability. For medical devices this aim can be achieved by the consistent implementation of harmonized international interoperability standards. The ISO/IEEE 11073 (x73) family of standards is a reference standard for medical device interoperability. In its Personal Health Device (PHD) version several devices have been included, but an ECG device specialization is not yet available. On the other hand, the SCP-ECG standard for short-term diagnostic ECGs (EN1064) has been recently approved as an international standard ISO/IEEE 11073-91064:2009. In this paper, the relationships between a proposed x73-PHD model for an ECG device and the fields of the SCP-ECG standard are investigated. A proof-of-concept implementation of the proposed x73-PHD ECG model is also presented, identifying open issues to be addressed by standards development for the wider interoperability adoption of x73-PHD standards.

  19. Pseudo-real-time low-pass filter in ECG, self-adjustable to the frequency spectra of the waves.

    PubMed

    Christov, Ivaylo; Neycheva, Tatyana; Schmid, Ramun; Stoyanov, Todor; Abächerli, Roger

    2017-02-04

    The electrocardiogram (ECG) acquisition is often accompanied by high-frequency electromyographic (EMG) noise. The noise is difficult to be filtered, due to considerable overlapping of its frequency spectrum to the frequency spectrum of the ECG. Today, filters must conform to the new guidelines (2007) for low-pass filtering in ECG with cutoffs of 150 Hz for adolescents and adults, and to 250 Hz for children. We are suggesting a pseudo-real-time low-pass filter, self-adjustable to the frequency spectra of the ECG waves. The filter is based on the approximation procedure of Savitzky-Golay with dynamic change in the cutoff frequency. The filter is implemented pseudo-real-time (real-time with a certain delay). An additional option is the automatic on/off triggering, depending on the presence/absence of EMG noise. The analysis of the proposed filter shows that the low-frequency components of the ECG (low-power P- and T-waves, PQ-, ST- and TP-segments) are filtered with a cutoff of 14 Hz, the high-power P- and T-waves are filtered with a cutoff frequency in the range of 20-30 Hz, and the high-frequency QRS complexes are filtered with cutoff frequency of higher than 100 Hz. The suggested dynamic filter satisfies the conflicting requirements for a strong suppression of EMG noise and at the same time a maximal preservation of the ECG high-frequency components.

  20. An adaptive Kalman filter for ECG signal enhancement.

    PubMed

    Vullings, Rik; de Vries, Bert; Bergmans, Jan W M

    2011-04-01

    The ongoing trend of ECG monitoring techniques to become more ambulatory and less obtrusive generally comes at the expense of decreased signal quality. To enhance this quality, consecutive ECG complexes can be averaged triggered on the heartbeat, exploiting the quasi-periodicity of the ECG. However, this averaging constitutes a tradeoff between improvement of the SNR and loss of clinically relevant physiological signal dynamics. Using a bayesian framework, in this paper, a sequential averaging filter is developed that, in essence, adaptively varies the number of complexes included in the averaging based on the characteristics of the ECG signal. The filter has the form of an adaptive Kalman filter. The adaptive estimation of the process and measurement noise covariances is performed by maximizing the bayesian evidence function of the sequential ECG estimation and by exploiting the spatial correlation between several simultaneously recorded ECG signals, respectively. The noise covariance estimates thus obtained render the filter capable of ascribing more weight to newly arriving data when these data contain morphological variability, and of reducing this weight in cases of no morphological variability. The filter is evaluated by applying it to a variety of ECG signals. To gauge the relevance of the adaptive noise-covariance estimation, the performance of the filter is compared to that of a Kalman filter with fixed, (a posteriori) optimized noise covariance. This comparison demonstrates that, without using a priori knowledge on signal characteristics, the filter with adaptive noise estimation performs similar to the filter with optimized fixed noise covariance, favoring the adaptive filter in cases where no a priori information is available or where signal characteristics are expected to fluctuate.

  1. The Resting Brain of Alcoholics

    PubMed Central

    Müller-Oehring, Eva M.; Jung, Young-Chul; Pfefferbaum, Adolf; Sullivan, Edith V.; Schulte, Tilman

    2015-01-01

    Chronic alcohol consumption affects multiple cognitive processes supported by far-reaching cerebral networks. To identify neurofunctional mechanisms underlying selective deficits, 27 sober alcoholics and 26 age-matched controls underwent resting-state functional magnetic resonance imaging and neuropsychological testing. Functional connectivity analysis assessed the default mode network (DMN); integrative executive control (EC), salience (SA), and attention (AT) networks; primary somatosensory, auditory, and visual (VI) input networks; and subcortical reward (RW) and emotion (EM) networks. The groups showed an extensive overlap of intrinsic connectivity in all brain networks examined, suggesting overall integrity of large-scale functional networks. Despite these similar patterns, connectivity analyses identified network-specific differences of weaker within-network connectivity and expanded connectivity to regions outside the main networks in alcoholics compared with controls. For AT and VI networks, better task performance was related to expanded connectivity in alcoholism, supporting the concept of network expansion as a neural mechanism for functional compensation. For default mode, SA, RW, and EC networks, both weaker within-network and expanded outside-network connectivity correlated with poorer performance and mood. Current smoking contributed to some of these abnormalities in connectivity. The observed pattern of resting-state connectivity might reflect neural vulnerability of intrinsic networking in alcoholics and suggests a mechanism to explain signature impairments in EM, RW evaluation, and EC ability. PMID:24935777

  2. Concept Design for a 1-Lead Wearable/Implantable ECG Front-End: Power Management

    PubMed Central

    George, Libin; Gargiulo, Gaetano Dario; Lehmann, Torsten; Hamilton, Tara Julia

    2015-01-01

    Power supply quality and stability are critical for wearable and implantable biomedical applications. For this reason we have designed a reconfigurable switched-capacitor DC-DC converter that, aside from having an extremely small footprint (with an active on-chip area of only 0.04 mm2), uses a novel output voltage control method based upon a combination of adaptive gain and discrete frequency scaling control schemes. This novel DC-DC converter achieves a measured output voltage range of 1.0 to 2.2 V with power delivery up to 7.5 mW with 75% efficiency. In this paper, we present the use of this converter as a power supply for a concept design of a wearable (15 mm × 15 mm) 1-lead ECG front-end sensor device that simultaneously harvests power and communicates with external receivers when exposed to a suitable RF field. Due to voltage range limitations of the fabrication process of the current prototype chip, we focus our analysis solely on the power supply of the ECG front-end whose design is also detailed in this paper. Measurement results show not just that the power supplied is regulated, clean and does not infringe upon the ECG bandwidth, but that there is negligible difference between signals acquired using standard linear power-supplies and when the power is regulated by our power management chip. PMID:26610497

  3. Concept Design for a 1-Lead Wearable/Implantable ECG Front-End: Power Management.

    PubMed

    George, Libin; Gargiulo, Gaetano Dario; Lehmann, Torsten; Hamilton, Tara Julia

    2015-11-19

    Power supply quality and stability are critical for wearable and implantable biomedical applications. For this reason we have designed a reconfigurable switched-capacitor DC-DC converter that, aside from having an extremely small footprint (with an active on-chip area of only 0.04 mm²), uses a novel output voltage control method based upon a combination of adaptive gain and discrete frequency scaling control schemes. This novel DC-DC converter achieves a measured output voltage range of 1.0 to 2.2 V with power delivery up to 7.5 mW with 75% efficiency. In this paper, we present the use of this converter as a power supply for a concept design of a wearable (15 mm × 15 mm) 1-lead ECG front-end sensor device that simultaneously harvests power and communicates with external receivers when exposed to a suitable RF field. Due to voltage range limitations of the fabrication process of the current prototype chip, we focus our analysis solely on the power supply of the ECG front-end whose design is also detailed in this paper. Measurement results show not just that the power supplied is regulated, clean and does not infringe upon the ECG bandwidth, but that there is negligible difference between signals acquired using standard linear power-supplies and when the power is regulated by our power management chip.

  4. Predictable and reliable ECG monitoring over IEEE 802.11 WLANs within a hospital.

    PubMed

    Park, Juyoung; Kang, Kyungtae

    2014-09-01

    Telecardiology provides mobility for patients who require constant electrocardiogram (ECG) monitoring. However, its safety is dependent on the predictability and robustness of data delivery, which must overcome errors in the wireless channel through which the ECG data are transmitted. We report here a framework that can be used to gauge the applicability of IEEE 802.11 wireless local area network (WLAN) technology to ECG monitoring systems in terms of delay constraints and transmission reliability. For this purpose, a medical-grade WLAN architecture achieved predictable delay through the combination of a medium access control mechanism based on the point coordination function provided by IEEE 802.11 and an error control scheme based on Reed-Solomon coding and block interleaving. The size of the jitter buffer needed was determined by this architecture to avoid service dropout caused by buffer underrun, through analysis of variations in transmission delay. Finally, we assessed this architecture in terms of service latency and reliability by modeling the transmission of uncompressed two-lead electrocardiogram data from the MIT-BIH Arrhythmia Database and highlight the applicability of this wireless technology to telecardiology.

  5. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

    PubMed Central

    Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2013-01-01

    Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

  6. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition.

    PubMed

    Diaz, B Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I; De Geus, Eco; Mansvelder, Huibert D; Van Someren, Eus J W; Linkenkaer-Hansen, Klaus

    2013-01-01

    Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition-and tools to quantify them-have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease.

  7. MicroECG: An Integrated Platform for the Cardiac Arrythmia Detection and Characterization

    NASA Astrophysics Data System (ADS)

    Nascimento, Bruno; Batista, Arnaldo; Alves, Luis Brandão; Ortigueira, Manuel; Rato, Raul

    A software tool for the analysis of the High-Resolution Electrocardiogram (HR-ECG) for Arrhythmia detection is introduced. New algorithms based on Wavelet analysis are presented and compared with the classic Simson protocol over the P and QRS segments of the Electrocardiogram (EEG). A novel procedure based on a two step wavelet analysis and synthesis is performed in order to obtain a frequency description of the P, T or QRS segments. This frequency "signature" is useful for the detection of otherwise asymptomatic Arrhythmia patients. The tool has been developed in Matlab, and deployed for a standalone C application.

  8. Resting-State Functional Connectivity by Independent Component Analysis-Based Markers Corresponds to Areas of Initial Seizure Propagation Established by Prior Modalities from the Hypothalamus

    PubMed Central

    Wilfong, Angus A.; Curry, Daniel J.

    2016-01-01

    Abstract The aims of this study were to evaluate a clinically practical functional connectivity (fc) protocol designed to blindly identify the corresponding areas of initial seizure propagation and also to differentiate these areas from remote secondary areas affected by seizure. The patients in this cohort had intractable epilepsy caused by intrahypothalamic hamartoma, which is the location of the ictal focus. The ictal propagation pathway is homogeneous and established, thus creating the optimum situation for the proposed method validation study. Twelve patients with seizures from hypothalamic hamartoma and six normal control patients underwent resting-state functional MRI, using independent component analysis (ICA) to identify network differences in patients. This was followed by seed-based connectivity measures to determine the extent of fc derangement between hypothalamus and these areas. The areas with significant change in connectivity were compared with the results of prior studies' modalities used to evaluate seizure propagation. The left amygdala-parahippocampal gyrus area, cingulate gyrus, and occipitotemporal gyrus demonstrated the highest derangement in connectivity with the hypothalamus, p < 0.01, corresponding to the initial seizure propagation areas established by prior modalities. Areas of secondary ictal propagation were differentiated from these initial locations by first being identified as an abnormal neuronal signal source through ICA, but did not show significant connectivity directly with the known ictal focus. Noninvasive connectivity measures correspond to areas of initial ictal propagation and differentiate such areas from secondary ictal propagation, which may aid in ictal focus surgical disconnection planning and support the use of this newer modality for adjunctive information in epilepsy surgery evaluation. PMID:27503346

  9. Effects of non-neuronal components for functional connectivity analysis from resting-state functional MRI toward automated diagnosis of schizophrenia

    NASA Astrophysics Data System (ADS)

    Kim, Junghoe; Lee, Jong-Hwan

    2014-03-01

    A functional connectivity (FC) analysis from resting-state functional MRI (rsfMRI) is gaining its popularity toward the clinical application such as diagnosis of neuropsychiatric disease. To delineate the brain networks from rsfMRI data, non-neuronal components including head motions and physiological artifacts mainly observed in cerebrospinal fluid (CSF), white matter (WM) along with a global brain signal have been regarded as nuisance variables in calculating the FC level. However, it is still unclear how the non-neuronal components can affect the performance toward diagnosis of neuropsychiatric disease. In this study, a systematic comparison of classification performance of schizophrenia patients was provided employing the partial correlation coefficients (CCs) as feature elements. Pair-wise partial CCs were calculated between brain regions, in which six combinatorial sets of nuisance variables were considered. The partial CCs were used as candidate feature elements followed by feature selection based on the statistical significance test between two groups in the training set. Once a linear support vector machine was trained using the selected features from the training set, the classification performance was evaluated using the features from the test set (i.e. leaveone- out cross validation scheme). From the results, the error rate using all non-neuronal components as nuisance variables (12.4%) was significantly lower than those using remaining combination of non-neuronal components as nuisance variables (13.8 ~ 20.0%). In conclusion, the non-neuronal components substantially degraded the automated diagnosis performance, which supports our hypothesis that the non-neuronal components are crucial in controlling the automated diagnosis performance of the neuropsychiatric disease using an fMRI modality.

  10. Investigating neural primacy in Major Depressive Disorder: multivariate Granger causality analysis of resting-state fMRI time-series data.

    PubMed

    Hamilton, J P; Chen, G; Thomason, M E; Schwartz, M E; Gotlib, I H

    2011-07-01

    Major Depressive Disorder (MDD) has been conceptualized as a neural network-level disease. Few studies of the neural bases of depression, however, have used analytical techniques that are capable of testing network-level hypotheses of neural dysfunction in this disorder. Moreover, of those that have, fewer still have attempted to determine the directionality of influence within functionally abnormal networks of structures. We used multivariate GC analysis, a technique that estimates the extent to which preceding neural activity in one or more seed regions predicts subsequent activity in target brain regions, to analyze blood-oxygen-level-dependent (BOLD) data collected during eyes-closed rest from depressed and never-depressed persons. We found that activation in the hippocampus predicted subsequent increases in ventral anterior cingulate cortex (vACC) activity in depression, and that activity in the medial prefrontal cortex and vACC were mutually reinforcing in MDD. Hippocampal and vACC activation in depressed participants predicted subsequent decreases in dorsal cortical activity. This study shows that, on a moment-by-moment basis, there is increased excitatory activity among limbic and paralimbic structures, as well as increased inhibition in the activity of dorsal cortical structures, by limbic structures in depression; these aberrant patterns of effective connectivity implicate disturbances in the mesostriatal dopamine system in depression. These findings advance the neural theory of depression by detailing specific patterns of limbic excitation in MDD, by making explicit the primary role of limbic inhibition of dorsal cortex in the cortico-limbic relation posited to underlie depression, and by presenting an integrated neurofunctional account of altered dopamine function in this disorder.

  11. A mobile phone-based ECG monitoring system.

    PubMed

    Iwamoto, Junichi; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton

    2006-01-01

    We have developed a telemedicine system for monitoring a patient's electrocardiogram during daily activities. The recording system consists of three ECG chest electrodes, a variable gain instrumentation amplifier, a low power 8-bit single-chip microcomputer, a 256 KB EEPROM and a 2.4 GHz low transmitting power mobile phone (PHS). The complete system is mounted on a single, lightweight, chest electrode array. When a heart discomfort is felt, the patient pushes the data transmission switch on the recording system. The system sends the recorded ECG waveforms of the two prior minutes and ECG waveforms of the two minutes after the switch is pressed, directly in the hospital server computer via the PHS. The server computer sends the data to the physician on call. The data is displayed on the doctor's Java mobile phone LCD (Liquid Crystal Display), so he or she can monitor the ECG regardless of their location. The developed ECG monitoring system is not only applicable to at-home patients, but should also be useful for monitoring hospital patients.

  12. Fast multi-scale feature fusion for ECG heartbeat classification

    NASA Astrophysics Data System (ADS)

    Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian

    2015-12-01

    Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

  13. Exploiting prior knowledge in compressed sensing wireless ECG systems.

    PubMed

    Polanía, Luisa F; Carrillo, Rafael E; Blanco-Velasco, Manuel; Barner, Kenneth E

    2015-03-01

    Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of compression rate and reconstruction quality of the ECG, still falls short of the performance attained by state-of-the-art wavelet-based algorithms. In this paper, we propose to exploit the structure of the wavelet representation of the ECG signal to boost the performance of CS-based methods for compression and reconstruction of ECG signals. More precisely, we incorporate prior information about the wavelet dependencies across scales into the reconstruction algorithms and exploit the high fraction of common support of the wavelet coefficients of consecutive ECG segments. Experimental results utilizing the MIT-BIH Arrhythmia Database show that significant performance gains, in terms of compression rate and reconstruction quality, can be obtained by the proposed algorithms compared to current CS-based methods.

  14. Acute “Pseudoischemic” ECG Abnormalities after Right Pneumonectomy

    PubMed Central

    Dimic-Janjic, Sanja; Stevic, Ruza; Milenkovic, Branislava; Djukanovic, Verica

    2017-01-01

    New onset of electrocardiographic (ECG) abnormalities can occur after lung surgery due to the changes in the position of structures and organs in the chest cavity. The most common heart rhythm disorder is atrial fibrillation. So-called “pseudoischemic” ECG changes that mimic classic ECG signs of acute myocardial ischemia are also often noticed. We report the case of a 68-year-old male, with no prior cardiovascular disease, who underwent extensive surgical resection for lung cancer. On a second postoperative day, clinical and electrocardiographic signs of acute myocardial ischemia occurred. According to clinical course, diagnostic procedures, and therapeutic response, we excluded acute coronary syndrome. We concluded that physical lesion of the pericardium, caused by extended pneumonectomy with resection of the pericardium, provoked the symptoms and ECG signs that mimic acute coronary syndrome. Our final diagnosis was postpericardiotomy syndrome after extended pneumonectomy and further treatment with nonsteroidal anti-inflammatory drugs (NSAIDs) was recommended. It is necessary to consider possibility that nature of ECG changes after extended pneumonectomy could be “pseudoischemic.” PMID:28197356

  15. PIC microcontroller-based RF wireless ECG monitoring system.

    PubMed

    Oweis, R J; Barhoum, A

    2007-01-01

    This paper presents a radio-telemetry system that provides the possibility of ECG signal transmission from a patient detection circuit via an RF data link. A PC then receives the signal through the National Instrument data acquisition card (NIDAQ). The PC is equipped with software allowing the received ECG signals to be saved, analysed, and sent by email to another part of the world. The proposed telemetry system consists of a patient unit and a PC unit. The amplified and filtered ECG signal is sampled 360 times per second, and the A/D conversion is performed by a PIC16f877 microcontroller. The major contribution of the final proposed system is that it detects, processes and sends patients ECG data over a wireless RF link to a maximum distance of 200 m. Transmitted ECG data with different numbers of samples were received, decoded by means of another PIC microcontroller, and displayed using MATLAB program. The designed software is presented in a graphical user interface utility.

  16. Comparison of baroreflex sensitivity estimated from ECG R-R and inter-systolic intervals obtained by finger plethysmography and radial tonometry.

    PubMed

    Viehweg, Juliane; Reimann, Manja; Gasch, Julia; Rüdiger, Heinz; Ziemssen, Tjalf

    2016-05-01

    Spontaneous BRS estimates may considerable vary according to the technique of blood pressure and heart rate assessment. To optimise and standardise BRS estimation for clinical use we evaluated possible differences between spontaneous BRS indices estimated from either finger plethysmography or radial tonometry. Forty-five healthy volunteers underwent simultaneous recordings of electrocardiogram, finger plethysmography and radial tonometry in supine position and during 60° head-up tilt. BRS was computed by spectral analysis from either R-R time series and/or arterial pressure pulse. Radial tonometry generated higher mean BRS estimates than finger plethysmography. The difference decreased upon postural change from supine to upright. In the upright position, BRS estimates based on R-R interval proved to be generally lower compared to BRS indices estimated from arterial pressure pulse. The ratio of low-to-high-frequency power of inter-systolic interval and systolic blood pressure from tonometry was lower than that from plethysmography in supine and approximated in upright position. Spectral parameters of inter-systolic interval and R-R interval did not differ in supine but diverged in upright position. Changes of spectral parameters were most pronounced in R-R interval. Arterial pressure pulse is adequate for estimation of BRS under resting conditions but it may distort BRS estimates under physical load. We, therefore, recommend using an ECG signal for BRS estimation especially in non-stationary conditions.

  17. A new mobile phone-based ECG monitoring system.

    PubMed

    Iwamoto, Junichi; Yonezawa, Yoshiharu; Ogawa, Hiromichi Maki Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton

    2007-01-01

    We have developed a system for monitoring a patient's electrocardiogram (ECG) and movement during daily activities. The complete system is mounted on chest electrodes and continuously samples the ECG and three axis accelerations. When the patient feels a heart discomfort, he or she pushes the data transmission switch on the recording system and the system sends the recorded ECG waveforms and three axis accelerations of the two prior minutes, and for two minutes after the switch is pressed. The data goes directly to a hospital server computer via a 2.4 GHz low power mobile phone. These data are stored on a server computer and downloaded to the physician's Java mobile phone. The physician can display the data on the phone's liquid crystal display.

  18. Chaos control applied to cardiac rhythms represented by ECG signals

    NASA Astrophysics Data System (ADS)

    Borem Ferreira, Bianca; Amorim Savi, Marcelo; Souza de Paula, Aline

    2014-10-01

    The control of irregular or chaotic heartbeats is a key issue in cardiology. In this regard, chaos control techniques represent a good alternative since they suggest treatments different from those traditionally used. This paper deals with the application of the extended time-delayed feedback control method to stabilize pathological chaotic heart rhythms. Electrocardiogram (ECG) signals are employed to represent the cardiovascular behavior. A mathematical model is employed to generate ECG signals using three modified Van der Pol oscillators connected with time delay couplings. This model provides results that qualitatively capture the general behavior of the heart. Controlled ECG signals show the ability of the strategy either to control or to suppress the chaotic heart dynamics generating less-critical behaviors.

  19. ECG Holter monitor with alert system and mobile application

    NASA Astrophysics Data System (ADS)

    Teron, Abigail C.; Rivera, Pedro A.; Goenaga, Miguel A.

    2016-05-01

    This paper proposes a new approach on the Holter monitor by creating a portable Electrocardiogram (ECG) Holter monitor that will alert the user by detecting abnormal heart beats using a digital signal processing software. The alarm will be triggered when the patient experiences arrhythmias such as bradycardia and tachycardia. The equipment is simple, comfortable and small in size that fit in the hand. It can be used at any time and any moment by placing three leads to the person's chest which is connected to an electronic circuit. The ECG data will be transmitted via Bluetooth to the memory of a selected mobile phone using an application that will store the collected data for up to 24 hrs. The arrhythmia is identified by comparing the reference signals with the user's signal. The diagnostic results demonstrate that the ECG Holter monitor alerts the user when an arrhythmia is detected thru the Holter monitor and mobile application.

  20. Convolutional Neural Networks for patient-specific ECG classification.

    PubMed

    Kiranyaz, Serkan; Ince, Turker; Hamila, Ridha; Gabbouj, Moncef

    2015-01-01

    We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and classification into a unified learner. In this way, a dedicated CNN will be trained for each patient by using relatively small common and patient-specific training data and thus it can also be used to classify long ECG records such as Holter registers in a fast and accurate manner. Alternatively, such a solution can conveniently be used for real-time ECG monitoring and early alert system on a light-weight wearable device. The experimental results demonstrate that the proposed system achieves a superior classification performance for the detection of ventricular ectopic beats (VEB) and supraventricular ectopic beats (SVEB).

  1. Non-contact ECG sensing employing gradiometer electrodes.

    PubMed

    Peng, GuoChen; Bocko, Mark F

    2013-01-01

    Noncontact, capacitive electrocardiogram (ECG) measurements are complicated by motion artifacts from the relative movement between the ECG electrodes and the subject. To compensate for such motion we propose to employ first and second order gradiometer electrode designs. A MATLAB-based simulation tool to enable assessment of different electrode configurations and placements on human subjects has been developed to guide the refinement of electrode designs. Experimental measurements of the sensitivity, motion artifact cancellation, and common mode rejection for various prototype designs were conducted with human subjects. Second order gradiometer electrode designs appear to give the best performance as measured by signal to noise plus distortion ratio. Finally, both gradiometer designs were compared with standard ECG recording methods and showed less than 1% beat detection mismatch employing an open source beat detection algorithm.

  2. ECG Interpretation Using the CRISP Method: A Guide for Nurses.

    PubMed

    Atwood, Denise; Wadlund, Diana L

    2015-10-01

    Nurses often struggle with identifying electrocardiogram (ECG) rhythms, but rapidly interpreting these rhythms is an essential skill that every nurse should master, especially in the perioperative setting. The CRISP (Cardiac Rhythm Identification for Simple People) method is an algorithm designed to help nurses rapidly interpret ECGs. Key aspects of assisting patients with suspected cardiac issues include the nursing assessment, correct three-lead ECG placement, and calculation of the heart rate. Then the perioperative nurse can use the steps of the CRISP method to identify nursing actions related to specific arrhythmias, including determining whether QRS complexes are present, P waves are present, and QRS complexes are wide or narrow or whether there are more P waves than QRS complexes.

  3. Design intelligent wheelchair with ECG measurement and wireless transmission function.

    PubMed

    Chou, Hsi-Chiang; Wang, Yi-Ming; Chang, Huai-Yuan

    2015-01-01

    The phenomenon of aging populations has produced widespread health awareness and magnified the need for improved medical quality and technologies. Statistics show that ischemic heart disease is the leading cause of death for older people and people with reduced mobility; therefore, wheelchairs have become their primary means of transport. Hence, an arrhythmia-detecting smart wheelchair was proposed in this study to provide real-time electrocardiography (ECG)-monitoring to patients with heart disease and reduced mobility. A self-developed, handheld ECG-sensing instrument was integrated with a wheelchair and a lab-written, arrhythmia-detecting program. The measured ECG data were transmitted through a Wi-Fi module and analyzed and diagnosed using the human-machine interface.

  4. Rest tremor suppression may separate essential from parkinsonian rest tremor.

    PubMed

    Papengut, Frank; Raethjen, Jan; Binder, Andreas; Deuschl, Günther

    2013-07-01

    Rest tremor at 4-6 Hz is typical for classical rest tremor (PT) of Parkinson's disease (PD). But rest tremor also appears in other tremor syndromes and may therefore cause a misdiagnosis. In this study we evaluated if suppression of tremor during movement onset is a characteristic feature of Parkinsonian Tremor distinguishing PT from Essential tremor (ET) and if this sign can be reliably diagnosed. Clinically diagnosed patients with PT (n = 44) and ET (n = 22) with rest tremor were included. Video sequences were recorded according to a standardized protocol focusing on the change of tremor amplitude during transition from rest to posture (test 1) or to a target-directed movement (test 2). These videos were assessed for rest tremor suppression by 4 reviewers (2 specialists and 2 residents) blinded to the clinical diagnosis and were compared to the personal assessment of an unblinded movement disorder specialist. Rest tremor suppression was found in 39/44 PD patients and in 2/22 patients with ET during the personal assessment. Rest tremor suppression showed a high sensitivity (0.92-1.00) and an acceptable specificity (0.69-0.95) for PD tremor in both tests. The interrater-reliability of the video-sequences was good to very good (κ 0.73-0.91). Less than 3% of the video sequences were misclassified. We conclude that the assessment of the suppression of rest tremor during movement initiation is a simple and reliable tool to separate PT from rest tremor in ET also suggesting that the mechanisms of rest tremor in these two diseases are different.

  5. Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies. The SEARCH-AF study.

    PubMed

    Lowres, Nicole; Neubeck, Lis; Salkeld, Glenn; Krass, Ines; McLachlan, Andrew J; Redfern, Julie; Bennett, Alexandra A; Briffa, Tom; Bauman, Adrian; Martinez, Carlos; Wallenhorst, Christopher; Lau, Jerrett K; Brieger, David B; Sy, Raymond W; Freedman, S Ben

    2014-06-01

    Atrial fibrillation (AF) causes a third of all strokes, but often goes undetected before stroke. Identification of unknown AF in the community and subsequent anti-thrombotic treatment could reduce stroke burden. We investigated community screening for unknown AF using an iPhone electrocardiogram (iECG) in pharmacies, and determined the cost-effectiveness of this strategy.Pharmacists performedpulse palpation and iECG recordings, with cardiologist iECG over-reading. General practitioner review/12-lead ECG was facilitated for suspected new AF. An automated AF algorithm was retrospectively applied to collected iECGs. Cost-effectiveness analysis incorporated costs of iECG screening, and treatment/outcome data from a United Kingdom cohort of 5,555 patients with incidentally detected asymptomatic AF. A total of 1,000 pharmacy customers aged ≥65 years (mean 76 ± 7 years; 44% male) were screened. Newly identified AF was found in 1.5% (95% CI, 0.8-2.5%); mean age 79 ± 6 years; all had CHA2DS2-VASc score ≥2. AF prevalence was 6.7% (67/1,000). The automated iECG algorithm showed 98.5% (CI, 92-100%) sensitivity for AF detection and 91.4% (CI, 89-93%) specificity. The incremental cost-effectiveness ratio of extending iECG screening into the community, based on 55% warfarin prescription adherence, would be $AUD5,988 (€3,142; $USD4,066) per Quality Adjusted Life Year gained and $AUD30,481 (€15,993; $USD20,695) for preventing one stroke. Sensitivity analysis indicated cost-effectiveness improved with increased treatment adherence.Screening with iECG in pharmacies with an automated algorithm is both feasible and cost-effective. The high and largely preventable stroke/thromboembolism risk of those with newly identified AF highlights the likely benefits of community AF screening. Guideline recommendation of community iECG AF screening should be considered.

  6. The ECG vertigo in diabetes and cardiac autonomic neuropathy.

    PubMed

    Voulgari, Christina; Tentolouris, Nicholas; Stefanadis, Christodoulos

    2011-01-01

    The importance of diabetes in the epidemiology of cardiovascular diseases cannot be overemphasized. About one third of acute myocardial infarction patients have diabetes, and its prevalence is steadily increasing. The decrease in cardiac mortality in people with diabetes is lagging behind that of the general population. Cardiovascular disease is a broad term which includes any condition causing pathological changes in blood vessels, cardiac muscle or valves, and cardiac rhythm. The ECG offers a quick, noninvasive clinical and research screen for the early detection of cardiovascular disease in diabetes. In this paper, the clinical and research value of the ECG is readdressed in diabetes and in the presence of cardiac autonomic neuropathy.

  7. A World Wide Web accessible multi-species ECG database.

    PubMed

    Hammann, H P; Suedmeyer, W K; Hahn, A W

    1997-01-01

    We have developed a system for remotely accessible secure electronic storage of electrocardiographic (ECG) and other associated data. It allows entry of data from any authorized remote user and is specifically built to accommodate the ECGs of multiple species. The present system is implemented on a Sun Sparc Solaris 2.5 platform using Oracle 7.3.2, and the Oracle 7.3.2 Web server. It may be easily ported to any other UNIX or Windows NT platform. No client is needed other than an Internet Protocol connected computer using a web browser such as Netscape Navigator or Microsoft Internet Explorer.

  8. Effects of noise and filtering on SVD-based morphological parameters of the T wave in the ECG.

    PubMed

    Lehtola, L; Karsikas, M; Koskinen, M; Huikuri, H; Seppanen, T

    2008-01-01

    Singular value decomposition (SVD) based electrocardiogram (ECG) morphology analysis is a novel method in the assessment of subtle abnormalities in the T wave morphology of 12-lead ECG. As various types of noise contaminate the ECG signal and create a bias for the morphological analyses, this study was designed to estimate the effects of noise on the SVD method in an experimental setup. Ideal signals were generated by filtering real ECG signals several times with the Savitzky-Golay filter. Random and real noise samples were superimposed on the ideal signals. The noisy signals were filtered with a power line interference filter combined with the Savitzky-Golay or the wavelet filter. Results show that noise increased both the dipolar and non-dipolar components significantly unless filtering was applied. R-TWR (relative T wave residuum) and A-TWR (absolute T wave residuum) were four to eight times higher in noisy signals. The experiments with patient data demonstrated that certain types of noise may even lead to erroneous classification of patients. Filtering brings the median values closer to the correct ones and decreases significantly the variance of the values of parameters.

  9. Architecture design of the multi-functional wavelet-based ECG microprocessor for realtime detection of abnormal cardiac events.

    PubMed

    Cheng, Li-Fang; Chen, Tung-Chien; Chen, Liang-Gee

    2012-01-01

    Most of the abnormal cardiac events such as myocardial ischemia, acute myocardial infarction (AMI) and fatal arrhythmia can be diagnosed through continuous electrocardiogram (ECG) analysis. According to recent clinical research, early detection and alarming of such cardiac events can reduce the time delay to the hospital, and the clinical outcomes of these individuals can be greatly improved. Therefore, it would be helpful if there is a long-term ECG monitoring system with the ability to identify abnormal cardiac events and provide realtime warning for the users. The combination of the wireless body area sensor network (BASN) and the on-sensor ECG processor is a possible solution for this application. In this paper, we aim to design and implement a digital signal processor that is suitable for continuous ECG monitoring and alarming based on the continuous wavelet transform (CWT) through the proposed architectures--using both programmable RISC processor and application specific integrated circuits (ASIC) for performance optimization. According to the implementation results, the power consumption of the proposed processor integrated with an ASIC for CWT computation is only 79.4 mW. Compared with the single-RISC processor, about 91.6% of the power reduction is achieved.

  10. Improvement of surface ECG recording in adult zebrafish reveals that the value of this model exceeds our expectation

    PubMed Central

    Liu, Chi Chi; Li, Li; Lam, Yun Wah; Siu, Chung Wah; Cheng, Shuk Han

    2016-01-01

    The adult zebrafish has been used to model the electrocardiogram (ECG) for human cardiovascular studies. Nonetheless huge variations are observed among studies probably because of the lack of a reliable and reproducible recording method. In our study, an adult zebrafish surface ECG recording technique was improved using a multi-electrode method and by pre-opening the pericardial sac. A convenient ECG data analysis method without wavelet transform was also established. Intraperitoneal injection of KCl in zebrafish induced an arrhythmia similar to that of humans, and the arrhythmia was partially rescued by calcium gluconate. Amputation and cryoinjury of the zebrafish heart induced ST segment depression and affected QRS duration after injury. Only cryoinjury decelerated the heart rate. Different changes were also observed in the QT interval during heart regeneration in these two injury models. We also characterized the electrocardiophysiology of breakdance zebrafish mutant with a prolonged QT interval, that has not been well described in previous studies. Our study provided a reliable and reproducible means to record zebrafish ECG and analyse data. The detailed characterization of the cardiac electrophysiology of zebrafish and its mutant revealed that the potential of the zebrafish in modeling the human cardiovascular system exceeds expectations. PMID:27125643

  11. A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

    PubMed Central

    Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong

    2013-01-01

    This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875

  12. Bed Rest Muscular Atrophy

    NASA Technical Reports Server (NTRS)

    Greenleaf, John E.

    2000-01-01

    A major debilitating response from prolonged bed rest (BR) is muscle atrophy, defined as a "decrease in size of a part of tissue after full development has been attained: a wasting away of tissue as from disuse, old age, injury or disease". Part of the complicated mechanism for the dizziness, increased body instability, and exaggerated gait in patients who arise immediately after BR may be a result of not only foot pain, but also of muscular atrophy and associated reduction in lower limb strength. Also, there seems to be a close association between muscle atrophy and bone atrophy. A discussion of many facets of the total BR homeostatic syndrome has been published. The old adage that use determines form which promotes function of bone (Wolff's law) also applies to those people exposed to prolonged BR (without exercise training) in whom muscle atrophy is a consistent finding. An extreme case involved a 16-year-old boy who was ordered to bed by his mother in 1932: after 50 years in bed he had "a lily-white frame with limbs as thin as the legs of a ladder-back chair". These findings emphasize the close relationship between muscle atrophy and bone atrophy. In addition to loss of muscle mass during deconditioning, there is a significant loss of muscle strength and a decrease in protein synthesis. Because the decreases in force (strength) are proportionately greater than those in fiber size or muscle cross-sectional area, other contributory factors must be involved; muscle fiber dehydration may be important.

  13. ECG-derived spatial QRS-T angle is associated with ICD implantation, mortality and heart failure admissions in patients with LV systolic dysfunction

    PubMed Central

    Dugo, Clementina; Cave, Andrew; Zhou, Lifeng; Ayar, Zina; Christiansen, Jonathan; Scott, Tony; Dawson, Liane; Gavin, Andrew

    2017-01-01

    echocardiographic variables with an increasing degree of disease. Conclusion Spatial QRS-T angle >110° was strongly associated with arrhythmic events and all-cause death. Deep analysis of global ECG and echocardiographic metadata revealed underlying relationships, which otherwise would not have been appreciated. Delivered at scale such techniques may prove useful in clinical decision making in the future. PMID:28358801

  14. Power spectral density analysis of physiological, rest and action tremor in Parkinson’s disease patients treated with deep brain stimulation

    PubMed Central

    2013-01-01

    Background Observation of the signals recorded from the extremities of Parkinson’s disease patients showing rest and/or action tremor reveal a distinct high power resonance peak in the frequency band corresponding to tremor. The aim of the study was to investigate, using quantitative measures, how clinically effective and less effective deep brain stimulation protocols redistribute movement power over the frequency bands associated with movement, pathological and physiological tremor, and whether normal physiological tremor may reappear during those periods that tremor is absent. Methods The power spectral density patterns of rest and action tremor were studied in 7 Parkinson’s disease patients treated with (bilateral) deep brain stimulation of the subthalamic nucleus. Two tests were carried out: 1) the patient was sitting at rest; 2) the patient performed a hand or foot tapping movement. Each test was repeated four times for each extremity with different stimulation settings applied during each repetition. Tremor intermittency was taken into account by classifying each 3-second window of the recorded angular velocity signals as a tremor or non-tremor window. Results The distribution of power over the low frequency band (<3.5 Hz – voluntary movement), tremor band (3.5-7.5 Hz) and high frequency band (>7.5 Hz – normal physiological tremor) revealed that rest and action tremor show a similar power-frequency shift related to tremor absence and presence: when tremor is present most power is contained in the tremor frequency band; when tremor is absent lower frequencies dominate. Even under resting conditions a relatively large low frequency component became prominent, which seemed to compensate for tremor. Tremor absence did not result in the reappearance of normal physiological tremor. Conclusion Parkinson’s disease patients continuously balance between tremor and tremor suppression or compensation expressed by power shifts between the low frequency band and

  15. Physiology Of Prolonged Bed Rest

    NASA Technical Reports Server (NTRS)

    Greenleaf, John E.

    1991-01-01

    Report describes physiological effects of prolonged bed rest. Rest for periods of 24 hours or longer deconditions body to some extent; healing proceeds simultaneously with deconditioning. Report provides details on shifts in fluid electrolytes and loss of lean body mass, which comprises everything in body besides fat - that is, water, muscle, and bone. Based on published research.

  16. REST and stress resistance in ageing and Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Lu, Tao; Aron, Liviu; Zullo, Joseph; Pan, Ying; Kim, Haeyoung; Chen, Yiwen; Yang, Tun-Hsiang; Kim, Hyun-Min; Drake, Derek; Liu, X. Shirley; Bennett, David A.; Colaiácovo, Monica P.; Yankner, Bruce A.

    2014-03-01

    Human neurons are functional over an entire lifetime, yet the mechanisms that preserve function and protect against neurodegeneration during ageing are unknown. Here we show that induction of the repressor element 1-silencing transcription factor (REST; also known as neuron-restrictive silencer factor, NRSF) is a universal feature of normal ageing in human cortical and hippocampal neurons. REST is lost, however, in mild cognitive impairment and Alzheimer's disease. Chromatin immunoprecipitation with deep sequencing and expression analysis show that REST represses genes that promote cell death and Alzheimer's disease pathology, and induces the expression of stress response genes. Moreover, REST potently protects neurons from oxidative stress and amyloid β-protein toxicity, and conditional deletion of REST in the mouse brain leads to age-related neurodegeneration. A functional orthologue of REST, Caenorhabditis elegans SPR-4, also protects against oxidative stress and amyloid β-protein toxicity. During normal ageing, REST is induced in part by cell non-autonomous Wnt signalling. However, in Alzheimer's disease, frontotemporal dementia and dementia with Lewy bodies, REST is lost from the nucleus and appears in autophagosomes together with pathological misfolded proteins. Finally, REST levels during ageing are closely correlated with cognitive preservation and longevity. Thus, the activation state of REST may distinguish neuroprotection from neurodegeneration in the ageing brain.

  17. ECG Identification System Using Neural Network with Global and Local Features

    ERIC Educational Resources Information Center

    Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

    2016-01-01

    This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

  18. Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

    PubMed Central

    Sivaraks, Haemwaan

    2015-01-01

    Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

  19. Robust and accurate anomaly detection in ECG artifacts using time series motif discovery.

    PubMed

    Sivaraks, Haemwaan; Ratanamahatana, Chotirat Ann

    2015-01-01

    Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods.

  20. Accurate Interpretation of the 12-Lead ECG Electrode Placement: A Systematic Review

    ERIC Educational Resources Information Center

    Khunti, Kirti

    2014-01-01

    Background: Coronary heart disease (CHD) patients require monitoring through ECGs; the 12-lead electrocardiogram (ECG) is considered to be the non-invasive gold standard. Examples of incorrect treatment because of inaccurate or poor ECG monitoring techniques have been reported in the literature. The findings that only 50% of nurses and less than…

  1. Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients

    PubMed Central

    Corsi, Cristiana; Cortesi, Marilisa; Callisesi, Giulia; De Bie, Johan; Napolitano, Carlo; Santoro, Antonio; Mortara, David; Severi, Stefano

    2017-01-01

    Blood potassium concentration ([K+]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K+] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K+] varies significantly during the therapy. To elucidate the mechanism linking [K+] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K+] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (TS/A) was used as starting point for an ECG-based [K+] estimate (KECG). Leave-one-out cross-validation was performed. Agreement between KECG and reference [K+] from blood samples was promising (error: −0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of KECG correlation to blood [K+]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia. PMID:28198403

  2. ECG Monitoring in Cardiac Rehabilitation: Is It Needed?

    ERIC Educational Resources Information Center

    Greenland, Philip; Pomilla, Paul V.

    1989-01-01

    Discusses the controversial use of continuous electrocardiogram (ECG) monitoring as a safety measure in cardiac rehabilitation exercise programs. Little evidence substantiates its value for all patients during exercise. In the absence of empirical evidence documenting the worth of this expensive procedure, it is recommended for use with high-risk…

  3. ECG-based heartbeat classification for arrhythmia detection: A survey.

    PubMed

    Luz, Eduardo José da S; Schwartz, William Robson; Cámara-Chávez, Guillermo; Menotti, David

    2016-04-01

    An electrocardiogram (ECG) measures the electric activity of the heart and has been widely used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing the electrical signal of each heartbeat, i.e., the combination of action impulse waveforms produced by different specialized cardiac tissues found in the heart, it is possible to detect some of its abnormalities. In the last decades, several works were developed to produce automatic ECG-based heartbeat classification methods. In this work, we survey the current state-of-the-art methods of ECG-based automated abnormalities heartbeat classification by presenting the ECG signal preprocessing, the heartbeat segmentation techniques, the feature description methods and the learning algorithms used. In addition, we describe some of the databases used for evaluation of methods indicated by a well-known standard developed by the Association for the Advancement of Medical Instrumentation (AAMI) and described in ANSI/AAMI EC57:1998/(R)2008 (ANSI/AAMI, 2008). Finally, we discuss limitations and drawbacks of the methods in the literature presenting concluding remarks and future challenges, and also we propose an evaluation process workflow to guide authors in future works.

  4. Measurement of ventricular function by ECG gating during atrial fibrillation

    SciTech Connect

    Bacharach, S.L.; Green, M.V.; Bonow, R.O.; Findley, S.L.; Ostrow, H.G.; Johnston, G.S.

    1981-03-01

    The assumptions necessary to perform ECG-gated cardiac studies are seemingly not valid for patients in atrial fibrillation (AF). To evaluate the effect of AF on equilibrium gated scintigraphy, beat-by-beat measurements of left-ventricular function were made on seven subjects in AF (mean heart rate 64 bpm), using a high-efficiency nonimaging detector. The parameters evaluated were ejection fraction (EF), time to end-systole (TES), peak rates of ejection and filling (PER,PFR), and their times of occurrence (TPER, TPFR). By averaging together single-beat values of EF, PER, etc., it was possible to determine the true mean values of these parameters. The single-beam mean values were compared with the corresponding parameters calculated from one ECG-gated time-activity curve (TAC) obtained by superimposing all the single-beat TACs irrespective of their length. For this population with slow heart rates, we find that the values for EF, etc., produced from ECG-gated time-activity curves, are very similar to those obtained from the single-beat data. Thus use of ECG gating at low heart rates may allow reliable estimation of average cardiac function even in subjects with AF.

  5. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Radiographic ECG/respirator synchronizer. 892.1970 Section 892.1970 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic...

  6. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Radiographic ECG/respirator synchronizer. 892.1970 Section 892.1970 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic...

  7. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Radiographic ECG/respirator synchronizer. 892.1970 Section 892.1970 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic...

  8. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Radiographic ECG/respirator synchronizer. 892.1970 Section 892.1970 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic...

  9. Cardiac Electrophysiology: Normal and Ischemic Ionic Currents and the ECG

    ERIC Educational Resources Information Center

    Klabunde, Richard E.

    2017-01-01

    Basic cardiac electrophysiology is foundational to understanding normal cardiac function in terms of rate and rhythm and initiation of cardiac muscle contraction. The primary clinical tool for assessing cardiac electrical events is the electrocardiogram (ECG), which provides global and regional information on rate, rhythm, and electrical…

  10. ECG gated NMR-CT for cardiovascular diseases

    SciTech Connect

    Nishikawa, J.; Ohtake, T.; Machida, K.; Iio, M.; Yoshimoto, N.; Sugimoto, T.

    1985-05-01

    The authors have been applying ECG gated NMR-CT to mainly patients with myocardial infarction (MI), and hypertrophic cardiomyopathy (HCM). Thirteen patients with MI, 8 with HCM and 5 without any heart diseases were studied by ECG gated NMR imaging (spin-echo technique, TR: depends on patient heart rate, TE: 35 and 70 msec.) with 0.35 T superconducting magnet. On NMR images (MRI), the authors examined the wall thickness, wall motion and T/sub 2/ relaxation time in the area of diseased myocardium. The lesions of old MI were depicted as the area of thin wall and T/sub 2/ relaxation time of those lesions were similar to the area of non-infarcted myocardium. The lesions of recent MI (up to 3.5 months from the recent attack) were shown as the same wall thickness as the non-infarcted myocardium and the area of prolonged T/sub 2/ relaxation time compared with that of non-infarcted myocardium. MRI demonstrated diffusely thick myocardium in all patients with HCM. T/sub 2/ relaxation time of the areas of HCM was almost the same as that of normal myocardium, and it's difference among each ventricular wall in patients with HCM was not statistically significant. The authors conclude that ECG gated NMR-CT offers 3-D morphological information of the heart without any contrast material nor radioisotopes. ECG gated MRI provides the useful informations to diagnose MI, especially in the differential diagnosis between old and recent MI.

  11. Mean-shape vector quantizer for ECG signal compression.

    PubMed

    Cárdenas-Barrera, J L; Lorenzo-Ginori, J V

    1999-01-01

    A direct waveform mean-shape vector quantization (MSVQ) is proposed here as an alternative for electrocardiographic (ECG) signal compression. In this method, the mean values for short ECG signal segments are quantized as scalars and compression of the single-lead ECG by average beat substraction and residual differencing their waveshapes coded through a vector quantizer. An entropy encoder is applied to both, mean and vector codes, to further increase compression without degrading the quality of the reconstructed signals. In this paper, the fundamentals of MSVQ are discussed, along with various parameters specifications such as duration of signal segments, the wordlength of the mean-value quantization and the size of the vector codebook. The method is assessed through percent-residual-difference measures on reconstructed signals, whereas its computational complexity is analyzed considering its real-time implementation. As a result, MSVQ has been found to be an efficient compression method, leading to high compression ratios (CR's) while maintaining a low level of waveform distortion and, consequently, preserving the main clinically interesting features of the ECG signals. CR's in excess of 39 have been achieved, yielding low data rates of about 140 bps. This compression factor makes this technique especially attractive in the area of ambulatory monitoring.

  12. A portable system for acquiring and removing motion artefact from ECG signals

    NASA Astrophysics Data System (ADS)

    Griffiths, A.; Das, A.; Fernandes, B.; Gaydecki, P.

    2007-07-01

    A novel electrocardiograph (ECG) signal acquisition and display system is under development. It is designed for patients ranging from the elderly to athletes. The signals are obtained from electrodes integrated into a vest, amplified, digitally processed and transmitted via Bluetooth to a PC with a Labview ® interface. Digital signal processing is performed to remove movement artefact and electromyographic (EMG) noise, which severely distorts signal morphology and complicates clinical diagnosis. Independent component analysis (ICA) is also used to improve the signal quality. The complete system will integrate the electronics into a single module which will be embedded in the vest.

  13. The Effects of Long Duration Bed Rest on Functional Mobility and Balance: Relationship to Resting State Motor Cortex Connectivity

    NASA Technical Reports Server (NTRS)

    Erdeniz, B.; Koppelmans, V.; Bloomberg, J. J.; Kofman, I. S.; DeDios, Y. E.; Riascos-Castaneda, R. F.; Wood, S. J.; Mulavara, A. P.; Seidler, R. D.

    2014-01-01

    NASA offers researchers from a variety of backgrounds the opportunity to study bed rest as an experimental analog for space flight. Extended exposure to a head-down tilt position during long duration bed rest can resemble many of the effects of a low-gravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The aim of our study is to a) identify changes in brain function that occur with prolonged bed rest and characterize their recovery time course; b) assess whether and how these changes impact behavioral and neurocognitive performance. Thus far, we completed data collection from six participants that include task based and resting state fMRI. The data have been acquired through the bed rest facility located at the University of Texas Medical Branch (Galveston, TX). Subjects remained in bed with their heads tilted down 6 degrees below their feet for 70 consecutive days. Behavioral measures and neuroimaging assessments were obtained at seven time points: a) 7 and 12 days before bed rest; b) 7, 30, and 65 days during bed rest; and c) 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (FcMRI) analysis was performed to assess the connectivity of motor cortex in and out of bed rest. We found a decrease in motor cortex connectivity with vestibular cortex and the cerebellum from pre bed rest to in bed rest. We also used a battery of behavioral measures including the functional mobility test and computerized dynamic posturography collected before and after bed rest. We will report the preliminary results of analyses relating brain and behavior changes. Furthermore, we will also report the preliminary results of a spatial working memory task and vestibular stimulation during in and out of bed rest.

  14. RESTful Web Services at BNL

    SciTech Connect

    Casella, R.

    2011-06-14

    RESTful (REpresentational State Transfer) web services are an alternative implementation to SOAP/RPC web services in a client/server model. BNLs IT Division has started deploying RESTful Web Services for enterprise data retrieval and manipulation. Data is currently used by system administrators for tracking configuration information and as it is expanded will be used by Cyber Security for vulnerability management and as an aid to cyber investigations. This talk will describe the implementation and outstanding issues as well as some of the reasons for choosing RESTful over SOAP/RPC and future directions.

  15. Serial thallium-201 imaging at rest in patients with unstable and stable angina pectoris: relationship of myocardial perfusion at rest to presenting clinical syndrome

    SciTech Connect

    Brown, K.A.; Okada, R.D.; Boucher, C.A.; Phillips, H.R.; Strauss, H.W.; Pohost, G.M.

    1983-07-01

    In order to determine whether there are differences in myocardial perfusion at rest among patients with various unstable and stable angina syndromes, serial thallium-201 imaging was performed at rest in 19 patients presenting with rapidly worsening exertional angina (unstable angina, group A), 12 patients with rest angina alone without exertional symptoms (unstable angina, group B), and 34 patients with chronic stable angina. No patient had an episode of angina within 4 hours of study. Nineteen of 19 (100%) patients in group A demonstrated transient defects compared to only 3 of 12 (25%) patients in group B (p less than 0.0001) and 4 of 34 (12%) stable angina patients (p less than 0.0001). The majority of zones demonstrating transient defects in group A were associated with hypokinesis of the corresponding left ventriculogram segment without associated ECG evidence of previous infarction. There were no significant differences in the frequency of persistent thallium defects, severity of angiographic coronary artery disease, or frequency of regional wall motion abnormalities of myocardial segments supplied by stenotic coronary arteries among the three groups of patients. Transient defects have been shown to reflect reduction in regional coronary blood flow to viable myocardium. Therefore, we conclude that regional resting hypoperfusion of viable myocardium is far more common in patients with exertional unstable angina symptoms than in patients with rest angina alone or chronic stable angina.

  16. Predicting Scenarios for Successful Autodissemination of Pyriproxyfen by Malaria Vectors from Their Resting Sites to Aquatic Habitats; Description and Simulation Analysis of a Field-Parameterizable Model

    PubMed Central

    Kiware, Samson S.; Corliss, George; Merrill, Stephen; Lwetoijera, Dickson W.; Devine, Gregor; Majambere, Silas; Killeen, Gerry F.

    2015-01-01

    Background Large-cage experiments indicate pyriproxifen (PPF) can be transferred from resting sites to aquatic habitats by Anopheles arabiensis - malaria vector mosquitoes to inhibit emergence of their own offspring. PPF coverage is amplified twice: (1) partial coverage of resting sites with PPF contamination results in far higher contamination coverage of adult mosquitoes because they are mobile and use numerous resting sites per gonotrophic cycle, and (2) even greater contamination coverage of aquatic habitats results from accumulation of PPF from multiple oviposition events. Methods and Findings Deterministic mathematical models are described that use only field-measurable input parameters and capture the biological processes that mediate PPF autodissemination. Recent successes in large cages can be rationalized, and the plausibility of success under full field conditions can be evaluated a priori. The model also defines measurable properties of PPF delivery prototypes that may be optimized under controlled experimental conditions to maximize chances of success in full field trials. The most obvious flaw in this model is the endogenous relationship that inevitably occurs between the larval habitat coverage and the measured rate of oviposition into those habitats if the target mosquito species is used to mediate PPF transfer. However, this inconsistency also illustrates the potential advantages of using a different, non-target mosquito species for contamination at selected resting sites that shares the same aquatic habitats as the primary target. For autodissemination interventions to eliminate malaria transmission or vector populations during the dry season window of opportunity will require comprehensive contamination of the most challenging subset of aquatic habitats (Clx) that persist or retain PPF activity (Ux) for only one week (Clx→1, where Ux = 7 days). To achieve >99% contamination coverage of these habitats will necessitate values for the product of

  17. Flight Analogs (Bed Rest Research)

    NASA Video Gallery

    Flight Analogs / Bed Rest Research Projects provide NASA with a ground based research platform to complement space research. By mimicking the conditions of weightlessness in the human body here on ...

  18. Rest Mutant zebrafish swim erratically and display atypical spatial preferences

    PubMed Central

    Moravec, Cara E.; Li, Edward; Maaswinkel, Hans; Kritzer, Mary F.; Weng, Wei; Sirotkin, Howard I.

    2015-01-01

    The Rest/Nrsf transcriptional repressor modulates expression of a large set of neural specific genes. Many of these target genes have well characterized roles in nervous system processes including development, plasticity and synaptogenesis. However, the impact of Rest-mediated transcriptional regulation on behavior has been understudied due in part to the embryonic lethality of the mouse knockout. To investigate the requirement for Rest in behavior, we employed the zebrafish rest mutant to explore a range of behaviors in adults and larva. Adult rest mutants of both sexes showed abnormal behaviors in a novel environment including increased vertical swimming, erratic swimming patterns and a proclivity for the tank walls. Adult males also had diminished reproductive success. At 6 days post fertilization (dpf), rest mutant larva were hypoactive, but displayed normal evoked responses to light and sound stimuli. Overall, these results provide evidence that rest dysfunction produces atypical swimming patterns and preferences in adults, and reduced locomotor activity in larvae. This study provides the first behavioral analysis of rest mutants and reveals specific behaviors that are modulated by Rest. PMID:25712696

  19. Rest mutant zebrafish swim erratically and display atypical spatial preferences.

    PubMed

    Moravec, Cara E; Li, Edward; Maaswinkel, Hans; Kritzer, Mary F; Weng, Wei; Sirotkin, Howard I

    2015-05-01

    The Rest/Nrsf transcriptional repressor modulates expression of a large set of neural specific genes. Many of these target genes have well characterized roles in nervous system processes including development, plasticity and synaptogenesis. However, the impact of Rest-mediated transcriptional regulation on behavior has been understudied due in part to the embryonic lethality of the mouse knockout. To investigate the requirement for Rest in behavior, we employed the zebrafish rest mutant to explore a range of behaviors in adults and larva. Adult rest mutants of both sexes showed abnormal behaviors in a novel environment including increased vertical swimming, erratic swimming patterns and a proclivity for the tank walls. Adult males also had diminished reproductive success. At 6 days post fertilization (dpf), rest mutant larva were hypoactive, but displayed normal evoked responses to light and sound stimuli. Overall, these results provide evidence that rest dysfunction produces atypical swimming patterns and preferences in adults, and reduced locomotor activity in larvae. This study provides the first behavioral analysis of rest mutants and reveals specific behaviors that are modulated by Rest.

  20. Exploring Neuro-Physiological Correlates of Drivers' Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Data

    PubMed Central

    Ahn, Sangtae; Nguyen, Thien; Jang, Hyojung; Kim, Jae G.; Jun, Sung C.

    2016-01-01

    Investigations of the neuro-physiological correlates of mental loads, or states, have attracted significant attention recently, as it is particularly important to evaluate mental fatigue in drivers operating a motor vehicle. In this research, we collected multimodal EEG/ECG/EOG and fNIRS data simultaneously to develop algorithms to explore neuro-physiological correlates of drivers' mental states. Each subject performed simulated driving under two different conditions (well-rested and sleep-deprived) on different days. During the experiment, we used 68 electrodes for EEG/ECG/EOG and 8 channels for fNIRS recordings. We extracted the prominent features of each modality to distinguish between the well-rested and sleep-deprived conditions, and all multimodal features, except EOG, were combined to quantify mental fatigue during driving. Finally, a novel driving condition level (DCL) was proposed that distinguished clearly between the features of well-rested and sleep-deprived conditions. This proposed DCL measure may be applicable to real-time monitoring of the mental states of vehicle drivers. Further, the combination of methods based on each classifier yielded substantial improvements in the classification accuracy between these two conditions. PMID:27242483

  1. Exploring Neuro-Physiological Correlates of Drivers' Mental Fatigue Caused by Sleep Deprivation Using Simultaneous EEG, ECG, and fNIRS Data.

    PubMed

    Ahn, Sangtae; Nguyen, Thien; Jang, Hyojung; Kim, Jae G; Jun, Sung C

    2016-01-01

    Investigations of the neuro-physiological correlates of mental loads, or states, have attracted significant attention recently, as it is particularly important to evaluate mental fatigue in drivers operating a motor vehicle. In this research, we collected multimodal EEG/ECG/EOG and fNIRS data simultaneously to develop algorithms to explore neuro-physiological correlates of drivers' mental states. Each subject performed simulated driving under two different conditions (well-rested and sleep-deprived) on different days. During the experiment, we used 68 electrodes for EEG/ECG/EOG and 8 channels for fNIRS recordings. We extracted the prominent features of each modality to distinguish between the well-rested and sleep-deprived conditions, and all multimodal features, except EOG, were combined to quantify mental fatigue during driving. Finally, a novel driving condition level (DCL) was proposed that distinguished clearly between the features of well-rested and sleep-deprived conditions. This proposed DCL measure may be applicable to real-time monitoring of the mental states of vehicle drivers. Further, the combination of methods based on each classifier yielded substantial improvements in the classification accuracy between these two conditions.

  2. Noninvasive ECG as a tool for predicting termination of paroxysmal atrial fibrillation.

    PubMed

    Chiarugi, Franco; Varanini, Maurizio; Cantini, Federico; Conforti, Fabrizio; Vrouchos, Giorgos

    2007-08-01

    Atrial fibrillation (AF) is the most common cardiac arrhythmia and entails an increased risk of thromboembolic events. Prediction of the termination of an AF episode, based on noninvasive techniques, can benefit patients, doctors and health systems. The method described in this paper is based on two-lead surface electrocardiograms (ECGs): 1-min ECG recordings of AF episodes including N-type (not terminating within an hour after the end of the record), S-type (terminating 1 min after the end of the record) and T-type (terminating immediately after the end of the record). These records are organised into three learning sets (N, S and T) and two test sets (A and B). Starting from these ECGs, the atrial and ventricular activities were separated using beat classification and class averaged beat subtraction, followed by the evaluation of seven parameters representing atrial or ventricular activity. Stepwise discriminant analysis selected the set including dominant atrial frequency (DAF, index of atrial activity) and average HR (HRmean, index of ventricular activity) as optimal for discrimination between N/T-type episodes. The linear classifier, estimated on the 20 cases of the N and T learning sets, provided a performance of 90% on the 30 cases of a test set for the N/T-type discrimination. The same classifier led to correct classification in 89% of the 46 cases for N/S-type discrimination. The method has shown good results and seems to be suitable for clinical application, although a larger dataset would be very useful for improvement and validation of the algorithms and the development of an earlier predictor of paroxysmal AF spontaneous termination time.

  3. Irreversible Electroporation Near the Heart: Ventricular Arrhythmias Can Be Prevented With ECG Synchronization

    PubMed Central

    Deodhar, Ajita; Dickfeld, Timm; Single, Gordon W.; Hamilton, William C.; Thornton, Raymond H.; Sofocleous, Constantinos T.; Maybody, Majid; Gónen, Mithat; Rubinsky, Boris; Solomon, Stephen B.

    2013-01-01

    OBJECTIVE Irreversible electroporation is a nonthermal ablative tool that uses direct electrical pulses to create irreversible membrane pores and cell death. The ablation zone is surrounded by a zone of reversibly increased permeability; either zone can cause cardiac arrhythmias. Our purpose was to establish a safety profile for the use of irreversible electroporation close to the heart. MATERIALS and METHODS The effect of unsynchronized and synchronized (with the R wave on ECG) irreversible electroporation in swine lung and myocardium was studied in 11 pigs. Twelve lead ECG recordings were analyzed by an electrophysiologist for the presence of arrhythmia. Ventricular arrhythmias were categorized as major events. Minor events included all other dysrhythmias or ECG changes. Cardiac and lung tissue was submitted for histopathologic analysis. Electrical field modeling was performed to predict the distance from the applicators over which cells show electroporation-induced increased permeability. RESULTS At less than or equal to 1.7 cm from the heart, fatal (major) events occurred with all unsynchronized irreversible electroporation. No major and three minor events were seen with synchronized irreversible electroporation. At more than 1.7 cm from the heart, two minor events occurred with only unsynchronized irreversible electroporation. Electrical field modeling correlates well with the clinical results, revealing increased cell membrane permeability up to 1.7 cm away from the applicators. Complete lung ablation without intervening live cells was seen. No myocardial injury was seen. CONCLUSION Unsynchronized irreversible electroporation close to the heart can cause fatal ventricular arrhythmias. Synchronizing irreversible electroporation pulse delivery with absolute refractory period avoids significant cardiac arrhythmias. PMID:21343484

  4. Clinical physiology of bed rest

    NASA Technical Reports Server (NTRS)

    Greenleaf, John E.

    1993-01-01

    Maintenance of optimal health in humans requires the proper balance between exercise, rest, and sleep as well as time in the upright position. About one-third of a lifetime is spent sleeping; and it is no coincidence that sleeping is performed in the horizontal position, the position in which gravitational influence on the body is minimal. Although enforced bed rest is necessary for the treatment of some ailments, in some cases it has probably been used unwisely. In addition to the lower hydrostatic pressure with the normally dependent regions of the cardiovascular system, body fuid compartments during bed rest in the horizontal body position, and virtual elimination of compression on the long bones of the skeletal system during bed rest (hypogravia), there is often reduction in energy metabolism due to the relative confinement (hypodynamia) and alteration of ambulatory circadian variations in metabolism, body temperature, and many hormonal systems. If patients are also moved to unfamiliar surroundings, they probably experience some feelings of anxiety and some sociopsychological problems. Adaptive physiological responses during bed rest are normal for that environment. They are attempts by the body to reduce unnecessary energy expenditure, to optimize its function, and to enhance its survival potential. Many of the deconditioning responses begin within the first day or two of bed rest; these early responses have prompted physicians to insist upon early resumption of the upright posture and ambulation of bedridden patients.

  5. Rest myocardial perfusion imaging in a patient with atypical chest pain and a nondiagnostic electrocardiogram.

    PubMed

    Grube, Heinrich; Rosenblatt, Jeffrey

    2010-02-01

    ACC/AHA guidelines assign a class I indication for use of myocardial perfusion imaging (MPI) for the evaluation of chest pain in patients with acute coronary syndromes and a nondiagnostic ECG. However, MPI is not a widely used modality for the evaluation of patients who present to the ER with chest pain and an intermediate pretest probability for coronary artery disease.We report a case in which resting MPI was pivotal in diagnosing acute myocardial infarction and expedited the appropriate reperfusion strategy.

  6. PocketECG: A New Noninvasive Method for Continuous and Real-Time ECG Monitoring-Initial Results in Children and Adolescents.

    PubMed

    Bieganowska, Katarzyna; Kaszuba, Agnieszka; Bieganowski, Maciej; Kaczmarek, Krzysztof

    2017-03-01

    Long-term ECG is widely used in diagnosis and assessment of many cardiac symptoms which may be caused by dangerous arrhythmias that sometimes can be difficult to document. The PocketECG system is a new technological solution for a long-term, noninvasive, continuous and real-time ECG monitoring that provides automatic diagnosis of dysrhythmias. ECG data transmission occurs over a mobile network. The goal of this study was to assess the reliability of long-term ECG recordings acquired with the PocketECG system. One hundred and fifteen patients (43 girls and 72 boys) of an average age of 15.5 ± 2.5 years were examined at the Department of Cardiology at the Children's Memorial Health Institute. Two simultaneous 24-h ECG recordings were conducted: one with a Holter monitor and one with the PocketECG system. A linear correlation was demonstrated between the two methods with regard to the recorded QRS complexes [H = 1173.0 (-1946.40; 4838.50) + PocketECG*0.98 (0.94; 1.02)]. Mean diurnal heart rhythms were comparable (p > 0.05) despite the fact that the slowest and the fastest rates were different. The rate of detection for ventricular, supraventricular dysrhythmias and pauses in ventricular rhythm were comparable in both methods. The PocketECG system for continuous and real-time ECG recording is a reliable method for the assessment of heart rhythm and dysrhythmias in children and adolescents.

  7. QRS complex detection in ECG signal for wearable devices.

    PubMed

    Arefin, M Riadh; Tavakolian, Kouhyar; Fazel-Rezai, Reza

    2015-01-01

    This paper presents QRS complex detection algorithm based on dual slope technique, which is suitable for wearable electrocardiogram (ECG) applications. For cardiac patients of different arrhythmias, ECG signals are needed to be monitored over an extensive period of time. Thus, the wearable heart monitoring system needs computationally efficient QRS detection technique with good accuracy. In this paper, a method of QRS detection based on two slopes on both sides of an R peak is presented which is computationally efficient. Based on the slopes, first, a variable measuring steepness is developed, then by introducing an adjustable R-R interval based window and adaptive thresholding techniques, depending on the number of peaks detected in such window, R peaks are detected. The algorithm was evaluated against MIT/BIH arrhythmia database and achieved 99.16% detection rate with sensitivity of 0.9935 and positive predictivity of 0.9981. The method was compared with two widely used R peaks detection algorithms.

  8. Patient ECG recording control for an automatic implantable defibrillator

    NASA Technical Reports Server (NTRS)

    Fountain, Glen H. (Inventor); Lee, Jr., David G. (Inventor); Kitchin, David A. (Inventor)

    1986-01-01

    An implantable automatic defibrillator includes sensors which are placed on or near the patient's heart to detect electrical signals indicative of the physiology of the heart. The signals are digitally converted and stored into a FIFO region of a RAM by operation of a direct memory access (DMA) controller. The DMA controller operates transparently with respect to the microprocessor which is part of the defibrillator. The implantable defibrillator includes a telemetry communications circuit for sending data outbound from the defibrillator to an external device (either a patient controller or a physician's console or other) and a receiver for sensing at least an externally generated patient ECG recording command signal. The patient recording command signal is generated by the hand held patient controller. Upon detection of the patient ECG recording command, DMA copies the contents of the FIFO into a specific region of the RAM.

  9. Using ordinal partition transition networks to analyze ECG data

    NASA Astrophysics Data System (ADS)

    Kulp, Christopher W.; Chobot, Jeremy M.; Freitas, Helena R.; Sprechini, Gene D.

    2016-07-01

    Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patterns. The ordinal patterns form the nodes of the network and edges are defined through the time ordering of the ordinal patterns in the symbolized time series. A network measure, called the mean degree, is computed from each time series-generated network. In addition, the entropy and number of non-occurring ordinal patterns (NFP) is computed for each series. The distribution of mean degrees, entropies, and NFPs for each heart condition studied is compared. A statistically significant difference between healthy patients and several groups of unhealthy patients with varying heart conditions is found for the distributions of the mean degrees, unlike for any of the distributions of the entropies or NFPs.

  10. [Changes in ECG examination of patients with trichinosis].

    PubMed

    Siwak, E; Droń, D; Pancewicz, S; Zajkowska, J; Snarska, I; Szpakowicz, T; Januszkiewicz, E

    1994-07-01

    In the years 1963-1992, 560 patients with the diagnosis of trichinosis were treated in the Department of Parasitic Diseases and Neuroinfections, including 310 women (55.3%) and 250 men (44.7%) aged from 6 to 75 years. Out of this number of patients in 59 cases (10.5%) myocardial damage was found in the course of the disease. The most frequently found changes in ECG record were ventricular repolarization disturbances (66.1%) which persisted in 18.6% of cases before discharge from the hospital. Depolarization disturbances accounted for 32.2% of cases and persisted before discharge from the hospital in 10.1% of patients. In 6.7% of patients, persistence of pathological ECG record was found during the 4th month after the hospitalization which may be an evidence of prolongation of the inflammatory process within the myocardium.

  11. Using ordinal partition transition networks to analyze ECG data.

    PubMed

    Kulp, Christopher W; Chobot, Jeremy M; Freitas, Helena R; Sprechini, Gene D

    2016-07-01

    Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patterns. The ordinal patterns form the nodes of the network and edges are defined through the time ordering of the ordinal patterns in the symbolized time series. A network measure, called the mean degree, is computed from each time series-generated network. In addition, the entropy and number of non-occurring ordinal patterns (NFP) is computed for each series. The distribution of mean degrees, entropies, and NFPs for each heart condition studied is compared. A statistically significant difference between healthy patients and several groups of unhealthy patients with varying heart conditions is found for the distributions of the mean degrees, unlike for any of the distributions of the entropies or NFPs.

  12. [Development of a portable dynamic state ECG based on DSP].

    PubMed

    Song, Li; Meng, Qing-jian; Zhang, Guang-yu; Cao, Wei-fang

    2009-11-01

    The Portable dynamic state electrocardiogram collecting system is introduced by using TMS302VC5402, TLC320AD50C, liquid crystal display model, and so on. This dissertation describes the work principle of the system and uses the united algorithm based on wavelet to identify and locate the ECG characteristic waves. This system has as follows of advantages: big memory, low noise,high common mode rejection ratio, the low power consume,the long record time etc.

  13. Discussion of "Computational Electrocardiography: Revisiting Holter ECG Monitoring".

    PubMed

    Baumgartner, Christian; Caiani, Enrico G; Dickhaus, Hartmut; Kulikowski, Casimir A; Schiecke, Karin; van Bemmel, Jan H; Witte, Herbert

    2016-08-05

    This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Computational Electrocardiography: Revisiting Holter ECG Monitoring" written by Thomas M. Deserno and Nikolaus Marx. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Deserno and Marx. In subsequent issues the discussion can continue through letters to the editor.

  14. Real-time ECG transmission via Internet for nonclinical applications.

    PubMed

    Hernández, A I; Mora, F; Villegas, G; Passariello, G; Carrault, G

    2001-09-01

    Telemedicine is producing a great impact in the monitoring of patients located in remote nonclinical environments such as homes, elder communities, gymnasiums, schools, remote military bases, ships, and the like. A number of applications, ranging from data collection, to chronic patient surveillance, and even to the control of therapeutic procedures, are being implemented in many parts of the world. As part of this growing trend, this paper discusses the problems in electrocardiogram (ECG) real-time data acquisition, transmission, and visualization over the Internet. ECG signals are transmitted in real time from a patient in a remote nonclinical environment to the specialist in a hospital or clinic using the current capabilities and availability of the Internet. A prototype system is composed of a portable data acquisition and preprocessing module connected to the computer in the remote site via its RS-232 port, a Java-based client-server platform, and software modules to handle communication protocols between data acquisition module and the patient's personal computer, and to handle client-server communication. The purpose of the system is the provision of extended monitoring for patients under drug therapy after infarction, data collection in some particular cases, remote consultation, and low-cost ECG monitoring for the elderly.

  15. Compressive sensing exploiting wavelet-domain dependencies for ECG compression

    NASA Astrophysics Data System (ADS)

    Polania, Luisa F.; Carrillo, Rafael E.; Blanco-Velasco, Manuel; Barner, Kenneth E.

    2012-06-01

    Compressive sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist sampling of sparse signals. Extensive previous work has exploited the sparse representation of ECG signals in compression applications. In this paper, we propose the use of wavelet domain dependencies to further reduce the number of samples in compressive sensing-based ECG compression while decreasing the computational complexity. R wave events manifest themselves as chains of large coefficients propagating across scales to form a connected subtree of the wavelet coefficient tree. We show that the incorporation of this connectedness as additional prior information into a modified version of the CoSaMP algorithm can significantly reduce the required number of samples to achieve good quality in the reconstruction. This approach also allows more control over the ECG signal reconstruction, in particular, the QRS complex, which is typically distorted when prior information is not included in the recovery. The compression algorithm was tested upon records selected from the MIT-BIH arrhythmia database. Simulation results show that the proposed algorithm leads to high compression ratios associated with low distortion levels relative to state-of-the-art compression algorithms.

  16. Extended Kalman smoother with differential evolution technique for denoising of ECG signal.

    PubMed

    Panigrahy, D; Sahu, P K

    2016-09-01

    Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.

  17. Capacitive ECG system with direct access to standard leads and body surface potential mapping.

    PubMed

    Oehler, Martin; Schilling, Meinhard; Esperer, Hans Dieter

    2009-12-01

    Capacitive electrodes provide the same access to the human electrocardiogram (ECG) as galvanic electrodes, but without the need of direct electrical skin contact and even through layers of clothing. Thus, potential artifacts as a result of poor electrode contact to the skin are avoided and preparation time is significantly reduced. Our system integrates such capacitive electrodes in a 15 sensor array, which is combined with a Tablet PC. This integrated lightweight ECG system (cECG) is easy to place on the chest wall and allows for simultaneous recordings of 14 ECG channels, even if the patient is slightly dressed, e.g., with a t-shirt. In this paper, we present preliminary results on the performance of the cECG regarding the capability of recording body surface potential maps (BSPMs) and obtaining reconstructed standard ECG leads including Einthoven, Goldberger and, with some limitations, Wilson leads. All signals were measured having the subject lie in a supine position and wear a cotton shirt. Signal quality and diagnostic ECG information of the extracted leads are compared with standard ECG measurements. The results show a very close correlation between both types of ECG measurements. It is concluded that the cECG lends itself to rapid screening in clinically unstable patients.

  18. An optimized DSP implementation of adaptive filtering and ICA for motion artifact reduction in ambulatory ECG monitoring.

    PubMed

    Berset, Torfinn; Geng, Di; Romero, Iñaki

    2012-01-01

    Noise from motion artifacts is currently one of the main challenges in the field of ambulatory ECG recording. To address this problem, we propose the use of two different approaches. First, an adaptive filter with electrode-skin impedance as a reference signal is described. Secondly, a multi-channel ECG algorithm based on Independent Component Analysis is introduced. Both algorithms have been designed and further optimized for real-time work embedded in a dedicated Digital Signal Processor. We show that both algorithms improve the performance of a beat detection algorithm when applied in high noise conditions. In addition, an efficient way of choosing this methods is suggested with the aim of reduce the overall total system power consumption.

  19. Prognostic Role of Ventricular Ectopic Beats in Systemic Sclerosis: A Prospective Cohort Study Shows ECG Indexes Predicting the Worse Outcome

    PubMed Central

    Gabrielli, Francesca Augusta; Berardi, Giorgia; Parisi, Federico; Rucco, Manuela; Canestrari, Giovanni; Loperfido, Francesco; Galiuto, Leonarda; Crea, Filippo; Ferraccioli, Gianfranco

    2016-01-01

    Background Arrhythmias are frequent in Systemic Sclerosis (SSc) and portend a bad prognosis, accounting alone for 6% of total deaths. Many of these patients die suddenly, thus prevention and intensified risk-stratification represent unmet medical needs. The major goal of this study was the definition of ECG indexes of poor prognosis. Methods We performed a prospective cohort study to define the role of 24h-ECG-Holter as an additional risk-stratification technique in the identification of SSc-patients at high risk of life-threatening arrhythmias and sudden cardiac death (SCD). One-hundred SSc-patients with symptoms and/or signs suggestive of cardiac involvement underwent 24h-ECG-Holter. The primary end-point was a composite of SCD or need for implantable cardioverter defibrillator (ICD). Results Fifty-six patients (56%) had 24h-ECG-Holter abnormalities and 24(24%) presented frequent ventricular ectopic beats (VEBs). The number of VEBs correlated with high-sensitive cardiac troponin T (hs-cTnT) levels and inversely correlated with left-ventricular ejection fraction (LV-EF) on echocardiography. During a mean follow-up of 23.1±16.0 months, 5 patients died suddenly and two required ICD-implantation. The 7 patients who met the composite end-point had a higher number of VEBs, higher levels of hs-cTnT and NT-proBNP and lower LV-EF (p = 0.001 for all correlations). All these 7 patients had frequent VEBs, while LV-EF was not reduced in all and its range was wide. At ROC curve, VEBs>1190/24h showed 100% of sensitivity and 83% of specificity to predict the primary end-point (AUROC = 0.92,p<0.0001). Patients with VEBS>1190/24h had lower LV-EF and higher hs-cTnT levels and, at multivariate analysis, the presence of increased hs-cTnT and of right bundle branch block on ECG emerged as independent predictors of VEBs>1190/24h. None of demographic or disease-related characteristics emerged as predictors of poor outcome. Conclusions VEBS>1190/24h identify patients at high risk of

  20. Developing new predictive alarms based on ECG metrics for bradyasystolic cardiac arrest.

    PubMed

    Ding, Quan; Bai, Yong; Tinoco, Adelita; Mortara, David; Do, Duc; Boyle, Noel G; Pelter, Michele M; Hu, Xiao

    2015-12-01

    We investigated 17 metrics derived from four leads of electrocardiographic (ECG) signals from hospital patient monitors to develop new ECG alarms for predicting adult bradyasystolic cardiac arrest events.A retrospective case-control study was designed to analyze 17 ECG metrics from 27 adult bradyasystolic and 304 control patients. The 17 metrics consisted of PR interval (PR), P-wave duration (Pdur), QRS duration (QRSdur), RR interval (RR), QT interval (QT), estimate of serum K  +  using only frontal leads (SerumK2), T-wave complexity (T Complex), ST segment levels for leads I, II, V (ST I, ST II, ST V), and 7 heart rate variability (HRV) metrics. These 7 HRV metrics were standard deviation of normal to normal intervals (SDNN), total power, very low frequency power, low frequency power, high frequency power, normalized low frequency power, and normalized high frequency power. Controls were matched by gender, age (±5 years), admission to the same hospital unit within the same month, and the same major diagnostic category. A research ECG analysis software program developed by co-author D M was used to automatically extract the metrics. The absolute value for each ECG metric, and the duration, terminal value, and slope of the dominant trend for each ECG metric, were derived and tested as the alarm conditions. The maximal true positive rate (TPR) of detecting cardiac arrest at a prescribed maximal false positive rate (FPR) based on the trending conditions was reported. Lead time was also recorded as the time between the first time alarm condition was triggered and the event of cardiac arrest.While conditions based on the absolute values of ECG metrics do not provide discriminative information to predict bradyasystolic cardiac arrest, the trending conditions can be useful. For example, with a max FPR  =  5.0%, some derived alarms conditions are: trend duration of PR  >  2.8 h (TPR  =  48.2%, lead time  =  10.0  ±  6.6

  1. Detection of segments with fetal QRS complex from abdominal maternal ECG recordings using support vector machine

    NASA Astrophysics Data System (ADS)

    Delgado, Juan A.; Altuve, Miguel; Nabhan Homsi, Masun

    2015-12-01

    This paper introduces a robust method based on the Support Vector Machine (SVM) algorithm to detect the presence of Fetal QRS (fQRS) complexes in electrocardiogram (ECG) recordings provided by the PhysioNet/CinC challenge 2013. ECG signals are first segmented into contiguous frames of 250 ms duration and then labeled in six classes. Fetal segments are tagged according to the position of fQRS complex within each one. Next, segment features extraction and dimensionality reduction are obtained by applying principal component analysis on Haar-wavelet transform. After that, two sub-datasets are generated to separate representative segments from atypical ones. Imbalanced class problem is dealt by applying sampling without replacement on each sub-dataset. Finally, two SVMs are trained and cross-validated using the two balanced sub-datasets separately. Experimental results show that the proposed approach achieves high performance rates in fetal heartbeats detection that reach up to 90.95% of accuracy, 92.16% of sensitivity, 88.51% of specificity, 94.13% of positive predictive value and 84.96% of negative predictive value. A comparative study is also carried out to show the performance of other two machine learning algorithms for fQRS complex estimation, which are K-nearest neighborhood and Bayesian network.

  2. ECG on the road: robust and unobtrusive estimation of heart rate.

    PubMed

    Wartzek, Tobias; Eilebrecht, Benjamin; Lem, Jeroen; Lindner, Hans-Joachim; Leonhardt, Steffen; Walter, Marian

    2011-11-01

    Modern automobiles include an increasing number of assistance systems to increase the driver's safety. This feasibility study investigated unobtrusive capacitive ECG measurements in an automotive environment. Electrodes integrated into the driving seat allowed to measure a reliable ECG in 86% of the drivers; when only (light) cotton clothing was worn by the drivers, this value increased to 95%. Results show that an array of sensors is needed that can adapt to the different drivers and sitting positions. Measurements while driving show that traveling on the highway does not distort the signal any more than with the car engine turned OFF, whereas driving in city traffic results in a lowered detection rate due to the driver's heavier movements. To enable robust and reliable estimation of heart rate, an algorithm is presented (based on principal component analysis) to detect and discard time intervals with artifacts. This, then, allows a reliable estimation of heart rate of up to 61% in city traffic and up to 86% on the highway: as a percentage of the total driving period with at least four consecutive QRS complexes.

  3. Information Flow Between Resting-State Networks

    PubMed Central

    Diez, Ibai; Erramuzpe, Asier; Escudero, Iñaki; Mateos, Beatriz; Cabrera, Alberto; Marinazzo, Daniele; Sanz-Arigita, Ernesto J.; Stramaglia, Sebastiano

    2015-01-01

    Abstract The resting brain dynamics self-organize into a finite number of correlated patterns known as resting-state networks (RSNs). It is well known that techniques such as independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method to compute the information flow (IF) between different RSNs from resting-state magnetic resonance imaging. After hemodynamic response function blind deconvolution of all voxel signals, and under the hypothesis that RSNs define regions of interest, our method first uses principal component analysis to reduce dimensionality in each RSN to next compute IF (estimated here in terms of transfer entropy) between the different RSNs by systematically increasing k (the number of principal components used in the calculation). When k=1, this method is equivalent to computing IF using the average of all voxel activities in each RSN. For k≥1, our method calculates the k multivariate IF between the different RSNs. We find that the average IF among RSNs is dimension dependent, increasing from k=1 (i.e., the average voxel activity) up to a maximum occurring at k=5 and to finally decay to zero for k≥10. This suggests that a small number of components (close to five) is sufficient to describe the IF pattern between RSNs. Our method—addressing differences in IF between RSNs for any generic data—can be used for group comparison in health or disease. To illustrate this, we have calculated the inter-RSN IF in a data set of Alzheimer's disease (AD) to find that the most significant differences between AD and controls occurred for k=2, in addition to AD showing increased IF w.r.t. controls. The spatial localization of the k=2 component, within RSNs, allows the characterization of IF differences between AD and controls. PMID:26177254

  4. [Rest for safety: which stakes?].

    PubMed

    Mion, G; Ricouard, S

    2007-01-01

    In 2003 were promulgated the texts regulating rest and safety, in the USA (approved by the ACGME) and in France (January 9th, 2001 and September 14th, 2001). The institution of the "rest for safety", an eleven hours duration interruption of activity, immediately after a night-call, can be viewed as a progress in the search for safety. Several studies showed a link between excessive work hours and occurrence of medical incidents related to tiredness. However published data do not show a link between tiredness and patients endangering. The tiredness resulting from sleep deprivation and disturbances in circadian rhythms is a cumulative phenomenon erased by a period of rest. In spite of a large individual variability, tiredness increases anxiety scores, irritability, depression and it deteriorates cognitive performances. The concept of "prophylactic" rest considers that a subject cannot start, rested, a work if he did not sleep at least 5 hours the previous night, or 12 hours during the previous 48 hours. The second important aspect of the rest for safety is the long-term prevention of potential pathologies in medical staff, in particular burnout syndrome. In our profession, night calls are considered most stressful; the psychological stress related to anticipation and night context causes measurable cardiovascular disturbances in anesthesiologists. Shift-work sleep disorders may induce gastric ulcers, heart attacks, metabolic syndrome, depression and accidents related to somnolence. Long duration work-hours, accompanied by sleep deprivation, may double the risk of car accidents in junior physicians, in whom vigilance levels can compare with those of patients concerned by narcolepsy or with the cognitive disturbances induced by alcohol intoxication. Reduced work-hours improve vigilance and divide by three the rate of serious medical errors. True opportunities of sleep and control of sleep duration at the individual level could be suggested. The idea that taking the

  5. Noise and baseline wandering suppression of ECG signals by morphological filter.

    PubMed

    Taouli, S A; Bereksi-Reguig, F

    2010-02-01

    Electrocardiogram (ECG) signals describe the electrical activity of the heart, and are universally by physicists in the diagnosis of cardiac pathologies. However, during the acquisition of ECGs they are often contaminated with different sources of noise, making interpretation difficult. Different techniques have been used to filter the ECG signal, in order to optimize the signal to noise ratio (S/N). In this paper, an approach based on morphological filtering is developed in order to filter the ECG. Morphological filtering is concerned with the detection of the ECG morphology, therefore allowing the suppression of noises and particularly baseline wandering. The implemented filter is evaluated using signals taken from the MIT-BIH ECG universal database. The results show that the performance of this filter is good compared with other filtering techniques.

  6. Software design of a remote real-time ECG monitoring system

    NASA Astrophysics Data System (ADS)

    Yu, Chengbo; Tao, Hongyan

    2005-12-01

    Heart disease is one of the main diseases that threaten the health and lives of human beings. At present, the normal remote ECG monitoring system has the disadvantages of a short testing distance and limitation of monitoring lines. Because of accident and paroxysmal disease, ECG monitoring has extended from the hospital to the family. Therefore, remote ECG monitoring through the Internet has the actual value and significance. The principle and design method of software of the remote dynamic ECG monitor was presented and discussed. The monitoring software is programmed with Delphi software based on client-sever interactive mode. The application program of the system, which makes use of multithreading technology, is shown to perform in an excellent manner. The program includes remote link users and ECG processing, i.e. ECG data's receiving, real-time displaying, recording and replaying. The system can connect many clients simultaneously and perform real-time monitoring to patients.

  7. Abnormal regional homogeneity as potential imaging biomarker for psychosis risk syndrome: a resting-state fMRI study and support vector machine analysis

    PubMed Central

    Wang, Shuai; Wang, Guodong; Lv, Hailong; Wu, Renrong; Zhao, Jingping; Guo, Wenbin

    2016-01-01

    Subjects with psychosis risk syndrome (PRS) have structural and functional abnormalities in several brain regions. However, regional functional synchronization of PRS has not been clarified. We recruited 34 PRS subjects and 37 healthy controls. Regional homogeneity (ReHo) of resting-state functional magnetic resonance scans was employed to analyze regional functional synchronization in these participants. Receiver operating characteristic curves and support vector machines were used to detect whether abnormal regional functional synchronization could be utilized to separate PRS subjects from healthy controls. We observed that PRS subjects showed significant ReHo decreases in the left inferior temporal gyrus and increases in the right inferior frontal gyrus and right putamen compared with the controls. No correlations between abnormal regional functional synchronization in these brain regions and clinical characteristics existed. A combination of the ReHo values in the three brain regions showed sensitivity, specificity, and accuracy of 88.24%, 91.89%, and 90.14%, respectively, for discriminating PRS subjects from healthy controls. We inferred that abnormal regional functional synchronization exists in the cerebrum of PRS subjects, and a combination of ReHo values in these abnormal regions could be applied as potential image biomarker to identify PRS subjects from healthy controls. PMID:27272341

  8. Semi-analytical approach for free vibration analysis of cracked beams resting on two-parameter elastic foundation with elastically restrained ends

    NASA Astrophysics Data System (ADS)

    Mirzabeigy, Alborz; Bakhtiari-Nejad, Firooz

    2014-06-01

    In present study, free vibration of cracked beams resting on two-parameter elastic foundation with elastically restrained ends is considered. Euler-Bernoulli beam hypothesis has been applied and translational and rotational elastic springs in each end considered as support. The crack is modeled as a mass-less rotational spring which divides beam into two segments. After governing the equations of motion, the differential transform method (DTM) has been served to determine dimensionless frequencies and normalized mode shapes. DTM is a semi-analytical approach based on Taylor expansion series that converts differential equations to recursive algebraic equations. The DTM results for the natural frequencies in special cases are in very good agreement with results reported by well-known references. Also, the DTM procedure yields rapid convergence beside high accuracy without any frequency missing. Comprehensive studies to analyze the effects of crack location, crack severity, parameters of elastic foundation and boundary conditions on dimensionless frequencies as well as effects of elastic boundary conditions on cracked beams mode shapes are carried out and some problems handled for first time in this paper. Since this paper deals with general problem, the derived formulation has capability for analyzing free vibration of cracked beam with every boundary condition.

  9. On the improved correlative prediction scheme for aliased electrocardiogram (ECG) data compression.

    PubMed

    Gao, Xin

    2012-01-01

    An improved scheme for aliased electrocardiogram (ECG) data compression has been constructed, where the predictor exploits the correlative characteristics of adjacent QRS waveforms. The twin-R correlation prediction and lifting wavelet transform (LWT) for periodical ECG waves exhibits feasibility and high efficiency to achieve lower distortion rates with realizable compression ratio (CR); grey predictions via GM(1, 1) model have been adopted to evaluate the parametric performance for ECG data compression. Simulation results illuminate the validity of our approach.

  10. Development of a portable wireless system for bipolar concentric ECG recording

    NASA Astrophysics Data System (ADS)

    Prats-Boluda, G.; Ye-Lin, Y.; Bueno Barrachina, J. M.; Senent, E.; Rodriguez de Sanabria, R.; Garcia-Casado, J.

    2015-07-01

    Cardiovascular diseases (CVDs) remain the biggest cause of deaths worldwide. ECG monitoring is a key tool for early diagnosis of CVDs. Conventional monitors use monopolar electrodes resulting in poor spatial resolution surface recordings and requiring extensive wiring. High-spatial resolution surface electrocardiographic recordings provide valuable information for the diagnosis of a wide range of cardiac abnormalities, including infarction and arrhythmia. The aim of this work was to develop and test a wireless recording system for acquiring high spatial resolution ECG signals, based on a flexible tripolar concentric electrode (TCE) without cable wiring or external reference electrode which would make more comnfortable its use in clinical practice. For this, a portable, wireless sensor node for analogue conditioning, digitalization and transmission of a bipolar concentric ECG signal (BC-ECG) using a TCE and a Mason-likar Lead-I ECG (ML-Lead-I ECG) signal was developed. Experimental results from a total of 32 healthy volunteers showed that the ECG fiducial points in the BC-ECG signals, recorded with external and internal reference electrode, are consistent with those of simultaneous ML-Lead-I ECG. No statistically significant difference was found in either signal amplitude or morphology, regardless of the reference electrode used, being the signal-to-noise similar to that of ML-Lead-I ECG. Furthermore, it has been observed that BC-ECG signals contain information that could not available in conventional records, specially related to atria activity. The proposed wireless sensor node provides non-invasive high-local resolution ECG signals using only a TCE without additional wiring, which would have great potential in medical diagnosis of diseases such as atrial or ventricular fibrillations or arrhythmias that currently require invasive diagnostic procedures (catheterization).

  11. The NASA Bed Rest Project

    NASA Technical Reports Server (NTRS)

    Rhodes, Bradley; Meck, Janice

    2005-01-01

    NASA s National Vision for Space Exploration includes human travel beyond low earth orbit and the ultimate safe return of the crews. Crucial to fulfilling the vision is the successful and timely development of countermeasures for the adverse physiological effects on human systems caused by long term exposure to the microgravity environment. Limited access to in-flight resources for the foreseeable future increases NASA s reliance on ground-based analogs to simulate these effects of microgravity. The primary analog for human based research will be head-down bed rest. By this approach NASA will be able to evaluate countermeasures in large sample sizes, perform preliminary evaluations of proposed in-flight protocols and assess the utility of individual or combined strategies before flight resources are requested. In response to this critical need, NASA has created the Bed Rest Project at the Johnson Space Center. The Project establishes the infrastructure and processes to provide a long term capability for standardized domestic bed rest studies and countermeasure development. The Bed Rest Project design takes a comprehensive, interdisciplinary, integrated approach that reduces the resource overhead of one investigator for one campaign. In addition to integrating studies operationally relevant for exploration, the Project addresses other new Vision objectives, namely: 1) interagency cooperation with the NIH allows for Clinical Research Center (CRC) facility sharing to the benefit of both agencies, 2) collaboration with our International Partners expands countermeasure development opportunities for foreign and domestic investigators as well as promotes consistency in approach and results, 3) to the greatest degree possible, the Project also advances research by clinicians and academia alike to encourage return to earth benefits. This paper will describe the Project s top level goals, organization and relationship to other Exploration Vision Projects, implementation

  12. Wavelet-based ECG compression by bit-field preserving and running length encoding.

    PubMed

    Chan, Hsiao-Lung; Siao, You-Chen; Chen, Szi-Wen; Yu, Shih-Fan

    2008-04-01

    Efficient electrocardiogram (ECG) compression can reduce the payload of real-time ECG transmission as well as reduce the amount of data storage in long-term ECG recording. In this paper an ECG compression/decompression architecture based on the bit-field preserving (BFP) and running length encoding (RLE)/decoding schemes incorporated with the discrete wavelet transform (DWT) is proposed. Compared to complex and repetitive manipulations in the set partitioning in hierarchical tree (SPIHT) coding and the vector quantization (VQ), the proposed algorithm has advantages of simple manipulations and a feedforward structure that would be suitable to implement on very-large-scale integrated circuits and general microcontrollers.

  13. ECG De-noising: A comparison between EEMD-BLMS and DWT-NN algorithms.

    PubMed

    Kærgaard, Kevin; Jensen, Søren Hjøllund; Puthusserypady, Sadasivan

    2015-08-01

    Electrocardiogram (ECG) is a widely used non-invasive method to study the rhythmic activity of the heart and thereby to detect the abnormalities. However, these signals are often obscured by artifacts from various sources and minimization of these artifacts are of paramount important. This paper proposes two adaptive techniques, namely the EEMD-BLMS (Ensemble Empirical Mode Decomposition in conjunction with the Block Least Mean Square algorithm) and DWT-NN (Discrete Wavelet Transform followed by Neural Network) methods in minimizing the artifacts from recorded ECG signals, and compares their performance. These methods were first compared on two types of simulated noise corrupted ECG signals: Type-I (desired ECG+noise frequencies outside the ECG frequency band) and Type-II (ECG+noise frequencies both inside and outside the ECG frequency band). Subsequently, they were tested on real ECG recordings. Results clearly show that both the methods works equally well when used on Type-I signals. However, on Type-II signals the DWT-NN performed better. In the case of real ECG data, though both methods performed similar, the DWT-NN method was a slightly better in terms of minimizing the high frequency artifacts.

  14. A Low Power Linear Phase Digital FIR Filter for Wearable ECG Devices.

    PubMed

    Lian, Yong; Yu, Jianghong

    2005-01-01

    In this paper we present a low power linear phase digital FIR filter which is a part of an ECG-on-Chip. The ECG-on-Chip can be embedded into clothing to acquire the electrocardiogram (ECG) signal and send a warning message to a mobile phone or PDA if an abnormal ECG is detected. The proposed new filter structure significantly reduces the arithmetic operations for each sample which in turn lowers the power consumption. The filter is developed based on the interpolated finite impulse filter technique and is very attractive for a low cost and low power VLSI implementation.

  15. Embedding patients confidential data in ECG signal for healthcare information systems.

    PubMed

    Ibaida, Ayman; Khalil, Ibrahim; Al-Shammary, Dhiah

    2010-01-01

    In Wireless tele-cardiology applications, ECG signal is widely used to monitor cardiac activities of patients. Accordingly, in most e-health applications, ECG signals need to be combined with patient confidential information. Data hiding and watermarking techniques can play a crucial role in ECG wireless tele-monitoring systems by combining the confidential information with the ECG signal since digital ECG data is huge enough to act as host to carry tiny amount of additional secret data. In this paper, a new steganography technique is proposed that helps embed confidential information of patients into specific locations (called special range numbers) of digital ECG host signal that will cause minimal distortion to ECG, and at the same time, any secret information embedded is completely extractable. We show that there are 2.1475 × 10(9) possible special range numbers making it extremely difficult for intruders to identify locations of secret bits. Experiments show that percentage residual difference (PRD) of watermarked ECGs can be as low as 0.0247% and 0.0678% for normal and abnormal ECG segments (taken from MIT-BIH Arrhythmia database) respectively.

  16. The Telemetric and Holter ECG Warehouse (THEW): the first three years of development and research.

    PubMed

    Couderc, Jean-Philippe

    2012-01-01

    The Telemetric and Holter ECG Warehouse (THEW) hosts more than 3700 digital 24-Holter ECG recordings from 13 independent studies. In addition to the ECGs, the repository includes patient information in separate clinical database with content varying according to the study focus. In its third year of activities, the THEW database has been accessed by researchers from 37 universities and 16 corporations located in 16 countries worldwide. Twenty publications were released primarily focusing on the development and validation of ECG-based technologies. This communication describes the content of the databases of the repository with brief summary of the research and development projects completed using these data.

  17. A novel approach to ECG classification based upon two-layered HMMs in body sensor networks.

    PubMed

    Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang

    2014-03-27

    This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen.

  18. Simultaneous powerline interference and baseline wander removal from ECG and EMG signals by sinusoidal modeling.

    PubMed

    Zivanovic, Miroslav; González-Izal, Miriam

    2013-10-01

    We present a compact approach to joint modeling of powerline interference (PLI) and baseline wonder (BW) for denoising of biopotential signals. Both PLI and BW are modeled by a set of harmonically related sinusoids modulated by low-order time polynomials. The sinusoids account on the harmonicity and mean instantaneous frequency of the PLI in the analysis window, while the polynomials capture the frequency and amplitude deviations from their nominal values and characterize the BW at the same time. The resulting model is linear-in-parameters and the solution to the corresponding linear system is estimated in a simple and efficient way through linear least-squares. The proposed modeling method was evaluated on real electrocardiographic (ECG) and electromyographic (EMG) signals against three reference methods for different analysis scenarios. The comparative study suggests that the proposed method outperforms the reference methods in terms of residual interference energy in the denoised biopotential signals.

  19. Cardiac Repolarization Abnormalities and Potential Evidence for Loss of Cardiac Sodium Currents on ECGs of Patients with Chagas' Heart Disease

    NASA Technical Reports Server (NTRS)

    Schlegel, T. T.; Medina, R.; Jugo, D.; Nunez, T. J.; Borrego, A.; Arellano, E.; Arenare, B.; DePalma, J. L.; Greco, E. C.; Starc, V.

    2007-01-01

    Some individuals with Chagas disease develop right precordial lead ST segment elevation in response to an ajmaline challenge test, and the prevalence of right bundle branch block (RBBB) is also high in Chagas disease. Because these same electrocardiographic abnormalities occur in the Brugada syndrome, which involves genetically defective cardiac sodium channels, acquired damage to cardiac sodium channels may also occur in Chagas disease. We studied several conventional and advanced resting 12-lead/derived Frank-lead ECG parameters in 34 patients with Chagas -related heart disease (mean age 39 14 years) and in 34 age-/gender-matched healthy controls. All ECG recordings were of 5-10 min duration, obtained in the supine position using high fidelity hardware/software (CardioSoft, Houston, TX). Even after excluding those Chagas patients who had resting BBBs, tachycardia and/or pathologic arrhythmia (n=8), significant differences remained in multiple conventional and advanced ECG parameters between the Chagas and control groups (n=26/group), especially in their respective QT interval variability indices, maximal spatial QRS-T angles and low frequency HRV powers (p=0.0006, p=0.0015 and p=0.0314 respectively). In relation to the issue of potential damage to cardiac sodium channels, the Chagas patients had: 1) greater than or equal to twice the incidence of resting ST segment elevation in leads V1-V3 (n=10/26 vs. n=5/26) and of both leftward (n=5/26 versus n=0/26) and rightward (n=7/26 versus n=3/26) QRS axis deviation than controls; 2) significantly increased filtered (40-250 Hz) QRS interval durations (92.1 8.5 versus 85.3 plus or minus 9.0 ms, p=0.022) versus controls; and 3) significantly decreased QT and especially JT interval durations versus controls (QT interval: 387.5 plus or minus 26.4 versus 408.9 plus or minus 34.6 ms, p=0.013; JT interval: 290.5 plus or minus 26.3 versus 314.8 plus or minus 31.3 ms; p=0.0029). Heart rates and Bazett-corrected QTc/JTc intervals

  20. Real–Time ECG Algorithms for Ambulatory Patient Monitoring

    PubMed Central

    Pino, Esteban; Ohno–Machado, Lucila; Wiechmann, Eduardo; Curtis, Dorothy

    2005-01-01

    Brigham & Women’s Hospital is designing a wireless monitoring system for patients in the waiting area of the Emergency Department. A real–time ECG algorithm is required to monitor and alert changes in patients that have not yet been admitted to the Emergency Room. For this purpose, three simple algorithms are compared in terms of processing time, beat detection accuracy and heart rate (HR) estimation. Varying amounts of noise were added to records from the MIT-BIH Arrhythmia Database [1] to mimic expected waiting room conditions. Some recommendations regarding selection of an algorithm and further processing of HR series are presented. PMID:16779111

  1. Wearable ECG Based on Impulse-Radio-Type Human Body Communication.

    PubMed

    Wang, Jianqing; Fujiwara, Takuya; Kato, Taku; Anzai, Daisuke

    2016-09-01

    Human body communication (HBC) provides a promising physical layer for wireless body area networks (BANs) in healthcare and medical applications, because of its low propagation loss and high security characteristics. In this study, we have developed a wearable electrocardiogram (ECG) which employs impulse radio (IR)-type HBC technology for transmitting vital signals on the human body in a wearable BAN scenario. The HBC-based wearable ECG has two excellent features. First, the wideband performance of the IR scheme contributed to very low radiation power so that the transceiver is easy to satisfy the extremely weak radio laws, which does not need a license. This feature can provide big convenience in the use and spread of the wearable ECG. Second, the realization of common use of sensing and transmitting electrodes based on time sharing and capacitive coupling largely simplified the HBC-based ECG structure and contributed to its miniaturization. To verify the validity of the HBC-based ECG, we evaluated its communication performance and ECG acquisition performance. The measured bit error rate, smaller than 10 (-3) at 1.25 Mb/s, showed a good physical layer communication performance, and the acquired ECG waveform and various heart-rate variability parameters in time and frequency domains exhibited good agreement with a commercially available radio-frequency ECG and a Holter ECG. These results sufficiently showed the validity and feasibility of the HBC-based ECG for healthcare applications. This should be the first time to have realized a real-time ECG transmission by using the HBC technology.

  2. Presurgical Mapping of the Language Network Using Resting State Functional Connectivity

    PubMed Central

    Tanaka, Naoaki; Stufflebeam, Steven M.

    2016-01-01

    Resting-state functional magnetic resonance imaging (Resting-state fMRI) is a tool for investigating the functional networks that arise during the resting-state of the brain. Recent advances of the resting-state fMRI analysis suggest its feasibility for evaluating language function. The most common clinical application is for presurgical mapping of cortex for a brain tumor or for resective epilespy surgery. In this article, we review the techniques and presurgical applications of resting-state fMRI analysis for language evaluation, and discuss the use in the clinical setting, focusing on planning for neurosurgery. PMID:26848557

  3. Presurgical Mapping of the Language Network Using Resting-state Functional Connectivity.

    PubMed

    Tanaka, Naoaki; Stufflebeam, Steven M

    2016-02-01

    Resting-state functional magnetic resonance imaging (resting-state fMRI) is a tool for investigating the functional networks that arise during the resting state of the brain. Recent advances of the resting-state fMRI analysis suggest its feasibility for evaluating language function. The most common clinical application is for presurgical mapping of cortex for a brain tumor or for resective epilespy surgery. In this article, we review the techniques and presurgical applications of resting-state fMRI analysis for language evaluation, and discuss the use in the clinical setting, focusing on planning for neurosurgery.

  4. Long-Term Continuous Ambulatory ECG Monitors and External Cardiac Loop Recorders for Cardiac Arrhythmia: A Health Technology Assessment

    PubMed Central

    Kabali, Conrad; Xie, Xuanqian; Higgins, Caroline

    2017-01-01

    Background Ambulatory electrocardiography (ECG) monitors are often used to detect cardiac arrhythmia. For patients with symptoms, an external cardiac loop recorder will often be recommended. The improved recording capacity of newer Holter monitors and similar devices, collectively known as longterm continuous ambulatory ECG monitors, suggests that they will perform just as well as, or better than, external loop recorders. This health technology assessment aimed to evaluate the effectiveness, cost-effectiveness, and budget impact of longterm continuous ECG monitors compared with external loop recorders in detecting symptoms of cardiac arrhythmia. Methods Based on our systematic search for studies published up to January 15, 2016, we did not identify any studies directly comparing the clinical effectiveness of longterm continuous ECG monitors and external loop recorders. Therefore, we conducted an indirect comparison, using a 24-hour Holter monitor as a common comparator. We used a meta-regression model to control for bias due to variation in device-wearing time and baseline syncope rate across studies. We conducted a similar systematic search for cost-utility and cost-effectiveness studies comparing the two types of devices; none were found. Finally, we used historical claims data (2006–2014) to estimate the future 5-year budget impact in Ontario, Canada, of continued public funding for both types of longterm ambulatory ECG monitors. Results Our clinical literature search yielded 7,815 non-duplicate citations, of which 12 cohort studies were eligible for indirect comparison. Seven studies assessed the effectiveness of longterm continuous monitors and five assessed external loop recorders. Both types of devices were more effective than a 24-hour Holter monitor, and we found no substantial difference between them in their ability to detect symptoms (risk difference 0.01; 95% confidence interval −0.18, 0.20). Using GRADE for network meta-analysis, we evaluated the

  5. Rest in underperforming elite competitors.

    PubMed Central

    Koutedakis, Y; Budgett, R; Faulmann, L

    1990-01-01

    This study examines the effects of 3-5 weeks of physical rest on selected physical, physiological and psychological parameters obtained from 12 Olympic but latterly underperforming competitors and their matched control subjects. Cardiorespiratory data were directly determined from their work to volitional exhaustion on either a treadmill, cycle, or rowing ergometer. Anaerobic power and capacity were evaluated through modified Wingate tests. For psychometric assessments, the Profile of Mood States (POMS) was used. For the Olympic competitors, one-way analyses of variance (ANOVA) revealed significant increases (p less than 0.05) in body weight, maximum respiratory exchange ratio, maximum oxygen consumption, and heart rate at the anaerobic threshold, following the rest period. There was also a significant reduction in fatigue and mood profile score, and a significant increase in vigour. No significant changes were found in the matched control subjects. The present data show that resting for 3-5 weeks assists underperforming elite competitors to improve their aerobic performance. PMID:2097024

  6. An XML based middleware for ECG format conversion.

    PubMed

    Li, Xuchen; Vojisavljevic, Vuk; Fang, Qiang

    2009-01-01

    With the rapid development of information and communication technologies, various e-health solutions have been proposed. The digitized medical images as well as the mono-dimension medical signals are two major forms of medical information that are stored and manipulated within an electronic medical environment. Though a variety of industrial and international standards such as DICOM and HL7 have been proposed, many proprietary formats are still pervasively used by many Hospital Information System (HIS) and Picture Archiving and Communication System (PACS) vendors. Those proprietary formats are the big hurdle to form a nationwide or even worldwide e-health network. Thus there is an imperative need to solve the medical data integration problem. Moreover, many small clinics, many hospitals in developing countries and some regional hospitals in developed countries, which have limited budget, have been shunned from embracing the latest medical information technologies due to their high costs. In this paper, we propose an XML based middleware which acts as a translation engine to seamlessly integrate clinical ECG data from a variety of proprietary data formats. Furthermore, this ECG translation engine is designed in a way that it can be integrated into an existing PACS to provide a low cost medical information integration and storage solution.

  7. A Mobile Device System for Early Warning of ECG Anomalies

    PubMed Central

    Szczepański, Adam; Saeed, Khalid

    2014-01-01

    With the rapid increase in computational power of mobile devices the amount of ambient intelligence-based smart environment systems has increased greatly in recent years. A proposition of such a solution is described in this paper, namely real time monitoring of an electrocardiogram (ECG) signal during everyday activities for identification of life threatening situations. The paper, being both research and review, describes previous work of the authors, current state of the art in the context of the authors' work and the proposed aforementioned system. Although parts of the solution were described in earlier publications of the authors, the whole concept is presented completely for the first time along with the prototype implementation on mobile device—a Windows 8 tablet with Modern UI. The system has three main purposes. The first goal is the detection of sudden rapid cardiac malfunctions and informing the people in the patient's surroundings, family and friends and the nearest emergency station about the deteriorating health of the monitored person. The second goal is a monitoring of ECG signals under non-clinical conditions to detect anomalies that are typically not found during diagnostic tests. The third goal is to register and analyze repeatable, long-term disturbances in the regular signal and finding their patterns. PMID:24955946

  8. Ubiquitous wireless ECG recording: a powerful tool physicians should embrace.

    PubMed

    Saxon, Leslie A

    2013-04-01

    The use of smart phones has increased dramatically and there are nearly a billion users on 3G and 4G networks worldwide. Nearly 60% of the U.S. population uses smart phones to access the internet, and smart phone sales now surpass those of desktop and laptop computers. The speed of wireless communication technology on 3G and 4G networks and the widespread adoption and use of iOS equipped smart phones (Apple Inc., Cupertino, CA, USA) provide infrastructure for the transmission of wireless biomedical data, including ECG data. These technologies provide an unprecedented opportunity for physicians to continually access data that can be used to detect issues before symptoms occur or to have definitive data when symptoms are present. The technology also greatly empowers and enables the possibility for unprecedented patient participation in their own medical education and health status as well as that of their social network. As patient advocates, physicians and particularly cardiac electrophysiologists should embrace the future and promise of wireless ECG recording, a technology solution that can truly scale across the global population.

  9. Effects of fluorocarbon propellants on respiratory flow and ECG.

    PubMed Central

    Valić, F; Skurić, Z; Bantić, Z; Rudar, M; Hećej, M

    1977-01-01

    Ten subjects were exposed to the propellants freon 11, freon 12, freon 114, to two mixtures of freon 11 and 12 and to a mixture of freon 12 and 114. The length of exposure was 15, 45 or 60 seconds. Maximum expiratory flow-volume (MEF) curves and ECG were recorded before, and intermittently up to 1 hour after, exposure. Breathing level concentrations of propellants during exposure were determined by gas chromatography. All freons induced biphasic reduction of ventilatory capacity on inhalation. The first fall occurred within a few minutes of exposure while the second was delayed 13-30 minutes after exposure. The effects of mixtures were greater than those of individual freons. The relative fall in MEF 75% was more pronounced than that in MEF 50%. No clear-cut pathological changes in ECG were found. Nevertheless, most subjects developed variations in heart rate exceeding those noted before exposure. In a few cases inversion of the T wave, and in one case atrioventricular block, were observed. PMID:871444

  10. CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API.

    PubMed

    Ono, Keiichiro; Muetze, Tanja; Kolishovski, Georgi; Shannon, Paul; Demchak, Barry

    2015-01-01

    As bioinformatic workflows become increasingly complex and involve multiple specialized tools, so does the difficulty of reliably reproducing those workflows. Cytoscape is a critical workflow component for executing network visualization, analysis, and publishing tasks, but it can be operated only manually via a point-and-click user interface. Consequently, Cytoscape-oriented tasks are laborious and often error prone, especially with multistep protocols involving many networks. In this paper, we present the new cyREST Cytoscape app and accompanying harmonization libraries. Together, they improve workflow reproducibility and researcher productivity by enabling popular languages (e.g., Python and R, JavaScript, and C#) and tools (e.g., IPython/Jupyter Notebook and RStudio) to directly define and query networks, and perform network analysis, layouts and renderings. We describe cyREST's API and overall construction, and present Python- and R-based examples that illustrate how Cytoscape can be integrated into large scale data analysis pipelines. cyREST is available in the Cytoscape app store (http://apps.cytoscape.org) where it has been downloaded over 1900 times since its release in late 2014.

  11. Application of Lead Field Theory and Computerized Thorax Modeling for the ECG Inverse Problem

    DTIC Science & Technology

    2007-11-02

    Takano, P. Laarne, J. Malmivuo Ragnar Granit Institute, Tampere University of Technology, Finland Abstract – The ECG inverse problem is a...Performing Organization Name(s) and Address(es) Ragnar Granit Institute, Tampere University of Technology, Finland Performing Organization Report Number...computational load for calculating ECG inverse solutions. ACKNOWLEDGMENTS This work has been kindly supported by The Ragnar Granit Foundation, The

  12. Interactive Videoconference Supported Teaching in Undergraduate Nursing: A Case Study for ECG

    ERIC Educational Resources Information Center

    Celikkan, Ufuk; Senuzun, Fisun; Sari, Dilek; Sahin, Yasar Guneri

    2013-01-01

    This paper describes how interactive videoconference can benefit the Electrocardiography (ECG) skills of undergraduate nursing students. We have implemented a learning system that interactively transfers the visual and practical aspects of ECG from a nursing skills lab into a classroom where the theoretical part of the course is taught. The…

  13. Anomaly Detection using Multi-channel FLAC for Supporting Diagnosis of ECG

    NASA Astrophysics Data System (ADS)

    Ye, Jiaxing; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Otsu, Nobuyuki

    In this paper, we propose an approach for abnormality detection in multi-channel ECG signals. This system serves as front end to detect the irregular sections in ECG signals, where symptoms may be observed. Thereby, the doctor can focus on only the detected suspected symptom sections, ignoring the disease-free parts. Hence the workload of the inspection by the doctors is significantly reduced and the diagnosis efficiency can be sharply improved. For extracting the predominant characteristics of multi-channel ECG signals, we propose multi-channel Fourier local auto-correlations (m-FLAC) features on multi-channel complex spectrograms. The method characterizes the amplitude and phase information as well as temporal dynamics of the multi-channel ECG signal. At the anomaly detection stage, we employ complex subspace method for statistically modeling the normal (healthy) ECG patterns as in one-class learning. Then, we investigate the input ECG signals by measuring its deviation distance to the trained subspace. The ECG sections with disordered spectral distributions can be effectively discerned based on such distance metric. To validate the proposed approach, we conducted experiments on ECG dataset. The experimental results demonstrated the effectiveness of the proposed approach including promising performance and high efficiency, compared to conventional methods.

  14. Interoperability in digital electrocardiography: harmonization of ISO/IEEE x73-PHD and SCP-ECG.

    PubMed

    Trigo, Jesús D; Chiarugi, Franco; Alesanco, Alvaro; Martínez-Espronceda, Miguel; Serrano, Luis; Chronaki, Catherine E; Escayola, Javier; Martínez, Ignacio; García, José

    2010-11-01

    The ISO/IEEE 11073 (x73) family of standards is a reference frame for medical device interoperability. A draft for an ECG device specialization (ISO/IEEE 11073-10406-d02) has already been presented to the Personal Health Device (PHD) Working Group, and the Standard Communications Protocol for Computer-Assisted ElectroCardioGraphy (SCP-ECG) Standard for short-term diagnostic ECGs (EN1064:2005+A1:2007) has recently been approved as part of the x73 family (ISO 11073-91064:2009). These factors suggest the coordinated use of these two standards in foreseeable telecardiology environments, and hence the need to harmonize them. Such harmonization is the subject of this paper. Thus, a mapping of the mandatory attributes defined in the second draft of the ISO/IEEE 11073-10406-d02 and the minimum SCP-ECG fields is presented, and various other capabilities of the SCP-ECG Standard (such as the messaging part) are also analyzed from an x73-PHD point of view. As a result, this paper addresses and analyzes the implications of some inconsistencies in the coordinated use of these two standards. Finally, a proof-of-concept implementation of the draft x73-PHD ECG device specialization is presented, along with the conversion from x73-PHD to SCP-ECG. This paper, therefore, provides recommendations for future implementations of telecardiology systems that are compliant with both x73-PHD and SCP-ECG.

  15. A review on digital ECG formats and the relationships between them.

    PubMed

    Trigo, Jesús Daniel; Alesanco, Alvaro; Martínez, Ignacio; García, José

    2012-05-01

    A plethora of digital ECG formats have been proposed and implemented. This heterogeneity hinders the design and development of interoperable systems and entails critical integration issues for the healthcare information systems. This paper aims at performing a comprehensive overview on the current state of affairs of the interoperable exchange of digital ECG signals. This includes 1) a review on existing digital ECG formats, 2) a collection of applications and cardiology settings using such formats, 3) a compilation of the relationships between such formats, and 4) a reflection on the current situation and foreseeable future of the interoperable exchange of digital ECG signals. The objectives have been approached by completing and updating previous reviews on the topic through appropriate database mining. 39 digital ECG formats, 56 applications, tools or implantation experiences, 47 mappings/converters, and 6 relationships between such formats have been found in the literature. The creation and generalization of a single standardized ECG format is a desirable goal. However, this unification requires political commitment and international cooperation among different standardization bodies. Ongoing ontology-based approaches covering ECG domain have recently emerged as a promising alternative for reaching fully fledged ECG interoperability in the near future.

  16. Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

    PubMed

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2014-01-01

    Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

  17. Rest requirements and rest management of personnel in shift work

    SciTech Connect

    Hammell, B.D.; Scheuerle, A.

    1995-12-31

    A difficulty-weighted shift assignment scheme is proposed for use in prolonged and strenuous field operations such as emergency response, site testing, and short term hazardous waste remediation projects. The purpose of the work rotation plan is to increase productivity, safety, and moral of workers. Job weighting is accomplished by assigning adjustments to the mental and physical intensity of the task, the protective equipment worn, and the climatic conditions. The plan is based on medical studies of sleep deprivation, the effects of rest adjustments, and programs to reduce sleep deprivation and normalize shift schedules.

  18. Pelvic muscles during rest: responses to pelvic muscle exercise.

    PubMed

    Griffin, C; Dougherty, M C; Yarandi, H

    1994-01-01

    The purpose of the research was to study pelvic muscle changes in the resting phase between voluntary contractions (during pelvic muscle assessment) and in response to pelvic muscle exercise (PME) through secondary analysis of data. The sample consisted of healthy women (N = 38) aged 35 to 54. Analysis of variance showed a significant difference in resting pressure within each assessment (F = 2.92, p < .04). A significant difference in resting pressures within subjects was found (F = 3.54, p < .02). Within-subject variance suggests exercises performed without a warmup may result in incomplete relaxation prior to contraction. Significant change between baseline and Level 1 of the graded PME program suggests slow relaxation of untrained muscles. Increases in resting pressure at Levels 3 and 4 may be a more accurate reflection of muscle hypertrophy. The results of this research indicate that care should be taken in establishing the point from which changes during contractions are measured. It is recommended that the resting pressure be used. Exercise continued for more than 3 or 4 weeks accounts for nearly all strength gains and explains the increases in resting pressure at PME Levels 3 and 4.

  19. Resting and Postexercise Heart Rate Detection From Fingertip and Facial Photoplethysmography Using a Smartphone Camera: A Validation Study

    PubMed Central

    Chan, Christy KY; Li, Christien KH; To, Olivia TL; Lai, William HS; Tse, Gary; Poh, Yukkee C; Poh, Ming-Zher

    2017-01-01

    Background Modern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color. Objective The objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app. Methods A total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone’s back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds’ duration each were acquired at rest, and immediately after moderate- (50%-70% maximum HR) and vigorous- (70%-85% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ≤5 beats/min or ≤10%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard. Results We analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44%) than with postmoderate

  20. Relative Amplitude based Features of characteristic ECG-Peaks for Identification of Coronary Artery Disease

    NASA Astrophysics Data System (ADS)

    Gohel, Bakul; Tiwary, U. S.; Lahiri, T.

    Coronary artery disease or Myocardial Infarction is the leading cause of death and disability in the world. ECG is widely used as a cheap diagnostic tool for diagnosis of coronary artery disease but has low sensitivity with the present criteria based on ST-segment, T wave and Q wave changes. So to increase the sensitivity of the ECG we have introduced relative amplitude based new features of characteristic ‘R’ and ‘S’ ECG-peaks between two leads. Relative amplitude based features shows remarkable capability in discriminating Myocardial Infarction and Healthy pattern using backpropogation neural network classifier yield results with 81.82% sensitivity and 81.82% specificity. Also relative amplitude might be an efficient method in minimizing the effect of body composition on ECG amplitude based features without use of any information from other than ECG

  1. Performance of human body communication-based wearable ECG with capacitive coupling electrodes.

    PubMed

    Sakuma, Jun; Anzai, Daisuke; Wang, Jianqing

    2016-09-01

    Wearable electrocardiogram (ECG) is attracting much attention in daily healthcare applications, and human body communication (HBC) technology provides an evident advantage in making the sensing electrodes of ECG also working for transmission through the human body. In view of actual usage in daily life, however, non-contact electrodes to the human body are desirable. In this Letter, the authors discussed the ECG circuit structure in the HBC-based wearable ECG for removing the common mode noise when employing non-contact capacitive coupling electrodes. Through the comparison of experimental results, they have shown that the authors' proposed circuit structure with the third electrode directly connected to signal ground can provide an effect on common mode noise reduction similar to the usual drive-right-leg circuit, and a sufficiently good acquisition performance of ECG signals.

  2. Utility of Electrocardiography (ECG)-Gated Computed Tomography (CT) for Preoperative Evaluations of Thymic Epithelial Tumors

    PubMed Central

    Ozawa, Yoshiyuki; Hara, Masaki; Nakagawa, Motoo; Shibamoto, Yuta

    2016-01-01

    Summary Background Preoperative evaluation of invasion to the adjacent organs is important for the thymic epithelial tumors on CT. The purpose of our study was to evaluate the utility of electrocardiography (ECG)-gated CT for assessing thymic epithelial tumors with regard to the motion artifacts produced and the preoperative diagnostic accuracy of the technique. Material/Methods Forty thymic epithelial tumors (36 thymomas and 4 thymic carcinomas) were examined with ECG-gated contrast-enhanced CT using a dual source scanner. The scan delay after the contrast media injection was 30 s for the non-ECG-gated CT and 100 s for the ECG-gated CT. Two radiologists blindly evaluated both the non-ECG-gated and ECG-gated CT images for motion artifacts and determined whether the tumors had invaded adjacent structures (mediastinal fat, superior vena cava, brachiocephalic veins, aorta, pulmonary artery, pericardium, or lungs) on each image. Motion artifacts were evaluated using a 3-grade scale. Surgical and pathological findings were used as a reference standard for tumor invasion. Results Motion artifacts were significantly reduced for all structures by ECG gating (p=0.0089 for the lungs and p<0.0001 for the other structures). Non-ECG-gated CT and ECG-gated CT demonstrated 79% and 95% accuracy, respectively, during assessments of pericardial invasion (p=0.03). Conclusions ECG-gated CT reduced the severity of motion artifacts and might be useful for preoperative assessment whether thymic epithelial tumors have invaded adjacent structures. PMID:27920842

  3. Resting energy expenditure among Japanese.

    PubMed

    Hosoya, N; Mitsuhashi, F; Sugiyama, M

    2002-10-01

    1. Resting energy expenditure (REE) provides appropriate basic data for the calculation of energy requirements. 2. The REE of 6498 subjects according to sex and age (1 year stratification), with a minimum of 10 subjects per group, was measured systematically using the easy portable calorimeter (Metavine; Vine, Tokyo, Japan). 3. The REE or the REE/kg according to age and sex was observed to obtain the amount of standard deviation (20-25%). 4. The REE/kg for male and female subjects was maintained at a steady level after the age of 15 years and was estimated to be around 29 kcal/kg.

  4. A novel, fully implantable, multichannel biotelemetry system for measurement of blood flow, pressure, ECG, and temperature.

    PubMed

    Axelsson, M; Dang, Q; Pitsillides, K; Munns, S; Hicks, J; Kassab, G S

    2007-03-01

    Biotelemetry provides high-quality data in awake, free-ranging animals without the effects of anesthesia and surgery. Although many biological parameters can be measured using biotelemetry, simultaneous telemetric measurements of pressure and flow have not been available. The objective of this study was to evaluate simultaneous measurements of blood flow, pressure, ECG, and temperature in a fully implantable system. This novel system allows the measurement of up to four channels of blood flow, up to three channels of pressure, and a single channel each of ECG and temperature. The system includes a bidirectional radio-frequency link that allows the implant to send data and accept commands to perform various tasks. The system is controlled by a base station decoder/controller that decodes the data stream sent by the implant into analog signals. The system also converts the data into a digital data stream that can be sent via ethernet to a remote computer for storage and/or analysis. The system was chronically implanted in swine and alligators for up to 5 wk. Both bench and in vivo animal tests were performed to evaluate system performance. Results show that this biotelemetry system is capable of long-term accurate monitoring of simultaneous blood flow and pressure. The system allows, within the room, recordings, since the implant transmission range is between 6 and 10 m, and, with a relay, backpack transmission distance of up to 500 m can be achieved. This system will have significant utility in chronic models of cardiovascular physiology and pathology.

  5. Physiological noise correction using ECG-derived respiratory signals for enhanced mapping of spontaneous neuronal activity with simultaneous EEG-fMRI.

    PubMed

    Abreu, Rodolfo; Nunes, Sandro; Leal, Alberto; Figueiredo, Patrícia

    2016-08-12

    The study of spontaneous brain activity based on BOLD-fMRI may be seriously compromised by the presence of signal fluctuations of non-neuronal origin, most prominently due to cardiac and respiratory mechanisms. Methods used for modeling and correction of the so-called physiological noise usually rely on the concurrent measurement of cardiac and respiratory signals. In simultaneous EEG-fMRI recordings, which are primarily aimed at the study of spontaneous brain activity, the electrocardiogram (ECG) is typically measured as part of the EEG setup but respiratory data are not generally available. Here, we propose to use the ECG-derived respiratory (EDR) signal estimated by Empirical Mode Decomposition (EMD) as a surrogate of the respiratory signal, for retrospective physiological noise correction of typical simultaneous EEG-fMRI data. A physiological noise model based on these physiological signals (P-PNM) complemented with fMRI-derived noise regressors was generated, and evaluated, for 17 simultaneous EEG-fMRI datasets acquired from a group of seven epilepsy patients imaged at 3T. The respiratory components of P-PNM were found to explain BOLD variance significantly in addition to the cardiac components, suggesting that the EDR signal was successfully extracted from the ECG, and P-PNM outperformed an image-based model (I-PNM) in terms of total BOLD variance explained. Further, the impact of the correction using P-PNM on fMRI mapping of patient-specific epileptic networks and the resting-state default mode network (DMN) was assessed in terms of sensitivity and specificity and, when compared with an ICA-based procedure and a standard pre-processing pipeline, P-PNM achieved the best performance. Overall, our results support the feasibility and utility of extracting physiological noise models of the BOLD signal resorting to ECG data exclusively, with substantial impact on the simultaneous EEG-fMRI mapping of resting-state networks, and, most importantly, epileptic networks

  6. Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

    PubMed

    Castaldo, R; Xu, W; Melillo, P; Pecchia, L; Santamaria, L; James, C

    2016-08-01

    Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minutes) HRV has been not. This study aims to detect mental stress using linear and non-linear HRV features extracted from 3 minutes ECG excerpts recorded from 42 university students, during oral examination (stress) and at rest after a vacation. HRV features were then extracted and analyzed according to the literature using validated software tools. Statistical and data mining analysis were then performed on the extracted HRV features. The best performing machine learning method was the C4.5 tree algorithm, which discriminated between stress and rest with sensitivity, specificity and accuracy rate of 78%, 80% and 79% respectively.

  7. Physiology of prolonged bed rest

    NASA Technical Reports Server (NTRS)

    Greenleaf, J. E.

    1988-01-01

    Bed rest has been a normal procedure used by physicians for centuries in the treatment of injury and disease. Exposure of patients to prolonged bed rest in the horizontal position induces adaptive deconditioning responses. While deconditioning responses are appropriate for patients or test subjects in the horizontal position, they usually result in adverse physiological responses (fainting, muscular weakness) when the patient assume the upright posture. These deconditioning responses result from reduction in hydrostatic pressure within the cardiovascular system, virtual elimination of longitudinal pressure on the long bones, some decrease in total body metabolism, changes in diet, and perhaps psychological impact from the different environment. Almost every system in the body is affected. An early stimulus is the cephalic shift of fluid from the legs which increases atrial pressure and induces compensatory responses for fluid and electrolyte redistribution. Without countermeasures, deterioration in strength and muscle function occurs within 1 wk while increased calcium loss may continue for months. Research should also focus on drug and carbohydrate metabolism.

  8. Personalized USB Biosensor Module for Effective ECG Monitoring.

    PubMed

    Sladojević, Srdjan; Arsenović, Marko; Lončar-Turukalo, Tatjana; Sladojević, Miroslava; Ćulibrk, Dubravko

    2016-01-01

    The burden of chronic disease and associated disability present a major threat to financial sustainability of healthcare delivery systems. The need for cost-effective early diagnosis and disease prevention is evident driving the development of personalized home health solutions. The proposed solution presents an easy to use ECG monitoring system. The core hardware component is a biosensor dongle with sensing probes at one end, and micro USB interface at the other end, offering reliable and unobtrusive sensing, preprocessing and storage. An additional component is a smart phone, providing both the biosensor's power supply and an intuitive user application for the real-time data reading. The system usage is simplified, with innovative solutions offering plug and play functionality avoiding additional driver installation. Personalized needs could be met with different sensor combinations enabling adequate monitoring in chronic disease, during physical activity and in the rehabilitation process.

  9. Ambulatory measurement of the ECG T-wave amplitude.

    PubMed

    van Lien, René; Neijts, Melanie; Willemsen, Gonneke; de Geus, Eco J C

    2015-02-01

    Ambulatory recording of the preejection period (PEP) can be used to measure changes in cardiac sympathetic nervous system (SNS) activity under naturalistic conditions. Here, we test the ECG T-wave amplitude (TWA) as an alternative measure, using 24-h ambulatory monitoring of PEP and TWA in a sample of 564 healthy adults. The TWA showed a decrease in response to mental stress and a monotonic decrease from nighttime sleep to daytime sitting and more physically active behaviors. Within-participant changes in TWA were correlated with changes in the PEP across the standardized stressors (r = .42) and the unstandardized naturalistic conditions (mean r = .35). Partialling out changes in heart rate and vagal effects attenuated these correlations, but they remained significant. Ambulatory TWA cannot replace PEP, but simultaneous recording of TWA and PEP provides a more comprehensive picture of changes in cardiac SNS activity in real-life settings.

  10. ECG findings after myocardial infarction in children after Kawasaki disease

    SciTech Connect

    Nakanishi, T.; Takao, A.; Kondoh, C.; Nakazawa, M.; Hiroe, M.; Matsumoto, Y.

    1988-10-01

    Standard 12-lead ECGs were evaluated in 17 children with myocardial infarction and 78 children without myocardial infarction after Kawasaki disease; sensitivity and specificity of the ECG infarction criteria were determined. The presence or absence of myocardial infarction was determined from either clinical examination results (coronary angiography, ventriculography, and thallium-201 myocardial imaging) or autopsy findings. Of seven patients with inferior infarction, abnormally deep Q waves in lead II, III, or aVF were observed in six, but the duration was greater than 0.04 second in only one (14%). The sensitivity and specificity of inferior infarction criteria based on Q wave amplitude were 86% and 97%, respectively. Of eight patients with anterior infarction, seven (88%) had abnormally deep and wide (greater than or equal to 0.04 second) Q waves in anterior chest leads. The sensitivity and specificity of the infarction criteria based on the amplitude and duration of the Q wave were 75% and 99%, respectively. Of seven patients with lateral infarction, Q waves were observed in lead I, aVL, or both in four patients, and in all of these patients Q waves were wider than 0.04 second. In two patients with both inferior and anterior infarction, Q waves were observed only in leads II, III, and aVF; in only one patient were the Q waves wider than 0.04 second. Thus deep Q waves in lead II, III, or aVF that are not wider than 0.04 second may indicate inferior infarction in children. Q waves in lead I, aVL, and chest leads associated with anterolateral infarction are in most instances deep and wide.

  11. Resting Heart Rate and Aortic Stiffness in Normotensive Adults

    PubMed Central

    Logan, Jeongok G.

    2016-01-01

    Background and Objectives Large-artery stiffness is an independent predictor of cardiovascular disease (CVD), and carotid-femoral pulse wave velocity (cfPWV) is considered the gold standard measure of arterial stiffness. A resting heart rate is an easily measured vital sign that is also associated with CVD morbidity and mortality. Previous studies have reported the significant relationship of a resting heart rate with arterial stiffness as measured by cfPWV only in hypertensive subjects; their relationship in nonhypertensive subjects remains unknown. The present study, therefore, examined their relationship in normotensive subjects. Subjects and Methods In 102 healthy Korean Americans between ages 20 and 60 years, their resting heart rate was measured by an automated blood pressure measuring device after a 10 minute rest in the supine position. Arterial stiffness was measured by cfPWV using the SphygmoCor device. Results The mean resting heart rate of participants (mean age, 39.64 years; 59% women) was 61.91 bpm (standard deviation [SD], 9.62 bpm) and mean the cfPWV was 6.99 (SD, 1.14) m/s. A multiple regression