Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

Long-range acoustic detection and localization of blue whale calls in the northeast Pacific Ocean.

PubMed

Stafford, K M; Fox, C G; Clark, D S

1998-12-01

Analysis of acoustic signals recorded from the U.S. Navy's SOund SUrveillance System (SOSUS) was used to detect and locate blue whale (Balaenoptera musculus) calls offshore in the northeast Pacific. The long, low-frequency components of these calls are characteristic of calls recorded in the presence of blue whales elsewhere in the world. Mean values for frequency and time characteristics from field-recorded blue whale calls were used to develop a simple matched filter for detecting such calls in noisy time series. The matched filter was applied to signals from three different SOSUS arrays off the coast of the Pacific Northwest to detect and associate individual calls from the same animal on the different arrays. A U.S. Navy maritime patrol aircraft was directed to an area where blue whale calls had been detected on SOSUS using these methods, and the presence of vocalizing blue whale was confirmed at the site with field recordings from sonobuoys.

Susceptibility study of audio recording devices to electromagnetic stimulations

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

Halligan, Matthew S.; Grant, Steven L.; Beetner, Daryl G.

2014-02-01

Little research has been performed to study how intentional electromagnetic signals may couple into recording devices. An electromagnetic susceptibility study was performed on an analog tape recorder, a digital video camera, a wired computer microphone, and a wireless microphone system to electromagnetic interference. Devices were subjected to electromagnetic stimulations in the frequency range of 1-990 MHz and field strengths up to 4.9 V/m. Carrier and message frequencies of the stimulation signals were swept, and the impacts of device orientation and antenna polarization were explored. Message signals coupled into all devices only when amplitude modulated signals were used as stimulation signals.more » Test conditions that produced maximum sensitivity were highly specific to each device. Only narrow carrier frequency ranges could be used for most devices to couple messages into recordings. A basic detection technique using cross-correlation demonstrated the need for messages to be as long as possible to maximize message detection and minimize detection error. Analysis suggests that detectable signals could be coupled to these recording devices under realistic ambient conditions.« less

Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings.

PubMed

Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild

2013-08-01

This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2006-12-12

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Cellular telephone-based radiation detection instrument

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2011-06-14

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Cellular telephone-based wide-area radiation detection network

DOEpatents

Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

2009-06-09

A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

Acoustic detection of biosonar activity of deep diving odontocetes at Josephine Seamount High Seas Marine Protected Area.

PubMed

Giorli, Giacomo; Au, Whitlow W L; Ou, Hui; Jarvis, Susan; Morrissey, Ronald; Moretti, David

2015-05-01

The temporal occurrence of deep diving cetaceans in the Josephine Seamount High Seas Marine Protected Area (JSHSMPA), south-west Portugal, was monitored using a passive acoustic recorder. The recorder was deployed on 13 May 2010 at a depth of 814 m during the North Atlantic Treaty Organization Centre for Maritime Research and Experimentation cruise "Sirena10" and recovered on 6 June 2010. The recorder was programmed to record 40 s of data every 2 min. Acoustic data analysis, for the detection and classification of echolocation clicks, was performed using automatic detector/classification systems: M3R (Marine Mammal Monitoring on Navy Ranges), a custom matlab program, and an operator-supervised custom matlab program to assess the classification performance of the detector/classification systems. M3R CS-SVM algorithm contains templates to detect beaked whales, sperm whales, blackfish (pilot and false killer whales), and Risso's dolphins. The detections of each group of odontocetes was monitored as a function of time. Blackfish and Risso's dolphins were detected every day, while beaked whales and sperm whales were detected almost every day. The hourly distribution of detections reveals that blackfish and Risso's dolphins were more active at night, while beaked whales and sperm whales were more active during daylight hours.

Presence of nonlinearity in intracranial EEG recordings: detected by Lyapunov exponents

NASA Astrophysics Data System (ADS)

Liu, Chang-Chia; Shiau, Deng-Shan; Chaovalitwongse, W. Art; Pardalos, Panos M.; Sackellares, J. C.

2007-11-01

In this communication, we performed nonlinearity analysis in the EEG signals recorded from patients with temporal lobe epilepsy (TLE). The largest Lyapunov exponent (Lmax) and phase randomization surrogate data technique were employed to form the statistical test. EEG recordings were acquired invasively from three patients in six brain regions (left and right temporal depth, sub-temporal and orbitofrontal) with 28-32 depth electrodes placed in depth and subdural of the brain. All three patients in this study have unilateral epileptic focus region on the right hippocampus(RH). Nonlinearity was detected by comparing the Lmax profiles of the EEG recordings to its surrogates. The nonlinearity was seen in all different states of the patient with the highest found in post-ictal state. Further our results for all patients exhibited higher degree of differences, quantified by paired t-test, in Lmax values between original and its surrogate from EEG signals recorded from epileptic focus regions. The results of this study demonstrated the Lmax is capable to capture spatio-temporal dynamics that may not be able to detect by linear measurements in the intracranial EEG recordings.

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.

Marine mammal tracks from two-hydrophone acoustic recordings made with a glider

NASA Astrophysics Data System (ADS)

Küsel, Elizabeth T.; Munoz, Tessa; Siderius, Martin; Mellinger, David K.; Heimlich, Sara

2017-04-01

A multinational oceanographic and acoustic sea experiment was carried out in the summer of 2014 off the western coast of the island of Sardinia, Mediterranean Sea. During this experiment, an underwater glider fitted with two hydrophones was evaluated as a potential tool for marine mammal population density estimation studies. An acoustic recording system was also tested, comprising an inexpensive, off-the-shelf digital recorder installed inside the glider. Detection and classification of sounds produced by whales and dolphins, and sometimes tracking and localization, are inherent components of population density estimation from passive acoustics recordings. In this work we discuss the equipment used as well as analysis of the data obtained, including detection and estimation of bearing angles. A human analyst identified the presence of sperm whale (Physeter macrocephalus) regular clicks as well as dolphin clicks and whistles. Cross-correlating clicks recorded on both data channels allowed for the estimation of the direction (bearing) of clicks, and realization of animal tracks. Insights from this bearing tracking analysis can aid in population density estimation studies by providing further information (bearings), which can improve estimates.

Temporal analysis of the frequency and duration of low and high streamflow: Years of record needed to characterize streamflow variability

USGS Publications Warehouse

Huh, S.; Dickey, D.A.; Meador, M.R.; Ruhl, K.E.

2005-01-01

A temporal analysis of the number and duration of exceedences of high- and low-flow thresholds was conducted to determine the number of years required to detect a level shift using data from Virginia, North Carolina, and South Carolina. Two methods were used - ordinary least squares assuming a known error variance and generalized least squares without a known error variance. Using ordinary least squares, the mean number of years required to detect a one standard deviation level shift in measures of low-flow variability was 57.2 (28.6 on either side of the break), compared to 40.0 years for measures of high-flow variability. These means become 57.6 and 41.6 when generalized least squares is used. No significant relations between years and elevation or drainage area were detected (P>0.05). Cluster analysis did not suggest geographic patterns in years related to physiography or major hydrologic regions. Referring to the number of observations required to detect a one standard deviation shift as 'characterizing' the variability, it appears that at least 20 years of record on either side of a shift may be necessary to adequately characterize high-flow variability. A longer streamflow record (about 30 years on either side) may be required to characterize low-flow variability. ?? 2005 Elsevier B.V. All rights reserved.

In vivo flow cytometry for blood cell analysis using differential epi-detection of forward scattered light

NASA Astrophysics Data System (ADS)

Paudel, Hari P.; Jung, Yookyung; Raphael, Anthony; Alt, Clemens; Wu, Juwell; Runnels, Judith; Lin, Charles P.

2018-02-01

The present standard of blood cell analysis is an invasive procedure requiring the extraction of patient's blood, followed by ex-vivo analysis using a flow cytometer or a hemocytometer. We are developing a noninvasive optical technique that alleviates the need for blood extraction. For in-vivo blood analysis we need a high speed, high resolution and high contrast label-free imaging technique. In this proceeding report, we reported a label-free method based on differential epi-detection of forward scattered light, a method inspired by Jerome Mertz's oblique back-illumination microscopy (OBM) (Ford et al, Nat. Meth. 9(12) 2012). The differential epi-detection of forward light gives phase contrast image at diffraction-limited resolution. Unlike reflection confocal microscopy (RCM), which detects only sharp refractive index variation and suffers from speckle noise, this technique is suitable for detection of subtle variation of refractive index in biological tissue and it provides the shape and the size of cells. A custom built high speed electronic detection circuit board produces a real-time differential signal which yields image contrast based on phase gradient in the sample. We recorded blood flow in-vivo at 17.2k lines per second in line scan mode, or 30 frames per second (full frame), or 120 frame per second (quarter frame) in frame scan mode. The image contrast and speed of line scan data recording show the potential of the system for noninvasive blood cell analysis.

An application of HOMER and ACMANT for homogenising monthly precipitation records in Ireland

NASA Astrophysics Data System (ADS)

Coll, John; Curley, Mary; Domonkos, Peter; Aguilar, Enric; Walsh, Seamus; Sweeney, John

2015-04-01

Climate change studies based only on raw long-term data are potentially flawed due to the many breaks introduced from non-climatic sources. Consequently, accurate climate data is an essential prerequisite for basing climate related decision making on; and quality controlled, homogenised climate data are becoming integral to European Union Member State efforts to deliver climate services. Ireland has a good repository of monthly precipitation data at approximately 1900 locations stored in the Met Éireann database. The record length at individual precipitation stations varies greatly. However, an audit of the data established the continuous record length at each station and the number of missing months, and based on this two initial subsets of station series (n = 88 and n = 110) were identified for preliminary homogenisation efforts. The HOMER joint detection algorithm was applied to the combined network of these 198 longer station series on an Ireland-wide basis where contiguous intact monthly records ranged from ~40 to 71 years (1941 - 2010). HOMER detected 91 breaks in total in the country-wide series analysis distributed across 63 (~32%) of the 71 year series records analysed. In a separate approach, four sub-series clusters (n = 38 - 61) for the 1950 - 2010 period were used in a parallel analysis applying both ACMANT and HOMER to a regionalised split of the 198 series. By comparison ACMANT detected a considerably higher number of breaks across the four regional series clusters, 238 distributed across 123 (~62%) of the 61 year series records analysed. These preliminary results indicate a relatively high proportion of detected breaks in the series, a situation not generally reflected in observed later 20th century precipitation records across Europe (Domonkos, 2014). However, this elevated ratio of series with detected breaks (~32% in HOMER and ~62% in ACMANT) parallels the break detection rate in a recent analysis of series in the Netherlands (Buishand et al 2013). In the case of Ireland, the climate is even more markedly maritime than that of the Netherlands and the spatial correlations between the Irish series are high (>0.8). Therefore it is likely that both HOMER and ACMANT are detecting relatively small breaks in the series; e.g. the overall range of correction amplitudes derived by HOMER were small and only applied to sections of the corrected series. As Ireland has a relatively dense network of highly correlated station series, we anticipate continued high detection rates as the analysis is extended to incorporate a greater number of station series, and that the ongoing work will quantify the extent of any breaks in Ireland's monthly precipitation series. KEY WORDS: Ireland, precipitation, time series, homogenisation, HOMER, ACMANT. References Buishand, T.A., DeMartino, G., Spreeuw, J.N., Brandsma, T. (2013). Homogeneity of precipitation series in the Netherlands and their trends in the past century. International Journal of Climatology. 33:815-833 Domonkos, P. (2014). Homogenisation of precipitation time series with ACMANT. Theoretical and Applied Climatology. 118:1-2. DOI 10.1007/s00704-014-1298-5.

Analysis of surface EMG baseline for detection of hidden muscle activity

NASA Astrophysics Data System (ADS)

Zhang, Xu; Zhou, Ping

2014-02-01

Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

Analysis of Surface EMG Baseline for Detection of Hidden Muscle Activity

PubMed Central

Zhang, Xu; Zhou, Ping

2014-01-01

Objective This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used respectively. Both analyses were applied to computer simulations of surface EMG baseline with presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance The findings implied presence of hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level. PMID:24445526

GazeParser: an open-source and multiplatform library for low-cost eye tracking and analysis.

PubMed

Sogo, Hiroyuki

2013-09-01

Eye movement analysis is an effective method for research on visual perception and cognition. However, recordings of eye movements present practical difficulties related to the cost of the recording devices and the programming of device controls for use in experiments. GazeParser is an open-source library for low-cost eye tracking and data analysis; it consists of a video-based eyetracker and libraries for data recording and analysis. The libraries are written in Python and can be used in conjunction with PsychoPy and VisionEgg experimental control libraries. Three eye movement experiments are reported on performance tests of GazeParser. These showed that the means and standard deviations for errors in sampling intervals were less than 1 ms. Spatial accuracy ranged from 0.7° to 1.2°, depending on participant. In gap/overlap tasks and antisaccade tasks, the latency and amplitude of the saccades detected by GazeParser agreed with those detected by a commercial eyetracker. These results showed that the GazeParser demonstrates adequate performance for use in psychological experiments.

Molecular detection of Fasciola hepatica in water sources of District Nowshehra Khyber Pakhtunkhwa Pakistan

NASA Astrophysics Data System (ADS)

Khan, Imran; Khan, Amir Muhammad; Ayaz, Khan, Sanaullah; Anees, Muhammad; Khan, Shaukat Ali

2012-12-01

Fascioliasis is spread through contamination of water sources and cause morbidity throughout the world. In the current study 300 water samples were processed by PCR for detection of Fasciola hepatica. The overall prevalence in different water sources was 9.66 % (29/300). Highest prevalence was recorded in drain water16 % (16/100) followed by tube well water 10% (4/40), open well water 8 % (8/100) and the lowest was recorded in tap water 1.66 %(1/60). The significant difference P < 0.05 was recorded during data analysis. The highest prevalence was recorded in summer. It was concluded from the study that cleaning and filtration should be adopted to avoid the health hazards against water borne zoonotic parasites.

Can Link Analysis Be Applied to Identify Behavioral Patterns in Train Recorder Data?

PubMed

Strathie, Ailsa; Walker, Guy H

2016-03-01

A proof-of-concept analysis was conducted to establish whether link analysis could be applied to data from on-train recorders to detect patterns of behavior that could act as leading indicators of potential safety issues. On-train data recorders capture data about driving behavior on thousands of routine journeys every day and offer a source of untapped data that could be used to offer insights into human behavior. Data from 17 journeys undertaken by six drivers on the same route over a 16-hr period were analyzed using link analysis, and four key metrics were examined: number of links, network density, diameter, and sociometric status. The results established that link analysis can be usefully applied to data captured from on-vehicle recorders. The four metrics revealed key differences in normal driver behavior. These differences have promising construct validity as leading indicators. Link analysis is one method that could be usefully applied to exploit data routinely gathered by on-vehicle data recorders. It facilitates a proactive approach to safety based on leading indicators, offers a clearer understanding of what constitutes normal driving behavior, and identifies trends at the interface of people and systems, which is currently a key area of strategic risk. These research findings have direct applications in the field of transport data monitoring. They offer a means of automatically detecting patterns in driver behavior that could act as leading indicators of problems during operation and that could be used in the proactive monitoring of driver competence, risk management, and even infrastructure design. © 2015, Human Factors and Ergonomics Society.

Eyelid contour detection and tracking for startle research related eye-blink measurements from high-speed video records.

PubMed

Bernard, Florian; Deuter, Christian Eric; Gemmar, Peter; Schachinger, Hartmut

2013-10-01

Using the positions of the eyelids is an effective and contact-free way for the measurement of startle induced eye-blinks, which plays an important role in human psychophysiological research. To the best of our knowledge, no methods for an efficient detection and tracking of the exact eyelid contours in image sequences captured at high-speed exist that are conveniently usable by psychophysiological researchers. In this publication a semi-automatic model-based eyelid contour detection and tracking algorithm for the analysis of high-speed video recordings from an eye tracker is presented. As a large number of images have been acquired prior to method development it was important that our technique is able to deal with images that are recorded without any special parametrisation of the eye tracker. The method entails pupil detection, specular reflection removal and makes use of dynamic model adaption. In a proof-of-concept study we could achieve a correct detection rate of 90.6%. With this approach, we provide a feasible method to accurately assess eye-blinks from high-speed video recordings. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

Sanfilippo, Antonio P.; Chikkagoudar, Satish

We describe an approach to analyzing trade data which uses clustering to detect similarities across shipping manifest records, classification to evaluate clustering results and categorize new unseen shipping data records, and visual analytics to provide to support situation awareness in dynamic decision making to monitor and warn against the movement of radiological threat materials through search, analysis and forecasting capabilities. The evaluation of clustering results through classification and systematic inspection of the clusters show the clusters have strong semantic cohesion and offer novel ways to detect transactions related to nuclear smuggling.

Coherent ambient infrasound recorded by the global IMS network

NASA Astrophysics Data System (ADS)

Matoza, R. S.; Landes, M.; Le Pichon, A.; Ceranna, L.; Brown, D.

2011-12-01

The International Monitoring System (IMS) includes a global network of infrasound arrays, which is designed to detect atmospheric nuclear explosions anywhere on the planet. The infrasound network also has potential application in detection of natural hazards such as large volcanic explosions and severe weather. Ambient noise recorded by the network includes incoherent wind noise and coherent infrasound. We present a statistical analysis of coherent infrasound recorded by the IMS network. We have applied broadband (0.01 to 5 Hz) array processing systematically to the multi-year IMS historical dataset (2005-present) using an implementation of the Progressive Multi-Channel Correlation (PMCC) algorithm in log-frequency space. We show that IMS arrays consistently record coherent ambient infrasound across the broad frequency range from 0.01 to 5 Hz when wind-noise levels permit. Multi-year averaging of PMCC detection bulletins emphasizes continuous signals such as oceanic microbaroms, as well as persistent transient signals such as repetitive volcanic, surf, or anthropogenic activity (e.g., mining or industrial activity). While many of these continuous or repetitive signals are of interest in their own right, they may dominate IMS array detection bulletins and obscure or complicate detection of specific signals of interest. The new PMCC detection bulletins have numerous further applications, including in volcano and microbarom studies, and in IMS data quality assessment.

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.

Analysis of Infrared Signature Variation and Robust Filter-Based Supersonic Target Detection

PubMed Central

Sun, Sun-Gu; Kim, Kyung-Tae

2014-01-01

The difficulty of small infrared target detection originates from the variations of infrared signatures. This paper presents the fundamental physics of infrared target variations and reports the results of variation analysis of infrared images acquired using a long wave infrared camera over a 24-hour period for different types of backgrounds. The detection parameters, such as signal-to-clutter ratio were compared according to the recording time, temperature and humidity. Through variation analysis, robust target detection methodologies are derived by controlling thresholds and designing a temporal contrast filter to achieve high detection rate and low false alarm rate. Experimental results validate the robustness of the proposed scheme by applying it to the synthetic and real infrared sequences. PMID:24672290

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

PubMed Central

Pellegrino, Giovanni; Machado, Alexis; von Ellenrieder, Nicolas; Watanabe, Satsuki; Hall, Jeffery A.; Lina, Jean-Marc; Kobayashi, Eliane; Grova, Christophe

2016-01-01

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s. Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s. PMID:27047325

Optical recording of action potentials and other discrete physiological events: a perspective from signal detection theory.

PubMed

Sjulson, Lucas; Miesenböck, Gero

2007-02-01

Optical imaging of physiological events in real time can yield insights into biological function that would be difficult to obtain by other experimental means. However, the detection of all-or-none events, such as action potentials or vesicle fusion events, in noisy single-trial data often requires a careful balance of tradeoffs. The analysis of such experiments, as well as the design of optical reporters and instrumentation for them, is aided by an understanding of the principles of signal detection. This review illustrates these principles, using as an example action potential recording with optical voltage reporters.

A novel automated detection system for swallowing sounds during eating and speech under everyday conditions.

PubMed

Fukuike, C; Kodama, N; Manda, Y; Hashimoto, Y; Sugimoto, K; Hirata, A; Pan, Q; Maeda, N; Minagi, S

2015-05-01

The wave analysis of swallowing sounds has been receiving attention because the recording process is easy and non-invasive. However, up until now, an expert has been needed to visually examine the entire recorded wave to distinguish swallowing from other sounds. The purpose of this study was to establish a methodology to automatically distinguish the sound of swallowing from sound data recorded during a meal in the presence of everyday ambient sound. Seven healthy participants (mean age: 26·7 ± 1·3 years) participated in this study. A laryngeal microphone and a condenser microphone attached to the nostril were used for simultaneous recording. Recoding took place while participants were taking a meal and talking with a conversational partner. Participants were instructed to step on a foot pedal trigger switch when they swallowed, representing self-enumeration of swallowing, and also to achieve six additional noise-making tasks during the meal in a randomised manner. The automated analysis system correctly detected 342 out of the 352 self-enumerated swallowing events (sensitivity: 97·2%) and 479 out of the 503 semblable wave periods of swallowing (specificity: 95·2%). In this study, the automated detection system for swallowing sounds using a nostril microphone was able to detect the swallowing event with high sensitivity and specificity even under the conditions of daily life, thus showing potential utility in the diagnosis or screening of dysphagic patients in future studies. © 2014 John Wiley & Sons Ltd.

Automated detection of records in biological sequence databases that are inconsistent with the literature.

PubMed

Bouadjenek, Mohamed Reda; Verspoor, Karin; Zobel, Justin

2017-07-01

We investigate and analyse the data quality of nucleotide sequence databases with the objective of automatic detection of data anomalies and suspicious records. Specifically, we demonstrate that the published literature associated with each data record can be used to automatically evaluate its quality, by cross-checking the consistency of the key content of the database record with the referenced publications. Focusing on GenBank, we describe a set of quality indicators based on the relevance paradigm of information retrieval (IR). Then, we use these quality indicators to train an anomaly detection algorithm to classify records as "confident" or "suspicious". Our experiments on the PubMed Central collection show assessing the coherence between the literature and database records, through our algorithms, is an effective mechanism for assisting curators to perform data cleansing. Although fewer than 0.25% of the records in our data set are known to be faulty, we would expect that there are many more in GenBank that have not yet been identified. By automated comparison with literature they can be identified with a precision of up to 10% and a recall of up to 30%, while strongly outperforming several baselines. While these results leave substantial room for improvement, they reflect both the very imbalanced nature of the data, and the limited explicitly labelled data that is available. Overall, the obtained results show promise for the development of a new kind of approach to detecting low-quality and suspicious sequence records based on literature analysis and consistency. From a practical point of view, this will greatly help curators in identifying inconsistent records in large-scale sequence databases by highlighting records that are likely to be inconsistent with the literature. Copyright © 2017 Elsevier Inc. All rights reserved.

Transmission line relay mis-operation detection based on time-synchronized field data

DOE PAGES

Esmaeilian, Ahad; Popovic, Tomo; Kezunovic, Mladen

2015-05-04

In this paper, a real-time tool to detect transmission line relay mis-operation is implemented. The tool uses time-synchronized measurements obtained from both ends of the line during disturbances. The proposed fault analysis tool comes into the picture only after the protective device has operated and tripped the line. The proposed methodology is able not only to detect, classify, and locate transmission line faults, but also to accurately confirm whether the line was tripped due to a mis-operation of protective relays. The analysis report includes either detailed description of the fault type and location or detection of relay mis-operation. As such,more » it can be a source of very useful information to support the system restoration. The focus of the paper is on the implementation requirements that allow practical application of the methodology, which is illustrated using the field data obtained the real power system. Testing and validation is done using the field data recorded by digital fault recorders and protective relays. The test data included several hundreds of event records corresponding to both relay mis-operations and actual faults. The discussion of results addresses various challenges encountered during the implementation and validation of the presented methodology.« less

Electrodiagnostic applications of somatosensory evoked high-frequency EEG oscillations: Technical considerations.

PubMed

Simpson, A J; Cunningham, M O; Baker, M R

2018-03-01

High frequency oscillations (HFOs) embedded within the somatosensory evoked potential (SEP) are not routinely recorded/measured as part of standard clinical SEPs. However, HFOs could provide important additional diagnostic/prognostic information in various patient groups in whom SEPs are tested routinely. One area is the management of patients with hypoxic ischaemic encephalopathy (HIE) in the intensive care unit (ICU). However, the sensitivity of standard clinical SEP recording techniques for detecting HFOs is unknown. SEPs were recorded using routine clinical methods in 17 healthy subjects (median nerve stimulation; 0.5 ms pulse width; 5 Hz; maximum 4000 stimuli) in an unshielded laboratory. Bipolar EEG recordings were acquired (gain 50 k; bandpass 3Hz-2 kHz; sampling rate 5 kHz; non-inverting electrode 2 cm anterior to C3/C4; inverting electrode 2 cm posterior to C3/C4). Data analysis was performed in MATLAB. SEP-HFOs were detected in 65% of controls using standard clinical recording techniques. In 3 controls without significant HFOs, experiments were repeated using a linear electrode array with higher spatial sampling frequency. SEP-HFOs were observed in all 3 subjects. Currently standard clinical methods of recording SEPs are not sufficiently sensitive to permit the inclusion of SEP-HFOs in routine clinical diagnostic/prognostic assessments. Whilst an increase in the number/density of EEG electrodes should improve the sensitivity for detecting SEP-HFOs, this requires confirmation. By improving and standardising clinical SEP recording protocols to permit the acquisition/analysis of SEP-HFOs, it should be possible to gain important insights into the pathophysiology of neurological disorders and refine the management of conditions such as HIE. Copyright © 2018. Published by Elsevier Inc.

Long-term recording and automatic analysis of cough using filtered acoustic signals and movements on static charge sensitive bed.

PubMed

Salmi, T; Sovijärvi, A R; Brander, P; Piirilä, P

1988-11-01

Reliable long-term assessment of cough is necessary in many clinical and scientific settings. A new method for long-term recording and automatic analysis of cough is presented. The method is based on simultaneous recording of two independent signals: high-pass filtered cough sounds and cough-induced fast movements of the body. The acoustic signals are recorded with a dynamic microphone in the acoustic focus of a glass fiber paraboloid mirror. Body movements are recorded with a static charge-sensitive bed located under an ordinary plastic foam mattress. The patient can be studied lying or sitting with no transducers or electrodes attached. A microcomputer is used for sampling of signals, detection of cough, statistical analyses, and on-line printing of results. The method was validated in seven adult patients with a total of 809 spontaneous cough events, using clinical observation as a reference. The sensitivity of the method to detect cough was 99.0 percent, and the positive predictivity was 98.1 percent. The system ignored speaking and snoring. The method provides a convenient means of reliable long-term follow-up of cough in clinical work and research.

Description, characteristics and testing of the NASA airborne radar

NASA Technical Reports Server (NTRS)

Jones, W. R.; Altiz, O.; Schaffner, P.; Schrader, J. H.; Blume, H. J. C.

1991-01-01

Presented here is a description of a coherent radar scattermeter and its associated signal processing hardware, which have been specifically designed to detect microbursts and record their radar characteristics. Radar parameters, signal processing techniques and detection algorithms, all under computer control, combine to sense and process reflectivity, clutter, and microburst data. Also presented is the system's high density, high data rate recording system. This digital system is capable of recording many minutes of the in-phase and quadrature components and corresponding receiver gains of the scattered returns for selected spatial regions, as well as other aircraft and hardware related parameters of interest for post-flight analysis. Information is given in viewgraph form.

Using external data sources to improve audit trail analysis.

PubMed

Herting, R L; Asaro, P V; Roth, A C; Barnes, M R

1999-01-01

Audit trail analysis is the primary means of detection of inappropriate use of the medical record. While audit logs contain large amounts of information, the information required to determine useful user-patient relationships is often not present. Adequate information isn't present because most audit trail analysis systems rely on the limited information available within the medical record system. We report a feature of the STAR (System for Text Archive and Retrieval) audit analysis system where information available in the medical record is augmented with external information sources such as: database sources, Light-weight Directory Access Protocol (LDAP) server sources, and World Wide Web (WWW) database sources. We discuss several issues that arise when combining the information from each of these disparate information sources. Furthermore, we explain how the enhanced person specific information obtained can be used to determine user-patient relationships that might signify a motive for inappropriately accessing a patient's medical record.

Psychotropics and weak opioid analgesics in plasma samples of older hip fracture patients - detection frequencies and consistency with drug records.

PubMed

Waade, Ragnhild Birkeland; Molden, Espen; Martinsen, Mette Irene; Hermann, Monica; Ranhoff, Anette Hylen

2017-07-01

To determine use of psychotropic drugs and weak opioids in hip fracture patients by analysing plasma samples at admission, and compare detected drug frequencies with prescription registry data and drug records. Plasma from 250 hip fracture patients aged ≥65 years sampled at hospital admission were analysed by ultra-performance liquid chromatography-tandem mass spectrometry methods for detection of psychotropic drugs and weak opioid analgesics (alcohol also determined). Odds ratios for drugs detected in plasma of hip fracture patients vs. prescription frequencies of the same drugs in an age-, time- and region-matched reference population were calculated. Moreover, recorded and measured drugs were compared. Psychotropic drugs and/or weak opioid analgesics were detected in 158 (63%) of the patients (median age 84 years; 76% females), while alcohol was found in 19 patients (7.6%). The occurrence of diazepam (odds ratio 1.6; 95% confidence interval 1.1-2.4), nitrazepam (2.3; 1.3-4.1), selective serotonin reuptake inhibitors (1.9; 1.3-2.9) and mirtazapine (2.3; 1.2-4.3) was significantly higher in plasma samples of hip fracture patients than in prescription data from the reference population. Poor consistency between recorded and measured drugs was disclosed for z-hypnotics and benzodiazepines; e.g. diazepam was detected in 29 (11.6%), but only recorded in six (2.4%) of the patients. Plasma analysis shows that use of antidepressants and benzodiazepines in hip fracture patients is significantly more frequent than respective prescription frequencies in the general elderly population. Moreover, consistency between recorded and actual use of psychotropic fall-risk drugs is poor at hospital admission of hip fracture patients. © 2017 The British Pharmacological Society.

Detection of Mouse Cough Based on Sound Monitoring and Respiratory Airflow Waveforms

PubMed Central

Chen, Liyan; Lai, Kefang; Lomask, Joseph Mark; Jiang, Bert; Zhong, Nanshan

2013-01-01

Detection for cough in mice has never yielded clearly audible sounds, so there is still a great deal of debates as to whether mice can cough in response to tussive stimuli. Here we introduce an approach for detection of mouse cough based on sound monitoring and airflow signals. 40 Female BALB/c mice were pretreated with normal saline, codeine, capasazepine or desensitized with capsaicin. Single mouse was put in a plethysmograph, exposed to aerosolized 100 µmol/L capsaicin for 3 min, followed by continuous observation for 3 min. Airflow signals of total 6 min were recorded and analyzed to detect coughs. Simultaneously, mouse cough sounds were sensed by a mini-microphone, monitored manually by an operator. When manual and automatic detection coincided, the cough was positively identified. Sound and sound waveforms were also recorded and filtered for further analysis. Body movements were observed by operator. Manual versus automated counts were compared. Seven types of airflow signals were identified by integrating manual and automated monitoring. Observation of mouse movements and analysis of sound waveforms alone did not produce meaningful data. Mouse cough numbers decreased significantly after all above drugs treatment. The Bland-Altman and consistency analysis between automatic and manual counts was 0.968 and 0.956. The study suggests that the mouse is able to present with cough, which could be detected by sound monitoring and respiratory airflow waveform changes. PMID:23555643

Mixed-methods analytic approach for determining potential impacts of vessel noise on sperm whale click behavior.

PubMed

Azzara, Alyson J; von Zharen, Wyndylyn M; Newcomb, Joal J

2013-12-01

The Gulf of Mexico is a center of marine activities from seismic exploration to shipping, drilling, platform installation, lightering, and construction, among others. This analysis explored whether sperm whales respond to the passage of vessels using changes in total number of clicks during vessel passages as a proxy for potential variation in behavior. The data for this analysis were collected in 2001 as part of a larger Littoral Acoustic Demonstration Center project using the Environmental Acoustics Recording System buoys. These buoys were bottom moored, autonomous, and self-recording systems consisting of an omni-directional hydrophone and instrument package. Data from 36 days of continuous acoustic monitoring were recorded at a sampling rate of 11.725 kHz, and produced reliable recordings from 5 Hz to ∼5.8 kHz. Multiple preparatory steps were executed including calibration of an automatic click detector. Results indicate a significant decrease (32%) in the number of clicks detected as a ship approached an area. There were also significantly fewer clicks detected after the vessel passed than before (23%).

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

USGS Publications Warehouse

Dorazio, Robert; Karanth, K. Ullas

2017-01-01

MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.

A substitution method to improve completeness of events documentation in anesthesia records.

PubMed

Lamer, Antoine; De Jonckheere, Julien; Marcilly, Romaric; Tavernier, Benoît; Vallet, Benoît; Jeanne, Mathieu; Logier, Régis

2015-12-01

AIMS are optimized to find and display data and curves about one specific intervention but is not retrospective analysis on a huge volume of interventions. Such a system present two main limitation; (1) the transactional database architecture, (2) the completeness of documentation. In order to solve the architectural problem, data warehouses were developed to propose architecture suitable for analysis. However, completeness of documentation stays unsolved. In this paper, we describe a method which allows determining of substitution rules in order to detect missing anesthesia events in an anesthesia record. Our method is based on the principle that missing event could be detected using a substitution one defined as the nearest documented event. As an example, we focused on the automatic detection of the start and the end of anesthesia procedure when these events were not documented by the clinicians. We applied our method on a set of records in order to evaluate; (1) the event detection accuracy, (2) the improvement of valid records. For the year 2010-2012, we obtained event detection with a precision of 0.00 (-2.22; 2.00) min for the start of anesthesia and 0.10 (0.00; 0.35) min for the end of anesthesia. On the other hand, we increased by 21.1% the data completeness (from 80.3 to 97.2% of the total database) for the start and the end of anesthesia events. This method seems to be efficient to replace missing "start and end of anesthesia" events. This method could also be used to replace other missing time events in this particular data warehouse as well as in other kind of data warehouses.

A computational study on outliers in world music.

PubMed

Panteli, Maria; Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as 'outliers'. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the 'uniqueness' of the music of each country.

A computational study on outliers in world music

PubMed Central

Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country. PMID:29253027

Discriminating movements of liquid and gas in the rabbit colon with impedance manometry.

PubMed

Mohd Rosli, R; Leibbrandt, R E; Wiklendt, L; Costa, M; Wattchow, D A; Spencer, N J; Brookes, S J; Omari, T I; Dinning, P G

2018-05-01

High-resolution impedance manometry is a technique that is well established in esophageal motility studies for relating motor patterns to bolus flow. The use of this technique in the colon has not been established. In isolated segments of rabbit proximal colon, we recorded motor patterns and the movement of liquid or gas boluses with a high-resolution impedance manometry catheter. These detected movements were compared to video recorded changes in gut diameter. Using the characteristic shapes of the admittance (inverse of impedance) and pressure signals associated with gas or liquid flow we developed a computational algorithm for the automated detection of these events. Propagating contractions detected by video were also recorded by manometry and impedance. Neither pressure nor admittance signals alone could distinguish between liquid and gas transit, however the precise relationship between admittance and pressure signals during bolus flow could. Training our computational algorithm upon these characteristic shapes yielded a detection accuracy of 87.7% when compared to gas or liquid bolus events detected by manual analysis. Characterizing the relationship between both admittance and pressure recorded with high-resolution impedance manometry can not only help in detecting luminal transit in real time, but also distinguishes between liquid and gaseous content. This technique holds promise for determining the propulsive nature of human colonic motor patterns. © 2017 John Wiley & Sons Ltd.

Detection of subtle nocturnal motor activity from 3-D accelerometry recordings in epilepsy patients.

PubMed

Nijsen, Tamara M E; Cluitmans, Pierre J M; Arends, Johan B A M; Griep, Paul A M

2007-11-01

This paper presents a first step towards reliable detection of nocturnal epileptic seizures based on 3-D accelerometry (ACM) recordings. The main goal is to distinguish between data with and without subtle nocturnal motor activity, thus reducing the amount of data that needs further (more complex) analysis for seizure detection. From 15 ACM signals (measured on five positions on the body), two features are computed, the variance and the jerk. In the resulting 2-D feature space, a linear threshold function is used for classification. For training and testing, the algorithm ACM data along with video data is used from nocturnal registrations in seven mentally retarded patients with severe epilepsy. Per patient, the algorithm detected 100% of the periods of motor activity that are marked in video recordings and the ACM signals by experts. From all the detections, 43%-89% was correct (mean =65%). We were able to reduce the amount of data that need to be analyzed considerably. The results show that our approach can be used for detection of subtle nocturnal motor activity. Furthermore, our results indicate that our algorithm is robust for fluctuations across patients. Consequently, there is no need for training the algorithm for each new patient.

Detecting a periodic signal in the terrestrial cratering record

NASA Technical Reports Server (NTRS)

Grieve, Richard A. F.; Rupert, James D.; Goodacre, Alan K.; Sharpton, Virgil L.

1988-01-01

A time-series analysis of model periodic data, where the period and phase are known, has been performed in order to investigate whether a significant period can be detected consistently from a mix of random and periodic impacts. Special attention is given to the effect of age uncertainties and random ages in the detection of a periodic signal. An equivalent analysis is performed with observed data on crater ages and compared with the model data, and the effects of the temporal distribution of crater ages on the results from the time-series analysis are studied. Evidence for a consistent 30-m.y. period is found to be weak.

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

PubMed

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

2007-01-01

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

[Study for portable dynamic ECG monitor and recorder].

PubMed

Yang, Pengcheng; Li, Yongqin; Chen, Bihua

2012-09-01

This Paper presents a portable dynamic ECG monitor system based on MSP430F149 microcontroller. The electrocardiogram detecting system consists of ECG detecting circuit, man-machine interaction module, MSP430F149 and upper computer software. The ECG detecting circuit including a preamplifier, second-order Butterworth low-pass filter, high-pass filter, and 50Hz trap circuit to detects electrocardiogram and depresses various kinds of interference effectively. A microcontroller is used to collect three channel analog signals which can be displayed on TFT LCD. A SD card is used to record real-time data continuously and implement the FTA16 file system. In the end, a host computer system interface is also designed to analyze the ECG signal and the analysis results can provide diagnosis references to clinical doctors.

The use of ion mobility spectrometry and gas chromatography/mass spectrometry for the detection of illicit drugs on clandestine records

NASA Technical Reports Server (NTRS)

Donnelly, Brian; Jourdan, Thomas; Fetterolf, Dean D.; Beasley, James O., II

1995-01-01

Illicit drug distribution has over the past decade grown tremendously from simple 'drug pushing' where drugs were distributed from poorly organized individuals to today's well organized and well financed drug cartels. This change to a more 'corporate-like' atmosphere has resulted in a greater use of record keeping to monitor the profits generated. The use of record keeping by drug distributors is not restricted to high level drug smugglers but is used at all levels within the distribution network. Dealers at all levels including street dealers are generally 'fronted', given on consignment quantities of drugs that they in turn sell to customers, thereby requiring the need for records to keep track of drug sales versus liabilities. These records because of their illicit nature are often encrypted to hide the fact that they are indeed records of drug transactions. The creation of a handwritten notation concerning a drug transaction is normally brought on because of a purchase or sale. In a sale, this is commonly accomplished through a consignment, or the designation of a quantity to a customer to whom that amount has been 'fronted'. Because this activity generates a debt, it follows that an accounting for payments made, as well as new transactions completed, is only logical. One of the most common means of representing these is through an 'accounting flow', in which payments are subtracted from a running balance while new sales are added to it. The examination of illicit drug records has been the key to the prosecution of numerous federal, state, and local drug cases for a number of years. The Document Section of the FBI Laboratory, through its Racketeering Records Analysis Unit (RRAU), has been involved in such analytical efforts since 1983. Detailed analytical research brought about an evolution in the systematic approach utilized in the RRAU since that time. The close proximity of the drugs to the records often results in trace drug evidence being transferred to the records. The detection of trace drug residue on surfaces by ion mobility spectrometry (IMS) is well documented in literature. The following procedure will deal primarily with the newer techniques of trace drug analysis and drug record analysis developed by the Chemistry/Toxicology Unit of the FBI Laboratory since the more traditional techniques of latent finger print analysis and document analysis are well known.

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

PubMed

Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

2017-01-01

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Method and apparatus for detecting and determining event characteristics with reduced data collection

NASA Technical Reports Server (NTRS)

Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

2007-01-01

A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

Automated nystagmus analysis. [on-line computer technique for eye data processing

NASA Technical Reports Server (NTRS)

Oman, C. M.; Allum, J. H. J.; Tole, J. R.; Young, L. R.

1973-01-01

Several methods have recently been used for on-line analysis of nystagmus: A digital computer program has been developed to accept sampled records of eye position, detect fast phase components, and output cumulative slow phase position, continuous slow phase velocity, instantaneous fast phase frequency, and other parameters. The slow phase velocity is obtained by differentiation of the calculated cumulative position rather than the original eye movement record. Also, a prototype analog device has been devised which calculates the velocity of the slow phase component during caloric testing. Examples of clinical and research eye movement records analyzed with these devices are shown.

Statistical analysis of storm electrical discharges reconstituted from a lightning mapping system, a lightning location system, and an acoustic array

NASA Astrophysics Data System (ADS)

Gallin, Louis-Jonardan; Farges, Thomas; Marchiano, Régis; Coulouvrat, François; Defer, Eric; Rison, William; Schulz, Wolfgang; Nuret, Mathieu

2016-04-01

In the framework of the European Hydrological Cycle in the Mediterranean Experiment project, a field campaign devoted to the study of electrical activity during storms took place in the south of France in 2012. An acoustic station composed of four microphones and four microbarometers was deployed within the coverage of a Lightning Mapping Array network. On the 26 October 2012, a thunderstorm passed just over the acoustic station. Fifty-six natural thunder events, due to cloud-to-ground and intracloud flashes, were recorded. This paper studies the acoustic reconstruction, in the low frequency range from 1 to 40 Hz, of the recorded flashes and their comparison with detections from electromagnetic networks. Concurrent detections from the European Cooperation for Lightning Detection lightning location system were also used. Some case studies show clearly that acoustic signal from thunder comes from the return stroke but also from the horizontal discharges which occur inside the clouds. The huge amount of observation data leads to a statistical analysis of lightning discharges acoustically recorded. Especially, the distributions of altitudes of reconstructed acoustic detections are explored in detail. The impact of the distance to the source on these distributions is established. The capacity of the acoustic method to describe precisely the lower part of nearby cloud-to-ground discharges, where the Lightning Mapping Array network is not effective, is also highlighted.

Telephony-based voice pathology assessment using automated speech analysis.

PubMed

Moran, Rosalyn J; Reilly, Richard B; de Chazal, Philip; Lacy, Peter D

2006-03-01

A system for remotely detecting vocal fold pathologies using telephone-quality speech is presented. The system uses a linear classifier, processing measurements of pitch perturbation, amplitude perturbation and harmonic-to-noise ratio derived from digitized speech recordings. Voice recordings from the Disordered Voice Database Model 4337 system were used to develop and validate the system. Results show that while a sustained phonation, recorded in a controlled environment, can be classified as normal or pathologic with accuracy of 89.1%, telephone-quality speech can be classified as normal or pathologic with an accuracy of 74.2%, using the same scheme. Amplitude perturbation features prove most robust for telephone-quality speech. The pathologic recordings were then subcategorized into four groups, comprising normal, neuromuscular pathologic, physical pathologic and mixed (neuromuscular with physical) pathologic. A separate classifier was developed for classifying the normal group from each pathologic subcategory. Results show that neuromuscular disorders could be detected remotely with an accuracy of 87%, physical abnormalities with an accuracy of 78% and mixed pathology voice with an accuracy of 61%. This study highlights the real possibility for remote detection and diagnosis of voice pathology.

Detecting oscillatory patterns and time lags from proxy records with non-uniform sampling: Some pitfalls and possible solutions

NASA Astrophysics Data System (ADS)

Donner, Reik

2013-04-01

Time series analysis offers a rich toolbox for deciphering information from high-resolution geological and geomorphological archives and linking the thus obtained results to distinct climate and environmental processes. Specifically, on various time-scales from inter-annual to multi-millenial, underlying driving forces exhibit more or less periodic oscillations, the detection of which in proxy records often allows linking them to specific mechanisms by which the corresponding drivers may have affected the archive under study. A persistent problem in geomorphology is that available records do not present a clear signal of the variability of environmental conditions, but exhibit considerable uncertainties of both the measured proxy variables and the associated age model. Particularly, time-scale uncertainty as well as the heterogeneity of sampling in the time domain are source of severe conceptual problems that may lead to false conclusions about the presence or absence of oscillatory patterns and their mutual phasing in different archives. In my presentation, I will discuss how one can cope with non-uniformly sampled proxy records to detect and quantify oscillatory patterns in one or more data sets. For this purpose, correlation analysis is reformulated using kernel estimates which are found superior to classical estimators based on interpolation or Fourier transform techniques. In order to characterize non-stationary or noisy periodicities and their relative phasing between different records, an extension of continuous wavelet transform is utilized. The performance of both methods is illustrated for different case studies. An extension to explicitly considering time-scale uncertainties by means of Bayesian techniques is briefly outlined.

An automated multi-scale network-based scheme for detection and location of seismic sources

NASA Astrophysics Data System (ADS)

Poiata, N.; Aden-Antoniow, F.; Satriano, C.; Bernard, P.; Vilotte, J. P.; Obara, K.

2017-12-01

We present a recently developed method - BackTrackBB (Poiata et al. 2016) - allowing to image energy radiation from different seismic sources (e.g., earthquakes, LFEs, tremors) in different tectonic environments using continuous seismic records. The method exploits multi-scale frequency-selective coherence in the wave field, recorded by regional seismic networks or local arrays. The detection and location scheme is based on space-time reconstruction of the seismic sources through an imaging function built from the sum of station-pair time-delay likelihood functions, projected onto theoretical 3D time-delay grids. This imaging function is interpreted as the location likelihood of the seismic source. A signal pre-processing step constructs a multi-band statistical representation of the non stationary signal, i.e. time series, by means of higher-order statistics or energy envelope characteristic functions. Such signal-processing is designed to detect in time signal transients - of different scales and a priori unknown predominant frequency - potentially associated with a variety of sources (e.g., earthquakes, LFE, tremors), and to improve the performance and the robustness of the detection-and-location location step. The initial detection-location, based on a single phase analysis with the P- or S-phase only, can then be improved recursively in a station selection scheme. This scheme - exploiting the 3-component records - makes use of P- and S-phase characteristic functions, extracted after a polarization analysis of the event waveforms, and combines the single phase imaging functions with the S-P differential imaging functions. The performance of the method is demonstrated here in different tectonic environments: (1) analysis of the one year long precursory phase of 2014 Iquique earthquake in Chile; (2) detection and location of tectonic tremor sources and low-frequency earthquakes during the multiple episodes of tectonic tremor activity in southwestern Japan.

Tectonic Tremor analysis with the Taiwan Chelungpu-Fault Drilling Program (TCDP) downhole seismometer array

NASA Astrophysics Data System (ADS)

Lin, Y.; Hillers, G.; Ma, K.; Campillo, M.

2011-12-01

We study tectonic tremor activity in the Taichung area, Taiwan, analyzing continuous seismic records from 6 short-period sensors of the TCDP borehole array situated around 1 km depth. The low background noise level facilitates the detection of low-amplitude tectonic tremor and low-frequency earthquake (LFE) waveforms. We apply a hierarchical analysis to first detect transient amplitude increases, and to subsequently verify its tectonic origin, i.e. to associate it with tremor signals. The frequency content of tremor usually exceeds the background noise around 2-8 Hz; hence, in the first step, we use BHS1, BHS4 and BHS7 (top, center, bottom sensor) records to detect amplitude anomalies in this frequency range. We calculate the smoothed spectra of 30 second non-overlapping windows taken daily from 5 night time hours to avoid increased day time amplitudes associated with cultural activities. Amplitude detection is then performed on frequency dependent median values of 5 minute advancing, 10 minute long time windows, yielding a series of threshold dependent increased-energy spectra-envelopes, indicating teleseismic waveforms, potential tremor records, or other transients related to anthropogenic or natural sources. To verify the transients' tectonic origin, potential tremor waveforms detected by the amplitude method are manually picked in the time domain. We apply the Brown et al. (2008) LFE matched filter technique to three-component data from the 6 available sensors. Initial few-second templates are taken from the analyst-picked, minute-long segments, and correlated component-wise with 24-h data. Significantly increased similarity between templates and matched waveform segments is detected using the array-average 7-fold MAD measure. Harvested waveforms associated with this initial `weak' detection are stacked, and the thus created master templates are used in an iterative correlation procedure to arrive at robust LFE detections. The increased similarity of waveforms, showing essentially no moveout across the array, suggests a common source and path effect, therefore increasing the likelihood of a tectonic origin. Preliminary results from a pilot analysis confirm the existence of tremor-like signals in the tremor-typical frequency range. We present results from a comprehensive analysis of at least 2 years of continuous data. A limited resolution location procedure is applied, testament to the receiver geometry, and the inferred locations are discussed in relation to the tectonic situation.

A computer aided treatment event recognition system in radiation therapy.

PubMed

Xia, Junyi; Mart, Christopher; Bayouth, John

2014-01-01

To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012-November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors' clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when executed on either a desktop computer or a mobile device. CATERS offers an effective tool to detect and report treatment events. Automation and rapid processing enables electronic record interrogation daily, alerting the medical physicist of deviations potentially days prior to performing weekly check. The output of CATERS could also be utilized as an important input to failure mode and effects analysis.

Detection of ventricular fibrillation from multiple sensors

NASA Astrophysics Data System (ADS)

Lindsley, Stephanie A.; Ludeman, Lonnie C.

1992-07-01

Ventricular fibrillation is a potentially fatal medical condition in which the flow of blood through the body is terminated due to the lack of an organized electric potential in the heart. Automatic implantable defibrillators are becoming common as a means for helping patients confronted with repeated episodes of ventricular fibrillation. Defibrillators must first accurately detect ventricular fibrillation and then provide an electric shock to the heart to allow a normal sinus rhythm to resume. The detection of ventricular fibrillation by using an array of multiple sensors to distinguish between signals recorded from single (normal sinus rhythm) or multiple (ventricular fibrillation) sources is presented. An idealistic model is presented and the analysis of data generated by this model suggests that the method is promising as a method for accurately and quickly detecting ventricular fibrillation from signals recorded from sensors placed on the epicardium.

Measurement and classification of heart and lung sounds by using LabView for educational use.

PubMed

Altrabsheh, B

2010-01-01

This study presents the design, development and implementation of a simple low-cost method of phonocardiography signal detection. Human heart and lung signals are detected by using a simple microphone through a personal computer; the signals are recorded and analysed using LabView software. Amplitude and frequency analyses are carried out for various phonocardiography pathological cases. Methods for automatic classification of normal and abnormal heart sounds, murmurs and lung sounds are presented. Various cases of heart and lung sound measurement are recorded and analysed. The measurements can be saved for further analysis. The method in this study can be used by doctors as a detection tool aid and may be useful for teaching purposes at medical and nursing schools.

Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea.

PubMed

de Chazal, Philip; Heneghan, Conor; Sheridan, Elaine; Reilly, Richard; Nolan, Philip; O'Malley, Mark

2003-06-01

A method for the automatic processing of the electrocardiogram (ECG) for the detection of obstructive apnoea is presented. The method screens nighttime single-lead ECG recordings for the presence of major sleep apnoea and provides a minute-by-minute analysis of disordered breathing. A large independently validated database of 70 ECG recordings acquired from normal subjects and subjects with obstructive and mixed sleep apnoea, each of approximately eight hours in duration, was used throughout the study. Thirty-five of these recordings were used for training and 35 retained for independent testing. A wide variety of features based on heartbeat intervals and an ECG-derived respiratory signal were considered. Classifiers based on linear and quadratic discriminants were compared. Feature selection and regularization of classifier parameters were used to optimize classifier performance. Results show that the normal recordings could be separated from the apnoea recordings with a 100% success rate and a minute-by-minute classification accuracy of over 90% is achievable.

Earthquake recording at the Stanford DAS Array with fibers in existing telecomm conduits

NASA Astrophysics Data System (ADS)

Biondi, B. C.; Martin, E. R.; Yuan, S.; Cole, S.; Karrenbach, M. H.

2017-12-01

The Stanford Distributed Acoustic Sensing Array (SDASA-1) has been continuously recording seismic data since September 2016 on 2.5 km of single mode fiber optics in existing telecommunications conduits under Stanford's campus. The array is figure-eight shaped and roughly 600 m along its widest side with a channel spacing of roughly 8 m. This array is easy to maintain and is nonintrusive, making it well suited to urban environments, but it sacrifices some cable-to-ground coupling compared to more traditional seismometers. We have been testing its utility for earthquake recording, active seismic, and ambient noise interferometry. This talk will focus on earthquake observations. We will show comparisons between the strain rates measured throughout the DAS array and the particle velocities measured at the nearby Jasper Ridge Seismic Station (JRSC). In some of these events, we will point out directionality features specific to DAS that can require slight modifications in data processing. We also compare repeatability of DAS and JRSC recordings of blasts from a nearby quarry. Using existing earthquake databases, we have created a small catalog of DAS earthquake observations by pulling records of over 700 Northern California events spanning Sep. 2016 to Jul. 2017 from both the DAS data and JRSC. On these events we have tested common array methods for earthquake detection and location including beamforming and STA/LTA analysis in time and frequency. We have analyzed these events to approximate thresholds on what distances and magnitudes are clearly detectible by the DAS array. Further analysis should be done on detectability with methods tailored to small events (for example, template matching). In creating this catalog, we have developed open source software available for free download that can manage large sets of continuous seismic data files (both existing files, and files as they stream in). This software can both interface with existing earthquake networks, and efficiently extract earthquake recordings from many continuous recordings saved on the users machines.

Analysis of Speech Disorders in Acute Pseudobulbar Palsy: a Longitudinal Study of a Patient with Lingual Paralysis.

ERIC Educational Resources Information Center

Leroy-Malherbe, V.; Chevrie-Muller, C.; Rigoard, M. T.; Arabia, C.

1998-01-01

This case report describes the case of a 52-year-old man with bilateral central lingual paralysis following a myocardial infarction. Analysis of speech recordings 15 days and 18 months after the attack were acoustically analyzed. The case demonstrates the usefulness of acoustic analysis to detect slight acoustic differences. (DB)

The spatial coherence structure of infrasonic waves: analysis of data from International Monitoring System arrays

NASA Astrophysics Data System (ADS)

Green, David N.

2015-04-01

The spatial coherence structure of 30 infrasound array detections, with source-to-receiver ranges of 25-6500 km, has been measured within the 0.25-1 Hz passband. The data were recorded at International Monitoring System (IMS) microbarograph arrays with apertures of between 1 and 4 km. Such array detections are of interest for Comprehensive Nuclear-Test-Ban Treaty monitoring. The majority of array detections (e.g. 80 per cent of recordings in the third-octave passband centred on 0.63 Hz) exhibit spatial coherence loss anisotropy that is consistent with previous lower frequency atmospheric acoustic studies; coherence loss is more rapid perpendicular to the acoustic propagation direction than parallel to it. The thirty array detections display significant interdetection variation in the magnitude of spatial coherence loss. The measurements can be explained by the simultaneous arrival of wave fronts at the recording array with angular beamwidths of between 0.4 and 7° and velocity bandwidths of between 2 and 40 m s-1. There is a statistically significant positive correlation between source-to-receiver range and the magnitude of coherence loss. Acoustic multipathing generated by interactions with fine-scale wind and temperature gradients along stratospheric propagation paths is qualitatively consistent with the observations. In addition, the study indicates that to isolate coherence loss generated by propagation effects, analysis of signals exhibiting high signal-to-noise ratios (SNR) is required (SNR2 > 11 in this study). The rapid temporal variations in infrasonic noise observed in recordings at IMS arrays indicates that correcting measured coherence values for the effect of noise, using pre-signal estimates of noise power, is ineffective.

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.

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.

Prevalence and risk of malignancy of focal incidental uptake detected by fluorine-18-fluorodeoxyglucose positron emission tomography in the parotid gland: a meta-analysis.

PubMed

Treglia, Giorgio; Bertagna, Francesco; Sadeghi, Ramin; Muoio, Barbara; Giovanella, Luca

2015-12-01

This study aimed at performing a meta-analysis on the prevalence and risk of malignancy of focal parotid incidental uptake (FPIU) detected by hybrid fluorine-18-fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) or (18)F-FDG PET alone. A comprehensive literature search of studies published up to July 2014 was performed. Records reporting at least 5 FPIUs were selected. Pooled prevalence and malignancy risk of FPIU were calculated including 95 % confidence intervals (95 % CI). Twelve records were selected for our meta-analysis. Pooled prevalence of FPIU detected by (18)F-FDG PET or PET/CT was 0.6 % (95 % CI 0.4-0.7 %), collecting data of 220 patients with FPIU. Overall, 181 FPIUs underwent further evaluation and 165 FPIUs were pathologically proven. Pooled risk of malignancy was 9.6 % (95 % CI 5.4-14.8 %), 10.9 % (95 % CI 5.8-17.3 %) and 20.4 % (95 % CI 12.3-30 %), considering all FPIUs detected, only those which underwent further evaluation and only those pathologically proven, respectively. Selection bias in the included studies, the heterogeneity among studies and the publication bias are limitations of our meta-analysis. Overall FPIUs are observed in about 1 % of (18)F-FDG PET or PET/CT scans and they are benign in most of the cases. Nevertheless, further evaluation is needed whenever FPIUs are detected by (18)F-FDG-PET or PET/CT to exclude malignant lesions or with possible malignant degeneration. Prospective studies are needed to confirm the findings reported by our meta-analysis.

The Influence of Solar Spectral Lines on Electron Concentration in Terrestrial Ionosphere

NASA Astrophysics Data System (ADS)

Nina, A.; Čadež, V.; Srećković, V. A.; Šulić, D.

One of the methods of detection and analysis of solar flares is observing the time variations of certain solar spectral lines. During solar flares, a raise of electron concentration occurs in Earth's ionosphere which results in amplitude and phase variations of the recorded very low frequency (VLF) waves. We compared the data obtained by the analysis of recorded VLF signals and line spectra for different solar flares. In this paper we treated the DHO VLF signal transmitted from Germany at the frequency of 23.4 kHz recorded by the AWESOME system in Belgrade (Serbia) during solar flares in the period between 10:40 UT and 13:00 UT on 2011 April 22.

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 quality of the evidence as low. Our budget impact analysis showed that use of the longterm continuous monitors has grown steadily in Ontario since they became publicly funded in 2006, particularly since 2011 when monitors that can record for 14 days or longer became funded, and the use of external cardiac loop recorders has correspondingly declined. The analysis suggests that, with these trends, continued public funding of both types of longterm ambulatory ECG testing will result in additional costs ranging from $130,000 to $370,000 per year over the next 5 years. Conclusions Although both longterm continuous ambulatory ECG monitors and external cardiac loop recorders were more effective than a 24-hour Holter monitor in detecting symptoms of cardiac arrhythmia, we found no evidence to suggest that these two devices differ in effectiveness. Assuming that the use of longterm continuous monitors will continue to increase in the next 5 years, the public health care system in Ontario can expect to see added costs of $130,000 to $370,000 per year. PMID:28194254

Recording of electrohysterogram laplacian potential.

PubMed

Alberola-Rubio, J; Garcia-Casado, J; Ye-Lin, Y; Prats-Boluda, G; Perales, A

2011-01-01

Preterm birth is the main cause of the neonatal morbidity. Noninvasive recording of uterine myoelectrical activity (electrohysterogram, EHG) could be an alternative to the monitoring of uterine dynamics which are currently based on tocodynamometers (TOCO). The analysis of uterine electromyogram characteristics could help the early diagnosis of preterm birth. Laplacian recordings of other bioelectrical signals have proved to enhance spatial selectivity and to reduce interferences in comparison to monopolar and bipolar surface recordings. The main objective of this paper is to check the feasibility of the noninvasive recording of uterine myoelectrical activity by means of laplacian techniques. Four bipolar EHG signals, discrete laplacian obtained from five monopolar electrodes and the signals picked up by two active concentric-ringed-electrodes were recorded on 5 women with spontaneous or induced labor. Intrauterine pressure (IUP) and TOCO were also simultaneously recorded. To evaluate the uterine contraction detectability of the different noninvasive methods in comparison to IUP the contractions consistency index (CCI) was calculated. Results show that TOCO is less consistent (83%) than most EHG bipolar recording channels (91%, 83%, 87%, and 76%) to detect the uterine contractions identified in IUP. Moreover laplacian EHG signals picked up by ringed-electrodes proved to be as consistent (91%) as the best bipolar recordings in addition to significantly reduce ECG interference.

Predictive modeling of structured electronic health records for adverse drug event detection.

PubMed

Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik

2015-01-01

The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and combined. We have demonstrated how machine learning can be applied to electronic health records for the purpose of detecting adverse drug events and proposed solutions to some of the challenges this presents, including how to represent the various data types. Overall, clinical codes are more useful than measurements and, in specific cases, it is beneficial to combine the two.

Predictive modeling of structured electronic health records for adverse drug event detection

PubMed Central

2015-01-01

Background The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Methods Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Results Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and combined. Conclusions We have demonstrated how machine learning can be applied to electronic health records for the purpose of detecting adverse drug events and proposed solutions to some of the challenges this presents, including how to represent the various data types. Overall, clinical codes are more useful than measurements and, in specific cases, it is beneficial to combine the two. PMID:26606038

Detecting Seismic Activity with a Covariance Matrix Analysis of Data Recorded on Seismic Arrays

NASA Astrophysics Data System (ADS)

Seydoux, L.; Shapiro, N.; de Rosny, J.; Brenguier, F.

2014-12-01

Modern seismic networks are recording the ground motion continuously all around the word, with very broadband and high-sensitivity sensors. The aim of our study is to apply statistical array-based approaches to processing of these records. We use the methods mainly brought from the random matrix theory in order to give a statistical description of seismic wavefields recorded at the Earth's surface. We estimate the array covariance matrix and explore the distribution of its eigenvalues that contains information about the coherency of the sources that generated the studied wavefields. With this approach, we can make distinctions between the signals generated by isolated deterministic sources and the "random" ambient noise. We design an algorithm that uses the distribution of the array covariance matrix eigenvalues to detect signals corresponding to coherent seismic events. We investigate the detection capacity of our methods at different scales and in different frequency ranges by applying it to the records of two networks: (1) the seismic monitoring network operating on the Piton de la Fournaise volcano at La Réunion island composed of 21 receivers and with an aperture of ~15 km, and (2) the transportable component of the USArray composed of ~400 receivers with ~70 km inter-station spacing.

Using a high spatial resolution tactile sensor for intention detection.

PubMed

Castellini, Claudio; Koiva, Risto

2013-06-01

Intention detection is the interpretation of biological signals with the aim of automatically, reliably and naturally understanding what a human subject desires to do. Although intention detection is not restricted to disabled people, such methods can be crucial in improving a patient's life, e.g., aiding control of a robotic wheelchair or of a self-powered prosthesis. Traditionally, intention detection is done using, e.g., gaze tracking, surface electromyography and electroencephalography. In this paper we present exciting initial results of an experiment aimed at intention detection using a high-spatial-resolution, high-dynamic-range tactile sensor. The tactile image of the ventral side of the forearm of 9 able-bodied participants was recorded during a variable-force task stimulated at the fingertip. Both the forces at the fingertip and at the forearm were synchronously recorded. We show that a standard dimensionality reduction technique (Principal Component Analysis) plus a Support Vector Machine attain almost perfect detection accuracy of the direction and the intensity of the intended force. This paves the way for high spatial resolution tactile sensors to be used as a means for intention detection.

Quantitative analysis on electrooculography (EOG) for neurodegenerative disease

NASA Astrophysics Data System (ADS)

Liu, Chang-Chia; Chaovalitwongse, W. Art; Pardalos, Panos M.; Seref, Onur; Xanthopoulos, Petros; Sackellares, J. C.; Skidmore, Frank M.

2007-11-01

Many studies have documented abnormal horizontal and vertical eye movements in human neurodegenerative disease as well as during altered states of consciousness (including drowsiness and intoxication) in healthy adults. Eye movement measurement may play an important role measuring the progress of neurodegenerative diseases and state of alertness in healthy individuals. There are several techniques for measuring eye movement, Infrared detection technique (IR). Video-oculography (VOG), Scleral eye coil and EOG. Among those available recording techniques, EOG is a major source for monitoring the abnormal eye movement. In this real-time quantitative analysis study, the methods which can capture the characteristic of the eye movement were proposed to accurately categorize the state of neurodegenerative subjects. The EOG recordings were taken while 5 tested subjects were watching a short (>120 s) animation clip. In response to the animated clip the participants executed a number of eye movements, including vertical smooth pursued (SVP), horizontal smooth pursued (HVP) and random saccades (RS). Detection of abnormalities in ocular movement may improve our diagnosis and understanding a neurodegenerative disease and altered states of consciousness. A standard real-time quantitative analysis will improve detection and provide a better understanding of pathology in these disorders.

Decision Support System for Medical Care Quality Assessment Based on Health Records Analysis in Russia.

PubMed

Taranik, Maksim; Kopanitsa, Georgy

2017-01-01

The paper presents developed decision system, oriented for healthcare providers. The system allows healthcare providers to detect and decrease nonconformities in health records and forecast the sum of insurance payments taking into account nonconformities. The components are ISO13606, fuzzy logic and case-based reasoning concept. The result of system implementation allowed to 10% increase insurance payments for healthcare provider.

Simulate different environments TDLAS On the analysis of the test signal strength

NASA Astrophysics Data System (ADS)

Li, Xin; Zhou, Tao; Jia, Xiaodong

2014-12-01

TDLAS system is the use of the wavelength tuning characteristics of the laser diode, for detecting the absorption spectrum of the gas absorption line. Detecting the gas space, temperature, pressure and flow rate and concentration. The use of laboratory techniques TDLAS gas detection, experimental simulation engine combustion water vapor and smoke. using an optical lens system receives the signal acquisition and signal interference test analysis. Analog water vapor and smoke in two different environments in the sample pool interference. In both experiments environmental interference gas absorption in the optical signal acquisition, signal amplitude variation analysis, and records related to the signal data. In order to study site conditions in the engine combustion process for signal acquisition provides an ideal experimental data .

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

Detection of traffic incidents using nonlinear time series analysis

NASA Astrophysics Data System (ADS)

Fragkou, A. D.; Karakasidis, T. E.; Nathanail, E.

2018-06-01

In this study, we present results of the application of nonlinear time series analysis on traffic data for incident detection. More specifically, we analyze daily volume records of Attica Tollway (Greece) collected from sensors located at various locations. The analysis was performed using the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) method of the volume data of the lane closest to the median. The results show that it is possible to identify, through the abrupt change of the dynamics of the system revealed by RPs and RQA, the occurrence of incidents on the freeway and differentiate from recurrent traffic congestion. The proposed methodology could be of interest for big data traffic analysis.

Influence of erroneous patient records on population pharmacokinetic modeling and individual bayesian estimation.

PubMed

van der Meer, Aize Franciscus; Touw, Daniël J; Marcus, Marco A E; Neef, Cornelis; Proost, Johannes H

2012-10-01

Observational data sets can be used for population pharmacokinetic (PK) modeling. However, these data sets are generally less precisely recorded than experimental data sets. This article aims to investigate the influence of erroneous records on population PK modeling and individual maximum a posteriori Bayesian (MAPB) estimation. A total of 1123 patient records of neonates who were administered vancomycin were used for population PK modeling by iterative 2-stage Bayesian (ITSB) analysis. Cut-off values for weighted residuals were tested for exclusion of records from the analysis. A simulation study was performed to assess the influence of erroneous records on population modeling and individual MAPB estimation. Also the cut-off values for weighted residuals were tested in the simulation study. Errors in registration have limited the influence on outcomes of population PK modeling but can have detrimental effects on individual MAPB estimation. A population PK model created from a data set with many registration errors has little influence on subsequent MAPB estimates for precisely recorded data. A weighted residual value of 2 for concentration measurements has good discriminative power for identification of erroneous records. ITSB analysis and its individual estimates are hardly affected by most registration errors. Large registration errors can be detected by weighted residuals of concentration.

QRS Detection Algorithm for Telehealth Electrocardiogram Recordings.

PubMed

Khamis, Heba; Weiss, Robert; Xie, Yang; Chang, Chan-Wei; Lovell, Nigel H; Redmond, Stephen J

2016-07-01

QRS detection algorithms are needed to analyze electrocardiogram (ECG) recordings generated in telehealth environments. However, the numerous published QRS detectors focus on clean clinical data. Here, a "UNSW" QRS detection algorithm is described that is suitable for clinical ECG and also poorer quality telehealth ECG. The UNSW algorithm generates a feature signal containing information about ECG amplitude and derivative, which is filtered according to its frequency content and an adaptive threshold is applied. The algorithm was tested on clinical and telehealth ECG and the QRS detection performance is compared to the Pan-Tompkins (PT) and Gutiérrez-Rivas (GR) algorithm. For the MIT-BIH Arrhythmia database (virtually artifact free, clinical ECG), the overall sensitivity (Se) and positive predictivity (+P) of the UNSW algorithm was >99%, which was comparable to PT and GR. When applied to the MIT-BIH noise stress test database (clinical ECG with added calibrated noise) after artifact masking, all three algorithms had overall Se >99%, and the UNSW algorithm had higher +P (98%, p < 0.05) than PT and GR. For 250 telehealth ECG records (unsupervised recordings; dry metal electrodes), the UNSW algorithm had 98% Se and 95% +P which was superior to PT (+P: p < 0.001) and GR (Se and +P: p < 0.001). This is the first study to describe a QRS detection algorithm for telehealth data and evaluate it on clinical and telehealth ECG with superior results to published algorithms. The UNSW algorithm could be used to manage increasing telehealth ECG analysis workloads.

The Feasibility of Using Large-Scale Text Mining to Detect Adverse Childhood Experiences in a VA-Treated Population.

PubMed

Hammond, Kenric W; Ben-Ari, Alon Y; Laundry, Ryan J; Boyko, Edward J; Samore, Matthew H

2015-12-01

Free text in electronic health records resists large-scale analysis. Text records facts of interest not found in encoded data, and text mining enables their retrieval and quantification. The U.S. Department of Veterans Affairs (VA) clinical data repository affords an opportunity to apply text-mining methodology to study clinical questions in large populations. To assess the feasibility of text mining, investigation of the relationship between exposure to adverse childhood experiences (ACEs) and recorded diagnoses was conducted among all VA-treated Gulf war veterans, utilizing all progress notes recorded from 2000-2011. Text processing extracted ACE exposures recorded among 44.7 million clinical notes belonging to 243,973 veterans. The relationship of ACE exposure to adult illnesses was analyzed using logistic regression. Bias considerations were assessed. ACE score was strongly associated with suicide attempts and serious mental disorders (ORs = 1.84 to 1.97), and less so with behaviorally mediated and somatic conditions (ORs = 1.02 to 1.36) per unit. Bias adjustments did not remove persistent associations between ACE score and most illnesses. Text mining to detect ACE exposure in a large population was feasible. Analysis of the relationship between ACE score and adult health conditions yielded patterns of association consistent with prior research. Copyright © 2015 International Society for Traumatic Stress Studies.

Robust QRS peak detection by multimodal information fusion of ECG and blood pressure signals.

PubMed

Ding, Quan; Bai, Yong; Erol, Yusuf Bugra; Salas-Boni, Rebeca; Zhang, Xiaorong; Hu, Xiao

2016-11-01

QRS peak detection is a challenging problem when ECG signal is corrupted. However, additional physiological signals may also provide information about the QRS position. In this study, we focus on a unique benchmark provided by PhysioNet/Computing in Cardiology Challenge 2014 and Physiological Measurement focus issue: robust detection of heart beats in multimodal data, which aimed to explore robust methods for QRS detection in multimodal physiological signals. A dataset of 200 training and 210 testing records are used, where the testing records are hidden for evaluating the performance only. An information fusion framework for robust QRS detection is proposed by leveraging existing ECG and ABP analysis tools and combining heart beats derived from different sources. Results show that our approach achieves an overall accuracy of 90.94% and 88.66% on the training and testing datasets, respectively. Furthermore, we observe expected performance at each step of the proposed approach, as an evidence of the effectiveness of our approach. Discussion on the limitations of our approach is also provided.

Hidden Process Models

DTIC Science & Technology

2009-12-18

cannot be detected with univariate techniques, but require multivariate analysis instead (Kamitani and Tong [2005]). Two other time series analysis ...learning for time series analysis . The historical record of DBNs can be traced back to Dean and Kanazawa [1988] and Dean and Wellman [1991], with...Rev. 8-98) Prescribed by ANSI Std Z39-18 Keywords: Hidden Process Models, probabilistic time series modeling, functional Magnetic Resonance Imaging

Recording human cortical population spikes non-invasively--An EEG tutorial.

PubMed

Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel

2015-07-30

Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.

Motion analysis for duplicate frame removal in wireless capsule endoscope

NASA Astrophysics Data System (ADS)

Lee, Hyun-Gyu; Choi, Min-Kook; Lee, Sang-Chul

2011-03-01

Wireless capsule endoscopy (WCE) has been intensively researched recently due to its convenience for diagnosis and extended detection coverage of some diseases. Typically, a full recording covering entire human digestive system requires about 8 to 12 hours for a patient carrying a capsule endoscope and a portable image receiver/recorder unit, which produces 120,000 image frames on average. In spite of the benefits of close examination, WCE based test has a barrier for quick diagnosis such that a trained diagnostician must examine a huge amount of images for close investigation, normally over 2 hours. The main purpose of our work is to present a novel machine vision approach to reduce diagnosis time by automatically detecting duplicated recordings caused by backward camera movement, typically containing redundant information, in small intestine. The developed technique could be integrated with a visualization tool which supports intelligent inspection method, such as automatic play speed control. Our experimental result shows high accuracy of the technique by detecting 989 duplicate image frames out of 10,000, equivalently to 9.9% data reduction, in a WCE video from a real human subject. With some selected parameters, we achieved the correct detection ratio of 92.85% and the false detection ratio of 13.57%.

Estimating challenge load due to disease outbreaks and other challenges using reproduction records of sows.

PubMed

Mathur, P K; Herrero-Medrano, J M; Alexandri, P; Knol, E F; ten Napel, J; Rashidi, H; Mulder, H A

2014-12-01

A method was developed and tested to estimate challenge load due to disease outbreaks and other challenges in sows using reproduction records. The method was based on reproduction records from a farm with known disease outbreaks. It was assumed that the reduction in weekly reproductive output within a farm is proportional to the magnitude of the challenge. As the challenge increases beyond certain threshold, it is manifested as an outbreak. The reproduction records were divided into 3 datasets. The first dataset called the Training dataset consisted of 57,135 reproduction records from 10,901 sows from 1 farm in Canada with several outbreaks of porcine reproductive and respiratory syndrome (PRRS). The known disease status of sows was regressed on the traits number born alive, number of losses as a combination of still birth and mummified piglets, and number of weaned piglets. The regression coefficients from this analysis were then used as weighting factors for derivation of an index measure called challenge load indicator. These weighting factors were derived with i) a two-step approach using residuals or year-week solutions estimated from a previous step, and ii) a single-step approach using the trait values directly. Two types of models were used for each approach: a logistic regression model and a general additive model. The estimates of challenge load indicator were then compared based on their ability to detect PRRS outbreaks in a Test dataset consisting of records from 65,826 sows from 15 farms in the Netherlands. These farms differed from the Canadian farm with respect to PRRS virus strains, severity and frequency of outbreaks. The single-step approach using a general additive model was best and detected 14 out of the 15 outbreaks. This approach was then further validated using the third dataset consisting of reproduction records of 831,855 sows in 431 farms located in different countries in Europe and America. A total of 41 out of 48 outbreaks detected using data analysis were confirmed based on diagnostic information received from the farms. Among these, 30 outbreaks were due to PRRS while 11 were due to other diseases and challenging conditions. The results suggest that proposed method could be useful for estimation of challenge load and detection of challenge phases such as disease outbreaks.

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis

PubMed Central

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-01-01

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human–machine interaction. PMID:27367687

Microsoft Kinect Visual and Depth Sensors for Breathing and Heart Rate Analysis.

PubMed

Procházka, Aleš; Schätz, Martin; Vyšata, Oldřich; Vališ, Martin

2016-06-28

This paper is devoted to a new method of using Microsoft (MS) Kinect sensors for non-contact monitoring of breathing and heart rate estimation to detect possible medical and neurological disorders. Video sequences of facial features and thorax movements are recorded by MS Kinect image, depth and infrared sensors to enable their time analysis in selected regions of interest. The proposed methodology includes the use of computational methods and functional transforms for data selection, as well as their denoising, spectral analysis and visualization, in order to determine specific biomedical features. The results that were obtained verify the correspondence between the evaluation of the breathing frequency that was obtained from the image and infrared data of the mouth area and from the thorax movement that was recorded by the depth sensor. Spectral analysis of the time evolution of the mouth area video frames was also used for heart rate estimation. Results estimated from the image and infrared data of the mouth area were compared with those obtained by contact measurements by Garmin sensors (www.garmin.com). The study proves that simple image and depth sensors can be used to efficiently record biomedical multidimensional data with sufficient accuracy to detect selected biomedical features using specific methods of computational intelligence. The achieved accuracy for non-contact detection of breathing rate was 0.26% and the accuracy of heart rate estimation was 1.47% for the infrared sensor. The following results show how video frames with depth data can be used to differentiate different kinds of breathing. The proposed method enables us to obtain and analyse data for diagnostic purposes in the home environment or during physical activities, enabling efficient human-machine interaction.

Analysis of capture-recapture models with individual covariates using data augmentation

USGS Publications Warehouse

Royle, J. Andrew

2009-01-01

I consider the analysis of capture-recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles (Microtus pennsylvanicus) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double-observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability.

Improvement of a picking algorithm real-time P-wave detection by kurtosis

NASA Astrophysics Data System (ADS)

Ishida, H.; Yamada, M.

2016-12-01

Earthquake early warning (EEW) requires fast and accurate P-wave detection. The current EEW system in Japan uses the STA/LTAalgorithm (Allen, 1978) to detect P-wave arrival.However, some stations did not trigger during the 2011 Great Tohoku Earthquake due to the emergent onset. In addition, accuracy of the P-wave detection is very important: on August 1, 2016, the EEW issued a false alarm with M9 in Tokyo region due to a thunder noise.To solve these problems, we use a P-wave detection method using kurtosis statistics. It detects the change of statistic distribution of the waveform amplitude. This method was recently developed (Saragiotis et al., 2002) and used for off-line analysis such as making seismic catalogs. To apply this method for EEW, we need to remove an acausal calculation and enable a real-time processing. Here, we propose a real-time P-wave detection method using kurtosis statistics with a noise filter.To avoid false triggering by a noise, we incorporated a simple filter to classify seismic signal and noise. Following Kong et al. (2016), we used the interquartilerange and zero cross rate for the classification. The interquartile range is an amplitude measure that is equal to the middle 50% of amplitude in a certain time window. The zero cross rate is a simple frequency measure that counts the number of times that the signal crosses baseline zero. A discriminant function including these measures was constructed by the linear discriminant analysis.To test this kurtosis method, we used strong motion records for 62 earthquakes between April, 2005 and July, 2015, which recorded the seismic intensity greater equal to 6 lower in the JMA intensity scale. The records with hypocentral distance < 200km were used for the analysis. An attached figure shows the error of P-wave detection speed for STA/LTA and kurtosis methods against manual picks. It shows that the median error is 0.13 sec and 0.035 sec for STA/LTA and kurtosis method. The kurtosis method tends to be more sensitive to small changes in amplitude.Our approach will contribute to improve the accuracy of source location determination of earthquakes and improve the shaking intensity estimation for an earthquake early warning.

Quantitative complexity analysis in multi-channel intracranial EEG recordings form epilepsy brains

PubMed Central

Liu, Chang-Chia; Pardalos, Panos M.; Chaovalitwongse, W. Art; Shiau, Deng-Shan; Ghacibeh, Georges; Suharitdamrong, Wichai; Sackellares, J. Chris

2008-01-01

Epilepsy is a brain disorder characterized clinically by temporary but recurrent disturbances of brain function that may or may not be associated with destruction or loss of consciousness and abnormal behavior. Human brain is composed of more than 10 to the power 10 neurons, each of which receives electrical impulses known as action potentials from others neurons via synapses and sends electrical impulses via a sing output line to a similar (the axon) number of neurons. When neuronal networks are active, they produced a change in voltage potential, which can be captured by an electroencephalogram (EEG). The EEG recordings represent the time series that match up to neurological activity as a function of time. By analyzing the EEG recordings, we sought to evaluate the degree of underlining dynamical complexity prior to progression of seizure onset. Through the utilization of the dynamical measurements, it is possible to classify the state of the brain according to the underlying dynamical properties of EEG recordings. The results from two patients with temporal lobe epilepsy (TLE), the degree of complexity start converging to lower value prior to the epileptic seizures was observed from epileptic regions as well as non-epileptic regions. The dynamical measurements appear to reflect the changes of EEG’s dynamical structure. We suggest that the nonlinear dynamical analysis can provide a useful information for detecting relative changes in brain dynamics, which cannot be detected by conventional linear analysis. PMID:19079790

Performance analysis of a generalized upset detection procedure

NASA Technical Reports Server (NTRS)

Blough, Douglas M.; Masson, Gerald M.

1987-01-01

A general procedure for upset detection in complex systems, called the data block capture and analysis upset monitoring process is described and analyzed. The process consists of repeatedly recording a fixed amount of data from a set of predetermined observation lines of the system being monitored (i.e., capturing a block of data), and then analyzing the captured block in an attempt to determine whether the system is functioning correctly. The algorithm which analyzes the data blocks can be characterized in terms of the amount of time it requires to examine a given length data block to ascertain the existence of features/conditions that have been predetermined to characterize the upset-free behavior of the system. The performance of linear, quadratic, and logarithmic data analysis algorithms is rigorously characterized in terms of three performance measures: (1) the probability of correctly detecting an upset; (2) the expected number of false alarms; and (3) the expected latency in detecting upsets.

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

PubMed Central

Biffi, E.; Ghezzi, D.; Pedrocchi, A.; Ferrigno, G.

2010-01-01

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems. PMID:20300592

Nuclear particle detection using a track-recording solid

NASA Technical Reports Server (NTRS)

Weber, M.; Weber, D.

1984-01-01

The design of the nuclear particle detector located in Purdue University's Get Away Special package which was flown aboard STS-7 is detailed. The experiment consisted of a stack of particle-detecting polymer sheets. The sheets show positive results of tracks throughout the block. A slide of each sheet was made for further analysis. Recommendations for similar experiments performed in the future are discussed.

Whistler-like Signals Detected Simultaneously by Swarm Satellites

NASA Astrophysics Data System (ADS)

Hulot, G.; Coisson, P.; Deram, P.; Leger, J. M.; Jager, T.; Brocco, L.

2016-12-01

The three Swarm satellites embark an absolute scalar magnetometer (ASM) that generates nominally 1 Hz filtered data of the intensity of the magnetic field. Its internal frequency of operation however allows to record data at higher sampling rate, generating so-called "burst-mode" data at 250 Hz. During the commissioning phase of the Swarm mission, between December 2013 and February 2014 several burst-mode sessions have been recorded. At the beginning the satellites were still on a pearls-on-string orbital configuration and later each satellite was successively moved to its final orbit. During the last two burst sessions satellites B and C were still following each other, while satellite A was already orbiting at a lower altitude, on the opposite side of the Earth. We present an analysis of the burst data recorded on 22 and 23 February 2014, when several short signals were detected, usually lasting less than 1 second, presenting a descending tone in the frequency band accessible using burst data (1-125 Hz), similar to the whistlers signals in VLF band. These signals were detected nearly simultaneously by satellites B and C, at about 300 km distance, corresponding to a horizontal speed of about 1500 km/s. We present an analysis of these events and of their coincidence with lighting activity on the ground in the area of visibility of these satellites, as provided by the WWLN.

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

PubMed

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

2017-12-01

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

Automated detection of follow-up appointments using text mining of discharge records.

PubMed

Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

2010-06-01

To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

The use of automated bioacoustic recorders to replace human wildlife surveys: an example using nightjars.

PubMed

Zwart, Mieke C; Baker, Andrew; McGowan, Philip J K; Whittingham, Mark J

2014-01-01

To be able to monitor and protect endangered species, we need accurate information on their numbers and where they live. Survey methods using automated bioacoustic recorders offer significant promise, especially for species whose behaviour or ecology reduces their detectability during traditional surveys, such as the European nightjar. In this study we examined the utility of automated bioacoustic recorders and the associated classification software as a way to survey for wildlife, using the nightjar as an example. We compared traditional human surveys with results obtained from bioacoustic recorders. When we compared these two methods using the recordings made at the same time as the human surveys, we found that recorders were better at detecting nightjars. However, in practice fieldworkers are likely to deploy recorders for extended periods to make best use of them. Our comparison of this practical approach with human surveys revealed that recorders were significantly better at detecting nightjars than human surveyors: recorders detected nightjars during 19 of 22 survey periods, while surveyors detected nightjars on only six of these occasions. In addition, there was no correlation between the amount of vocalisation captured by the acoustic recorders and the abundance of nightjars as recorded by human surveyors. The data obtained from the recorders revealed that nightjars were most active just before dawn and just after dusk, and least active during the middle of the night. As a result, we found that recording at both dusk and dawn or only at dawn would give reasonably high levels of detection while significantly reducing recording time, preserving battery life. Our analyses suggest that automated bioacoustic recorders could increase the detection of other species, particularly those that are known to be difficult to detect using traditional survey methods. The accuracy of detection is especially important when the data are used to inform conservation.

Detection and analysis of radio frequency lightning emissions

NASA Technical Reports Server (NTRS)

Jalali, F.

1982-01-01

The feasibility study of detection of lightning discharges from a geosynchronous satellite requires adequate ground-based information regarding emission characteristics. In this investigation, a measurement system for collection of S-band emission data is set up and calibrated, and the operations procedures for rapid data collection during a storm activity developed. The system collects emission data in two modes; a digitized, high-resolution, short duration record stored in solid-state memory, and a continuous long-duration record on magnetic tape. Representative lightning flash data are shown. Preliminary results indicate appreciable RF emissions at 2 gHz from both the leader and return strokes portions of the cloud-to-ground discharge with strong peaks associated with the return strokes.

SpotMetrics: An Open-Source Image-Analysis Software Plugin for Automatic Chromatophore Detection and Measurement.

PubMed

Hadjisolomou, Stavros P; El-Haddad, George

2017-01-01

Coleoid cephalopods (squid, octopus, and sepia) are renowned for their elaborate body patterning capabilities, which are employed for camouflage or communication. The specific chromatic appearance of a cephalopod, at any given moment, is a direct result of the combined action of their intradermal pigmented chromatophore organs and reflecting cells. Therefore, a lot can be learned about the cephalopod coloration system by video recording and analyzing the activation of individual chromatophores in time. The fact that adult cephalopods have small chromatophores, up to several hundred thousand in number, makes measurement and analysis over several seconds a difficult task. However, current advancements in videography enable high-resolution and high framerate recording, which can be used to record chromatophore activity in more detail and accuracy in both space and time domains. In turn, the additional pixel information and extra frames per video from such recordings result in large video files of several gigabytes, even when the recording spans only few minutes. We created a software plugin, "SpotMetrics," that can automatically analyze high resolution, high framerate video of chromatophore organ activation in time. This image analysis software can track hundreds of individual chromatophores over several hundred frames to provide measurements of size and color. This software may also be used to measure differences in chromatophore activation during different behaviors which will contribute to our understanding of the cephalopod sensorimotor integration system. In addition, this software can potentially be utilized to detect numbers of round objects and size changes in time, such as eye pupil size or number of bacteria in a sample. Thus, we are making this software plugin freely available as open-source because we believe it will be of benefit to other colleagues both in the cephalopod biology field and also within other disciplines.

Statistical methods for change-point detection in surface temperature records

NASA Astrophysics Data System (ADS)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

Automated acoustic analysis in detection of spontaneous swallows in Parkinson's disease.

PubMed

Golabbakhsh, Marzieh; Rajaei, Ali; Derakhshan, Mahmoud; Sadri, Saeed; Taheri, Masoud; Adibi, Peyman

2014-10-01

Acoustic monitoring of swallow frequency has become important as the frequency of spontaneous swallowing can be an index for dysphagia and related complications. In addition, it can be employed as an objective quantification of ingestive behavior. Commonly, swallowing complications are manually detected using videofluoroscopy recordings, which require expensive equipment and exposure to radiation. In this study, a noninvasive automated technique is proposed that uses breath and swallowing recordings obtained via a microphone located over the laryngopharynx. Nonlinear diffusion filters were used in which a scale-space decomposition of recorded sound at different levels extract swallows from breath sounds and artifacts. This technique was compared to manual detection of swallows using acoustic signals on a sample of 34 subjects with Parkinson's disease. A speech language pathologist identified five subjects who showed aspiration during the videofluoroscopic swallowing study. The proposed automated method identified swallows with a sensitivity of 86.67 %, a specificity of 77.50 %, and an accuracy of 82.35 %. These results indicate the validity of automated acoustic recognition of swallowing as a fast and efficient approach to objectively estimate spontaneous swallow frequency.

Automated electrohysterographic detection of uterine contractions for monitoring of pregnancy: feasibility and prospects.

PubMed

Muszynski, C; Happillon, T; Azudin, K; Tylcz, J-B; Istrate, D; Marque, C

2018-05-08

Preterm birth is a major public health problem in developed countries. In this context, we have conducted research into outpatient monitoring of uterine electrical activity in women at risk of preterm delivery. The objective of this preliminary study was to perform automated detection of uterine contractions (without human intervention or tocographic signal, TOCO) by processing the EHG recorded on the abdomen of pregnant women. The feasibility and accuracy of uterine contraction detection based on EHG processing were tested and compared to expert decision using external tocodynamometry (TOCO) . The study protocol was approved by local Ethics Committees under numbers ID-RCB 2016-A00663-48 for France and VSN 02-0006-V2 for Iceland. Two populations of women were included (threatened preterm birth and labour) in order to test our system of recognition of the various types of uterine contractions. EHG signal acquisition was performed according to a standardized protocol to ensure optimal reproducibility of EHG recordings. A system of 18 Ag/AgCl surface electrodes was used by placing 16 recording electrodes between the woman's pubis and umbilicus according to a 4 × 4 matrix. TOCO was recorded simultaneously with EHG recording. EHG signals were analysed in real-time by calculation of the nonlinear correlation coefficient H 2 . A curve representing the number of correlated pairs of signals according to the value of H 2 calculated between bipolar signals was then plotted. High values of H 2 indicated the presence of an event that may correspond to a contraction. Two tests were performed after detection of an event (fusion and elimination of certain events) in order to increase the contraction detection rate. The EHG database contained 51 recordings from pregnant women, with a total of 501 contractions previously labelled by analysis of the corresponding tocographic recording. The percentage recognitions obtained by application of the method based on coefficient H 2 was 100% with 782% of false alarms. Addition of fusion and elimination tests to the previously obtained detections allowed the false alarm rate to be divided by 8.5, while maintaining an excellent detection rate (96%). These preliminary results appear to be encouraging for monitoring of uterine contractions by algorithm-based automated detection to process the electrohysterographic signal (EHG). This compact recording system, based on the use of surface electrodes attached to the skin, appears to be particularly suitable for outpatient monitoring of uterine contractions, possibly at home, allowing telemonitoring of pregnancies. One of the advantages of EHG processing is that useful information concerning contraction efficiency can be extracted from this signal, which is not possible with the TOCO signal.

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

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

Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the datamore » into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.« less

Detection of changes of high-frequency activity by statistical time-frequency analysis in epileptic spikes

PubMed Central

Kobayashi, Katsuhiro; Jacobs, Julia; Gotman, Jean

2013-01-01

Objective A novel type of statistical time-frequency analysis was developed to elucidate changes of high-frequency EEG activity associated with epileptic spikes. Methods The method uses the Gabor Transform and detects changes of power in comparison to background activity using t-statistics that are controlled by the false discovery rate (FDR) to correct type I error of multiple testing. The analysis was applied to EEGs recorded at 2000 Hz from three patients with mesial temporal lobe epilepsy. Results Spike-related increase of high-frequency oscillations (HFOs) was clearly shown in the FDR-controlled t-spectra: it was most dramatic in spikes recorded from the hippocampus when the hippocampus was the seizure onset zone (SOZ). Depression of fast activity was observed immediately after the spikes, especially consistently in the discharges from the hippocampal SOZ. It corresponded to the slow wave part in case of spike-and-slow-wave complexes, but it was noted even in spikes without apparent slow waves. In one patient, a gradual increase of power above 200 Hz preceded spikes. Conclusions FDR-controlled t-spectra clearly detected the spike-related changes of HFOs that were unclear in standard power spectra. Significance We developed a promising tool to study the HFOs that may be closely linked to the pathophysiology of epileptogenesis. PMID:19394892

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach.

PubMed

Krug, Johannes W; Rose, Georg; Clifford, Gari D; Oster, Julien

2013-11-19

In Cardiovascular Magnetic Resonance (CMR), the synchronization of image acquisition with heart motion is performed in clinical practice by processing the electrocardiogram (ECG). The ECG-based synchronization is well established for MR scanners with magnetic fields up to 3 T. However, this technique is prone to errors in ultra high field environments, e.g. in 7 T MR scanners as used in research applications. The high magnetic fields cause severe magnetohydrodynamic (MHD) effects which disturb the ECG signal. Image synchronization is thus less reliable and yields artefacts in CMR images. A strategy based on Independent Component Analysis (ICA) was pursued in this work to enhance the ECG contribution and attenuate the MHD effect. ICA was applied to 12-lead ECG signals recorded inside a 7 T MR scanner. An automatic source identification procedure was proposed to identify an independent component (IC) dominated by the ECG signal. The identified IC was then used for detecting the R-peaks. The presented ICA-based method was compared to other R-peak detection methods using 1) the raw ECG signal, 2) the raw vectorcardiogram (VCG), 3) the state-of-the-art gating technique based on the VCG, 4) an updated version of the VCG-based approach and 5) the ICA of the VCG. ECG signals from eight volunteers were recorded inside the MR scanner. Recordings with an overall length of 87 min accounting for 5457 QRS complexes were available for the analysis. The records were divided into a training and a test dataset. In terms of R-peak detection within the test dataset, the proposed ICA-based algorithm achieved a detection performance with an average sensitivity (Se) of 99.2%, a positive predictive value (+P) of 99.1%, with an average trigger delay and jitter of 5.8 ms and 5.0 ms, respectively. Long term stability of the demixing matrix was shown based on two measurements of the same subject, each being separated by one year, whereas an averaged detection performance of Se = 99.4% and +P = 99.7% was achieved.Compared to the state-of-the-art VCG-based gating technique at 7 T, the proposed method increased the sensitivity and positive predictive value within the test dataset by 27.1% and 42.7%, respectively. The presented ICA-based method allows the estimation and identification of an IC dominated by the ECG signal. R-peak detection based on this IC outperforms the state-of-the-art VCG-based technique in a 7 T MR scanner environment.

A Healthcare Utilization Analysis Framework for Hot Spotting and Contextual Anomaly Detection

PubMed Central

Hu, Jianying; Wang, Fei; Sun, Jimeng; Sorrentino, Robert; Ebadollahi, Shahram

2012-01-01

Patient medical records today contain vast amount of information regarding patient conditions along with treatment and procedure records. Systematic healthcare resource utilization analysis leveraging such observational data can provide critical insights to guide resource planning and improve the quality of care delivery while reducing cost. Of particular interest to providers are hot spotting: the ability to identify in a timely manner heavy users of the systems and their patterns of utilization so that targeted intervention programs can be instituted, and anomaly detection: the ability to identify anomalous utilization cases where the patients incurred levels of utilization that are unexpected given their clinical characteristics which may require corrective actions. Past work on medical utilization pattern analysis has focused on disease specific studies. We present a framework for utilization analysis that can be easily applied to any patient population. The framework includes two main components: utilization profiling and hot spotting, where we use a vector space model to represent patient utilization profiles, and apply clustering techniques to identify utilization groups within a given population and isolate high utilizers of different types; and contextual anomaly detection for utilization, where models that map patient’s clinical characteristics to the utilization level are built in order to quantify the deviation between the expected and actual utilization levels and identify anomalies. We demonstrate the effectiveness of the framework using claims data collected from a population of 7667 diabetes patients. Our analysis demonstrates the usefulness of the proposed approaches in identifying clinically meaningful instances for both hot spotting and anomaly detection. In future work we plan to incorporate additional sources of observational data including EMRs and disease registries, and develop analytics models to leverage temporal relationships among medical encounters to provide more in-depth insights. PMID:23304306

A healthcare utilization analysis framework for hot spotting and contextual anomaly detection.

PubMed

Hu, Jianying; Wang, Fei; Sun, Jimeng; Sorrentino, Robert; Ebadollahi, Shahram

2012-01-01

Patient medical records today contain vast amount of information regarding patient conditions along with treatment and procedure records. Systematic healthcare resource utilization analysis leveraging such observational data can provide critical insights to guide resource planning and improve the quality of care delivery while reducing cost. Of particular interest to providers are hot spotting: the ability to identify in a timely manner heavy users of the systems and their patterns of utilization so that targeted intervention programs can be instituted, and anomaly detection: the ability to identify anomalous utilization cases where the patients incurred levels of utilization that are unexpected given their clinical characteristics which may require corrective actions. Past work on medical utilization pattern analysis has focused on disease specific studies. We present a framework for utilization analysis that can be easily applied to any patient population. The framework includes two main components: utilization profiling and hot spotting, where we use a vector space model to represent patient utilization profiles, and apply clustering techniques to identify utilization groups within a given population and isolate high utilizers of different types; and contextual anomaly detection for utilization, where models that map patient's clinical characteristics to the utilization level are built in order to quantify the deviation between the expected and actual utilization levels and identify anomalies. We demonstrate the effectiveness of the framework using claims data collected from a population of 7667 diabetes patients. Our analysis demonstrates the usefulness of the proposed approaches in identifying clinically meaningful instances for both hot spotting and anomaly detection. In future work we plan to incorporate additional sources of observational data including EMRs and disease registries, and develop analytics models to leverage temporal relationships among medical encounters to provide more in-depth insights.

Sensitivity quantification of remote detection NMR and MRI

NASA Astrophysics Data System (ADS)

Granwehr, J.; Seeley, J. A.

2006-04-01

A sensitivity analysis is presented of the remote detection NMR technique, which facilitates the spatial separation of encoding and detection of spin magnetization. Three different cases are considered: remote detection of a transient signal that must be encoded point-by-point like a free induction decay, remote detection of an experiment where the transient dimension is reduced to one data point like phase encoding in an imaging experiment, and time-of-flight (TOF) flow visualization. For all cases, the sensitivity enhancement is proportional to the relative sensitivity between the remote detector and the circuit that is used for encoding. It is shown for the case of an encoded transient signal that the sensitivity does not scale unfavorably with the number of encoded points compared to direct detection. Remote enhancement scales as the square root of the ratio of corresponding relaxation times in the two detection environments. Thus, remote detection especially increases the sensitivity of imaging experiments of porous materials with large susceptibility gradients, which cause a rapid dephasing of transverse spin magnetization. Finally, TOF remote detection, in which the detection volume is smaller than the encoded fluid volume, allows partial images corresponding to different time intervals between encoding and detection to be recorded. These partial images, which contain information about the fluid displacement, can be recorded, in an ideal case, with the same sensitivity as the full image detected in a single step with a larger coil.

The construction and periodicity analysis of natural disaster database of Alxa area based on Chinese local records

NASA Astrophysics Data System (ADS)

Yan, Zheng; Mingzhong, Tian; Hengli, Wang

2010-05-01

Chinese hand-written local records were originated from the first century. Generally, these local records include geography, evolution, customs, education, products, people, historical sites, as well as writings of an area. Through such endeavors, the information of the natural materials of China nearly has had no "dark ages" in the evolution of its 5000-year old civilization. A compilation of all meaningful historical data of natural-disasters taken place in Alxa of inner-Mongolia, the second largest desert in China, is used here for the construction of a 500-year high resolution database. The database is divided into subsets according to the types of natural-disasters like sand-dust storm, drought events, cold wave, etc. Through applying trend, correlation, wavelet, and spectral analysis on these data, we can estimate the statistically periodicity of different natural-disasters, detect and quantify similarities and patterns of the periodicities of these records, and finally take these results in aggregate to find a strong and coherent cyclicity through the last 500 years which serves as the driving mechanism of these geological hazards. Based on the periodicity obtained from the above analysis, the paper discusses the probability of forecasting natural-disasters and the suitable measures to reduce disaster losses through history records. Keyword: Chinese local records; Alxa; natural disasters; database; periodicity analysis

Radar mechanocardiography: a novel analysis of the mechanical behavior of the heart.

PubMed

Tavakolian, Kouhyar; Zadeh, Faranak M; Chuo, Yindar; Siu, Tiffany; Vaseghi, Ali; Kaminska, Bozena

2008-01-01

In this paper a novel system for detection of the mechanical movement of heart, mechanocardiography (MCG), with no connection to the subject's body is presented. This signal is based on radar technology. The acquired signal is highly correlated to the acceleration-based ballistocardiograph signal (BCG) recorded directly from the sternum. It is shown that the heart and breathing rates can be reliably detected using this system.

Automatic burst detection for the EEG of the preterm infant.

PubMed

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

2011-10-01

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

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

PubMed Central

Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

PubMed

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Review of health maintenance program findings, 1960-1974

NASA Technical Reports Server (NTRS)

White, E. S.

1975-01-01

A preliminary analysis of the employee's examination records of the automated medical data base at the NASA Wallops Flight Center, Va., with an emphasis on the primary mission of the program-the early detection and control of cardiovascular disease, is presented.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

Optimisation of Embryonic and Larval ECG Measurement in Zebrafish for Quantifying the Effect of QT Prolonging Drugs

PubMed Central

Dhillon, Sundeep Singh; Dóró, Éva; Magyary, István; Egginton, Stuart; Sík, Attila; Müller, Ferenc

2013-01-01

Effective chemical compound toxicity screening is of paramount importance for safe cardiac drug development. Using mammals in preliminary screening for detection of cardiac dysfunction by electrocardiography (ECG) is costly and requires a large number of animals. Alternatively, zebrafish embryos can be used as the ECG waveform is similar to mammals, a minimal amount of chemical is necessary for drug testing, while embryos are abundant, inexpensive and represent replacement in animal research with reduced bioethical concerns. We demonstrate here the utility of pre-feeding stage zebrafish larvae in detection of cardiac dysfunction by electrocardiography. We have optimised an ECG recording system by addressing key parameters such as the form of immobilization, recording temperature, electrode positioning and developmental age. Furthermore, analysis of 3 days post fertilization (dpf) zebrafish embryos treated with known QT prolonging drugs such as terfenadine, verapamil and haloperidol led to reproducible detection of QT prolongation as previously shown for adult zebrafish. In addition, calculation of Z-factor scores revealed that the assay was sensitive and specific enough to detect large drug-induced changes in QTc intervals. Thus, the ECG recording system is a useful drug-screening tool to detect alteration to cardiac cycle components and secondary effects such as heart block and arrhythmias in zebrafish larvae before free feeding stage, and thus provides a suitable replacement for mammalian experimentation. PMID:23579446

40 CFR 63.11457 - What are the recordkeeping requirements?

Code of Federal Regulations, 2010 CFR

2010-07-01

... calibration and maintenance records. (7) For each bag leak detection system, the records specified in paragraphs (a)(7)(i) through (iii) of this section. (i) Records of the bag leak detection system output; (ii) Records of bag leak detection system adjustments, including the date and time of the adjustment, the...

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

PubMed

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Detection and Classification of Motor Vehicle Noise in a Forested Landscape

NASA Astrophysics Data System (ADS)

Brown, Casey L.; Reed, Sarah E.; Dietz, Matthew S.; Fristrup, Kurt M.

2013-11-01

Noise emanating from human activity has become a common addition to natural soundscapes and has the potential to harm wildlife and erode human enjoyment of nature. In particular, motor vehicles traveling along roads and trails produce high levels of both chronic and intermittent noise, eliciting varied responses from a wide range of animal species. Anthropogenic noise is especially conspicuous in natural areas where ambient background sound levels are low. In this article, we present an acoustic method to detect and analyze motor vehicle noise. Our approach uses inexpensive consumer products to record sound, sound analysis software to automatically detect sound events within continuous recordings and measure their acoustic properties, and statistical classification methods to categorize sound events. We describe an application of this approach to detect motor vehicle noise on paved, gravel, and natural-surface roads, and off-road vehicle trails in 36 sites distributed throughout a national forest in the Sierra Nevada, CA, USA. These low-cost, unobtrusive methods can be used by scientists and managers to detect anthropogenic noise events for many potential applications, including ecological research, transportation and recreation planning, and natural resource management.

A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique

NASA Astrophysics Data System (ADS)

Bocz, Péter; Vinkó, Ákos; Posgay, Zoltán

2018-03-01

This paper presents an automatic method for detecting vertical track irregularities on tramway operation using acceleration measurements on trams. For monitoring of tramway tracks, an unconventional measurement setup is developed, which records the data of 3-axes wireless accelerometers mounted on wheel discs. Accelerations are processed to obtain the vertical track irregularities to determine whether the track needs to be repaired. The automatic detection algorithm is based on time-frequency distribution analysis and determines the defect locations. Admissible limits (thresholds) are given for detecting moderate and severe defects using statistical analysis. The method was validated on frequented tram lines in Budapest and accurately detected severe defects with a hit rate of 100%, with no false alarms. The methodology is also sensitive to moderate and small rail surface defects at the low operational speed.

Seeking a fingerprint: analysis of point processes in actigraphy recording

NASA Astrophysics Data System (ADS)

Gudowska-Nowak, Ewa; Ochab, Jeremi K.; Oleś, Katarzyna; Beldzik, Ewa; Chialvo, Dante R.; Domagalik, Aleksandra; Fąfrowicz, Magdalena; Marek, Tadeusz; Nowak, Maciej A.; Ogińska, Halszka; Szwed, Jerzy; Tyburczyk, Jacek

2016-05-01

Motor activity of humans displays complex temporal fluctuations which can be characterised by scale-invariant statistics, thus demonstrating that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Previous studies on humans regularly deprived of sleep or suffering from sleep disorders predicted a change in the invariant scale parameters with respect to those for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organisation can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterising complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterising slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups.

Infrasonic detection of a near-Earth object impact over Indonesia on 8 October 2009

NASA Astrophysics Data System (ADS)

Silber, Elizabeth A.; Le Pichon, Alexis; Brown, Peter G.

2011-06-01

We present analysis of infrasonic signals produced by a large Earth-impacting fireball, believed to be among the most energetic instrumentally recorded during the last century that occurred on 8 October, 2009 over Indonesia. This extraordinary event, detected by 17 infrasonic stations of the global International Monitoring Network, generated stratospherically ducted infrasound returns at distances up to 17 500 km, the greatest range at which infrasound from a fireball has been detected since the 1908 Tunguska explosion. From these infrasonic records, we find the total source energy for this bolide as 8-67 kilotons of TNT equivalent explosive yield, with the favored best estimate near ˜50 kt. Global impact events of such energy are expected only once per decade and study of their impact effects can provide insight into the impactor threshold levels for ground damage and climate perturbations.

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.

Repeated attempted homicide by administration of drugs documented by hair analysis.

PubMed

Baillif-Couniou, Valérie; Bartoli, Christophe; Sastre, Caroline; Chèze, Marjorie; Deveaux, Marc; Léonetti, Georges; Pélissier-Alicot, Anne-Laure

2018-02-01

Attempted murder by repeated poisoning is quite rare. The authors describe the case of a 62-year-old man who was admitted to an intensive care unit (ICU) for neurological disturbances complicated by inhalation pneumopathy. He presented a loss of consciousness while his wife was visiting him at the ICU (H0). Forty-eight hours later (H48), police officers apprehended the patient's wife pouring a liquid into his fruit salad at the hospital. Toxicological analyses of a blood sample and the infusion equipment (H0), as well as the fruit salad and its container (H48), confirmed the attempted poisoning with cyamemazine (H0) and hydrochloric acid (H48). In order to evaluate the anteriority of poisonings, hair analysis was requested and the medical records of the 6 previous months were also examined. Two 6-cm brown hair strands were sampled and the victim's medical record was seized in order to determine the treatments he had been given during the previous six months. Segmental hair testing on two 6-cm brown hair was conducted by GC-MS, LC-DAD and LC-MS/MS (0-2/2-4/4-6 cm; pg/mg). Haloperidol (9200/1391/227), amitriptyline (7450/1850/3260), venlafaxine (332/560/260), that had never been part of the victim's treatment were detected, as well as some benzodiazepines (alprazolam, bromazepam, nordazepam); cyamemazine was also detected in all the segments (9960/1610/2367) though only a single dose administration was reported in the medical records. The toxicological analyses performed at H0 and H48 confirmed the homicide attempts in the ICU. In addition, comparison of the results in hair analysis with the medical records confirmed repeated poisoning attempts over the previous six months, and thus explain the origin of the disorders presented by the victim. This case serves to remind us that repeated attempted murder can be difficult to diagnose and that hair analysis can be an effective way to detect such attempts. Copyright © 2018. Published by Elsevier Ltd.

Continuous robust sound event classification using time-frequency features and deep learning

PubMed Central

Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification. PMID:28892478

Continuous robust sound event classification using time-frequency features and deep learning.

PubMed

McLoughlin, Ian; Zhang, Haomin; Xie, Zhipeng; Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification.

Printed strain sensors for early damage detection in engineering structures

NASA Astrophysics Data System (ADS)

Zymelka, Daniel; Yamashita, Takahiro; Takamatsu, Seiichi; Itoh, Toshihiro; Kobayashi, Takeshi

2018-05-01

In this paper, we demonstrate the analysis of strain measurements recorded using a screen-printed sensors array bonded to a metal plate and subjected to high strains. The analysis was intended to evaluate the capabilities of the printed strain sensors to detect abnormal strain distribution before actual defects (cracks) in the analyzed structures appear. The results demonstrate that the developed device can accurately localize the enhanced strains at the very early stage of crack formation. The promising performance and low fabrication cost confirm the potential suitability of the printed strain sensors for applications within the framework of structural health monitoring (SHM).

Reduction and analysis of data collected during the electromagnetic tornado experiment

NASA Technical Reports Server (NTRS)

Davisson, L. D.

1976-01-01

Techniques for data processing and analysis are described to support tornado detection by analysis of radio frequency interference in various frequency bands, and sea state determination from short pulse radar measurements. Activities include: strip chart recording of tornado data; the development and implementation of computer programs for digitalization and analysis of the data; data reduction techniques for short pulse radar data, and the simulation of radar returns from the sea surface by computer models.

You Learn by Your Mistakes. Effective Training Strategies Based on the Analysis of Video-Recorded Worked-Out Examples

ERIC Educational Resources Information Center

Cattaneo, Alberto A. P.; Boldrini, Elena

2017-01-01

This paper presents an empirical study on procedural learning from errors that was conducted within the field of vocational education. It examines whether, and to what extent, procedural learning can benefit more from the detection and written analysis of errors (experimental condition) than from the correct elements (control group). The study…

Auto correlation analysis of coda waves from local earthquakes for detecting temporal changes in shallow subsurface structures - The 2011 Tohoku-Oki, Japan, earthquake -

NASA Astrophysics Data System (ADS)

Nakahara, H.

2013-12-01

For monitoring temporal changes in subsurface structures, I propose to use auto correlation functions of coda waves from local earthquakes recorded at surface receivers, which probably contain more body waves than surface waves. Because the use of coda waves requires earthquakes, time resolution for monitoring decreases. But at regions with high seismicity, it may be possible to monitor subsurface structures in sufficient time resolutions. Studying the 2011 Tohoku-Oki (Mw 9.0), Japan, earthquake for which velocity changes have been already reported by previous studies, I try to validate the method. KiK-net stations in northern Honshu are used in the analysis. For each moderate earthquake, normalized auto correlation functions of surface records are stacked with respect to time windows in S-wave coda. Aligning the stacked normalized auto correlation functions with time, I search for changes in arrival times of phases. The phases at lag times of less than 1s are studied because changes at shallow depths are focused. Based on the stretching method, temporal variations in the arrival times are measured at the stations. Clear phase delays are found to be associated with the mainshock and to gradually recover with time. Amounts of the phase delays are in the order of 10% on average with the maximum of about 50% at some stations. For validation, the deconvolution analysis using surface and subsurface records at the same stations are conducted. The results show that the phase delays from the deconvolution analysis are slightly smaller than those from the auto correlation analysis, which implies that the phases on the auto correlations are caused by larger velocity changes at shallower depths. The auto correlation analysis seems to have an accuracy of about several percents, which is much larger than methods using earthquake doublets and borehole array data. So this analysis might be applicable to detect larger changes. In spite of these disadvantages, this analysis is still attractive because it can be applied to many records on the surface in regions where no boreholes are available. Acknowledgements: Seismograms recorded by KiK-net managed by National Research Institute for Earth Science and Disaster Prevention (NIED) were used in this study. This study was partially supported by JST J-RAPID program and JSPS KAKENHI Grant Numbers 24540449 and 23540449.

Detection of Erroneous Payments Utilizing Supervised And Unsupervised Data Mining Techniques

DTIC Science & Technology

2004-09-01

will look at which statistical analysis technique will work best in developing and enhancing existing erroneous payment models . Chapter I and II... payment models that are used for selection of records to be audited. The models are set up such that if two or more records have the same payment...Identification Number, Invoice Number and Delivery Order Number are not compared. The DM0102 Duplicate Payment Model will be analyzed in this thesis

Burst and Principal Components Analyses of MEA Data Separates Chemicals by Class

EPA Science Inventory

Microelectrode arrays (MEAs) detect drug and chemical induced changes in action potential "spikes" in neuronal networks and can be used to screen chemicals for neurotoxicity. Analytical "fingerprinting," using Principal Components Analysis (PCA) on spike trains recorded from prim...

Total ozone trend over Cairo

NASA Technical Reports Server (NTRS)

Hassan, G. K. Y.

1994-01-01

A world wide interest in protecting ozone layer against manmade effects is now increasing. Assessment of the ozone depletion due to these activities depends on how successfully we can separate the natural variabilities from the data. The monthly mean values of total ozone over Cairo (30 05N) for the period 1968-1988, have been analyzed using the power spectral analysis technique. The technique used in this analysis does not depend on a pre-understanding of the natural fluctuations in the ozone data. The method depends on increasing the resolution of the spectral peaks in order to obtain the more accurate sinusoidal fluctuations with wavelength equal to or less than record length. Also it handles the possible sinusoidal fluctuations with wavelength equal to or less than record length. The results show that it is possible to detect some of the well known national fluctuations in the ozone record such as annual, semiannual, quasi-biennial and quasi-quadrennial oscillations. After separating the natural fluctuations from the ozone record, the trend analysis of total ozone over Cairo showed that a decrease of about -1.2% per decade has occurred since 1979.

Multi-instrument Observations of Transient Luminous Events Associated with a Small-scale Winter Thunderstorm

NASA Astrophysics Data System (ADS)

Kolmasova, I.; Santolik, O.; Spurny, P.; Borovicka, J.; Mlynarczyk, J.; Popek, M.; Lan, R.; Uhlir, L.; Diendorfer, G.; Slosiar, R.

2017-12-01

We present observations of transient luminous events (TLEs) produced by a small-scale winter thunderstorm which occurred on 2 April 2017 in the southwest of Czechia. Elves, sprites and associated positive lightning strokes have been simultaneously recorded by different observational techniques. Optical data include video recordings of TLEs from Nydek (Czechia) and data recorded by high time-resolution photometers at several stations of the Czech fireball network which measured the all-sky brightness originating from lightning return strokes. Electromagnetic data sets include 3-component VLF measurements conducted in Rustrel (France), 2-component ELF measurements recorded at the Hylaty station (Poland) and signal intensity variations of a VLF transmitter (DHO38, Rhauderfehn, Germany) recorded in Bojnice (Slovakia). Optical and electromagnetic data are completed by positions and peak currents of all strokes recorded during the observed thunderstorm by the EUCLID lightning detection network. We focus our analysis on positive lightning discharges with high peak currents and we compare properties of those which produced TLE with properties of discharges for which TLE was not detected. The current moment waveforms and charge moment changes associated with the TLE events are reconstructed from the ELF electromagnetic signals. Obtained current moment waveforms show excellent agreement with high time-resolution optical data.

Fine Structure of the Outermost Solid Core from Analysis of PKiKP Coda Waves

NASA Astrophysics Data System (ADS)

Krasnoshchekov, D.; Kaazik, P.; Ovtchinnikov, V.

2006-05-01

Near surface heterogeneities in the Earth's inner core have recently been confirmed to exist, and pods of partial melt or variations in seismic anisotropy either due to orientation of iron crystals or changes in strength were indicated as possible sources for such peculiarities. In the same time, analysis of the phase reflected from the inner core boundary (PKiKP) predicts complex character of the reflecting discontinuity in the form of local thin transition layers resulting in mosaic structure of the Earth's inner core's surface. Precritical PKiKP waveforms and coda waves provide necessary seismological constraints to investigate fine structure of the upper part of the Earth's inner core and its boundary, and rank high among researches that detected the described specifics of the solid core. PKiKP coda studies have to do with weak amplitudes and subtle effects, which frequently requires using a reference core related seismic phase and array data processing, as well as eliminating max number of factors biasing the resulting estimates (for example, source related inaccuracies typical for earthquake analysis). In this work we report new observations of PKiKP coda waves detected on records of a group of Underground Nuclear Explosions (UNEs) carried out in USSR and recorded at distances from 6 to 95 degrees by stations of the world seismological network. Our dataset benefits from using accurate ground truth information on source parameters (locations, origin times, depths, etc.), requires no accounting for different source radiation patterns and contains records corresponding to the whole range of precritical reflection including so called transparent zone where amplitudes of direct PKiKP phase are negligible. The processed dataset incorporates records of the array of sources consisted of the same magnitude explosions closely carried out at Semipalatinsk Test Site and recorded by stations located in Eurasia, Africa and North America. We detect PKiKP coda waves on records of all stations that registered this array. The performed frequency-wavenumber analysis and stacking of the array data reveal both scattering mechanism tracked in the form of slight dependence of PKiKP coda's frequency content on epicentral distance, and reflective mechanism evidenced by detection of distinct arrivals of waves reflected from isotropic or anisotropic discontinuities below the inner core boundary. We infer, that PKiKP coda is built by both volumetric scattering and reverberations on reflectors in the upper portion of the inner core. We also find no significant evidence for the presence of a constant depth global isotropic reflector all through 300 km below the ICB and attribute different types of the observed PKiKP coda patterns to variability in properties of the outermost portion of the Earth's inner core either due to its anisotropy or local specifics. The research described was made possible in part by contribution from grant RUG1-2675-MO-05 of the US Civilian Research & Development Foundation for the Independent States of the Former Soviet Union (CRDF) and the President Grant MK-1600.2005.5.

The Effects of Promoting Patient Access to Medical Records: A Review

PubMed Central

Ross, Stephen E.; Lin, Chen-Tan

2003-01-01

The Health Insurance Privacy and Portability Act (HIPPA) stipulates that patients must be permitted to review and amend their medical records. As information technology makes medical records more accessible to patients, it may become more commonplace for patients to review their records routinely. This article analyzes the potential benefits and drawbacks of facilitating patient access to the medical record by reviewing previously published research. Previous research includes analysis of clinical notes, surveys of patients and practitioners, and studies of patient-accessible medical records. Overall, studies suggest the potential for modest benefits (for instance, in enhancing doctor-patient communication). Risks (for instance, increasing patient worry or confusion) appear to be minimal in medical patients. The studies, however, were of limited quality and low statistical power to detect the variety of outcomes that may result from implementation of a patient-accessible medical record. The data from these studies lay the foundation for future research. PMID:12595402

[Prognostic value of chosen parameters of mechanical and bioelectrical uterine activity in prediction of threatening preterm labour].

PubMed

Zietek, Jerzy; Sikora, Jerzy; Horoba, Krzysztof; Matonia, Adam; Jezewski, Janusz; Magnucki, Jacek; Kobielska, Lucyna

2009-03-01

To record and analyse bioelectrical activity of the uterine muscle in the course of physiological pregnancy, labour and threatening premature labour; to define which parameters from the analysis of both electrohysterogram and mechanical activity signal allow us to predict threatening premature labour. Material comprised 62 pregnant women: Group I--27 patients in their first physiological pregnancy, Group II--21 patients in their first pregnancy with symptoms of threatening premature labour, and Group III--14 patients in the first labour period. The on-line analysis of the mechanical (TOCO) and electrical (EHG) contraction activity relied on determination of quantitative parameters of detected uterine contractions. The obtained statistical results demonstrated a possibility to differentiate between Group I and II through the amplitude and contraction area for EHG signal, and only the contraction amplitude for TOCO signal. Additionally, significant differentiating parameters for electrohysterogram are: contraction power and its median frequency. Analyzing Group I and III, significant differences were noted for contraction amplitude and area obtained both from EHG and TOCO signals. Similarly, the contraction power (from EHG) enables us to assign the contractions either to records from Group I or to labour type. There was no significant difference noted between Group II and III. Identification of pregnant women at risk of premature labour should lead to their inclusion in rigorous perinatal surveillance. This requires novel, more sensitive methods that are able to detect early symptoms of the uterine contraction activity increase. Electrohysterography provides complete information on principles of bioelectrical uterine activity. Quantitative parameters of EHG analysis enable the detection of records (contractions) with the symptoms of premature uterine contraction activity.

Pulse oximetry recorded from the Phone Oximeter for detection of obstructive sleep apnea events with and without oxygen desaturation in children.

PubMed

Garde, Ainara; Dehkordi, Parastoo; Wensley, David; Ansermino, J Mark; Dumont, Guy A

2015-01-01

Obstructive sleep apnea (OSA) disrupts normal ventilation during sleep and can lead to serious health problems in children if left untreated. Polysomnography, the gold standard for OSA diagnosis, is resource intensive and requires a specialized laboratory. Thus, we proposed to use the Phone Oximeter™, a portable device integrating pulse oximetry with a smartphone, to detect OSA events. As a proportion of OSA events occur without oxygen desaturation (defined as SpO2 decreases ≥ 3%), we suggest combining SpO2 and pulse rate variability (PRV) analysis to identify all OSA events and provide a more detailed sleep analysis. We recruited 160 children and recorded pulse oximetry consisting of SpO2 and plethysmography (PPG) using the Phone Oximeter™, alongside standard polysomnography. A sleep technician visually scored all OSA events with and without oxygen desaturation from polysomnography. We divided pulse oximetry signals into 1-min signal segments and extracted several features from SpO2 and PPG analysis in the time and frequency domain. Segments with OSA, especially the ones with oxygen desaturation, presented greater SpO2 variability and modulation reflected in the spectral domain than segments without OSA. Segments with OSA also showed higher heart rate and sympathetic activity through the PRV analysis relative to segments without OSA. PRV analysis was more sensitive than SpO2 analysis for identification of OSA events without oxygen desaturation. Combining SpO2 and PRV analysis enhanced OSA event detection through a multiple logistic regression model. The area under the ROC curve increased from 81% to 87%. Thus, the Phone Oximeter™ might be useful to monitor sleep and identify OSA events with and without oxygen desaturation at home.

Measurement, time-stamping, and analysis of electrodermal activity in fMRI

NASA Astrophysics Data System (ADS)

Smyser, Christopher; Grabowski, Thomas J.; Rainville, Pierre; Bechara, Antione; Razavi, Mehrdad; Mehta, Sonya; Eaton, Brent L.; Bolinger, Lizann

2002-04-01

A low cost fMRI-compatible system was developed for detecting electrodermal activity without inducing image artifact. Subject electrodermal activity was measured on the plantar surface of the foot using a standard recording circuit. Filtered analog skin conductance responses (SCR) were recorded with a general purpose, time-stamping data acquisition system. A conditioning paradigm involving painful thermal stimulation was used to demonstrate SCR detection and investigate neural correlates of conditioned autonomic activity. 128x128 pixel EPI-BOLD images were acquired with a GE 1.5T Signa scanner. Image analysis was performed using voxel-wise multiple linear regression. The covariate of interest was generated by convolving stimulus event onset with a standard hemodynamic response function. The function was time-shifted to determine optimal activation. Significance was tested using the t-statistic. Image quality was unaffected by the device, and conditioned and unconditioned SCRs were successfully detected. Conditioned SCRs correlated significantly with activity in the right anterior insular cortex. The effect was more robust when responses were scaled by SCR amplitude. The ability to measure and time register SCRs during fMRI acquisition enables studies of cognitive processes marked by autonomic activity, including those involving decision-making, pain, emotion, and addiction.

Detection of Transionospheric SuperDARN HF Waves by the Radio Receiver Instrument on the enhanced Polar Outflow Probe Satellite

NASA Astrophysics Data System (ADS)

Gillies, R. G.; Yau, A. W.; James, H. G.; Hussey, G. C.; McWilliams, K. A.

2014-12-01

The enhanced Polar Outflow Probe (ePOP) Canadian small-satellite was launched in September 2013. Included in this suite of eight scientific instruments is the Radio Receiver Instrument (RRI). The RRI has been used to measure VLF and HF radio waves from various ground and spontaneous ionospheric sources. The first dedicated ground transmission that was detected by RRI was from the Saskatoon Super Dual Auroral Radar Network (SuperDARN) radar on Nov. 7, 2013 at 14 MHz. Several other passes over the Saskatoon SuperDARN radar have been recorded since then. Ground transmissions have also been observed from other radars, such as the SPEAR, HAARP, and SURA ionospheric heaters. However, the focus of this study will be on the results obtained from the SuperDARN passes. An analysis of the signal recorded by the RRI provides estimates of signal power, Doppler shift, polarization, absolute time delay, differential mode delay, and angle of arrival. By comparing these parameters to similar parameters derived from ray tracing simulations, ionospheric electron density structures may be detected and measured. Further analysis of the results from the other ground transmitters and future SuperDARN passes will be used to refine these results.

Using bivariate signal analysis to characterize the epileptic focus: the benefit of surrogates.

PubMed

Andrzejak, R G; Chicharro, D; Lehnertz, K; Mormann, F

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

Using bivariate signal analysis to characterize the epileptic focus: The benefit of surrogates

NASA Astrophysics Data System (ADS)

Andrzejak, R. G.; Chicharro, D.; Lehnertz, K.; Mormann, F.

2011-04-01

The disease epilepsy is related to hypersynchronous activity of networks of neurons. While acute epileptic seizures are the most extreme manifestation of this hypersynchronous activity, an elevated level of interdependence of neuronal dynamics is thought to persist also during the seizure-free interval. In multichannel recordings from brain areas involved in the epileptic process, this interdependence can be reflected in an increased linear cross correlation but also in signal properties of higher order. Bivariate time series analysis comprises a variety of approaches, each with different degrees of sensitivity and specificity for interdependencies reflected in lower- or higher-order properties of pairs of simultaneously recorded signals. Here we investigate which approach is best suited to detect putatively elevated interdependence levels in signals recorded from brain areas involved in the epileptic process. For this purpose, we use the linear cross correlation that is sensitive to lower-order signatures of interdependence, a nonlinear interdependence measure that integrates both lower- and higher-order properties, and a surrogate-corrected nonlinear interdependence measure that aims to specifically characterize higher-order properties. We analyze intracranial electroencephalographic recordings of the seizure-free interval from 29 patients with an epileptic focus located in the medial temporal lobe. Our results show that all three approaches detect higher levels of interdependence for signals recorded from the brain hemisphere containing the epileptic focus as compared to signals recorded from the opposite hemisphere. For the linear cross correlation, however, these differences are not significant. For the nonlinear interdependence measure, results are significant but only of moderate accuracy with regard to the discriminative power for the focal and nonfocal hemispheres. The highest significance and accuracy is obtained for the surrogate-corrected nonlinear interdependence measure.

EEGgui: a program used to detect electroencephalogram anomalies after traumatic brain injury.

PubMed

Sick, Justin; Bray, Eric; Bregy, Amade; Dietrich, W Dalton; Bramlett, Helen M; Sick, Thomas

2013-05-21

Identifying and quantifying pathological changes in brain electrical activity is important for investigations of brain injury and neurological disease. An example is the development of epilepsy, a secondary consequence of traumatic brain injury. While certain epileptiform events can be identified visually from electroencephalographic (EEG) or electrocorticographic (ECoG) records, quantification of these pathological events has proved to be more difficult. In this study we developed MATLAB-based software that would assist detection of pathological brain electrical activity following traumatic brain injury (TBI) and present our MATLAB code used for the analysis of the ECoG. Software was developed using MATLAB(™) and features of the open access EEGLAB. EEGgui is a graphical user interface in the MATLAB programming platform that allows scientists who are not proficient in computer programming to perform a number of elaborate analyses on ECoG signals. The different analyses include Power Spectral Density (PSD), Short Time Fourier analysis and Spectral Entropy (SE). ECoG records used for demonstration of this software were derived from rats that had undergone traumatic brain injury one year earlier. The software provided in this report provides a graphical user interface for displaying ECoG activity and calculating normalized power density using fast fourier transform of the major brain wave frequencies (Delta, Theta, Alpha, Beta1, Beta2 and Gamma). The software further detects events in which power density for these frequency bands exceeds normal ECoG by more than 4 standard deviations. We found that epileptic events could be identified and distinguished from a variety of ECoG phenomena associated with normal changes in behavior. We further found that analysis of spectral entropy was less effective in distinguishing epileptic from normal changes in ECoG activity. The software presented here was a successful modification of EEGLAB in the Matlab environment that allows detection of epileptiform ECoG signals in animals after TBI. The code allows import of large EEG or ECoG data records as standard text files and uses fast fourier transform as a basis for detection of abnormal events. The software can also be used to monitor injury-induced changes in spectral entropy if required. We hope that the software will be useful for other investigators in the field of traumatic brain injury and will stimulate future advances of quantitative analysis of brain electrical activity after neurological injury or disease.

Auto Correlation Analysis of Coda Waves from Local Earthquakes for Detecting Temporal Changes in Shallow Subsurface Structures: the 2011 Tohoku-Oki, Japan Earthquake

NASA Astrophysics Data System (ADS)

Nakahara, Hisashi

2015-02-01

For monitoring temporal changes in subsurface structures I propose to use auto correlation functions of coda waves from local earthquakes recorded at surface receivers, which probably contain more body waves than surface waves. Use of coda waves requires earthquakes resulting in decreased time resolution for monitoring. Nonetheless, it may be possible to monitor subsurface structures in sufficient time resolutions in regions with high seismicity. In studying the 2011 Tohoku-Oki, Japan earthquake (Mw 9.0), for which velocity changes have been previously reported, I try to validate the method. KiK-net stations in northern Honshu are used in this analysis. For each moderate earthquake normalized auto correlation functions of surface records are stacked with respect to time windows in the S-wave coda. Aligning the stacked, normalized auto correlation functions with time, I search for changes in phases arrival times. The phases at lag times of <1 s are studied because changes at shallow depths are focused. Temporal variations in the arrival times are measured at the stations based on the stretching method. Clear phase delays are found to be associated with the mainshock and to gradually recover with time. The amounts of the phase delays are 10 % on average with the maximum of about 50 % at some stations. The deconvolution analysis using surface and subsurface records at the same stations is conducted for validation. The results show the phase delays from the deconvolution analysis are slightly smaller than those from the auto correlation analysis, which implies that the phases on the auto correlations are caused by larger velocity changes at shallower depths. The auto correlation analysis seems to have an accuracy of about several percent, which is much larger than methods using earthquake doublets and borehole array data. So this analysis might be applicable in detecting larger changes. In spite of these disadvantages, this analysis is still attractive because it can be applied to many records on the surface in regions where no boreholes are available.

Long-period Seismicity at the Napoleonville Salt Dome: Implications for Local Seismic Monitoring of Underground Hydrocarbon Storage Caverns

NASA Astrophysics Data System (ADS)

Dreger, D. S.; Ford, S. R.; Nayak, A.

2015-12-01

The formation of a large sinkhole at the Napoleonville salt dome, Assumption Parish, Louisiana, in August 2012 was accompanied by a rich sequence of complex seismic events, including long-period (LP) events that were recorded 11 km away at Transportable Array station 544A in White Castle, Louisiana. The LP events have relatively little energy at short periods, which make them difficult to detect using standard high-frequency power detectors, and the majority of energy that reaches the station is peaked near 0.4 Hz. The analysis of the local records reveals that the onset of the 0.4 Hz signals coincides with the S-wave arrival, and therefore it may be a shaking induced resonance in a fluid filled cavern. We created a low-frequency (0.1-0.6 Hz) power detector (short-term average / long-term average) that operated on all three components of the broadband instrument, since considerable energy was detected on the horizontal components. The detections from the power detector were then used as templates in three-channel correlation detectors thereby increasing the number of detections by a little more than a factor of two to nearly 3000. The rate of LP events is approximately one event every other day at the beginning of recording in March 2011. Around 2 May 2012 the rate changes to approximately 7 events per day and then increases to 25 events per day at the beginning of July 2012. Finally, in the days leading up to the sinkhole formation there are approximately 200 LP events per day. The analysis of these events could aid in the development of local seismic monitoring methods for underground industrial storage caverns. Prepared by LLNL under Contract DE-AC52-07NA27344.

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Godiwala, P. M.

1985-01-01

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.

Study of Sedative-Hypnotic Effects of Aloe vera L. Aqueous Extract through Behavioral Evaluations and EEG Recording in Rats

PubMed Central

Abdollahnejad, Fatemeh; Mosaddegh, Mahmoud; Nasoohi, Sanaz; Mirnajafi-Zadeh, Javad; Kamalinejad, Mohammad; Faizi, Mehrdad

2016-01-01

In this study, we investigated the sedative and hypnotic effects of the aqueous extract of Aloe vera on rats. In order to evaluate the overall hypnotic effects of the Aloe vera extract, open field and loss of righting reflex tests were primarily used. The sedative and hypnotic effects of the extract were then confirmed by detection of remarkable raise in the total sleeping time through analysis of electroencephalographic (EEG) recordings of animals. Analysis of the EEG recordings showed that there is concomitant change in Rapid Eye Movement (REM) and None Rapid Eye Movement (NREM) sleep in parallel with the prolonged total sleeping time. Results of the current research show that the extract has sedative-hypnotic effects on both functional and electrical activities of the brain. PMID:27610170

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively

PubMed Central

Shimamoto, Shoichi; Waldman, Zachary J.; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R.; Weiss, Shennan A.

2018-01-01

Objective To develop and validate a detector that identifies ripple (80–200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). Methods iEEG recordings from 16 patients were first band-pass filtered (80–600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. Results The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). Conclusions Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Significance Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers. PMID:29113719

Active matrix-based collection of airborne analytes: an analyte recording chip providing exposure history and finger print.

PubMed

Fang, Jun; Park, Se-Chul; Schlag, Leslie; Stauden, Thomas; Pezoldt, Jörg; Jacobs, Heiko O

2014-12-03

In the field of sensors that target the detection of airborne analytes, Corona/lens-based-collection provides a new path to achieve a high sensitivity. An active-matrix-based analyte collection approach referred to as "airborne analyte memory chip/recorder" is demonstrated, which takes and stores airborne analytes in a matrix to provide an exposure history for off-site analysis. © 2014 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

AFLP-based genetic diversity assessment of commercially important tea germplasm in India.

PubMed

Sharma, R K; Negi, M S; Sharma, S; Bhardwaj, P; Kumar, R; Bhattachrya, E; Tripathi, S B; Vijayan, D; Baruah, A R; Das, S C; Bera, B; Rajkumar, R; Thomas, J; Sud, R K; Muraleedharan, N; Hazarika, M; Lakshmikumaran, M; Raina, S N; Ahuja, P S

2010-08-01

India has a large repository of important tea accessions and, therefore, plays a major role in improving production and quality of tea across the world. Using seven AFLP primer combinations, we analyzed 123 commercially important tea accessions representing major populations in India. The overall genetic similarity recorded was 51%. No significant differences were recorded in average genetic similarity among tea populations cultivated in various geographic regions (northwest 0.60, northeast and south both 0.59). UPGMA cluster analysis grouped the tea accessions according to geographic locations, with a bias toward China or Assam/Cambod types. Cluster analysis results were congruent with principal component analysis. Further, analysis of molecular variance detected a high level of genetic variation (85%) within and limited genetic variation (15%) among the populations, suggesting their origin from a similar genetic pool.

Using presence of sign to measure habitats used by Roosevelt elk

USGS Publications Warehouse

Weckerly, Floyd W.; Ricca, Mark A.

2000-01-01

tract Radiotelemetry and pellet-group surveys are methods used commonly to measure habi- tat use by large ungulates. However, telemetry can be expensive and analysis of data col- lected from pellet-group surveys is restricted to rank analysis. We explored the feasibil- ity of recording the presence of Roosevelt elk (Cervus elaphus roosevelti) sign to identify habitats used by elk. We surveyed stations (1-ha circular plots) about 0.72 km apart for the presence of 0- to 4-day-old elk sign (tracks and feces) from October to April 1994-1997 at 2 sites in northwestern California. Our objectives were to: 1) measure errors in detecting and classifying elk presence at stations from sign, 2) determine auto- correlation of elk sign at stations to assess what is an independent data point, 3) examine the effect of 2 station sizes on the rate of sign detections, and 4) determine sample sizes needed to detect habitat use. We detected elk sign 96.6% of the time (n=68) when elk were observed at stations within 0-4 days. Elk sign was misclassified only 3 times (n= 70). No autocorrelations in sign detections across time or space were detected because observed data were similar to sign generated randomly at stations. The proportion of 1-ha (0.12) and 2-ha stations (0.13) with sign was similar. Sample sizes >400 were need- ed to have power >0.8 to detect relationships among habitat variables and frequency of sign at stations. Recording the presence of sign in stations appears to be a reliable and feasible technique to measure habitats used by elk.

Detection of Anomalous Insiders in Collaborative Environments via Relational Analysis of Access Logs

PubMed Central

Chen, You; Malin, Bradley

2014-01-01

Collaborative information systems (CIS) are deployed within a diverse array of environments, ranging from the Internet to intelligence agencies to healthcare. It is increasingly the case that such systems are applied to manage sensitive information, making them targets for malicious insiders. While sophisticated security mechanisms have been developed to detect insider threats in various file systems, they are neither designed to model nor to monitor collaborative environments in which users function in dynamic teams with complex behavior. In this paper, we introduce a community-based anomaly detection system (CADS), an unsupervised learning framework to detect insider threats based on information recorded in the access logs of collaborative environments. CADS is based on the observation that typical users tend to form community structures, such that users with low a nity to such communities are indicative of anomalous and potentially illicit behavior. The model consists of two primary components: relational pattern extraction and anomaly detection. For relational pattern extraction, CADS infers community structures from CIS access logs, and subsequently derives communities, which serve as the CADS pattern core. CADS then uses a formal statistical model to measure the deviation of users from the inferred communities to predict which users are anomalies. To empirically evaluate the threat detection model, we perform an analysis with six months of access logs from a real electronic health record system in a large medical center, as well as a publicly-available dataset for replication purposes. The results illustrate that CADS can distinguish simulated anomalous users in the context of real user behavior with a high degree of certainty and with significant performance gains in comparison to several competing anomaly detection models. PMID:25485309

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

NASA Astrophysics Data System (ADS)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Highly scalable parallel processing of extracellular recordings of Multielectrode Arrays.

PubMed

Gehring, Tiago V; Vasilaki, Eleni; Giugliano, Michele

2015-01-01

Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.

Identifying past fire regimes throughout the Holocene in Ireland using new and established methods of charcoal analysis

NASA Astrophysics Data System (ADS)

Hawthorne, Donna; Mitchell, Fraser J. G.

2016-04-01

Globally, in recent years there has been an increase in the scale, intensity and level of destruction caused by wildfires. This can be seen in Ireland where significant changes in vegetation, land use, agriculture and policy, have promoted an increase in fires in the Irish landscape. This study looks at wildfire throughout the Holocene and draws on lacustrine charcoal records from seven study sites spread across Ireland, to reconstruct the past fire regimes recorded at each site. This work utilises new and accepted methods of fire history reconstruction to provide a recommended analytical procedure for statistical charcoal analysis. Digital charcoal counting was used and fire regime reconstructions carried out via the CharAnalysis programme. To verify this record new techniques are employed; an Ensemble-Member strategy to remove the objectivity associated with parameter selection, a Signal to Noise Index to determine if the charcoal record is appropriate for peak detection, and a charcoal peak screening procedure to validate the identified fire events based on bootstrapped samples. This analysis represents the first study of its kind in Ireland, examining the past record of fire on a multi-site and paleoecological timescale, and will provide a baseline level of data which can be built on in the future when the frequency and intensity of fire is predicted to increase.

Methods for automatic detection of artifacts in microelectrode recordings.

PubMed

Bakštein, Eduard; Sieger, Tomáš; Wild, Jiří; Novák, Daniel; Schneider, Jakub; Vostatek, Pavel; Urgošík, Dušan; Jech, Robert

2017-10-01

Extracellular microelectrode recording (MER) is a prominent technique for studies of extracellular single-unit neuronal activity. In order to achieve robust results in more complex analysis pipelines, it is necessary to have high quality input data with a low amount of artifacts. We show that noise (mainly electromagnetic interference and motion artifacts) may affect more than 25% of the recording length in a clinical MER database. We present several methods for automatic detection of noise in MER signals, based on (i) unsupervised detection of stationary segments, (ii) large peaks in the power spectral density, and (iii) a classifier based on multiple time- and frequency-domain features. We evaluate the proposed methods on a manually annotated database of 5735 ten-second MER signals from 58 Parkinson's disease patients. The existing methods for artifact detection in single-channel MER that have been rigorously tested, are based on unsupervised change-point detection. We show on an extensive real MER database that the presented techniques are better suited for the task of artifact identification and achieve much better results. The best-performing classifiers (bagging and decision tree) achieved artifact classification accuracy of up to 89% on an unseen test set and outperformed the unsupervised techniques by 5-10%. This was close to the level of agreement among raters using manual annotation (93.5%). We conclude that the proposed methods are suitable for automatic MER denoising and may help in the efficient elimination of undesirable signal artifacts. Copyright © 2017 Elsevier B.V. All rights reserved.

Reliability of a portable device for the detection of sleep bruxism.

PubMed

Deregibus, Andrea; Castroflorio, Tommaso; Bargellini, Andrea; Debernardi, Cesare

2014-11-01

The aim of the study was to assess the repeatability in detecting sleep bruxism (SB) episodes by combined surface electromyography and heart rate (HR) signals recorded by a compact portable device (Bruxoff®). SB episodes are preceded by a sudden HR change. Thus, HR detection increases the precision of automatic detection of SB. Ten healthy subjects (five women and five men; 30.2 ± 11.02 years) were selected for the study. Rhythmic masseter muscle activities, constituting the basic pattern of SB, were detected during three nights of recording during three different weeks with the Bruxoff device. The two-way ANOVA was not significant for SB episodes per night, SB episodes per hour, and heart frequency: no significant differences were observed during the three different nights of recording for each of the abovementioned variables (P > 0.05). The intraclass correlation coefficient showed a good reproducibility for SB episodes per night (69 %), SB per hour (74 %), and heart frequency (82 %). A poor reproducibility was revealed for the number of masseter contractions (53 %). The Pearson analysis showed the absence of a significant correlation between the number of masseter contractions per night and the number of SB episodes per night (r = -0.02, P = 0.91). The Bruxoff device showed a good reproducibility of measurements of sleep bruxism episodes over time. These findings are important in the light of the need for simple and reliable portable devices for the diagnosis of SB both in the clinical and research settings.

Genetic component in learning ability in bees.

PubMed

Kerr, W E; Moura Duarte, F A; Oliveira, R S

1975-10-01

Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.

Optimizing detection and analysis of slow waves in sleep EEG.

PubMed

Mensen, Armand; Riedner, Brady; Tononi, Giulio

2016-12-01

Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploitation of the IMS and Other Data for a Comprehensive Advanced Analysis of the North Korean Nuclear Tests

DTIC Science & Technology

2010-02-01

vertical component records in a six-second window starting near the Lg detection time. Because our signal measurements are taken from the broadband...from the 2009 test. That is, comparable Love waves may have been generated by the 2006 test, but not at detectable levels. Secondary tectonic...kt., respectively.  Relative yield estimates based on Lg observations from the two tests are generally consistent with the yield estimates obtained

Time-Frequency Analyses of Tide-Gauge Sensor Data

PubMed Central

Erol, Serdar

2011-01-01

The real world phenomena being observed by sensors are generally non-stationary in nature. The classical linear techniques for analysis and modeling natural time-series observations are inefficient and should be replaced by non-linear techniques of whose theoretical aspects and performances are varied. In this manner adopting the most appropriate technique and strategy is essential in evaluating sensors’ data. In this study, two different time-series analysis approaches, namely least squares spectral analysis (LSSA) and wavelet analysis (continuous wavelet transform, cross wavelet transform and wavelet coherence algorithms as extensions of wavelet analysis), are applied to sea-level observations recorded by tide-gauge sensors, and the advantages and drawbacks of these methods are reviewed. The analyses were carried out using sea-level observations recorded at the Antalya-II and Erdek tide-gauge stations of the Turkish National Sea-Level Monitoring System. In the analyses, the useful information hidden in the noisy signals was detected, and the common features between the two sea-level time series were clarified. The tide-gauge records have data gaps in time because of issues such as instrumental shortcomings and power outages. Concerning the difficulties of the time-frequency analysis of data with voids, the sea-level observations were preprocessed, and the missing parts were predicted using the neural network method prior to the analysis. In conclusion the merits and limitations of the techniques in evaluating non-stationary observations by means of tide-gauge sensors records were documented and an analysis strategy for the sequential sensors observations was presented. PMID:22163829

Time-frequency analyses of tide-gauge sensor data.

PubMed

Erol, Serdar

2011-01-01

The real world phenomena being observed by sensors are generally non-stationary in nature. The classical linear techniques for analysis and modeling natural time-series observations are inefficient and should be replaced by non-linear techniques of whose theoretical aspects and performances are varied. In this manner adopting the most appropriate technique and strategy is essential in evaluating sensors' data. In this study, two different time-series analysis approaches, namely least squares spectral analysis (LSSA) and wavelet analysis (continuous wavelet transform, cross wavelet transform and wavelet coherence algorithms as extensions of wavelet analysis), are applied to sea-level observations recorded by tide-gauge sensors, and the advantages and drawbacks of these methods are reviewed. The analyses were carried out using sea-level observations recorded at the Antalya-II and Erdek tide-gauge stations of the Turkish National Sea-Level Monitoring System. In the analyses, the useful information hidden in the noisy signals was detected, and the common features between the two sea-level time series were clarified. The tide-gauge records have data gaps in time because of issues such as instrumental shortcomings and power outages. Concerning the difficulties of the time-frequency analysis of data with voids, the sea-level observations were preprocessed, and the missing parts were predicted using the neural network method prior to the analysis. In conclusion the merits and limitations of the techniques in evaluating non-stationary observations by means of tide-gauge sensors records were documented and an analysis strategy for the sequential sensors observations was presented.

Ultrasensitive, self-calibrated cavity ring-down spectrometer for quantitative trace gas analysis.

PubMed

Chen, Bing; Sun, Yu R; Zhou, Ze-Yi; Chen, Jian; Liu, An-Wen; Hu, Shui-Ming

2014-11-10

A cavity ring-down spectrometer is built for trace gas detection using telecom distributed feedback (DFB) diode lasers. The longitudinal modes of the ring-down cavity are used as frequency markers without active-locking either the laser or the high-finesse cavity. A control scheme is applied to scan the DFB laser frequency, matching the cavity modes one by one in sequence and resulting in a correct index at each recorded spectral data point, which allows us to calibrate the spectrum with a relative frequency precision of 0.06 MHz. Besides the frequency precision of the spectrometer, a sensitivity (noise-equivalent absorption) of 4×10^-11  cm^-1  Hz^-1/2 has also been demonstrated. A minimum detectable absorption coefficient of 5×10^-12  cm^-1 has been obtained by averaging about 100 spectra recorded in 2  h. The quantitative accuracy is tested by measuring the CO₂ concentrations in N₂ samples prepared by the gravimetric method, and the relative deviation is less than 0.3%. The trace detection capability is demonstrated by detecting CO₂ of ppbv-level concentrations in a high-purity nitrogen gas sample. Simple structure, high sensitivity, and good accuracy make the instrument very suitable for quantitative trace gas analysis.

Automatic Fatigue Detection of Drivers through Yawning Analysis

NASA Astrophysics Data System (ADS)

Azim, Tayyaba; Jaffar, M. Arfan; Ramzan, M.; Mirza, Anwar M.

This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The focus of the paper is on how to detect yawning which is an important cue for determining driver's fatigue. Initially, the face is located through Viola-Jones face detection method in a video frame. Then, a mouth window is extracted from the face region, in which lips are searched through spatial fuzzy c-means (s-FCM) clustering. The degree of mouth openness is extracted on the basis of mouth features, to determine driver's yawning state. If the yawning state of the driver persists for several consecutive frames, the system concludes that the driver is non-vigilant due to fatigue and is thus warned through an alarm. The system reinitializes when occlusion or misdetection occurs. Experiments were carried out using real data, recorded in day and night lighting conditions, and with users belonging to different race and gender.

Impact of OSHA final rule--recording hearing loss: an analysis of an industrial audiometric dataset.

PubMed

Rabinowitz, Peter M; Slade, Martin; Dixon-Ernst, Christine; Sircar, Kanta; Cullen, Mark

2003-12-01

The 2003 Occupational Safety and Health Administration (OSHA) Occupational Injury and Illness Recording and Reporting Final Rule changed the definition of recordable work-related hearing loss. We performed a study of the Alcoa Inc. audiometric database to evaluate the impact of this new rule. The 2003 rule increased the rate of potentially recordable hearing loss events from 0.2% to 1.6% per year. A total of 68.6% of potentially recordable cases had American Academy of Audiology/American Medical Association (AAO/AMA) hearing impairment at the time of recordability. On average, recordable loss occurred after onset of impairment, whereas the non-age-corrected 10-dB standard threshold shift (STS) usually preceded impairment. The OSHA Final Rule will significantly increase recordable cases of occupational hearing loss. The new case definition is usually accompanied by AAO/AMA hearing impairment. Other, more sensitive metrics should therefore be used for early detection and prevention of hearing loss.

Impact of OSHA Final Rule—Recording Hearing Loss: An Analysis of an Industrial Audiometric Dataset

PubMed Central

Rabinowitz, Peter M.; Slade, Martin; Dixon-Ernst, Christine; Sircar, Kanta; Cullen, Mark

2013-01-01

The 2003 Occupational Safety and Health Administration (OSHA) Occupational Injury and Illness Recording and Reporting Final Rule changed the definition of recordable work-related hearing loss. We performed a study of the Alcoa Inc. audiometric database to evaluate the impact of this new rule. The 2003 rule increased the rate of potentially recordable hearing loss events from 0.2% to 1.6% per year. A total of 68.6% of potentially recordable cases had American Academy of Audiology/American Medical Association (AAO/AMA) hearing impairment at the time of recordability. On average, recordable loss occurred after onset of impairment, whereas the non-age-corrected 10-dB standard threshold shift (STS) usually preceded impairment. The OSHA Final Rule will significantly increase recordable cases of occupational hearing loss. The new case definition is usually accompanied by AAO/AMA hearing impairment. Other, more sensitive metrics should therefore be used for early detection and prevention of hearing loss. PMID:14665813

Speckle correlation method used to measure object's in-plane velocity.

PubMed

Smíd, Petr; Horváth, Pavel; Hrabovský, Miroslav

2007-06-20

We present a measurement of an object's in-plane velocity in one direction by the use of the speckle correlation method. Numerical correlations of speckle patterns recorded periodically during motion of the object under investigation give information used to evaluate the object's in-plane velocity. The proposed optical setup uses a detection plane in the image field and enables one to detect the object's velocity within the interval (10-150) microm x s(-1). Simulation analysis shows a way of controlling the measuring range. The presented theory, simulation analysis, and setup are verified through an experiment of measurement of the velocity profile of an object.

On-line Tool Wear Detection on DCMT070204 Carbide Tool Tip Based on Noise Cutting Audio Signal using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Prasetyo, T.; Amar, S.; Arendra, A.; Zam Zami, M. K.

2018-01-01

This study develops an on-line detection system to predict the wear of DCMT070204 tool tip during the cutting process of the workpiece. The machine used in this research is CNC ProTurn 9000 to cut ST42 steel cylinder. The audio signal has been captured using the microphone placed in the tool post and recorded in Matlab. The signal is recorded at the sampling rate of 44.1 kHz, and the sampling size of 1024. The recorded signal is 110 data derived from the audio signal while cutting using a normal chisel and a worn chisel. And then perform signal feature extraction in the frequency domain using Fast Fourier Transform. Feature selection is done based on correlation analysis. And tool wear classification was performed using artificial neural networks with 33 input features selected. This artificial neural network is trained with back propagation method. Classification performance testing yields an accuracy of 74%.

Workshop on Bridging Satellite Climate Data Gaps.

PubMed

Cooksey, Catherine; Datla, Raju

2011-01-01

Detecting the small signals of climate change for the most essential climate variables requires that satellite sensors make highly accurate and consistent measurements. Data gaps in the time series (such as gaps resulting from launch delay or failure) and inconsistencies in radiometric scales between satellites undermine the credibility of fundamental climate data records, and can lead to erroneous analysis in climate change detection. To address these issues, leading experts in Earth observations from National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Adminstration (NOAA), United States Geological Survey (USGS), and academia assembled at the National Institute of Standards and Technology on December 10, 2009 for a workshop to prioritize strategies for bridging and mitigating data gaps in the climate record. This paper summarizes the priorities for ensuring data continuity of variables relevant to climate change in the areas of atmosphere, land, and ocean measurements and the recommendations made at the workshop for overcoming planned and unplanned gaps in the climate record.

Wrist ambulatory monitoring system and smart glove for real time emotional, sensorial and physiological analysis.

PubMed

Axisa, F; Gehin, C; Delhomme, G; Collet, C; Robin, O; Dittmar, A

2004-01-01

Improvement of the quality and efficiency of the quality of health in medicine, at home and in hospital becomes more and more important Designed to be user-friendly, smart clothes and gloves fit well for such a citizen use and health monitoring. Analysis of the autonomic nervous system using non-invasive sensors provides information for the emotional, sensorial, cognitive and physiological analysis. MARSIAN (modular autonomous recorder system for the measurement of autonomic nervous system) is a wrist ambulatory monitoring and recording system with a smart glove with sensors for the detection of the activity of the autonomic nervous system. It is composed of a "smart tee shirt", a "smart glove", a wrist device and PC which records data. The smart glove is one of the key point of MARSIAN. Complex movements, complex geometry, sensation make smart glove designing a challenge. MARSIAN has a large field of applications and researches (vigilance, behaviour, sensorial analysis, thermal environment for human, cognition science, sport, etc...) in various fields like neurophysiology, affective computing and health monitoring.

The AMIDAS Website: An Online Tool for Direct Dark Matter Detection Experiments

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

Shan, Chung-Lin

2010-02-10

Following our long-erm work on development of model-independent data analysis methods for reconstructing the one-dimensional velocity distribution function of halo WIMPs as well as for determining their mass and couplings on nucleons by using data from direct Dark Matter detection experiments directly, we combined the simulation programs to a compact system: AMIDAS (A Model-Independent Data Analysis System). For users' convenience an online system has also been established at the same time. AMIDAS has the ability to do full Monte Carlo simulations, faster theoretical estimations, as well as to analyze (real) data sets recorded in direct detection experiments without modifying themore » source code. In this article, I give an overview of functions of the AMIDAS code based on the use of its website.« less

Time-resolved lidar fluorosensor for sea pollution detection

NASA Technical Reports Server (NTRS)

Ferrario, A.; Pizzolati, P. L.; Zanzottera, E.

1986-01-01

A contemporary time and spectral analysis of oil fluorescence is useful for the detection and the characterization of oil spills on the sea surface. Nevertheless the fluorosensor lidars, which were realized up to now, have only partial capability to perform this double analysis. The main difficulties are the high resolution required (of the order of 1 nanosecond) and the complexity of the detection system for the recording of a two-dimensional matrix of data for each laser pulse. An airborne system whose major specifications were: time range, 30 to 75 ns; time resolution, 1 ns; spectral range, 350 to 700 nm; and spectral resolution, 10 nm was designed and constructed. The designed system of a short pulse ultraviolet laser source and a streak camera based detector are described.

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

PubMed Central

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-01-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions. PMID:25199907

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye

NASA Astrophysics Data System (ADS)

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-01

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.

Dew inspired breathing-based detection of genetic point mutation visualized by naked eye.

PubMed

Xie, Liping; Wang, Tongzhou; Huang, Tianqi; Hou, Wei; Huang, Guoliang; Du, Yanan

2014-09-09

A novel label-free method based on breathing-induced vapor condensation was developed for detection of genetic point mutation. The dew-inspired detection was realized by integration of target-induced DNA ligation with rolling circle amplification (RCA). The vapor condensation induced by breathing transduced the RCA-amplified variances in DNA contents into visible contrast. The image could be recorded by a cell phone for further or even remote analysis. This green assay offers a naked-eye-reading method potentially applied for point-of-care liver cancer diagnosis in resource-limited regions.

Analysis of Global Ultrasonic Sensor Data from a Full Scale Wing Panel Test

NASA Astrophysics Data System (ADS)

Michaels, Jennifer E.; Michaels, Thomas E.; Martin, Ramaldo S.

2009-03-01

A full scale wing panel fatigue test was undertaken in 2007 as a part of the DARPA Structural Integrity Prognosis System (SIPS) program. Both local and global ultrasonic sensors were installed on the wing panel and data were recorded periodically over a period of about seven weeks. The local ultrasonic sensors interrogated a small number of selected fastener holes, and the global ultrasonic sensors were arranged in a spatially distributed array surrounding an area encompassing multiple fastener holes of interest. The global ultrasonic sensor data is the focus of the work reported here. Waveforms were recorded from all pitch-catch sensor pairs as a function of static load while fatiguing was paused. The time windows over which the waveforms were recorded were long enough to include most of the reverberating energy. Partway through the test simulated defects were temporarily introduced by gluing masses onto the surface of the wing panel, and waveforms were recorded immediately before their attachment and after their removal. The overall fatigue test was terminated while cracks originating from the fastener holes were still relatively small and before they reached the surface of the wing panel. Both detection and localization results are shown for the artificial damage, and the overall repeatability and stability of the signals are analyzed. Also shown is an analysis of how the reverberating signals change as a function of applied load. The fastener hole fatigue cracks were not detected by the global transducer array, which is not surprising given the final sizes of the cracks as determined by later destructive analysis. However, signals were stable throughout the entire fatigue test, and effects of load on the received signals were significant, both in the short-time and long-time signal regimes.

Volcanic eruptions and solar activity

NASA Technical Reports Server (NTRS)

Stothers, Richard B.

1989-01-01

The historical record of large volcanic eruptions from 1500 to 1980 is subjected to detailed time series analysis. In two weak but probably statistically significant periodicities of about 11 and 80 yr, the frequency of volcanic eruptions increases (decreases) slightly around the times of solar minimum (maximum). Time series analysis of the volcanogenic acidities in a deep ice core from Greenland reveals several very long periods ranging from about 80 to about 350 yr which are similar to the very slow solar cycles previously detected in auroral and C-14 records. Solar flares may cause changes in atmospheric circulation patterns that abruptly alter the earth's spin. The resulting jolt probably triggers small earthquakes which affect volcanism.

Evaluation of autonomous recording units for detecting 3 species of secretive marsh birds

USGS Publications Warehouse

Sidie-Slettehahl, Anna M.; Jensen, Kent C.; Johnson, Rex R.; Arnold, Todd W.; Austin, Jane; Stafford, Joshua D.

2015-01-01

Population status and habitat use of yellow rails (Coturnicops noveboracensis), Nelson's sparrows (Ammodramus nelsoni), and Le Conte's sparrows (A. leconteii) are poorly known, so standardized surveys of these species are needed to inform conservation planning and management. A protocol for monitoring secretive marsh birds exists; however, these species regularly call at night and may be missed during early morning surveys. We tested the effectiveness of autonomous recording units (hereafter, recording units) to survey these species by analyzing recorded vocalizations using bioacoustics software. We deployed 22 recording units at 54 sites in northern Minnesota and eastern North Dakota, USA, and conducted traditional broadcast surveys during May–June, 2010 and 2011. We compared detection probabilities between recording units and standard monitoring protocols using robust-design occupancy models. On average, recording units detected 0.59 (SE = 0.11) fewer Le Conte's sparrows, 0.76 (SE = 0.15) fewer Nelson's sparrows, and 1.01 (SE = 0.14) fewer yellow rails per survey than were detected using the standard protocol. Detection probabilities using the standard protocol averaged 0.95 (yellow rail; 95% CI = 0.86–0.98), 0.93 (Le Conte's sparrow; 95% CI = 0.78–0.98), and 0.89 (Nelson's sparrow; 95% CI = 0.56–0.98), but averaged 0.71 (yellow rail; 95% CI = 0.56–0.83), 0.61 (Le Conte's sparrow; 95% CI = 0.42–0.78), and 0.51 (Nelson's sparrow; 95% CI = 0.19–0.82) using recording units. Reduced detection by recording units was likely due to the ability of human listeners to identify birds calling at greater distances. Recording units may be effective for surveying nocturnal secretive marsh birds if investigators correct for differential detectability. Reduced detectability may be outweighed by the increased spatial and temporal coverage feasible with recording units.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.

Deep Neural Architectures for Mapping Scalp to Intracranial EEG.

PubMed

Antoniades, Andreas; Spyrou, Loukianos; Martin-Lopez, David; Valentin, Antonio; Alarcon, Gonzalo; Sanei, Saeid; Took, Clive Cheong

2018-03-19

Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

SpotMetrics: An Open-Source Image-Analysis Software Plugin for Automatic Chromatophore Detection and Measurement

PubMed Central

Hadjisolomou, Stavros P.; El-Haddad, George

2017-01-01

Coleoid cephalopods (squid, octopus, and sepia) are renowned for their elaborate body patterning capabilities, which are employed for camouflage or communication. The specific chromatic appearance of a cephalopod, at any given moment, is a direct result of the combined action of their intradermal pigmented chromatophore organs and reflecting cells. Therefore, a lot can be learned about the cephalopod coloration system by video recording and analyzing the activation of individual chromatophores in time. The fact that adult cephalopods have small chromatophores, up to several hundred thousand in number, makes measurement and analysis over several seconds a difficult task. However, current advancements in videography enable high-resolution and high framerate recording, which can be used to record chromatophore activity in more detail and accuracy in both space and time domains. In turn, the additional pixel information and extra frames per video from such recordings result in large video files of several gigabytes, even when the recording spans only few minutes. We created a software plugin, “SpotMetrics,” that can automatically analyze high resolution, high framerate video of chromatophore organ activation in time. This image analysis software can track hundreds of individual chromatophores over several hundred frames to provide measurements of size and color. This software may also be used to measure differences in chromatophore activation during different behaviors which will contribute to our understanding of the cephalopod sensorimotor integration system. In addition, this software can potentially be utilized to detect numbers of round objects and size changes in time, such as eye pupil size or number of bacteria in a sample. Thus, we are making this software plugin freely available as open-source because we believe it will be of benefit to other colleagues both in the cephalopod biology field and also within other disciplines. PMID:28298896

Detection of Periodic Leg Movements by Machine Learning Methods Using Polysomnographic Parameters Other Than Leg Electromyography

PubMed Central

Umut, İlhan; Çentik, Güven

2016-01-01

The number of channels used for polysomnographic recording frequently causes difficulties for patients because of the many cables connected. Also, it increases the risk of having troubles during recording process and increases the storage volume. In this study, it is intended to detect periodic leg movement (PLM) in sleep with the use of the channels except leg electromyography (EMG) by analysing polysomnography (PSG) data with digital signal processing (DSP) and machine learning methods. PSG records of 153 patients of different ages and genders with PLM disorder diagnosis were examined retrospectively. A novel software was developed for the analysis of PSG records. The software utilizes the machine learning algorithms, statistical methods, and DSP methods. In order to classify PLM, popular machine learning methods (multilayer perceptron, K-nearest neighbour, and random forests) and logistic regression were used. Comparison of classified results showed that while K-nearest neighbour classification algorithm had higher average classification rate (91.87%) and lower average classification error value (RMSE = 0.2850), multilayer perceptron algorithm had the lowest average classification rate (83.29%) and the highest average classification error value (RMSE = 0.3705). Results showed that PLM can be classified with high accuracy (91.87%) without leg EMG record being present. PMID:27213008

Detection of Periodic Leg Movements by Machine Learning Methods Using Polysomnographic Parameters Other Than Leg Electromyography.

PubMed

Umut, İlhan; Çentik, Güven

2016-01-01

The number of channels used for polysomnographic recording frequently causes difficulties for patients because of the many cables connected. Also, it increases the risk of having troubles during recording process and increases the storage volume. In this study, it is intended to detect periodic leg movement (PLM) in sleep with the use of the channels except leg electromyography (EMG) by analysing polysomnography (PSG) data with digital signal processing (DSP) and machine learning methods. PSG records of 153 patients of different ages and genders with PLM disorder diagnosis were examined retrospectively. A novel software was developed for the analysis of PSG records. The software utilizes the machine learning algorithms, statistical methods, and DSP methods. In order to classify PLM, popular machine learning methods (multilayer perceptron, K-nearest neighbour, and random forests) and logistic regression were used. Comparison of classified results showed that while K-nearest neighbour classification algorithm had higher average classification rate (91.87%) and lower average classification error value (RMSE = 0.2850), multilayer perceptron algorithm had the lowest average classification rate (83.29%) and the highest average classification error value (RMSE = 0.3705). Results showed that PLM can be classified with high accuracy (91.87%) without leg EMG record being present.

The use of a fully integrated electronic medical record to minimize cumulative lifetime radiation exposure from CT scanning to detect urinary tract calculi.

PubMed

Kohler, Steven W; Chen, Richard; Kagan, Alex; Helvey, Dustin W; Buccigrossi, David

2013-06-01

In order to determine the effects of implementation of an electronic medical record on rates of repeat computed tomography (CT) scanning in the emergency department (ED) setting, we analyzed the utilization of CT of the kidneys, ureters, and bladder (CT KUB) for the detection of urinary tract calculi for periods before and after the implementation of a hospital-wide electronic medical record system. Rates of repeat CT scanning within a 6-month period of previous scan were determined pre- and post-implementation and compared. Prior to implementation, there was a 6-month repeat rate of 6.2 % compared with the post-implementation period, which was associated with a 6-month repeat rate of 4.1 %. Statistical analysis using a two-sample, one-tailed t test for difference of means was associated with a p value of 0.00007. This indicates that the implementation of the electronic medical record system was associated with a 34 % decrease in 6-month repeat CT KUB scans. We conclude that the use of an electronic medical record can be associated with a decrease in utilization of unnecessary repeat CT imaging, leading to decreased cumulative lifetime risk for cancer in these patients and more efficient utilization of ED and radiologic resources.

[Pharmacist's interventions on outpatient prescriptions in a university hospital drugs sales service].

PubMed

Chappuy, M; Garcia, S; Uhres, A-C; Janoly-Dumenil, A; Dessault, J; Chamouard, V; Bréant, V; Leboucher, G; Pivot, C; Carpentier, I

2015-07-01

For public health reasons, some drugs are only available in hospital drugs sales service. This activity takes place in a specific risk context of organization, patients and/or drugs. A systematic prescription analysis by pharmacist contributes to securise treatment dispensed. The aim of this paper is to present the main drugs problems in the analysis of outpatient prescriptions and pharmaceutical interventions in three units of hospital drugs sales service belong to university hospital. Throughout the year 2013, drug problems detected were recorded prospectively and systematically. Of the 22,279 prescriptions analyzed, 247 pharmaceutical interventions (1.1%) were detected including 27.6% of problems concerning the dosages, 15.4% the unconformity, 6.9% contraindications. Regarding ATC drugs classes, we found 43.7% for anti-infectives and 17.4% for antineoplatics. The overall acceptance rate is 81.8%. These results show the importance of the analysis of outpatient prescriptions before dispensing and the need to have all prescriptions, clinical and biological elements and to develop interprofessionality. The implementation of a platform for dematerialized data exchanges between professionals, including data from the pharmaceutical patient record should contribute to improving drug management of the patient. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

An intelligent crowdsourcing system for forensic analysis of surveillance video

NASA Astrophysics Data System (ADS)

Tahboub, Khalid; Gadgil, Neeraj; Ribera, Javier; Delgado, Blanca; Delp, Edward J.

2015-03-01

Video surveillance systems are of a great value for public safety. With an exponential increase in the number of cameras, videos obtained from surveillance systems are often archived for forensic purposes. Many automatic methods have been proposed to do video analytics such as anomaly detection and human activity recognition. However, such methods face significant challenges due to object occlusions, shadows and scene illumination changes. In recent years, crowdsourcing has become an effective tool that utilizes human intelligence to perform tasks that are challenging for machines. In this paper, we present an intelligent crowdsourcing system for forensic analysis of surveillance video that includes the video recorded as a part of search and rescue missions and large-scale investigation tasks. We describe a method to enhance crowdsourcing by incorporating human detection, re-identification and tracking. At the core of our system, we use a hierarchal pyramid model to distinguish the crowd members based on their ability, experience and performance record. Our proposed system operates in an autonomous fashion and produces a final output of the crowdsourcing analysis consisting of a set of video segments detailing the events of interest as one storyline.

A shift in the spatial pattern of Iberian droughts during the 17th century

NASA Astrophysics Data System (ADS)

Domínguez-Castro, F.; García-Herrera, R.; Ribera, P.; Barriendos, M.

2010-06-01

In this paper, series of drought occurrence and drought extension in the Iberian Peninsula are constructed for the 1600-1750 period from seven rogation series. These rogation ceremony records come from Bilbao, Catalonia, Zamora, Zaragoza, Toledo, Murcia and Seville. They are distributed across the Peninsula and include the areas with the most characteristic Iberian climate types, influenced by the Atlantic and the Mediterranean conditions, described from modern data. A seasonal division of the series shows that spring is a critical season for rogation series in most of Iberia, being Bilbao the only site were the highest number of rogations is detected for a different season. The annual analysis of the series shows a dramatic difference between the period 1600-1652, when droughts are characterized by its local character; and the period 1653-1749, when they affect to broader regions or even to the whole Peninsula. The analysis of spring series confirms the existence of the two periods detected in the annual analysis. Finally, secondary documentary sources are used to further characterise the two most extended droughts in the period, 1664 and 1680, and to verify the extension of the areas affected by droughts recorded through rogation series.

Complexity quantification of dense array EEG using sample entropy analysis.

PubMed

Ramanand, Pravitha; Nampoori, V P N; Sreenivasan, R

2004-09-01

In this paper, a time series complexity analysis of dense array electroencephalogram signals is carried out using the recently introduced Sample Entropy (SampEn) measure. This statistic quantifies the regularity in signals recorded from systems that can vary from the purely deterministic to purely stochastic realm. The present analysis is conducted with an objective of gaining insight into complexity variations related to changing brain dynamics for EEG recorded from the three cases of passive, eyes closed condition, a mental arithmetic task and the same mental task carried out after a physical exertion task. It is observed that the statistic is a robust quantifier of complexity suited for short physiological signals such as the EEG and it points to the specific brain regions that exhibit lowered complexity during the mental task state as compared to a passive, relaxed state. In the case of mental tasks carried out before and after the performance of a physical exercise, the statistic can detect the variations brought in by the intermediate fatigue inducing exercise period. This enhances its utility in detecting subtle changes in the brain state that can find wider scope for applications in EEG based brain studies.

Progressive data transmission for anatomical landmark detection in a cloud.

PubMed

Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D

2012-01-01

In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.

40 CFR 63.10899 - What are my recordkeeping and reporting requirements?

Code of Federal Regulations, 2011 CFR

2011-07-01

... of each inspection, and the results of any maintenance performed on the bag filters. (ii) The date... applicable, you must keep records for bag leak detection systems as follows: (i) Records of the bag leak detection system output; (ii) Records of bag leak detection system adjustments, including the date and time...

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials.

PubMed

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies.

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

PubMed Central

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies. PMID:26325291

Real-time pulse oximetry artifact annotation on computerized anaesthetic records.

PubMed

Gostt, Richard Karl; Rathbone, Graeme Dennis; Tucker, Adam Paul

2002-01-01

Adoption of computerised anaesthesia record keeping systems has been limited by the concern that they record artifactual data and accurate data indiscriminately. Data resulting from artifacts does not reflect the patient's true condition and presents a problem in later analysis of the record, with associated medico-legal implications. This study developed an algorithm to automatically annotate pulse oximetry artifacts and sought to evaluate the algorithm's accuracy in routine surgical procedures. MacAnaesthetist is a semi-automatic anaesthetic record keeping system developed for the Apple Macintosh computer, which incorporated an algorithm designed to automatically detect pulse oximetry artifacts. The algorithm labeled artifactual oxygen saturation values < 90%. This was done in real-time by analyzing physiological data captured from a Datex AS/3 Anaesthesia Monitor. An observational study was conducted to evaluate the accuracy of the algorithm during routine surgical procedures (n = 20). An anaesthetic record was made by an anaesthetist using the Datex AS/3 record keeper, while a second anaesthetic record was produced in parallel using MacAnaesthetist. A copy of the Datex AS/3 record was kept for later review by a group of anaesthetists (n = 20), who judged oxygen saturation values < 90% to be either genuine or artifact. MacAnaesthetist correctly labeled 12 out of 13 oxygen saturations < 90% (92.3% accuracy). A post-operative review of the Datex AS/3 anaesthetic records (n = 8) by twenty anaesthetists resulted in 127 correct responses out of total of 200 (63.5% accuracy). The remaining Datex AS/3 records (n = 12) were not reviewed, as they did not contain any oxygen saturations <90%. The real-time artifact detection algorithm developed in this study was more accurate than anaesthetists who post-operatively reviewed records produced by an existing computerised anaesthesia record keeping system. Algorithms have the potential to more accurately identify and annotate artifacts on computerised anaesthetic records, assisting clinicians to more correctly interpret abnormal data.

Relation between dietary pattern analysis (principal component analysis) and body mass index: a 5-year follow-up study in a Belgian military population.

PubMed

Mullie, Patrick; Clarys, P

2016-02-01

Increasing body mass index (BMI) has been related to many chronic diseases. Knowledge of nutritional determinants of BMI increase may be important to detect persons at risk. A longitudinal prospective study design was used in 805 Belgian soldiers. Daily nutrition was recorded with a validated food-frequency questionnaire. Weight and height were recorded from medical military data and principal component analysis was used to detect dietary patterns. During the 5 years follow-up, mean BMI increased from 25.8 (±3.3) kg/m(2) to 27.1 (±3.6) kg/m(2) (p<0.05). Consequently, the prevalence of being overweight and obesity increased from 46.2% and 9.6% to 51.6% and 19.9% (p<0.05), respectively. Mean (SD) weight gain differed between the BMI categories at baseline with a respective weight gain of 3.8 (±3.1) kg for normal weight at baseline, 4.2 (±3.2) kg for overweight and 5.1 (±3.4) kg for obesity (p for trend <0.05). Three dietary patterns were detected by principal component analysis: Meat, Sweet and Healthy dietary pattern. In energy-unadjusted and adjusted linear regressions, no dietary pattern was associated with BMI increase. No specific dietary pattern was related to BMI increase. Prevention of obesity should focus on total energy intake at all BMI categories. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Computerized Lung Sound Analysis as diagnostic aid for the detection of abnormal lung sounds: a systematic review and meta-analysis

PubMed Central

Gurung, Arati; Scrafford, Carolyn G; Tielsch, James M; Levine, Orin S; Checkley, William

2011-01-01

Rationale The standardized use of a stethoscope for chest auscultation in clinical research is limited by its inherent inter-listener variability. Electronic auscultation and automated classification of recorded lung sounds may help prevent some these shortcomings. Objective We sought to perform a systematic review and meta-analysis of studies implementing computerized lung sounds analysis (CLSA) to aid in the detection of abnormal lung sounds for specific respiratory disorders. Methods We searched for articles on CLSA in MEDLINE, EMBASE, Cochrane Library and ISI Web of Knowledge through July 31, 2010. Following qualitative review, we conducted a meta-analysis to estimate the sensitivity and specificity of CLSA for the detection of abnormal lung sounds. Measurements and Main Results Of 208 articles identified, we selected eight studies for review. Most studies employed either electret microphones or piezoelectric sensors for auscultation, and Fourier Transform and Neural Network algorithms for analysis and automated classification of lung sounds. Overall sensitivity for the detection of wheezes or crackles using CLSA was 80% (95% CI 72–86%) and specificity was 85% (95% CI 78–91%). Conclusions While quality data on CLSA are relatively limited, analysis of existing information suggests that CLSA can provide a relatively high specificity for detecting abnormal lung sounds such as crackles and wheezes. Further research and product development could promote the value of CLSA in research studies or its diagnostic utility in clinical setting. PMID:21676606

Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: a systematic review and meta-analysis.

PubMed

Gurung, Arati; Scrafford, Carolyn G; Tielsch, James M; Levine, Orin S; Checkley, William

2011-09-01

The standardized use of a stethoscope for chest auscultation in clinical research is limited by its inherent inter-listener variability. Electronic auscultation and automated classification of recorded lung sounds may help prevent some of these shortcomings. We sought to perform a systematic review and meta-analysis of studies implementing computerized lung sound analysis (CLSA) to aid in the detection of abnormal lung sounds for specific respiratory disorders. We searched for articles on CLSA in MEDLINE, EMBASE, Cochrane Library and ISI Web of Knowledge through July 31, 2010. Following qualitative review, we conducted a meta-analysis to estimate the sensitivity and specificity of CLSA for the detection of abnormal lung sounds. Of 208 articles identified, we selected eight studies for review. Most studies employed either electret microphones or piezoelectric sensors for auscultation, and Fourier Transform and Neural Network algorithms for analysis and automated classification of lung sounds. Overall sensitivity for the detection of wheezes or crackles using CLSA was 80% (95% CI 72-86%) and specificity was 85% (95% CI 78-91%). While quality data on CLSA are relatively limited, analysis of existing information suggests that CLSA can provide a relatively high specificity for detecting abnormal lung sounds such as crackles and wheezes. Further research and product development could promote the value of CLSA in research studies or its diagnostic utility in clinical settings. Copyright © 2011 Elsevier Ltd. All rights reserved.

A system for the rapid detection of bacterial contamination in cell-based therapeutica

NASA Astrophysics Data System (ADS)

Bolwien, Carsten; Erhardt, Christian; Sulz, Gerd; Thielecke, Hagen; Johann, Robert; Pudlas, Marieke; Mertsching, Heike; Koch, Steffen

2010-02-01

Monitoring the sterility of cell or tissue cultures is of major concern, particularly in the fields of regenerative medicine and tissue engineering when implanting cells into the human body. Our sterility-control system is based on a Raman micro-spectrometer and is able to perform fast sterility testing on microliters of liquid samples. In conventional sterility control, samples are incubated for weeks to proliferate the contaminants to concentrations above the detection limit of conventional analysis. By contrast, our system filters particles from the liquid sample. The filter chip fabricated in microsystem technology comprises a silicon nitride membrane with millions of sub-micrometer holes to retain particles of critical sizes and is embedded in a microfluidic cell specially suited for concomitant microscopic observation. After filtration, identification is carried out on the single particle level: image processing detects possible contaminants and prepares them for Raman spectroscopic analysis. A custom-built Raman-spectrometer-attachment coupled to the commercial microscope uses 532nm or 785nm Raman excitation and records spectra up to 3400cm-1. In the final step, the recorded spectrum of a single particle is compared to an extensive library of GMP-relevant organisms, and classification is carried out based on a support vector machine.

Preliminary evaluation of a nest usage sensor to detect double nest occupations of laying hens.

PubMed

Zaninelli, Mauro; Costa, Annamaria; Tangorra, Francesco Maria; Rossi, Luciana; Agazzi, Alessandro; Savoini, Giovanni

2015-01-26

Conventional cage systems will be replaced by housing systems that allow hens to move freely. These systems may improve hens' welfare, but they lead to some disadvantages: disease, bone fractures, cannibalism, piling and lower egg production. New selection criteria for existing commercial strains should be identified considering individual data about laying performance and the behavior of hens. Many recording systems have been developed to collect these data. However, the management of double nest occupations remains critical for the correct egg-to-hen assignment. To limit such events, most systems adopt specific trap devices and additional mechanical components. Others, instead, only prevent these occurrences by narrowing the nest, without any detection and management. The aim of this study was to develop and test a nest usage "sensor", based on imaging analysis, that is able to automatically detect a double nest occupation. Results showed that the developed sensor correctly identified the double nest occupation occurrences. Therefore, the imaging analysis resulted in being a useful solution that could simplify the nest construction for this type of recording system, allowing the collection of more precise and accurate data, since double nest occupations would be managed and the normal laying behavior of hens would not be discouraged by the presence of the trap devices.

Preliminary Evaluation of a Nest Usage Sensor to Detect Double Nest Occupations of Laying Hens

PubMed Central

Zaninelli, Mauro; Costa, Annamaria; Tangorra, Francesco Maria; Rossi, Luciana; Agazzi, Alessandro; Savoini, Giovanni

2015-01-01

Conventional cage systems will be replaced by housing systems that allow hens to move freely. These systems may improve hens' welfare, but they lead to some disadvantages: disease, bone fractures, cannibalism, piling and lower egg production. New selection criteria for existing commercial strains should be identified considering individual data about laying performance and the behavior of hens. Many recording systems have been developed to collect these data. However, the management of double nest occupations remains critical for the correct egg-to-hen assignment. To limit such events, most systems adopt specific trap devices and additional mechanical components. Others, instead, only prevent these occurrences by narrowing the nest, without any detection and management. The aim of this study was to develop and test a nest usage “sensor”, based on imaging analysis, that is able to automatically detect a double nest occupation. Results showed that the developed sensor correctly identified the double nest occupation occurrences. Therefore, the imaging analysis resulted in being a useful solution that could simplify the nest construction for this type of recording system, allowing the collection of more precise and accurate data, since double nest occupations would be managed and the normal laying behavior of hens would not be discouraged by the presence of the trap devices. PMID:25629704

Two particle tracking and detection in a single Gaussian beam optical trap.

PubMed

Praveen, P; Yogesha; Iyengar, Shruthi S; Bhattacharya, Sarbari; Ananthamurthy, Sharath

2016-01-20

We have studied in detail the situation wherein two microbeads are trapped axially in a single-beam Gaussian intensity profile optical trap. We find that the corner frequency extracted from a power spectral density analysis of intensity fluctuations recorded on a quadrant photodetector (QPD) is dependent on the detection scheme. Using forward- and backscattering detection schemes with single and two laser wavelengths along with computer simulations, we conclude that fluctuations detected in backscattering bear true position information of the bead encountered first in the beam propagation direction. Forward scattering, on the other hand, carries position information of both beads with substantial contribution from the bead encountered first along the beam propagation direction. Mie scattering analysis further reveals that the interference term from the scattering of the two beads contributes significantly to the signal, precluding the ability to resolve the positions of the individual beads in forward scattering. In QPD-based detection schemes, detection through backscattering, thereby, is imperative to track the true displacements of axially trapped microbeads for possible studies on light-mediated interbead interactions.

Monitoring the development of volcanic eruptions through volcanic lightning - Using a lightning mapping array, seismic and infrasound array, and visual plume analysis

NASA Astrophysics Data System (ADS)

Smith, C. M.; Thompson, G.; McNutt, S. R.; Behnke, S. A.; Edens, H. E.; Van Eaton, A. R.; Gaudin, D.; Thomas, R. J.

2017-12-01

The period of 28 May - 7 June 2015 at Sakurajima Volcano, Japan witnessed a multitude of Vulcanian eruptive events, which resulted in plumes reaching 500-3000m above the vent. These plumes varied from white, gas-rich plumes to dark grey and black ash-rich plumes, and were recorded on lowlight and infrared cameras. A nine-station lightning mapping array (LMA) was deployed to locate sources of VHF (67-73 MHz) radiation produced by lightning flashes and other types of electrical activity such as `continuous RF (radio frequency)'. Two Nanometrics Trillium broadband seismometers and six BSU infrasound sensors were deployed. Over this ten day period we recorded 1556 events that consisted of both seismic and infrasound signals, indicating explosive activity. There are an additional 1222 events that were recorded as only seismic or infrasound signals, which may be a result of precursory seismic signals or noise contamination. Plume discharge types included both distinct lightning flashes and `continuous RF'. The LMA ran continuously for the duration of the experiment. On 30 May 2015 at least seven lightning flashes were also detected by the Vaisala Global Lightning Detection 360 network, which detects VLF (3-30 kHz) radiation. However the University of Washington's World Wide Lightning Location Network, which also detects VLF radiation, detected no volcanic lightning flashes in this time period. This indicates that the electrical activity in Sakurajima's plume occurs near the lower limits of the VLF detection threshold. We investigate relationships between the plume dynamics, the geophysical signal and the corresponding electrical activity through: plume velocity and height; event waveform cross-correlation; volcano acoustic-seismic ratios; overall geophysical energy; RSAM records; and VHF sources detected by the LMA. By investigating these relationships we hope to determine the seismic/infrasound energy threshold required to generate measurable electrical activity. Seismic and infrasound are two of the most common volcanic monitoring methods. By developing the relationships between plume electrification and these geophysical methods we hope to expand the use of lightning for active volcano monitoring.

Specializing network analysis to detect anomalous insider actions

PubMed Central

Chen, You; Nyemba, Steve; Zhang, Wen; Malin, Bradley

2012-01-01

Collaborative information systems (CIS) enable users to coordinate efficiently over shared tasks in complex distributed environments. For flexibility, they provide users with broad access privileges, which, as a side-effect, leave such systems vulnerable to various attacks. Some of the more damaging malicious activities stem from internal misuse, where users are authorized to access system resources. A promising class of insider threat detection models for CIS focuses on mining access patterns from audit logs, however, current models are limited in that they assume organizations have significant resources to generate label cases for training classifiers or assume the user has committed a large number of actions that deviate from “normal” behavior. In lieu of the previous assumptions, we introduce an approach that detects when specific actions of an insider deviate from expectation in the context of collaborative behavior. Specifically, in this paper, we introduce a specialized network anomaly detection model, or SNAD, to detect such events. This approach assesses the extent to which a user influences the similarity of the group of users that access a particular record in the CIS. From a theoretical perspective, we show that the proposed model is appropriate for detecting insider actions in dynamic collaborative systems. From an empirical perspective, we perform an extensive evaluation of SNAD with the access logs of two distinct environments: the patient record access logs a large electronic health record system (6,015 users, 130,457 patients and 1,327,500 accesses) and the editing logs of Wikipedia (2,394,385 revisors, 55,200 articles and 6,482,780 revisions). We compare our model with several competing methods and demonstrate SNAD is significantly more effective: on average it achieves 20–30% greater area under an ROC curve. PMID:23399988

Unconstrained snoring detection using a smartphone during ordinary sleep.

PubMed

Shin, Hangsik; Cho, Jaegeol

2014-08-15

Snoring can be a representative symptom of a sleep disorder, and thus snoring detection is quite important to improving the quality of an individual's daily life. The purpose of this research is to develop an unconstrained snoring detection technique that can be integrated into a smartphone application. In contrast with previous studies, we developed a practical technique for snoring detection during ordinary sleep by using the built-in sound recording system of a smartphone, and the recording was carried out in a standard private bedroom. The experimental protocol was designed to include a variety of actions that frequently produce noise (including coughing, playing music, talking, rining an alarm, opening/closing doors, running a fan, playing the radio, and walking) in order to accurately recreate the actual circumstances during sleep. The sound data were recorded for 10 individuals during actual sleep. In total, 44 snoring data sets and 75 noise datasets were acquired. The algorithm uses formant analysis to examine sound features according to the frequency and magnitude. Then, a quadratic classifier is used to distinguish snoring from non-snoring noises. Ten-fold cross validation was used to evaluate the developed snoring detection methods, and validation was repeated 100 times randomly to improve statistical effectiveness. The overall results showed that the proposed method is competitive with those from previous research. The proposed method presented 95.07% accuracy, 98.58% sensitivity, 94.62% specificity, and 70.38% positive predictivity. Though there was a relatively high false positive rate, the results show the possibility for ubiquitous personal snoring detection through a smartphone application that takes into account data from normally occurring noises without training using preexisting data.

Advances in the application of holography for NDE

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.

1985-01-01

The basic methodology of holographic interferometry in nondestructive testing (NDT) applications are described. Applications to crack detection in ceramic materials, including a crack 50 microns deep in a turbine blade, are discussed in detail. The theoretical principles of holographic interferometry are explained, and a general description of a holographic interferometric recording system is given. A nondestructive interferometric technique for measuring the gradual erosion of calcareous stones exposed to acid rain is also presented. Detailed line drawings illustrating the hologram recording and interferometric fringe pattern analysis elements in an interferometric holographic NDT device are provided.

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

NASA Astrophysics Data System (ADS)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Modified Whittaker plots as an assessment and monitoring tool for vegetation in a lowland tropical rainforest.

PubMed

Campbell, Patrick; Comiskey, James; Alonso, Alfonso; Dallmeier, Francisco; Nuñez, Percy; Beltran, Hamilton; Baldeon, Severo; Nauray, William; de la Colina, Rafael; Acurio, Lucero; Udvardy, Shana

2002-05-01

Resource exploitation in lowland tropical forests is increasing and causing loss of biodiversity. Effective evaluation and management of the impacts of development on tropical forests requires appropriate assessment and monitoring tools. We propose the use of 0.1-ha multi-scale, modified Whittaker plots (MWPs) to assess and monitor vegetation in lowland tropical rainforests. We established MWPs at 4 sites to: (1) describe and compare composition and structure of the sites using MWPs, (2) compare these results to those of 1-ha permanent vegetation plots (BDPs), and (3) evaluate the ability of MWPs to detect changes in populations (statistical power). We recorded more than 400 species at each site. Species composition among the sites was distinctive, while mean abundance and basal area was similar. Comparisons between MWPs and BDPs show that they record similar species composition and abundance and that both perform equally well at detecting rare species. However, MWPs tend to record more species, and power analysis studies show that MWPs were more effective at detecting changes in the mean number of species of trees > or = 10 cm in diameter at breast height (dbh) and in herbaceous plants. Ten MWPs were sufficient to detect a change of 11% in the mean number of herb species, and they were able to detect a 14% change in the mean number of species of trees > or =10 cm dbh. The value of MWPs for assessment and monitoring is discussed, along with recommendations for improving the sampling design to increase power.

Deep-turbulence wavefront sensing using digital holography in the on-axis phase shifting recording geometry

NASA Astrophysics Data System (ADS)

Thornton, Douglas E.; Spencer, Mark F.; Perram, Glen P.

2017-09-01

The effects of deep turbulence in long-range imaging applications presents unique challenges to properly measure and correct for aberrations incurred along the atmospheric path. In practice, digital holography can detect the path-integrated wavefront distortions caused by deep turbulence, and di erent recording geometries offer different benefits depending on the application of interest. Previous studies have evaluated the performance of the off-axis image and pupil plane recording geometries for deep-turbulence sensing. This study models digital holography in the on-axis phase shifting recording geometry using wave optics simulations. In particular, the analysis models spherical-wave propagation through varying deep-turbulence conditions to estimate the complex optical field, and performance is evaluated by calculating the field-estimated Strehl ratio and RMS wavefront error. Altogether, the results show that digital holography in the on-axis phase shifting recording geometry is an effective wavefront-sensing method in the presence of deep turbulence.

Assessment of hearing threshold in adults with hearing loss using an automated system of cortical auditory evoked potential detection.

PubMed

Durante, Alessandra Spada; Wieselberg, Margarita Bernal; Roque, Nayara; Carvalho, Sheila; Pucci, Beatriz; Gudayol, Nicolly; de Almeida, Kátia

The use of hearing aids by individuals with hearing loss brings a better quality of life. Access to and benefit from these devices may be compromised in patients who present difficulties or limitations in traditional behavioral audiological evaluation, such as newborns and small children, individuals with auditory neuropathy spectrum, autism, and intellectual deficits, and in adults and the elderly with dementia. These populations (or individuals) are unable to undergo a behavioral assessment, and generate a growing demand for objective methods to assess hearing. Cortical auditory evoked potentials have been used for decades to estimate hearing thresholds. Current technological advances have lead to the development of equipment that allows their clinical use, with features that enable greater accuracy, sensitivity, and specificity, and the possibility of automated detection, analysis, and recording of cortical responses. To determine and correlate behavioral auditory thresholds with cortical auditory thresholds obtained from an automated response analysis technique. The study included 52 adults, divided into two groups: 21 adults with moderate to severe hearing loss (study group); and 31 adults with normal hearing (control group). An automated system of detection, analysis, and recording of cortical responses (HEARLab ® ) was used to record the behavioral and cortical thresholds. The subjects remained awake in an acoustically treated environment. Altogether, 150 tone bursts at 500, 1000, 2000, and 4000Hz were presented through insert earphones in descending-ascending intensity. The lowest level at which the subject detected the sound stimulus was defined as the behavioral (hearing) threshold (BT). The lowest level at which a cortical response was observed was defined as the cortical electrophysiological threshold. These two responses were correlated using linear regression. The cortical electrophysiological threshold was, on average, 7.8dB higher than the behavioral for the group with hearing loss and, on average, 14.5dB higher for the group without hearing loss for all studied frequencies. The cortical electrophysiological thresholds obtained with the use of an automated response detection system were highly correlated with behavioral thresholds in the group of individuals with hearing loss. Copyright © 2016 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Workplace measurements by the US Occupational Safety and Health Administration since 1979: descriptive analysis and potential uses for exposure assessment.

PubMed

Lavoue, J; Friesen, M C; Burstyn, I

2013-01-01

Inspectors from the US Occupational Safety and Health Administration (OSHA) have been collecting industrial hygiene samples since 1972 to verify compliance with Permissible Exposure Limits. Starting in 1979, these measurements were computerized into the Integrated Management Information System (IMIS). In 2010, a dataset of over 1 million personal sample results analysed at OSHA's central laboratory in Salt Lake City [Chemical Exposure Health Data (CEHD)], only partially overlapping the IMIS database, was placed into public domain via the internet. We undertook this study to inform potential users about the relationship between this newly available OSHA data and IMIS and to offer insight about the opportunities and challenges associated with the use of OSHA measurement data for occupational exposure assessment. We conducted a literature review of previous uses of IMIS in occupational health research and performed a descriptive analysis of the data recently made available and compared them to the IMIS database for lead, the most frequently sampled agent. The literature review yielded 29 studies reporting use of IMIS data, but none using the CEHD data. Most studies focused on a single contaminant, with silica and lead being most frequently analysed. Sixteen studies addressed potential bias in IMIS, mostly by examining the association between exposure levels and ancillary information. Although no biases of appreciable magnitude were consistently reported across studies and agents, these assessments may have been obscured by selective under-reporting of non-detectable measurements. The CEHD data comprised 1 450 836 records from 1984 to 2009, not counting analytical blanks and erroneous records. Seventy eight agents with >1000 personal samples yielded 1 037 367 records. Unlike IMIS, which contain administrative information (company size, job description), ancillary information in the CEHD data is mostly analytical. When the IMIS and CEHD measurements of lead were merged, 23 033 (39.2%) records were in common to both IMIS and CEHD datasets, 10 681 (18.2%) records were only in IMIS, and 25 012 (42.6%) records were only in the CEHD database. While IMIS-only records represent data analysed in other laboratories, CEHD-only records suggest partial reporting of sampling results by OSHA inspectors into IMIS. For lead, the percentage of non-detects in the CEHD-only data was 71% compared to 42% and 46% in the both-IMIS-CEHD and IMIS-only datasets, respectively, suggesting differential under-reporting of non-detects in IMIS. IMIS and the CEHD datasets represent the biggest source of multi-industry exposure data in the USA and should be considered as a valuable source of information for occupational exposure assessment. The lack of empirical data on biases, adequate interpretation of non-detects in OSHA data, complicated by suspected differential under-reporting, remain the principal challenges to the valid estimation of average exposure conditions. We advocate additional comparisons between IMIS and CEHD data and discuss analytical strategies that may play a key role in meeting these challenges.

Computer algorithms for automated detection and analysis of local Ca2+ releases in spontaneously beating cardiac pacemaker cells

PubMed Central

Kim, Mary S.; Tsutsui, Kenta; Stern, Michael D.; Lakatta, Edward G.; Maltsev, Victor A.

2017-01-01

Local Ca2+ Releases (LCRs) are crucial events involved in cardiac pacemaker cell function. However, specific algorithms for automatic LCR detection and analysis have not been developed in live, spontaneously beating pacemaker cells. In the present study we measured LCRs using a high-speed 2D-camera in spontaneously contracting sinoatrial (SA) node cells isolated from rabbit and guinea pig and developed a new algorithm capable of detecting and analyzing the LCRs spatially in two-dimensions, and in time. Our algorithm tracks points along the midline of the contracting cell. It uses these points as a coordinate system for affine transform, producing a transformed image series where the cell does not contract. Action potential-induced Ca2+ transients and LCRs were thereafter isolated from recording noise by applying a series of spatial filters. The LCR birth and death events were detected by a differential (frame-to-frame) sensitivity algorithm applied to each pixel (cell location). An LCR was detected when its signal changes sufficiently quickly within a sufficiently large area. The LCR is considered to have died when its amplitude decays substantially, or when it merges into the rising whole cell Ca2+ transient. Ultimately, our algorithm provides major LCR parameters such as period, signal mass, duration, and propagation path area. As the LCRs propagate within live cells, the algorithm identifies splitting and merging behaviors, indicating the importance of locally propagating Ca2+-induced-Ca2+-release for the fate of LCRs and for generating a powerful ensemble Ca2+ signal. Thus, our new computer algorithms eliminate motion artifacts and detect 2D local spatiotemporal events from recording noise and global signals. While the algorithms were developed to detect LCRs in sinoatrial nodal cells, they have the potential to be used in other applications in biophysics and cell physiology, for example, to detect Ca2+ wavelets (abortive waves), sparks and embers in muscle cells and Ca2+ puffs and syntillas in neurons. PMID:28683095

Recent enhancements of the PMCC infrasound signal detector

NASA Astrophysics Data System (ADS)

Brachet, N.; Mialle, P.; Matoza, R. S.; Le Pichon, A.; Cansi, Y.; Ceranna, L.

2010-12-01

The Progressive Multi-Channel Correlation (PMCC) is an antenna technique that is commonly being used by the scientific community for detecting coherent signals recorded on infrasound arrays. The PMCC detector, originally developed by CEA/DASE (Cansi, 1995), was installed in 2004 in the operational environment of the International Data Centre (IDC) of the Comprehensive nuclear Test Ban Treaty Organization (CTBTO) in Vienna. During the last 5 years, several changes have been made by the IDC to enhance the PMCC source code and parameter configuration, and the detector has exhibited good performance in terms of detection sensitivity and robustness. Recent studies performed at the CEA/DASE have shown that the IDC version (DFX/Geotool-PMCC) and the DASE version (WinPMCC) of PMCC software benefit from the implementation of the adaptive processing window duration and a log-spaced frequency bands. This tested configuration enables better detection and characterization of all received signals in their wave-front parameter space (e.g., frequency-azimuth space, frequency-trace-velocity space). A new release of the WinPMCC software - running under Windows or Linux operating systems - including a fully configurable filtering and detection parameters is now available upon request. We present the results of a statistical analysis on 10 years of infrasound data recorded at the IMS stations IS26, Germany and IS22, New Caledonia. A comparison is made between the automatic detections produced by the IDC, and the reprocessed detections using the optimized filtering and detection configuration parameters. Work is also underway at the CEA/DASE to determine more rigorously the azimuth and speed uncertainties. The current algorithm estimates the uncertainties based on statistical analysis of the distribution of PMCC detection pixels in the azimuth-speed space. The new code that is being considered performs the calculation of infrasound measurement errors as a function of physical parameters, i.e. dependant on the array geometry and the wave properties.

Ocean Basin Impact of Ambient Noise on Marine Mammal Detectability, Distribution, and Acoustic Communication

DTIC Science & Technology

2015-09-30

soundscapes , and unit of analysis methodology. The study has culminated in a complex analysis of all environmental factors that could be predictors of...regional soundscapes . To build the correlation matrices from ambient sound recordings, the raw data was first converted into a series of sound...sounds. To compare two different soundscape time periods, the correlation matrices for the two periods were then subtracted from each other

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning.

PubMed

Happel, Max F K; Deliano, Matthias; Ohl, Frank W

2015-10-22

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the necessary equipment is now available by several commercial companies. This protocol provides a detailed description of a two-way shuttle-box avoidance learning paradigm in rodents (here Mongolian gerbils; Meriones unguiculatus) in combination with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical electrophysiological in vivo recordings. The detailed protocol is applicable to study multiple aspects of learning behavior and perception in different rodent species. Site-specific ICMS of auditory cortical circuits as conditioned stimuli here is used as a tool to test the perceptual relevance of specific afferent, efferent and intracortical connections. Distinct activation patterns can be evoked by using different stimulation electrode arrays for local, layer-dependent ICMS or distant ICMS sites. Utilizing behavioral signal detection analysis it can be determined which stimulation strategy is most effective for eliciting a behaviorally detectable and salient signal. Further, parallel multichannel-recordings using different electrode designs (surface electrodes, depth electrodes, etc.) allow for investigating neuronal observables over the time course of such learning processes. It will be discussed how changes of the behavioral design can increase the cognitive complexity (e.g. detection, discrimination, reversal learning).

Combined Shuttle-Box Training with Electrophysiological Cortex Recording and Stimulation as a Tool to Study Perception and Learning

PubMed Central

Happel, Max F.K.

2015-01-01

Shuttle-box avoidance learning is a well-established method in behavioral neuroscience and experimental setups were traditionally custom-made; the necessary equipment is now available by several commercial companies. This protocol provides a detailed description of a two-way shuttle-box avoidance learning paradigm in rodents (here Mongolian gerbils; Meriones unguiculatus) in combination with site-specific electrical intracortical microstimulation (ICMS) and simultaneous chronical electrophysiological in vivo recordings. The detailed protocol is applicable to study multiple aspects of learning behavior and perception in different rodent species. Site-specific ICMS of auditory cortical circuits as conditioned stimuli here is used as a tool to test the perceptual relevance of specific afferent, efferent and intracortical connections. Distinct activation patterns can be evoked by using different stimulation electrode arrays for local, layer-dependent ICMS or distant ICMS sites. Utilizing behavioral signal detection analysis it can be determined which stimulation strategy is most effective for eliciting a behaviorally detectable and salient signal. Further, parallel multichannel-recordings using different electrode designs (surface electrodes, depth electrodes, etc.) allow for investigating neuronal observables over the time course of such learning processes. It will be discussed how changes of the behavioral design can increase the cognitive complexity (e.g. detection, discrimination, reversal learning). PMID:26556300

Modulation-frequency encoded multi-color fluorescent DNA analysis in an optofluidic chip.

PubMed

Dongre, Chaitanya; van Weerd, Jasper; Besselink, Geert A J; Vazquez, Rebeca Martinez; Osellame, Roberto; Cerullo, Giulio; van Weeghel, Rob; van den Vlekkert, Hans H; Hoekstra, Hugo J W M; Pollnau, Markus

2011-02-21

We introduce a principle of parallel optical processing to an optofluidic lab-on-a-chip. During electrophoretic separation, the ultra-low limit of detection achieved with our set-up allows us to record fluorescence from covalently end-labeled DNA molecules. Different sets of exclusively color-labeled DNA fragments-otherwise rendered indistinguishable by spatio-temporal coincidence-are traced back to their origin by modulation-frequency-encoded multi-wavelength laser excitation, fluorescence detection with a single ultrasensitive, albeit color-blind photomultiplier, and Fourier analysis decoding. As a proof of principle, fragments obtained by multiplex ligation-dependent probe amplification from independent human genomic segments, associated with genetic predispositions to breast cancer and anemia, are simultaneously analyzed.

Detection of large prehistoric earthquakes in the pacific northwest by microfossil analysis.

PubMed

Mathewes, R W; Clague, J J

1994-04-29

Geologic and palynological evidence for rapid sea level change approximately 3400 and approximately 2000 carbon-14 years ago (3600 and 1900 calendar years ago) has been found at sites up to 110 kilometers apart in southwestern British Columbia. Submergence on southern Vancouver Island and slight emergence on the mainland during the older event are consistent with a great (magnitude M >/= 8) earthquake on the Cascadia subduction zone. The younger event is characterized by submergence throughout the region and may also record a plate-boundary earthquake or a very large crustal or intraplate earthquake. Microfossil analysis can detect small amounts of coseismic uplift and subsidence that leave little or no lithostratigraphic signature.

Zipf's Law Application To Oil Spill Detection In The Ocean

NASA Astrophysics Data System (ADS)

Platonov, A.; Redondo, J. M.

One of the results of the CLEAN SEAS European Union project using SAR imaging of European Coastal Waters was the statistical analysis and detection of thousands of oil spills and slicks in the three compared sections, Baltic Sea, North Sea and N.W. Mediterranean. The results of another European Project, OIL WATCH together with the past 30 years of recorded mayor tanker accidental oil spills have been used in a predictive scheme that subject to spatial and temporal normalization of these two different scale processes clearly shows that the annual probability of the occurence of an oil spill follows Zipf's law. Local deviations from the law may be also explained in terms of multifractal analysis.

Rapid earthquake detection through GPU-Based template matching

NASA Astrophysics Data System (ADS)

Mu, Dawei; Lee, En-Jui; Chen, Po

2017-12-01

The template-matching algorithm (TMA) has been widely adopted for improving the reliability of earthquake detection. The TMA is based on calculating the normalized cross-correlation coefficient (NCC) between a collection of selected template waveforms and the continuous waveform recordings of seismic instruments. In realistic applications, the computational cost of the TMA is much higher than that of traditional techniques. In this study, we provide an analysis of the TMA and show how the GPU architecture provides an almost ideal environment for accelerating the TMA and NCC-based pattern recognition algorithms in general. So far, our best-performing GPU code has achieved a speedup factor of more than 800 with respect to a common sequential CPU code. We demonstrate the performance of our GPU code using seismic waveform recordings from the ML 6.6 Meinong earthquake sequence in Taiwan.

Network monitoring in the Tier2 site in Prague

NASA Astrophysics Data System (ADS)

Eliáš, Marek; Fiala, Lukáš; Horký, Jiří; Chudoba, Jiří; Kouba, Tomáš; Kundrát, Jan; Švec, Jan

2011-12-01

Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.

Whole-rock uranium analysis by fission track activation

NASA Technical Reports Server (NTRS)

Weiss, J. R.; Haines, E. L.

1974-01-01

We report a whole-rock uranium method in which the polished sample and track detector are separated in a vacuum chamber. Irradiation with thermal neutrons induces uranium fission in the sample, and the detector records the integrated fission track density. Detection efficiency and geometric factors are calculated and compared with calibration experiments.

Identification of Damaged Wheat Kernels and Cracked-Shell Hazelnuts with Impact Acoustics Time-Frequency Patterns

USDA-ARS?s Scientific Manuscript database

A new adaptive time-frequency (t-f) analysis and classification procedure is applied to impact acoustic signals for detecting hazelnuts with cracked shells and three types of damaged wheat kernels. Kernels were dropped onto a steel plate, and the resulting impact acoustic signals were recorded with ...

Envelope detection using temporal magnetization dynamics of resonantly interacting spin-torque oscillator

NASA Astrophysics Data System (ADS)

Nakamura, Y.; Nishikawa, M.; Osawa, H.; Okamoto, Y.; Kanao, T.; Sato, R.

2018-05-01

In this article, we propose the detection method of the recorded data pattern by the envelope of the temporal magnetization dynamics of resonantly interacting spin-torque oscillator on the microwave assisted magnetic recording for three-dimensional magnetic recording. We simulate the envelope of the waveform from recorded dots with the staggered magnetization configuration, which are calculated by using a micromagnetic simulation. We study the data detection methods for the envelope and propose a soft-output Viterbi algorithm (SOVA) for partial response (PR) system as a signal processing system for three dimensional magnetic recording.

Anomaly detection applied to a materials control and accounting database

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

Whiteson, R.; Spanks, L.; Yarbro, T.

An important component of the national mission of reducing the nuclear danger includes accurate recording of the processing and transportation of nuclear materials. Nuclear material storage facilities, nuclear chemical processing plants, and nuclear fuel fabrication facilities collect and store large amounts of data describing transactions that involve nuclear materials. To maintain confidence in the integrity of these data, it is essential to identify anomalies in the databases. Anomalous data could indicate error, theft, or diversion of material. Yet, because of the complex and diverse nature of the data, analysis and evaluation are extremely tedious. This paper describes the authors workmore » in the development of analysis tools to automate the anomaly detection process for the Material Accountability and Safeguards System (MASS) that tracks and records the activities associated with accountable quantities of nuclear material at Los Alamos National Laboratory. Using existing guidelines that describe valid transactions, the authors have created an expert system that identifies transactions that do not conform to the guidelines. Thus, this expert system can be used to focus the attention of the expert or inspector directly on significant phenomena.« less

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

PubMed

Puce, Aina; Hämäläinen, Matti S

2017-05-31

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.

Using natural archives to detect climate and environmental tipping points in the Earth System

NASA Astrophysics Data System (ADS)

Thomas, Zoë A.

2016-11-01

'Tipping points' in the Earth system are characterised by a nonlinear response to gradual forcing, and may have severe and wide-ranging impacts. Many abrupt events result from simple underlying system dynamics termed 'critical transitions' or 'bifurcations'. One of the best ways to identify and potentially predict threshold behaviour in the climate system is through analysis of natural ('palaeo') archives. Specifically, on the approach to a tipping point, early warning signals can be detected as characteristic fluctuations in a time series as a system loses stability. Testing whether these early warning signals can be detected in highly complex real systems is a key challenge, since much work is either theoretical or only tested with simple models. This is particularly problematic in palaeoclimate and palaeoenvironmental records with low resolution, non-equidistant data, which can limit accurate analysis. Here, a range of different datasets are examined to explore generic rules that can be used to detect such dramatic events. A number of key criteria are identified to be necessary for the reliable identification of early warning signals in natural archives, most crucially, the need for a low-noise record of sufficient data length, resolution and accuracy. A deeper understanding of the underlying system dynamics is required to inform the development of more robust system-specific indicators, or to indicate the temporal resolution required, given a known forcing. This review demonstrates that time series precursors from natural archives provide a powerful means of forewarning tipping points within the Earth System.

MyShake: Smartphone-based detection and analysis of Oklahoma earthquakes

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.; Schreier, L.

2016-12-01

MyShake is a global smartphone seismic network that harnesses the power of crowdsourcing (myshake.berkeley.edu). It uses the accelerometer data from phones to detect earthquake-like motion, and then uploads triggers and waveform data to a server for aggregation of the results. Since the public release in Feb 2016, more than 200,000 android-phone owners have installed the app, and the global network has recorded more than 300 earthquakes. In Oklahoma, there are about 200 active users each day providing enough data for the network to detect earthquakes and for us to perform analysis of the events. MyShake has recorded waveform data for M2.6 to M5.8 earthquakes in the state. For the September 3, 2016, M5.8 earthquake 14 phones detected the event and we can use the waveforms to determine event characteristics. MyShake data provides a location 3.95 km from the ANSS location and a magnitude of 5.7. We can also use MyShake data to estimate a stress drop of 7.4 MPa. MyShake is still a rapidly expanding network that has the ability to grow by thousands of stations/phones in a matter of hours as public interest increases. These initial results suggest that the data will be useful for a variety of scientific studies of induced seismicity phenomena in Oklahoma as well as having the potential to provide earthquake early warning in the future.

Deriving a sea surface temperature record suitable for climate change research from the along-track scanning radiometers

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Llewellyn-Jones, D.; Saunders, R. W.; Rayner, N. A.; Kent, E. C.; Old, C. P.; Berry, D.; Birks, A. R.; Blackmore, T.; Corlett, G. K.; Embury, O.; Jay, V. L.; Kennedy, J.; Mutlow, C. T.; Nightingale, T. J.; O'Carroll, A. G.; Pritchard, M. J.; Remedios, J. J.; Tett, S.

We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991 2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade-1, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.

Chronic disease detection and access: does access improve detection, or does detection make access more difficult?

PubMed

Anwar, Mohammed Saqib; Baker, Richard; Walker, Nicola; Mainous, Arch G; Bankart, M John

2012-05-01

The recorded detection of chronic disease by practices is generally lower than the prevalence predicted by population surveys. To determine whether patient-reported access to general practice predicts the recorded detection rates of chronic diseases in that setting. A cross-sectional study involving 146 general practices in Leicestershire and Rutland, England. The numbers of patients recorded as having chronic disease (coronary heart disease, chronic obstructive pulmonary disease, hypertension, diabetes) were obtained from Quality and Outcomes Framework (QOF) practice disease registers for 2008-2009. Characteristics of practice populations (deprivation, age, sex, ethnicity, proportion reporting poor health, practice turnover, list size) and practice performance (achievement of QOF disease indicators, patient experience of being able to consult a doctor within 2 working days and book an appointment >2 days in advance) were included in regression models. Patient characteristics (deprivation, age, poor health) and practice characteristics (list size, turnover, QOF achievement) were associated with recorded detection of more than one of the chronic diseases. Practices in which patients were more likely to report being able to book appointments had reduced recording rates of chronic disease. Being able to consult a doctor within 2 days was not associated with levels of recorded chronic disease. Practices with high levels of deprivation and older patients have increased rates of recorded chronic disease. As the number of patients recorded with chronic disease increased, the capacity of practices to meet patients' requests for appointments in advance declined. The capacity of some practices to detect and manage chronic disease may need improving.

Monitoring of bread cooling by statistical analysis of laser speckle patterns

NASA Astrophysics Data System (ADS)

Lyubenova, Tanya; Stoykova, Elena; Nacheva, Elena; Ivanov, Branimir; Panchev, Ivan; Sainov, Ventseslav

2013-03-01

The phenomenon of laser speckle can be used for detection and visualization of physical or biological activity in various objects (e.g. fruits, seeds, coatings) through statistical description of speckle dynamics. The paper presents the results of non-destructive monitoring of bread cooling by co-occurrence matrix and temporal structure function analysis of speckle patterns which have been recorded continuously within a few days. In total, 72960 and 39680 images were recorded and processed for two similar bread samples respectively. The experiments proved the expected steep decrease of activity related to the processes in the bread samples during the first several hours and revealed its oscillating character within the next few days. Characterization of activity over the bread sample surface was also obtained.

A simple computer-based measurement and analysis system of pulmonary auscultation sounds.

PubMed

Polat, Hüseyin; Güler, Inan

2004-12-01

Listening to various lung sounds has proven to be an important diagnostic tool for detecting and monitoring certain types of lung diseases. In this study a computer-based system has been designed for easy measurement and analysis of lung sound using the software package DasyLAB. The designed system presents the following features: it is able to digitally record the lung sounds which are captured with an electronic stethoscope plugged to a sound card on a portable computer, display the lung sound waveform for auscultation sites, record the lung sound into the ASCII format, acoustically reproduce the lung sound, edit and print the sound waveforms, display its time-expanded waveform, compute the Fast Fourier Transform (FFT), and display the power spectrum and spectrogram.

Emergency Department Chief Complaint and Diagnosis Data to Detect Influenza-Like Illness with an Electronic Medical Record

PubMed Central

May, Larissa S.; Griffin, Beth Ann; Bauers, Nicole Maier; Jain, Arvind; Mitchum, Marsha; Sikka, Neal; Carim, Marianne; Stoto, Michael A.

2010-01-01

Background: The purpose of syndromic surveillance is early detection of a disease outbreak. Such systems rely on the earliest data, usually chief complaint. The growing use of electronic medical records (EMR) raises the possibility that other data, such as emergency department (ED) diagnosis, may provide more specific information without significant delay, and might be more effective in detecting outbreaks if mechanisms are in place to monitor and report these data. Objective: The purpose of this study is to characterize the added value of the primary ICD-9 diagnosis assigned at the time of ED disposition compared to the chief complaint for patients with influenza-like illness (ILI). Methods: The study was a retrospective analysis of the EMR of a single urban, academic ED with an annual census of over 60, 000 patients per year from June 2005 through May 2006. We evaluate the objective in two ways. First, we characterize the proportion of patients whose ED diagnosis is inconsistent with their chief complaint and the variation by complaint. Second, by comparing time series and applying syndromic detection algorithms, we determine which complaints and diagnoses are the best indicators for the start of the influenza season when compared to the Centers for Disease Control regional data for Influenza-Like Illness for the 2005 to 2006 influenza season using three syndromic surveillance algorithms: univariate cumulative sum (CUSUM), exponentially weighted CUSUM, and multivariate CUSUM. Results: In the first analysis, 29% of patients had a different diagnosis at the time of disposition than suggested by their chief complaint. In the second analysis, complaints and diagnoses consistent with pneumonia, viral illness and upper respiratory infection were together found to be good indicators of the start of the influenza season based on temporal comparison with regional data. In all examples, the diagnosis data outperformed the chief-complaint data. Conclusion: Both analyses suggest the ED diagnosis contains useful information for detection of ILI. Where an EMR is available, the short time lag between complaint and diagnosis may be a price worth paying for additional information despite the brief potential delay in detection, especially considering that detection usually occurs over days rather than hours. PMID:20411066

Insertable cardiac event recorder in detection of atrial fibrillation after cryptogenic stroke: an audit report.

PubMed

Etgen, Thorleif; Hochreiter, Manfred; Mundel, Markus; Freudenberger, Thomas

2013-07-01

Atrial fibrillation (AF) is the most frequent risk factor in ischemic stroke but often remains undetected. We analyzed the value of insertable cardiac event recorder in detection of AF in a 1-year cohort of patients with cryptogenic ischemic stroke. All patients with cryptogenic stroke and eligibility for oral anticoagulation were offered the insertion of a cardiac event recorder. Regular follow-up for 1 year recorded the incidence of AF. Of the 393 patients with ischemic stroke, 65 (16.5%) had a cryptogenic stroke, and in 22 eligible patients, an event recorder was inserted. After 1 year, in 6 of 22 patients (27.3%), AF was detected. These preliminary data show that insertion of cardiac event recorder was eligible in approximately one third of patients with cryptogenic stroke and detected in approximately one quarter of these patients new AF.

Application of photogrammetry for analysis of occlusal contacts.

PubMed

Shigeta, Yuko; Hirabayashi, Rio; Ikawa, Tomoko; Kihara, Takuya; Ando, Eriko; Hirai, Shinya; Fukushima, Shunji; Ogawa, Takumi

2013-04-01

The conventional 2D-analysis methods for occlusal contacts provided limited information on tooth morphology. This present study aims to detect 3D positional information of occlusal contacts from 2D-photos via photogrammetry. We propose an image processing solution for analysis of occlusal contacts and facets via the black silicone method and a photogrammetric technique. The occlusal facets were reconstructed from a 2D-photograph data-set of inter-occlusal records into a 3D image via photogrammetry. The configuration of the occlusal surface was reproduced with polygons. In addition, the textures of the occlusal contacts were mapped to each polygon. DIFFERENCE FROM CONVENTIONAL METHODS: Constructing occlusal facets with 3D polygons from 2D-photos with photogrammetry was a defining characteristic of this image processing technique. It allowed us to better observe findings of the black silicone method. Compared with conventional 3D analysis using a 3D scanner, our 3D models did not reproduce the detail of the anatomical configuration. However, by merging the findings of the inter-occlusal record, the deformation of mandible and the displacement of periodontal ligaments under occlusal force were reflected in our model. EFFECT OR PERFORMANCE: Through the use of polygons in the conversion of 2D images to 3D images, we were able to define the relation between the location and direction of the occlusal contacts and facets, which was difficult to detect via conventional methods. Through our method of making a 3D polygon model, the findings of inter-occlusal records which reflected the jaw/teeth behavior under occlusal force could be observed 3-dimensionally. Copyright © 2012 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Classification of functional interactions from multi-electrodes data using conditional modularity analysis

NASA Astrophysics Data System (ADS)

Makhtar, Siti Noormiza; Senik, Mohd Harizal

2018-02-01

The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.

Video content analysis of surgical procedures.

PubMed

Loukas, Constantinos

2018-02-01

In addition to its therapeutic benefits, minimally invasive surgery offers the potential for video recording of the operation. The videos may be archived and used later for reasons such as cognitive training, skills assessment, and workflow analysis. Methods from the major field of video content analysis and representation are increasingly applied in the surgical domain. In this paper, we review recent developments and analyze future directions in the field of content-based video analysis of surgical operations. The review was obtained from PubMed and Google Scholar search on combinations of the following keywords: 'surgery', 'video', 'phase', 'task', 'skills', 'event', 'shot', 'analysis', 'retrieval', 'detection', 'classification', and 'recognition'. The collected articles were categorized and reviewed based on the technical goal sought, type of surgery performed, and structure of the operation. A total of 81 articles were included. The publication activity is constantly increasing; more than 50% of these articles were published in the last 3 years. Significant research has been performed for video task detection and retrieval in eye surgery. In endoscopic surgery, the research activity is more diverse: gesture/task classification, skills assessment, tool type recognition, shot/event detection and retrieval. Recent works employ deep neural networks for phase and tool recognition as well as shot detection. Content-based video analysis of surgical operations is a rapidly expanding field. Several future prospects for research exist including, inter alia, shot boundary detection, keyframe extraction, video summarization, pattern discovery, and video annotation. The development of publicly available benchmark datasets to evaluate and compare task-specific algorithms is essential.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

PubMed

Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

2018-01-01

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Comparison of acoustic recorders and field observers for monitoring tundra bird communities

USGS Publications Warehouse

Vold, Skyler T.; Handel, Colleen M.; McNew, Lance B.

2017-01-01

Acoustic recorders can be useful for studying bird populations but their efficiency and accuracy should be assessed in pertinent ecological settings before use. We investigated the utility of an acoustic recorder for monitoring abundance of tundra‐breeding birds relative to point‐count surveys in northwestern Alaska, USA, during 2014. Our objectives were to 1) compare numbers of birds and species detected by a field observer with those detected simultaneously by an acoustic recorder; 2) evaluate how detection probabilities for the observer and acoustic recorder varied with distance of birds from the survey point; and 3) evaluate whether avian guild‐specific detection rates differed between field observers and acoustic recorders relative to habitat. Compared with the observer, the acoustic recorder detected fewer species (βMethod = −0.39 ± 0.07) and fewer individuals (βMethod = −0.56 ± 0.05) in total and for 6 avian guilds. Discrepancies were attributed primarily to differences in effective area surveyed (91% missed by device were >100 m), but also to nonvocal birds being missed by the recorder (55% missed <100 m were silent). The observer missed a few individuals and one species detected by the device. Models indicated that relative abundance of various avian guilds was associated primarily with maximum shrub height and less so with shrub cover and visual obstruction. The absence of a significant interaction between survey method (observer vs. acoustic recorder) and any habitat characteristic suggests that traditional point counts and acoustic recorders would yield similar inferences about ecological relationships in tundra ecosystems. Pairing of the 2 methods could increase survey efficiency and allow for validation and archival of survey results.

Geomagnetic storm under laboratory conditions: randomized experiment

NASA Astrophysics Data System (ADS)

Gurfinkel, Yu I.; Vasin, A. L.; Pishchalnikov, R. Yu; Sarimov, R. M.; Sasonko, M. L.; Matveeva, T. A.

2017-10-01

The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

Geomagnetic storm under laboratory conditions: randomized experiment.

PubMed

Gurfinkel, Yu I; Vasin, A L; Pishchalnikov, R Yu; Sarimov, R M; Sasonko, M L; Matveeva, T A

2018-04-01

The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

PubMed Central

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration (High Freq) performed similarly to non-parametric methods, but had the highest recall values, suggesting that this method could be employed for automatic tremor detection. PMID:27258018

EEG seizure detection and prediction algorithms: a survey

NASA Astrophysics Data System (ADS)

Alotaiby, Turkey N.; Alshebeili, Saleh A.; Alshawi, Tariq; Ahmad, Ishtiaq; Abd El-Samie, Fathi E.

2014-12-01

Epilepsy patients experience challenges in daily life due to precautions they have to take in order to cope with this condition. When a seizure occurs, it might cause injuries or endanger the life of the patients or others, especially when they are using heavy machinery, e.g., deriving cars. Studies of epilepsy often rely on electroencephalogram (EEG) signals in order to analyze the behavior of the brain during seizures. Locating the seizure period in EEG recordings manually is difficult and time consuming; one often needs to skim through tens or even hundreds of hours of EEG recordings. Therefore, automatic detection of such an activity is of great importance. Another potential usage of EEG signal analysis is in the prediction of epileptic activities before they occur, as this will enable the patients (and caregivers) to take appropriate precautions. In this paper, we first present an overview of seizure detection and prediction problem and provide insights on the challenges in this area. Second, we cover some of the state-of-the-art seizure detection and prediction algorithms and provide comparison between these algorithms. Finally, we conclude with future research directions and open problems in this topic.

SIG-VISA: Signal-based Vertically Integrated Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.; Mayeda, K. M.; Myers, S. C.; Russell, S.

2013-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software; however, while such detections may constitute a useful summary of station activity, they discard large amounts of information present in the original recorded signal. We present SIG-VISA (Signal-based Vertically Integrated Seismic Analysis), a system for seismic monitoring through Bayesian inference on seismic signals. By directly modeling the recorded signal, our approach incorporates additional information unavailable to detection-based methods, enabling higher sensitivity and more accurate localization using techniques such as waveform matching. SIG-VISA's Bayesian forward model of seismic signal envelopes includes physically-derived models of travel times and source characteristics as well as Gaussian process (kriging) statistical models of signal properties that combine interpolation of historical data with extrapolation of learned physical trends. Applying Bayesian inference, we evaluate the model on earthquakes as well as the 2009 DPRK test event, demonstrating a waveform matching effect as part of the probabilistic inference, along with results on event localization and sensitivity. In particular, we demonstrate increased sensitivity from signal-based modeling, in which the SIGVISA signal model finds statistical evidence for arrivals even at stations for which the IMS station processing failed to register any detection.

Orbital forced frequencies in the 975000 year pollen record from Tenagi Philippon (Greece)

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

Mommersteeg, H.J.P.M.; Young, R.; Wijmstra, T.A.

Frequency analysis was applied to different time series obtained from the 975 ka pollen record of Tenagi Philippon (Macedonia, Greece). These time series are characteristic of different vegetation types related to specific climatic conditions. Time control of the 196 m deep core was based on 11 finite {sup 14}C dates in the upper 17 m, magnetostratigraphy and correlation with the marine oxygen isotope stratigraphy. Maximum entropy spectrum analyses and thomson multi-taper spectrum analysis were applied using the complete time series. Periods of 95-99, 40-45. 24.0-25.5 and 19-21 ka which can be related to orbital forcing, as well as periods ofmore » about 68, 30 ka and of about 15.5, 13.5, 12 and 10.5 ka were detected. The detected periods of about 68, 30 ka and 16, 14, 12, 10.5 ka are likely to be harmonics and combination tones of the periods related to orbital forcing. The period of around 30 ka is possibly a secondary peak of obliquity. To study the stability of the detected periods through time, analysis with a moving window was employed. Signals in the eccentricity band were detected clearly during the last 650 ka. In the precession band, detected periods of about 24 ka show an increase in amplitude during the last 650 ka. The evolution of orbital frequencies during the last 1.0 Ma is in general agreement with the results of other marine and continental time series. Time series related to different climatic settings showed a different response to orbital forcing. Time series of vegetational elements sensitive to changes in net precipitation were forced in the precession and obliquity bands. Changes in precession caused changes in the monsoon system, which indirectly had a strong influence on the climatic history of Greece. Time series of vegetational elements which are more indicative of changes in annual temperature are forced in the eccentricity band. 54 refs., 12 figs., 3 tabs.« less

Detection of sleep disordered breathing and its central/obstructive character using nasal cannula and finger pulse oximeter.

PubMed

Sommermeyer, Dirk; Zou, Ding; Grote, Ludger; Hedner, Jan

2012-10-15

To assess the accuracy of novel algorithms using an oximeter-based finger plethysmographic signal in combination with a nasal cannula for the detection and differentiation of central and obstructive apneas. The validity of single pulse oximetry to detect respiratory disturbance events was also studied. Patients recruited from four sleep laboratories underwent an ambulatory overnight cardiorespiratory polygraphy recording. The nasal flow and photoplethysmographic signals of the recording were analyzed by automated algorithms. The apnea hypopnea index (AHI(auto)) was calculated using both signals, and a respiratory disturbance index (RDI(auto)) was calculated from photoplethysmography alone. Apnea events were classified into obstructive and central types using the oximeter derived pulse wave signal and compared with manual scoring. Sixty-six subjects (42 males, age 54 ± 14 yrs, body mass index 28.5 ± 5.9 kg/m(2)) were included in the analysis. AHI(manual) (19.4 ± 18.5 events/h) correlated highly significantly with AHI(auto) (19.9 ± 16.5 events/h) and RDI(auto) (20.4 ± 17.2 events/h); the correlation coefficients were r = 0.94 and 0.95, respectively (p < 0.001) with a mean difference of -0.5 ± 6.6 and -1.0 ± 6.1 events/h. The automatic analysis of AHI(auto) and RDI(auto) detected sleep apnea (cutoff AHI(manual) ≥ 15 events/h) with a sensitivity/specificity of 0.90/0.97 and 0.86/0.94, respectively. The automated obstructive/central apnea indices correlated closely with manually scoring (r = 0.87 and 0.95, p < 0.001) with mean difference of -4.3 ± 7.9 and 0.3 ± 1.5 events/h, respectively. Automatic analysis based on routine pulse oximetry alone may be used to detect sleep disordered breathing with accuracy. In addition, the combination of photoplethysmographic signals with a nasal flow signal provides an accurate distinction between obstructive and central apneic events during sleep.

Target Detection Routine (TADER). User’s Guide.

DTIC Science & Technology

1987-09-01

o System range capability subset (one record - omitted for standoff SLAR and penetrating system) o System inherent detection probability subset ( IELT ...records, i.e., one per element type) * System capability modifier subset/A=1, E=1 ( IELT records) o System capability modifier subset/A=1, E=2 ( IELT ...records) s System capability modifier subset/A=2, E=1 ( IELT records) o System capability modifier subset/A=2, E=2 ( IELT records) Unit Data Set (one set

Detection of the Sleep Stages Throughout Non-Obtrusive Measures of Inter-Beat Fluctuations and Motion: Night and Day Sleep of Female Shift Workers

NASA Astrophysics Data System (ADS)

Mendez, Martin O.; Palacios-Hernandez, Elvia R.; Alba, Alfonso; Kortelainen, Juha M.; Tenhunen, Mirja L.; Bianchi, Anna M.

Automatic sleep staging based on inter-beat fluctuations and motion signals recorded through a pressure bed sensor during sleep is presented. The analysis of the sleep was based on the three major divisions of the sleep time: Wake, non-rapid eye movement (nREM) and rapid eye movement (REM) sleep stages. Twelve sleep recordings, from six females working alternate shift, with their respective annotations were used in the study. Six recordings were acquired during the night and six during the day after a night shift. A Time-Variant Autoregressive Model was used to extract features from inter-beat fluctuations which later were fed to a Support Vector Machine classifier. Accuracy, Kappa index, and percentage in wake, REM and nREM were used as performance measures. Comparison between the automatic sleep staging detection and the standard clinical annotations, shows mean values of 87% for accuracy 0.58 for kappa index, and mean errors of 5% for sleep stages. The performance measures were similar for night and day sleep recordings. In this sample of recordings, the results suggest that inter-beat fluctuations and motions acquired in non-obtrusive way carried valuable information related to the sleep macrostructure and could be used to support to the experts in extensive evaluation and monitoring of sleep.

Impact of Near-Field, Deep-Ocean Tsunami Observations on Forecasting the 7 December 2012 Japanese Tsunami

NASA Astrophysics Data System (ADS)

Bernard, Eddie; Wei, Yong; Tang, Liujuan; Titov, Vasily

2014-12-01

Following the devastating 11 March 2011 tsunami, two deep-ocean assessment and reporting of tsunamis (DART®)(DART® and the DART® logo are registered trademarks of the National Oceanic and Atmospheric Administration, used with permission) stations were deployed in Japanese waters by the Japanese Meteorological Agency. Two weeks after deployment, on 7 December 2012, a M w 7.3 earthquake off Japan's Pacific coastline generated a tsunami. The tsunami was recorded at the two Japanese DARTs as early as 11 min after the earthquake origin time, which set a record as the fastest tsunami detecting time at a DART station. These data, along with those recorded at other DARTs, were used to derive a tsunami source using the National Oceanic and Atmospheric Administration tsunami forecast system. The results of our analysis show that data provided by the two near-field Japanese DARTs can not only improve the forecast speed but also the forecast accuracy at the Japanese tide gauge stations. This study provides important guidelines for early detection and forecasting of local tsunamis.

Digital PCR to determine the number of transcripts from single neurons after patch-clamp recording.

PubMed

Faragó, Nóra; Kocsis, Ágnes K; Lovas, Sándor; Molnár, Gábor; Boldog, Eszter; Rózsa, Márton; Szemenyei, Viktor; Vámos, Enikő; Nagy, Lajos I; Tamás, Gábor; Puskás, László G

2013-06-01

Whole-cell patch-clamp recording enables detection of electrophysiological signals from single neurons as well as harvesting of perisomatic RNA through the patch pipette for subsequent gene expression analysis. Amplification and profiling of RNA with traditional quantitative real-time PCR (qRT-PCR) do not provide exact quantitation due to experimental variation caused by the limited amount of nucleic acid in a single cell. Here we describe a protocol for quantifying mRNA or miRNA expression in individual neurons after patch-clamp recording using high-density nanocapillary digital PCR (dPCR). Expression of a known cell-type dependent marker gene (gabrd), as well as oxidative-stress related induction of hspb1 and hmox1 expression, was quantified in individual neurogliaform and pyramidal cells, respectively. The miRNA mir-132, which plays a role in neurodevelopment, was found to be equally expressed in three different types of neurons. The accuracy and sensitivity of this method were further validated using synthetic spike-in templates and by detecting genes with very low levels of expression.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

NASA Astrophysics Data System (ADS)

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-03-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

PubMed Central

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-01-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy. PMID:28300146

Toward the 4-Micron Infrared Spectrum of the Transiting Extrasolar Planet HD 209458 b

NASA Astrophysics Data System (ADS)

Richardson, L. J.; Deming, D.

2003-12-01

We have continued our analysis of infrared spectra of the "transiting planet" system, HD 209458, recorded at the NASA IRTF in September 2001. The spectra cover two predicted secondary eclipse events, wherein the planet passed behind the star and re-emerged. We are attempting to detect the planet's infrared continuum peaks, by exploiting the spectral modulation which accompanies the secondary eclipse. Our initial analysis placed the strongest limits to date on the spectrum of the planet near 2.2 microns (Richardson, Deming & Seager 2003, recently appeared in ApJ). Further analysis of our long wavelength data (3.0--4.2 microns) decorrelates and removes most of the systematic errors due to seeing and guiding fluctuations. This decorrelation has improved the precision of our analysis to the level where a predicted 4-micron planetary flux peak may now be detectable.

METHOD AND APPARATUS FOR THE DETECTION OF LEAKS IN PIPE LINES

DOEpatents

Jefferson, S.; Cameron, J.F.

1961-11-28

A method is described for detecting leaks in pipe lines carrying fluid. The steps include the following: injecting a radioactive solution into a fluid flowing in the line; flushing the line clear of the radioactive solution; introducing a detector-recorder unit, comprising a radioactivity radiation detector and a recorder which records the detector signal over a time period at a substantially constant speed, into the line in association with a go-devil capable of propelling the detector-recorder unit through the line in the direction of the fluid flow at a substantia1ly constant velocity; placing a series of sources of radioactivity at predetermined distances along the downstream part of the line to make a characteristic signal on the recorder record at intervals corresponding to the location of said sources; recovering the detector-recorder unit at a downstream point along the line; transcribing the recorder record of any radioactivity detected during the travel of the detector- recorder unit in terms of distance along the line. (AEC)

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2014-01-01

A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

Patient safety in primary allied health care: what can we learn from incidents in a Dutch exploratory cohort study?

PubMed

van Dulmen, Simone A; Tacken, Margot A J B; Staal, J Bart; Gaal, Sander; Wensing, Michel; Nijhuis-van der Sanden, Maria W G

2011-12-01

Research on patient safety in allied healthcare is scarce. Our aim was to document patient safety in primary allied healthcare in the Netherlands and to identify factors associated with incidents. DESIGN AND SUBJECT: A retrospective study of 1000 patient records in a representative sample of 20 allied healthcare practices was combined with a prospective incident-reporting study. All records were reviewed by trained researchers to identify patient safety incidents. The incidents were classified and analyzed, using the Prevention and Recovery Information System for Monitoring and Analysis method. Factors associated with incidents were examined in a logistic regression analysis. In 18 out of 1000 (1.8%; 95% confidence interval: 1.0-2.6) records an incident was detected. The main causes of incidents were related to errors in clinical decisions (89%), communication with other healthcare providers (67%), and monitoring (56%). The probability of incidents was higher if more care providers had been involved and if patient records were incomplete (37% of the records). No incidents were reported in the prospective study. The absolute number of incidents was low, which could imply a low risk of harm in Dutch primary allied healthcare. Nevertheless, incompleteness of the patient records and the fact that incidents were mainly caused through human actions suggest that a focus on clinical reasoning and record keeping is needed to further enhance patient safety. Improvements in record keeping will be necessary before accurate incident reporting will be feasible and valid.

Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.

PubMed

Mammone, Nadia; Morabito, Francesco Carlo

2008-09-01

Artifacts are disturbances that may occur during signal acquisition and may affect their processing. The aim of this paper is to propose a technique for automatically detecting artifacts from the electroencephalographic (EEG) recordings. In particular, a technique based on both Independent Component Analysis (ICA) to extract artifactual signals and on Renyi's entropy to automatically detect them is presented. This technique is compared to the widely known approach based on ICA and the joint use of kurtosis and Shannon's entropy. The novel processing technique is shown to detect on average 92.6% of the artifactual signals against the average 68.7% of the previous technique on the studied available database. Moreover, Renyi's entropy is shown to be able to detect muscle and very low frequency activity as well as to discriminate them from other kinds of artifacts. In order to achieve an efficient rejection of the artifacts while minimizing the information loss, future efforts will be devoted to the improvement of blind artifact separation from EEG in order to ensure a very efficient isolation of the artifactual activity from any signals deriving from other brain tasks.

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

Shull, D.

This report documents the initial feasibility tests performed using a commercial acoustic emission instrument for the purpose of detecting beetles in Department of Energy 9975 shipping packages. The device selected for this testing was a commercial handheld instrument and probe developed for the detection of termites, weevils, beetles and other insect infestations in wooden structures, trees, plants and soil. The results of two rounds of testing are presented. The first tests were performed by the vendor using only the hand-held instrument’s indications and real-time operator analysis of the audio signal content. The second tests included hands-free positioning of the instrumentmore » probe and post-collection analysis of the recorded audio signal content including audio background comparisons. The test results indicate that the system is promising for detecting the presence of drugstore beetles, however, additional work would be needed to improve the ease of detection and to automate the signal processing to eliminate the need for human interpretation. Mechanisms for hands-free positioning of the probe and audio background discrimination are also necessary for reliable detection and to reduce potential operator dose in radiation environments.« less

Assessing bat detectability and occupancy with multiple automated echolocation detectors

USGS Publications Warehouse

Gorresen, P.M.; Miles, A.C.; Todd, C.M.; Bonaccorso, F.J.; Weller, T.J.

2008-01-01

Occupancy analysis and its ability to account for differential detection probabilities is important for studies in which detecting echolocation calls is used as a measure of bat occurrence and activity. We examined the feasibility of remotely acquiring bat encounter histories to estimate detection probability and occupancy. We used echolocation detectors coupled to digital recorders operating at a series of proximate sites on consecutive nights in 2 trial surveys for the Hawaiian hoary bat (Lasiurus cinereus semotus). Our results confirmed that the technique is readily amenable for use in occupancy analysis. We also conducted a simulation exercise to assess the effects of sampling effort on parameter estimation. The results indicated that the precision and bias of parameter estimation were often more influenced by the number of sites sampled than number of visits. Acceptable accuracy often was not attained until at least 15 sites or 15 visits were used to estimate detection probability and occupancy. The method has significant potential for use in monitoring trends in bat activity and in comparative studies of habitat use. ?? 2008 American Society of Mammalogists.

Multi-channel acoustic recording and automated analysis of Drosophila courtship songs

PubMed Central

2013-01-01

Background Drosophila melanogaster has served as a powerful model system for genetic studies of courtship songs. To accelerate research on the genetic and neural mechanisms underlying courtship song, we have developed a sensitive recording system to simultaneously capture the acoustic signals from 32 separate pairs of courting flies as well as software for automated segmentation of songs. Results Our novel hardware design enables recording of low amplitude sounds in most laboratory environments. We demonstrate the power of this system by collecting, segmenting and analyzing over 18 hours of courtship song from 75 males from five wild-type strains of Drosophila melanogaster. Our analysis reveals previously undetected modulation of courtship song features and extensive natural genetic variation for most components of courtship song. Despite having a large dataset with sufficient power to detect subtle modulations of song, we were unable to identify previously reported periodic rhythms in the inter-pulse interval of song. We provide detailed instructions for assembling the hardware and for using our open-source segmentation software. Conclusions Analysis of a large dataset of acoustic signals from Drosophila melanogaster provides novel insight into the structure and dynamics of species-specific courtship songs. Our new system for recording and analyzing fly acoustic signals should therefore greatly accelerate future studies of the genetics, neurobiology and evolution of courtship song. PMID:23369160

Influence of auditory attention on sentence recognition captured by the neural phase.

PubMed

Müller, Jana Annina; Kollmeier, Birger; Debener, Stefan; Brand, Thomas

2018-03-07

The aim of this study was to investigate whether attentional influences on speech recognition are reflected in the neural phase entrained by an external modulator. Sentences were presented in 7 Hz sinusoidally modulated noise while the neural response to that modulation frequency was monitored by electroencephalogram (EEG) recordings in 21 participants. We implemented a selective attention paradigm including three different attention conditions while keeping physical stimulus parameters constant. The participants' task was either to repeat the sentence as accurately as possible (speech recognition task), to count the number of decrements implemented in modulated noise (decrement detection task), or to do both (dual task), while the EEG was recorded. Behavioural analysis revealed reduced performance in the dual task condition for decrement detection, possibly reflecting limited cognitive resources. EEG analysis revealed no significant differences in power for the 7 Hz modulation frequency, but an attention-dependent phase difference between tasks. Further phase analysis revealed a significant difference 500 ms after sentence onset between trials with correct and incorrect responses for speech recognition, indicating that speech recognition performance and the neural phase are linked via selective attention mechanisms, at least shortly after sentence onset. However, the neural phase effects identified were small and await further investigation. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Analysis of real-time vibration data

USGS Publications Warehouse

Safak, E.

2005-01-01

In recent years, a few structures have been instrumented to provide continuous vibration data in real time, recording not only large-amplitude motions generated by extreme loads, but also small-amplitude motions generated by ambient loads. The main objective in continuous recording is to track any changes in structural characteristics, and to detect damage after an extreme event, such as an earthquake or explosion. The Fourier-based spectral analysis methods have been the primary tool to analyze vibration data from structures. In general, such methods do not work well for real-time data, because real-time data are mainly composed of ambient vibrations with very low amplitudes and signal-to-noise ratios. The long duration, linearity, and the stationarity of ambient data, however, allow us to utilize statistical signal processing tools, which can compensate for the adverse effects of low amplitudes and high noise. The analysis of real-time data requires tools and techniques that can be applied in real-time; i.e., data are processed and analyzed while being acquired. This paper presents some of the basic tools and techniques for processing and analyzing real-time vibration data. The topics discussed include utilization of running time windows, tracking mean and mean-square values, filtering, system identification, and damage detection.

A shift in the spatial pattern of Iberian droughts during the 17th century

NASA Astrophysics Data System (ADS)

Domínguez-Castro, F.; García-Herrera, R.; Ribera, P.; Barriendos, M.

2010-09-01

In this paper, series of drought occurrence and drought extension in the Iberian Peninsula are constructed for the 1600-1750 period from seven rogation series. These rogation ceremony records come from Bilbao, Catalonia, Zamora, Zaragoza, Toledo, Murcia and Seville. They are distributed across the Peninsula and include the areas with the most characteristic Iberian climate types, influenced by the Atlantic and the Mediterranean conditions, described from modern data. A seasonal division of the series shows that spring is a critical season for rogation series in most of Iberia, being Bilbao the only site were the highest number of rogations is detected for a different season. The annual analysis of the series shows a dramatic difference between the first half of the 17th century when droughts are characterized by its local character; and the rest of the period, when they affect to broader regions or even to the whole Peninsula. The analysis of spring series confirms the existence of the two periods detected in the annual analysis. Finally, secondary documentary sources are used to further characterise the two most extended droughts in the period, 1664 and 1680, and to verify the extension of the areas affected by droughts recorded through rogation series.

Automatic detection of sleep macrostructure based on a sensorized T-shirt.

PubMed

Bianchi, Anna M; Mendez, Martin O

2010-01-01

In the present work we apply a fully automatic procedure to the analysis of signal coming from a sensorized T-shit, worn during the night, for sleep evaluation. The goodness and reliability of the signals recorded trough the T-shirt was previously tested, while the employed algorithms for feature extraction and sleep classification were previously developed on standard ECG recordings and the obtained classification was compared to the standard clinical practice based on polysomnography (PSG). In the present work we combined T-shirt recordings and automatic classification and could obtain reliable sleep profiles, i.e. the sleep classification in WAKE, REM (rapid eye movement) and NREM stages, based on heart rate variability (HRV), respiration and movement signals.

Direct optical detection of protein-ligand interactions.

PubMed

Gesellchen, Frank; Zimmermann, Bastian; Herberg, Friedrich W

2005-01-01

Direct optical detection provides an excellent means to investigate interactions of molecules in biological systems. The dynamic equilibria inherent to these systems can be described in greater detail by recording the kinetics of a biomolecular interaction. Optical biosensors allow direct detection of interaction patterns without the need for labeling. An overview covering several commercially available biosensors is given, with a focus on instruments based on surface plasmon resonance (SPR) and reflectometric interference spectroscopy (RIFS). Potential assay formats and experimental design, appropriate controls, and calibration procedures, especially when handling low molecular weight substances, are discussed. The single steps of an interaction analysis combined with practical tips for evaluation, data processing, and interpretation of kinetic data are described in detail. In a practical example, a step-by-step procedure for the analysis of a low molecular weight compound interaction with serum protein, determined on a commercial SPR sensor, is presented.

Phylogenetic analysis of canine distemper virus in domestic dogs in Nanjing, China.

PubMed

Bi, Zhenwei; Wang, Yongshan; Wang, Xiaoli; Xia, Xingxia

2015-02-01

Canine distemper virus (CDV) infects a broad range of carnivores, including wild and domestic Canidae. The hemagglutinin gene, which encodes the attachment protein that determines viral tropism, has been widely used to determine the relationship between CDV strains of different lineages circulating worldwide. We determined the full-length H gene sequences of seven CDV field strains detected in domestic dogs in Nanjing, China. A phylogenetic analysis of the H gene sequences of CDV strains from different geographic regions and vaccine strains was performed. Four of the seven CDV strains were grouped in the same cluster of the Asia-1 lineage to which the vast majority of Chinese CDV strains belong, whereas the other three were clustered within the Asia-4 lineage, which has never been detected in China. This represents the first record of detection of strains of the Asia-4 lineage in China since this lineage was reported in Thailand in 2013.

Microorganisms detection on substrates using QCL spectroscopy

NASA Astrophysics Data System (ADS)

Padilla-Jiménez, Amira C.; Ortiz-Rivera, William; Castro-Suarez, John R.; Ríos-Velázquez, Carlos; Vázquez-Ayala, Iris; Hernández-Rivera, Samuel P.

2013-05-01

Recent investigations have focused on the improvement of rapid and accurate methods to develop spectroscopic markers of compounds constituting microorganisms that are considered biological threats. Quantum cascade lasers (QCL) systems have revolutionized many areas of research and development in defense and security applications, including his area of research. Infrared spectroscopy detection based on QCL was employed to acquire mid infrared (MIR) spectral signatures of Bacillus thuringiensis (Bt), Escherichia coli (Ec) and Staphylococcus epidermidis (Se), which were used as biological agent simulants of biothreats. The experiments were carried out in reflection mode on various substrates such as cardboard, glass, travel baggage, wood and stainless steel. Chemometrics statistical routines such as principal component analysis (PCA) regression and partial least squares-discriminant analysis (PLS-DA) were applied to the recorded MIR spectra. The results show that the infrared vibrational techniques investigated are useful for classification/detection of the target microorganisms on the types of substrates studied.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Sources of Infrasound events listed in IDC Reviewed Event Bulletin

NASA Astrophysics Data System (ADS)

Bittner, Paulina; Polich, Paul; Gore, Jane; Ali, Sherif; Medinskaya, Tatiana; Mialle, Pierrick

2017-04-01

Until 2003 two waveform technologies, i.e. seismic and hydroacoustic were used to detect and locate events included in the International Data Centre (IDC) Reviewed Event Bulletin (REB). The first atmospheric event was published in the REB in 2003, however automatic processing required significant improvements to reduce the number of false events. In the beginning of 2010 the infrasound technology was reintroduced to the IDC operations and has contributed to both automatic and reviewed IDC bulletins. The primary contribution of infrasound technology is to detect atmospheric events. These events may also be observed at seismic stations, which will significantly improve event location. Examples sources of REB events, which were detected by the International Monitoring System (IMS) infrasound network were fireballs (e.g. Bangkok fireball, 2015), volcanic eruptions (e.g. Calbuco, Chile 2015) and large surface explosions (e.g. Tjanjin, China 2015). Query blasts (e.g. Zheleznogorsk) and large earthquakes (e.g. Italy 2016) belong to events primarily recorded at seismic stations of the IMS network but often detected at the infrasound stations. In case of earthquakes analysis of infrasound signals may help to estimate the area affected by ground vibration. Infrasound associations to query blast events may help to obtain better source location. The role of IDC analysts is to verify and improve location of events detected by the automatic system and to add events which were missed in the automatic process. Open source materials may help to identify nature of some events. Well recorded examples may be added to the Reference Infrasound Event Database to help in analysis process. This presentation will provide examples of events generated by different sources which were included in the IDC bulletins.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

Passive wireless sensor systems can recognize activites of daily living.

PubMed

Urwyler, Prabitha; Stucki, Reto; Muri, Rene; Mosimann, Urs P; Nef, Tobias

2015-08-01

The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

Insulation Debond Detection

NASA Technical Reports Server (NTRS)

Johnston, G. D.; Coleman, A. D.; Portwood, J. N.; Saunders, J. M.; Porter, A. J.

1985-01-01

Load-cell and acoustic responses indicate bonding condition nondestructively. Signal recorded by load cell direct and instantaneous measure of local stiffness of material at point of impact. Separate and distinctly different measurement that sensed by microphone. Spectrum analysis of pulse obtained from debonded point will only show frequencies below 425 Hz because insulation alone does not have stiffness to support energy at higher frequencies.

Psychometric Analysis of the Systematic Observation of Red Flags for Autism Spectrum Disorder in Toddlers

ERIC Educational Resources Information Center

Dow, Deanna; Guthrie, Whitney; Stronach, Sheri T.; Wetherby, Amy M.

2017-01-01

The purpose of this study was to examine the utility of the Systematic Observation of Red Flags as an observational level-two screening measure to detect risk for autism spectrum disorder in toddlers when used with a video-recorded administration of the Communication and Symbolic Behavior Scales. Psychometric properties of the Systematic…

Data Mining of University Philanthropic Giving: Cluster-Discriminant Analysis and Pareto Effects

ERIC Educational Resources Information Center

Le Blanc, Louis A.; Rucks, Conway T.

2009-01-01

A large sample of 33,000 university alumni records were cluster-analyzed to generate six groups relatively unique in their respective attribute values. The attributes used to cluster the former students included average gift to the university's foundation and to the alumni association for the same institution. Cluster detection is useful in this…

Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

NASA Astrophysics Data System (ADS)

Huang, Liang; Ni, Xuan; Ditto, William L.; Spano, Mark; Carney, Paul R.; Lai, Ying-Cheng

2017-01-01

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.

Regional Patterns and Spatial Clusters of Nonstationarities in Annual Peak Instantaneous Streamflow

NASA Astrophysics Data System (ADS)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

Information about hydrologic changes resulting from changes in climate, land use, and land cover is a necessity planning and design or water resources infrastructure. The United States Army Corps of Engineers (USACE) evaluated and selected 12 methods to detect abrupt and slowly varying nonstationarities in records of maximum peak annual flows. They deployed a publicly available tool[1]in 2016 and a guidance document in 2017 to support identification of nonstationarities in a reproducible manner using a robust statistical framework. This statistical framework has now been applied to streamflow records across the continental United States to explore the presence of regional patterns and spatial clusters of nonstationarities in peak annual flow. Incorporating this geographic dimension into the detection of nonstationarities provides valuable insight for the process of attribution of these significant changes. This poster summarizes the methods used and provides the results of the regional analysis. [1] Available here - http://www.corpsclimate.us/ptcih.cfm

Excimer PRK testing in the clinic

NASA Astrophysics Data System (ADS)

Forrest, Gary T.

1994-06-01

Testing of the excimer lasers used in PRK requires special considerations in terms of ease of use, day-to-day reliability, and high resolution to see details of beam interference effects. SensorPhysics employs a patented photochromic material on a polyester substrate to record permanent, instant records of the laser and laser system output. Since each SensorCard is used only once concerns about detection device deterioration are not an issue. The SensorCards have a demonstrated resolving power on the order of 0.1 micrometers . A small, portable reading device is used to convert the SensorCard optical density to a mJ/cm2 value. Special software also measures beam uniformity to +/- 1% to provide both qualitative and quantitative analysis. Results of use in clinic environments will be presented. In particular detection of exposure `islands' will be demonstrated. The techniques employed are similar to those we developed for UV laser micromachining and lithography four years ago.

Cross-Cultural Detection of Depression from Nonverbal Behaviour.

PubMed

Alghowinem, Sharifa; Goecke, Roland; Cohn, Jeffrey F; Wagner, Michael; Parker, Gordon; Breakspear, Michael

2015-05-01

Millions of people worldwide suffer from depression. Do commonalities exist in their nonverbal behavior that would enable cross-culturally viable screening and assessment of severity? We investigated the generalisability of an approach to detect depression severity cross-culturally using video-recorded clinical interviews from Australia, the USA and Germany. The material varied in type of interview, subtypes of depression and inclusion healthy control subjects, cultural background, and recording environment. The analysis focussed on temporal features of participants' eye gaze and head pose. Several approaches to training and testing within and between datasets were evaluated. The strongest results were found for training across all datasets and testing across datasets using leave-one-subject-out cross-validation. In contrast, generalisability was attenuated when training on only one or two of the three datasets and testing on subjects from the dataset(s) not used in training. These findings highlight the importance of using training data exhibiting the expected range of variability.

Modelling of physical influences in sea level records for vertical crustal movement detection

NASA Technical Reports Server (NTRS)

Anderson, E. G.

1978-01-01

Attempts to specify and evaluate such physical influences are reviewed with the intention of identifying problem areas and promising approaches. An example of linear modelling based on air/water temperatures, atmospheric pressure, river discharges, geostrophic and/or local wind velocities, and including forced period terms to allow for the long period tides and Chandlerian polar motion is evaluated and applied to monthly mean sea levels recorded in Atlantic Canada. Refinement of the model to admit phase lag in the response to some of the driving phenomena is demonstrated. Spectral analysis of the residuals is employed to assess the model performance. The results and associated statistical parameters are discussed with emphasis on elucidating the sensitivity of the technique for detection of local episodic and secular vertical crustal movements, the problem areas most critical to the type of approach, and possible further developments.

An Information Transmission Measure for the Analysis of Effective Connectivity among Cortical Neurons

PubMed Central

Law, Andrew J.; Sharma, Gaurav; Schieber, Marc H.

2014-01-01

We present a methodology for detecting effective connections between simultaneously recorded neurons using an information transmission measure to identify the presence and direction of information flow from one neuron to another. Using simulated and experimentally-measured data, we evaluate the performance of our proposed method and compare it to the traditional transfer entropy approach. In simulations, our measure of information transmission outperforms transfer entropy in identifying the effective connectivity structure of a neuron ensemble. For experimentally recorded data, where ground truth is unavailable, the proposed method also yields a more plausible connectivity structure than transfer entropy. PMID:21096617

A Wavelet Packet Transform Inspired Method of Neutron-Gamma Discrimination

NASA Astrophysics Data System (ADS)

Shippen, David I.; Joyce, Malcolm J.; Aspinall, Michael D.

2010-10-01

A Simplified Digital Charge Collection (SDCC) method of discrimination between neutron and gamma pulses in an organic scintillator is presented and compared to the Pulse Gradient Analysis (PGA) discrimination method. Data used in this research were gathered from events arising from the 7Li(p,n)7Be reaction detected by an EJ-301 organic liquid scintillator recorded with a fast digital oscilloscope. Time-of-Flight (TOF) data were also recorded and used as a second means of identification. The SDCC method is found to improve on the figure of merit (FOM) given by PGA method at the equivalent sampling rate.

Quality Control Methodology Of A Surface Wind Observational Database In North Eastern North America

NASA Astrophysics Data System (ADS)

Lucio-Eceiza, Etor E.; Fidel González-Rouco, J.; Navarro, Jorge; Conte, Jorge; Beltrami, Hugo

2016-04-01

This work summarizes the design and application of a Quality Control (QC) procedure for an observational surface wind database located in North Eastern North America. The database consists of 526 sites (486 land stations and 40 buoys) with varying resolutions of hourly, 3 hourly and 6 hourly data, compiled from three different source institutions with uneven measurement units and changing measuring procedures, instrumentation and heights. The records span from 1953 to 2010. The QC process is composed of different phases focused either on problems related with the providing source institutions or measurement errors. The first phases deal with problems often related with data recording and management: (1) compilation stage dealing with the detection of typographical errors, decoding problems, site displacements and unification of institutional practices; (2) detection of erroneous data sequence duplications within a station or among different ones; (3) detection of errors related with physically unrealistic data measurements. The last phases are focused on instrumental errors: (4) problems related with low variability, placing particular emphasis on the detection of unrealistic low wind speed records with the help of regional references; (5) high variability related erroneous records; (6) standardization of wind speed record biases due to changing measurement heights, detection of wind speed biases on week to monthly timescales, and homogenization of wind direction records. As a result, around 1.7% of wind speed records and 0.4% of wind direction records have been deleted, making a combined total of 1.9% of removed records. Additionally, around 15.9% wind speed records and 2.4% of wind direction data have been also corrected.

RIPPLELAB: A Comprehensive Application for the Detection, Analysis and Classification of High Frequency Oscillations in Electroencephalographic Signals

PubMed Central

Alvarado-Rojas, Catalina; Le Van Quyen, Michel; Valderrama, Mario

2016-01-01

High Frequency Oscillations (HFOs) in the brain have been associated with different physiological and pathological processes. In epilepsy, HFOs might reflect a mechanism of epileptic phenomena, serving as a biomarker of epileptogenesis and epileptogenicity. Despite the valuable information provided by HFOs, their correct identification is a challenging task. A comprehensive application, RIPPLELAB, was developed to facilitate the analysis of HFOs. RIPPLELAB provides a wide range of tools for HFOs manual and automatic detection and visual validation; all of them are accessible from an intuitive graphical user interface. Four methods for automated detection—as well as several options for visualization and validation of detected events—were implemented and integrated in the application. Analysis of multiple files and channels is possible, and new options can be added by users. All features and capabilities implemented in RIPPLELAB for automatic detection were tested through the analysis of simulated signals and intracranial EEG recordings from epileptic patients (n = 16; 3,471 analyzed hours). Visual validation was also tested, and detected events were classified into different categories. Unlike other available software packages for EEG analysis, RIPPLELAB uniquely provides the appropriate graphical and algorithmic environment for HFOs detection (visual and automatic) and validation, in such a way that the power of elaborated detection methods are available to a wide range of users (experts and non-experts) through the use of this application. We believe that this open-source tool will facilitate and promote the collaboration between clinical and research centers working on the HFOs field. The tool is available under public license and is accessible through a dedicated web site. PMID:27341033

Antigravity posture for analysis of motor unit recruitment: the "45 degree test".

PubMed

Petajan, J H

1990-04-01

The maximum number of different motor unit action potentials (MUAPs), their firing rates, and total MUAP spikes/second recorded by monopolar needle electrode were determined for the biceps brachii muscle during 45-degree elbow flexion. There were 4.2 +/- 1.6 different MUAPs exceeding 100 microV. Mean firing rate was 10.0 +/- 1.7 Hz, and total MUAP spikes/second were 40.3 +/- 18. Recordings from 16 patients with neurogenic atrophy (NA) and just detectable weakness revealed corresponding values of 3.1 +/- 1.7 different MUAPs, a mean rate of 10.2 +/- 1.5 Hz and 30.6 +/- 19 total MUAP spikes/second, not different from normal. In these patients, increased force of muscle contraction was required to activate high threshold motor units firing at high rates. In each of 4 patients just able to hold the arm against gravity, 1 or 2 "overdriven" motor units firing at a mean rate greater than 20 Hz were recorded. In 8 patients with myopathy and just detectable weakness, greater than 100 total MUAP spikes/second were recorded. Antigravity posture as a reference level of innervation has the advantage that motor unit firing rate is set about that of physiologic tremor (10-13 Hz). Its application was helpful in quantifying recruitment.

Hyperspectral image analysis for standoff trace detection using IR laser spectroscopy

NASA Astrophysics Data System (ADS)

Jarvis, J.; Fuchs, F.; Hugger, S.; Ostendorf, R.; Butschek, L.; Yang, Q.; Dreyhaupt, A.; Grahmann, J.; Wagner, J.

2016-05-01

In the recent past infrared laser backscattering spectroscopy using Quantum Cascade Lasers (QCL) emitting in the molecular fingerprint region between 7.5 μm and 10 μm proved a highly promising approach for stand-off detection of dangerous substances. In this work we present an active illumination hyperspectral image sensor, utilizing QCLs as spectral selective illumination sources. A high performance Mercury Cadmium Telluride (MCT) imager is used for collection of the diffusely backscattered light. Well known target detection algorithms like the Adaptive Matched Subspace Detector and the Adaptive Coherent Estimator are used to detect pixel vectors in the recorded hyperspectral image that contain traces of explosive substances like PETN, RDX or TNT. In addition we present an extension of the backscattering spectroscopy technique towards real-time detection using a MOEMS EC-QCL.

Malware detection and analysis

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

Chiang, Ken; Lloyd, Levi; Crussell, Jonathan

Embodiments of the invention describe systems and methods for malicious software detection and analysis. A binary executable comprising obfuscated malware on a host device may be received, and incident data indicating a time when the binary executable was received and identifying processes operating on the host device may be recorded. The binary executable is analyzed via a scalable plurality of execution environments, including one or more non-virtual execution environments and one or more virtual execution environments, to generate runtime data and deobfuscation data attributable to the binary executable. At least some of the runtime data and deobfuscation data attributable tomore » the binary executable is stored in a shared database, while at least some of the incident data is stored in a private, non-shared database.« less

Study of interhemispheric asymmetries in electroencephalographic signals by frequency analysis

NASA Astrophysics Data System (ADS)

Zapata, J. F.; Garzón, J.

2011-01-01

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

Using video recording to identify management errors in pediatric trauma resuscitation.

PubMed

Oakley, Ed; Stocker, Sergio; Staubli, Georg; Young, Simon

2006-03-01

To determine the ability of video recording to identify management errors in trauma resuscitation and to compare this method with medical record review. The resuscitation of children who presented to the emergency department of the Royal Children's Hospital between February 19, 2001, and August 18, 2002, for whom the trauma team was activated was video recorded. The tapes were analyzed, and management was compared with Advanced Trauma Life Support guidelines. Deviations from these guidelines were recorded as errors. Fifty video recordings were analyzed independently by 2 reviewers. Medical record review was undertaken for a cohort of the most seriously injured patients, and errors were identified. The errors detected with the 2 methods were compared. Ninety resuscitations were video recorded and analyzed. An average of 5.9 errors per resuscitation was identified with this method (range: 1-12 errors). Twenty-five children (28%) had an injury severity score of >11; there was an average of 2.16 errors per patient in this group. Only 10 (20%) of these errors were detected in the medical record review. Medical record review detected an additional 8 errors that were not evident on the video recordings. Concordance between independent reviewers was high, with 93% agreement. Video recording is more effective than medical record review in detecting management errors in pediatric trauma resuscitation. Management errors in pediatric trauma resuscitation are common and often involve basic resuscitation principles. Resuscitation of the most seriously injured children was associated with fewer errors. Video recording is a useful adjunct to trauma resuscitation auditing.

[A cross-correlational analysis of the background neuronal pulse trains in surviving slices of the guinea pig neocortex].

PubMed

Bortnik, A T; Iakupova, L P

1991-01-01

Cross-correlation analysis of interdependence of the background spike activity was carried out for pairs of adjacent neurons simultaneously recorded in the incubated slices of the neocortex of guinea-pig. Statistical correlation of spike discharges was detected in 16 out of 26 recorded pairs of the neurons. Significant correlation was observed mainly in the range of +/- 100 ms from the null point. Cross-correlation had symmetric or asymmetric maxima up to 150 ms long and negative shifts up to 200 ms long. More complex positive-negative types of cross-correlations were also obtained. The data were compared to those known from other authors for the intact brain. The contribution of intrinsic intracortical interactions and extrinsic afferent influences in these correlations of activity is discussed.

Determination of glucose and uric acid with bienzyme colorimetry on microfluidic paper-based analysis devices.

PubMed

Chen, Xi; Chen, Jin; Wang, Fubin; Xiang, Xia; Luo, Ming; Ji, Xinghu; He, Zhike

2012-05-15

In this work, we first employ a drying method combining with the bienzyme colorimetric detection of glucose and uric acid on microfluidic paper-based analysis devices (μPADs). The channels of 3D μPADs are also designed by us to get better results. The color results are recorded by both Gel Documentation systems and a common camera. By using Gel Documentation systems, the limits of detection (LOD) of glucose and uric acid are 3.81 × 10(-5)M and 4.31 × 10(-5)M, respectively one order of magnitude lower than that of the reported methods on μPADs. By using a common camera, the limits of detection (LOD) of glucose and uric acid are 2.13 × 10(-4)M and 2.87 × 10(-4)M, respectively. Furthermore, the effects of detection conditions have been investigated and discussed comprehensively. Human serum samples are detected with satisfactory results, which are comparable with the clinical testing results. A low-cost, simple and rapid colorimetric method for the simultaneous detection of glucose and uric acid on the μPADs has been developed with enhanced sensitivity. Copyright © 2012 Elsevier B.V. All rights reserved.

Vocalisations of Killer Whales (Orcinus orca) in the Bremer Canyon, Western Australia.

PubMed

Wellard, Rebecca; Erbe, Christine; Fouda, Leila; Blewitt, Michelle

2015-01-01

To date, there has been no dedicated study in Australian waters on the acoustics of killer whales. Hence no information has been published on the sounds produced by killer whales from this region. Here we present the first acoustical analysis of recordings collected off the Western Australian coast. Underwater sounds produced by Australian killer whales were recorded during the months of February and March 2014 and 2015 in the Bremer Canyon in Western Australia. Vocalisations recorded included echolocation clicks, burst-pulse sounds and whistles. A total of 28 hours and 29 minutes were recorded and analysed, with 2376 killer whale calls (whistles and burst-pulse sounds) detected. Recordings of poor quality or signal-to-noise ratio were excluded from analysis, resulting in 142 whistles and burst-pulse vocalisations suitable for analysis and categorisation. These were grouped based on their spectrographic features into nine Bremer Canyon (BC) "call types". The frequency of the fundamental contours of all call types ranged from 600 Hz to 29 kHz. Calls ranged from 0.05 to 11.3 seconds in duration. Biosonar clicks were also recorded, but not studied further. Surface behaviours noted during acoustic recordings were categorised as either travelling or social behaviour. A detailed description of the acoustic characteristics is necessary for species acoustic identification and for the development of passive acoustic tools for population monitoring, including assessments of population status, habitat usage, migration patterns, behaviour and acoustic ecology. This study provides the first quantitative assessment and report on the acoustic features of killer whales vocalisations in Australian waters, and presents an opportunity to further investigate this little-known population.

Vocalisations of Killer Whales (Orcinus orca) in the Bremer Canyon, Western Australia

PubMed Central

Wellard, Rebecca; Erbe, Christine; Fouda, Leila; Blewitt, Michelle

2015-01-01

To date, there has been no dedicated study in Australian waters on the acoustics of killer whales. Hence no information has been published on the sounds produced by killer whales from this region. Here we present the first acoustical analysis of recordings collected off the Western Australian coast. Underwater sounds produced by Australian killer whales were recorded during the months of February and March 2014 and 2015 in the Bremer Canyon in Western Australia. Vocalisations recorded included echolocation clicks, burst-pulse sounds and whistles. A total of 28 hours and 29 minutes were recorded and analysed, with 2376 killer whale calls (whistles and burst-pulse sounds) detected. Recordings of poor quality or signal-to-noise ratio were excluded from analysis, resulting in 142 whistles and burst-pulse vocalisations suitable for analysis and categorisation. These were grouped based on their spectrographic features into nine Bremer Canyon (BC) “call types”. The frequency of the fundamental contours of all call types ranged from 600 Hz to 29 kHz. Calls ranged from 0.05 to 11.3 seconds in duration. Biosonar clicks were also recorded, but not studied further. Surface behaviours noted during acoustic recordings were categorised as either travelling or social behaviour. A detailed description of the acoustic characteristics is necessary for species acoustic identification and for the development of passive acoustic tools for population monitoring, including assessments of population status, habitat usage, migration patterns, behaviour and acoustic ecology. This study provides the first quantitative assessment and report on the acoustic features of killer whales vocalisations in Australian waters, and presents an opportunity to further investigate this little-known population. PMID:26352429

Detection of Sleep Disordered Breathing and Its Central/Obstructive Character Using Nasal Cannula and Finger Pulse Oximeter

PubMed Central

Sommermeyer, Dirk; Zou, Ding; Grote, Ludger; Hedner, Jan

2012-01-01

Study Objective: To assess the accuracy of novel algorithms using an oximeter-based finger plethysmographic signal in combination with a nasal cannula for the detection and differentiation of central and obstructive apneas. The validity of single pulse oximetry to detect respiratory disturbance events was also studied. Methods: Patients recruited from four sleep laboratories underwent an ambulatory overnight cardiorespiratory polygraphy recording. The nasal flow and photoplethysmographic signals of the recording were analyzed by automated algorithms. The apnea hypopnea index (AHIauto) was calculated using both signals, and a respiratory disturbance index (RDIauto) was calculated from photoplethysmography alone. Apnea events were classified into obstructive and central types using the oximeter derived pulse wave signal and compared with manual scoring. Results: Sixty-six subjects (42 males, age 54 ± 14 yrs, body mass index 28.5 ± 5.9 kg/m2) were included in the analysis. AHImanual (19.4 ± 18.5 events/h) correlated highly significantly with AHIauto (19.9 ± 16.5 events/h) and RDIauto (20.4 ± 17.2 events/h); the correlation coefficients were r = 0.94 and 0.95, respectively (p < 0.001) with a mean difference of −0.5 ± 6.6 and −1.0 ± 6.1 events/h. The automatic analysis of AHIauto and RDIauto detected sleep apnea (cutoff AHImanual ≥ 15 events/h) with a sensitivity/specificity of 0.90/0.97 and 0.86/0.94, respectively. The automated obstructive/central apnea indices correlated closely with manually scoring (r = 0.87 and 0.95, p < 0.001) with mean difference of −4.3 ± 7.9 and 0.3 ± 1.5 events/h, respectively. Conclusions: Automatic analysis based on routine pulse oximetry alone may be used to detect sleep disordered breathing with accuracy. In addition, the combination of photoplethysmographic signals with a nasal flow signal provides an accurate distinction between obstructive and central apneic events during sleep. Citation: Sommermeyer D; Zou D; Grote L; Hedner J. Detection of sleep disordered breathing and its central/obstructive character using nasal cannula and finger pulse oximeter. J Clin Sleep Med 2012;8(5):527-533. PMID:23066364

Analysis of Regionally Detected Icequakes Using the STEEP Network, South-Central AK

NASA Astrophysics Data System (ADS)

O'Neel, S.; Leblanc, L.; Larsen, C.; Truffer, M.; Hansen, R.; Rupert, N.; Pavlis, G.; None, N.

2007-12-01

Glaciers produce seismic energy that is detectable from local to teleseismic distances. Glaciolgical processes including calving, surface crevassing, basal sliding and other, yet unresolved source processes are capable of producing recordable seismicity. Twenty-two broadband sensors deployed in south-central Alaska during the SainT Elias TEctonics and Erosion Project (STEEP) provide an excellent means to study glacier-generated seismicity at regional distances. These instruments surround over 7500 km2 of glacier area including the Bering Glacier, Bagley Icefield and the tidewater calving glaciers of Icy Bay (Yahtse, Guyot, Tyndal). Our analysis shows that icequakes nominally occur several times hourly, and can be separated from tectonic seismicity using their unique spectral characteristics and hypocenter locations. The events typically propagate over 50-75 km distances, but occasionally are recorded at stations over 150 km away from the energy source. Hypocenters for more than 1000 events were manually calculated through a 26-day interval during October 2006, and suggest that a majority of the icequakes are associated with calving at tidewater glaciers that terminate in Icy Bay. Events with similar time and frequency domain characteristics also occur at locations away from calving fronts, but less often, and their mechanical origin remains undetermined. Automated detections from a frequency domain event detector exhibit strong correlation with the handpicked time series, and extend our analysis to all available data collected during 2006. We present the time distribution of several categories of icequakes and compare these distributions to environmental variables such as precipitation, temperature and tides to explore potential forcing for observed variability in icequake occurrence.

Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

PubMed

Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

2017-09-01

This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert neurophysiologists, EMG signal recording and user visual inspection. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Automatic cardiac cycle determination directly from EEG-fMRI data by multi-scale peak detection method.

PubMed

Wong, Chung-Ki; Luo, Qingfei; Zotev, Vadim; Phillips, Raquel; Chan, Kam Wai Clifford; Bodurka, Jerzy

2018-03-31

In simultaneous EEG-fMRI, identification of the period of cardioballistic artifact (BCG) in EEG is required for the artifact removal. Recording the electrocardiogram (ECG) waveform during fMRI is difficult, often causing inaccurate period detection. Since the waveform of the BCG extracted by independent component analysis (ICA) is relatively invariable compared to the ECG waveform, we propose a multiple-scale peak-detection algorithm to determine the BCG cycle directly from the EEG data. The algorithm first extracts the high contrast BCG component from the EEG data by ICA. The BCG cycle is then estimated by band-pass filtering the component around the fundamental frequency identified from its energy spectral density, and the peak of BCG artifact occurrence is selected from each of the estimated cycle. The algorithm is shown to achieve a high accuracy on a large EEG-fMRI dataset. It is also adaptive to various heart rates without the needs of adjusting the threshold parameters. The cycle detection remains accurate with the scan duration reduced to half a minute. Additionally, the algorithm gives a figure of merit to evaluate the reliability of the detection accuracy. The algorithm is shown to give a higher detection accuracy than the commonly used cycle detection algorithm fmrib_qrsdetect implemented in EEGLAB. The achieved high cycle detection accuracy of our algorithm without using the ECG waveforms makes possible to create and automate pipelines for processing large EEG-fMRI datasets, and virtually eliminates the need for ECG recordings for BCG artifact removal. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Determining the effects of routine fingermark detection techniques on the subsequent recovery and analysis of explosive residues on various substrates.

PubMed

King, Sam; Benson, Sarah; Kelly, Tamsin; Lennard, Chris

2013-12-10

An offender who has recently handled bulk explosives would be expected to deposit latent fingermarks that are contaminated with explosive residues. However, fingermark detection techniques need to be applied in order for these fingermarks to be detected and recorded. Little information is available in terms of how routine fingermark detection methods impact on the subsequent recovery and analysis of any explosive residues that may be present. If an identifiable fingermark is obtained and that fingermark is found to be contaminated with a particular explosive then that may be crucial evidence in a criminal investigation (including acts of terrorism involving improvised explosive devices). The principal aims of this project were to investigate: (i) the typical quantities of explosive material deposited in fingermarks by someone who has recently handled bulk explosives; and (ii) the effects of routine fingermark detection methods on the subsequent recovery and analysis of explosive residues in such fingermarks. Four common substrates were studied: paper, glass, plastic (polyethylene plastic bags), and metal (aluminium foil). The target explosive compounds were 2,4,6-trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), as well as chlorate and nitrate ions. Recommendations are provided in terms of the application of fingermark detection methods on surfaces that may contain explosive residues. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Feral Hogs Management at Merritt Island National Wildlife Refuge: Analysis of Current Management Program

NASA Technical Reports Server (NTRS)

Rosenfeld, Arie; Hinkle, C. Ross; Epstein, Marc

2002-01-01

This ST1 Technical Memorandum (TM) summarizes a two-month project on feral hog management in Merritt Island National Wildlife Refuge (MINWR). For this project, feral hogs were marked and recaptured, with the help of local trappers, to estimate population size and habitat preferences. Habitat covers included vegetation cover and Light Detection and Ranging (LIDAR) data for MINWR. In addition, an analysis was done of hunting records compiled by the Refuge and hog-car accidents compiled by KSC Security.

Detection and Characterization of Boundary-Layer Transition in Flight at Supersonic Conditions Using Infrared Thermography

NASA Technical Reports Server (NTRS)

Banks, Daniel W.

2008-01-01

Infrared thermography is a powerful tool for investigating fluid mechanics on flight vehicles. (Can be used to visualize and characterize transition, shock impingement, separation etc.). Updated onboard F-15 based system was used to visualize supersonic boundary layer transition test article. (Tollmien-Schlichting and cross-flow dominant flow fields). Digital Recording improves image quality and analysis capability. (Allows accurate quantitative (temperature) measurements, Greater enhancement through image processing allows analysis of smaller scale phenomena).

Workplace Measurements by the US Occupational Safety and Health Administration since 1979: Descriptive Analysis and Potential Uses for Exposure Assessment

PubMed Central

2013-01-01

Background : Inspectors from the US Occupational Safety and Health Administration (OSHA) have been collecting industrial hygiene samples since 1972 to verify compliance with Permissible Exposure Limits. Starting in 1979, these measurements were computerized into the Integrated Management Information System (IMIS). In 2010, a dataset of over 1 million personal sample results analysed at OSHA’s central laboratory in Salt Lake City [Chemical Exposure Health Data (CEHD)], only partially overlapping the IMIS database, was placed into public domain via the internet. We undertook this study to inform potential users about the relationship between this newly available OSHA data and IMIS and to offer insight about the opportunities and challenges associated with the use of OSHA measurement data for occupational exposure assessment. Methods : We conducted a literature review of previous uses of IMIS in occupational health research and performed a descriptive analysis of the data recently made available and compared them to the IMIS database for lead, the most frequently sampled agent. Results : The literature review yielded 29 studies reporting use of IMIS data, but none using the CEHD data. Most studies focused on a single contaminant, with silica and lead being most frequently analysed. Sixteen studies addressed potential bias in IMIS, mostly by examining the association between exposure levels and ancillary information. Although no biases of appreciable magnitude were consistently reported across studies and agents, these assessments may have been obscured by selective under-reporting of non-detectable measurements. The CEHD data comprised 1 450 836 records from 1984 to 2009, not counting analytical blanks and erroneous records. Seventy eight agents with >1000 personal samples yielded 1 037 367 records. Unlike IMIS, which contain administrative information (company size, job description), ancillary information in the CEHD data is mostly analytical. When the IMIS and CEHD measurements of lead were merged, 23 033 (39.2%) records were in common to both IMIS and CEHD datasets, 10 681 (18.2%) records were only in IMIS, and 25 012 (42.6%) records were only in the CEHD database. While IMIS-only records represent data analysed in other laboratories, CEHD-only records suggest partial reporting of sampling results by OSHA inspectors into IMIS. For lead, the percentage of non-detects in the CEHD-only data was 71% compared to 42% and 46% in the both-IMIS-CEHD and IMIS-only datasets, respectively, suggesting differential under-reporting of non-detects in IMIS. Conclusions : IMIS and the CEHD datasets represent the biggest source of multi-industry exposure data in the USA and should be considered as a valuable source of information for occupational exposure assessment. The lack of empirical data on biases, adequate interpretation of non-detects in OSHA data, complicated by suspected differential under-reporting, remain the principal challenges to the valid estimation of average exposure conditions. We advocate additional comparisons between IMIS and CEHD data and discuss analytical strategies that may play a key role in meeting these challenges. PMID:22952385

Identification and electrophysiological studies of (4 S,5 S)-5-hydroxy-4-methyl-3-heptanone and 4-methyl-3,5-heptanedione in male lucerne weevils

NASA Astrophysics Data System (ADS)

Unelius, C. R.; Park, K.-C.; McNeill, M.; Wee, S. L.; Bohman, B.; Suckling, D. M.

2013-02-01

An investigation to identify a sex or aggregation pheromone of Sitona discoideus Gyllenhål (Coleoptera: Curculionidae) is presented. Antenna flicking and attraction behaviors evoked by conspecifics of both sexes were recorded in arena bioassays, where attraction of females to males was observed. Air entrainment of both males and females was conducted in separate chambers. Gas chromatographic-mass spectrometric analysis of headspace volatiles revealed that two male-specific compounds, 4-methyl-3,5-heptanedione (major) and (4 S,5 S)-5-hydroxy-4-methyl-3-heptanone (minor), were emitted during the autumnal post-aestivatory flight period. The stereoisomers of the minor component were separated by enantioselective gas chromatography and their absolute configurations assigned by NMR (diastereomers) and the known preference of enantioselective transesterification reactions catalyzed by Candida antarctica lipase B. Electroantennogram and single sensillum recording studies indicate that 4-methyl-3,5-heptanedione as well as all individual stereoisomers of 5-hydroxy-4-methyl-3-heptanone are detected by the antennae of male and female S. discoideus. Further, single sensillum recordings suggest that both sexes of S. discoideus have specialized olfactory receptor neurons (ORNs) for detecting 4-methyl-3,5-heptanedione and different populations of stereoselective ORNs for detecting the stereoisomers of 5-hydroxy-4-methyl-3-heptanone. Some of these stereoselective ORNs appear to be sex-specific in S. discoideus.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

NASA Astrophysics Data System (ADS)

Nguyen, T. K. T.; Navratilova, Z.; Cabral, H.; Wang, L.; Gielen, G.; Battaglia, F. P.; Bartic, C.

2014-08-01

Objective. Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach. Approach. The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats. Main results. Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals. Significance. A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

Computer vision-based diameter maps to study fluoroscopic recordings of small intestinal motility from conscious experimental animals.

PubMed

Ramírez, I; Pantrigo, J J; Montemayor, A S; López-Pérez, A E; Martín-Fontelles, M I; Brookes, S J H; Abalo, R

2017-08-01

When available, fluoroscopic recordings are a relatively cheap, non-invasive and technically straightforward way to study gastrointestinal motility. Spatiotemporal maps have been used to characterize motility of intestinal preparations in vitro, or in anesthetized animals in vivo. Here, a new automated computer-based method was used to construct spatiotemporal motility maps from fluoroscopic recordings obtained in conscious rats. Conscious, non-fasted, adult, male Wistar rats (n=8) received intragastric administration of barium contrast, and 1-2 hours later, when several loops of the small intestine were well-defined, a 2 minutes-fluoroscopic recording was obtained. Spatiotemporal diameter maps (Dmaps) were automatically calculated from the recordings. Three recordings were also manually analyzed for comparison. Frequency analysis was performed in order to calculate relevant motility parameters. In each conscious rat, a stable recording (17-20 seconds) was analyzed. The Dmaps manually and automatically obtained from the same recording were comparable, but the automated process was faster and provided higher resolution. Two frequencies of motor activity dominated; lower frequency contractions (15.2±0.9 cpm) had an amplitude approximately five times greater than higher frequency events (32.8±0.7 cpm). The automated method developed here needed little investigator input, provided high-resolution results with short computing times, and automatically compensated for breathing and other small movements, allowing recordings to be made without anesthesia. Although slow and/or infrequent events could not be detected in the short recording periods analyzed to date (17-20 seconds), this novel system enhances the analysis of in vivo motility in conscious animals. © 2017 John Wiley & Sons Ltd.

Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

NASA Astrophysics Data System (ADS)

Ledezma, Carlos A.; Perpiñan, Gilberto; Severeyn, Erika; Altuve, Miguel

2015-12-01

Heart diseases are the main cause of death worldwide. The first step in the diagnose of these diseases is the analysis of the electrocardiographic (ECG) signal. In turn, the ECG analysis begins with the detection of the QRS complex, which is the one with the most energy in the cardiac cycle. Numerous methods have been proposed in the bibliography for QRS complex detection, but few authors have analyzed the possibility of taking advantage of the information redundancy present in multiple ECG leads (simultaneously acquired) to produce accurate QRS detection. In our previous work we presented such an approach, proposing various data fusion techniques to combine the detections made by an algorithm on multiple ECG leads. In this paper we present further studies that show the advantages of this multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance. A well known QRS detection algorithm was used to test the fusion techniques on the St. Petersburg Institute of Cardiological Technics database. Results show improvement in the detection performance with as little as three leads, but the reliability of these results becomes interesting only after using seven or more leads. Results were evaluated using the detection error rate (DER). The multi-lead detection approach allows an improvement from DER = 3:04% to DER = 1:88%. Further works are to be made in order to improve the detection performance by implementing further fusion steps.

Computer systems for automatic earthquake detection

USGS Publications Warehouse

Stewart, S.W.

1974-01-01

U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

[The reproducibility of multifocal ERG recordings].

PubMed

Meigen, T; Friedrich, A

2002-09-01

Multifocal electroretinogram recordings (mfERG) can be used to detect a local dysfunction of the retina. In this study we tested both the intrasessional and inter-sessional reproducibility of mfERG amplitudes. MfERGs from 6 eyes of 6 normal subjects were recorded on two different days using DTL electrodes. The relative coefficient of variation ( RCV) was used to quantify the amplitude reproducibility. We tested the effect of (a) session (inter- vs. intrasessional), (b) recording duration (7.3 vs. 3.6 min), (c) trace type (hexagon traces vs. ring averages), and (d) amplitude definition (peak-trough analysis vs. scalar product) on RCV. RCV was 6.5+/-0.4% (Mean+/-SEM, n=96) when averaged across all recording conditions and all subjects. The ANOVA showed a significant difference ( p=0.018) between hexagon traces and ring averages. Another significant effect ( p=0.016) occurred for the interaction of (a) and (b). MfERGs can be recorded with a high degree of reproducibility even for short recording durations and single hexagon traces. As the factor (a) did not show a significant effect, the new placement of the DTL electrode in the second session does not necessarily increase the retest variability compared to a second recording within the same session.

Analysis of sounds produced by Rhynchophorus ferrugineus and Oryctes elegans larvae and adults in data palm trees and offshoots in Saudi Arabian commercial orchards

USDA-ARS?s Scientific Manuscript database

Sounds produced by larval and adult palm tree pests in Saudi Arabian date palm orchards were recorded using commercially available insect acoustic detection instruments. The trees and offshoots were inspected for presence/absence of insects and other visual signs of infestation. Subsequently, the sp...

Fluctuations of hi-hat timing and dynamics in a virtuoso drum track of a popular music recording.

PubMed

Räsänen, Esa; Pulkkinen, Otto; Virtanen, Tuomas; Zollner, Manfred; Hennig, Holger

2015-01-01

Long-range correlated temporal fluctuations in the beats of musical rhythms are an inevitable consequence of human action. According to recent studies, such fluctuations also lead to a favored listening experience. The scaling laws of amplitude variations in rhythms, however, are widely unknown. Here we use highly sensitive onset detection and time series analysis to study the amplitude and temporal fluctuations of Jeff Porcaro's one-handed hi-hat pattern in "I Keep Forgettin'"-one of the most renowned 16th note patterns in modern drumming. We show that fluctuations of hi-hat amplitudes and interbeat intervals (times between hits) have clear long-range correlations and short-range anticorrelations separated by a characteristic time scale. In addition, we detect subtle features in Porcaro's drumming such as small drifts in the 16th note pulse and non-trivial periodic two-bar patterns in both hi-hat amplitudes and intervals. Through this investigation we introduce a step towards statistical studies of the 20th and 21st century music recordings in the framework of complex systems. Our analysis has direct applications to the development of drum machines and to drumming pedagogy.

Analysis of humpback whale sounds in shallow waters of the Southeastern Arabian Sea: An indication of breeding habitat.

PubMed

Mahanty, Madan M; Latha, G; Thirunavukkarasu, A

2015-06-01

The primary objective of this work was to present the acoustical identification of humpback whales, detected by using an autonomous ambient noise measurement system, deployed in the shallow waters of the Southeastern Arabian Sea (SEAS) during the period January to May 2011. Seven types of sounds were detected. These were characteristically upsweeps and downsweeps along with harmonics. Sounds produced repeatedly in a specific pattern were referred to as phrases (PQRS and ABC). Repeated phrases in a particular pattern were referred to as themes, and from the spectrographic analysis, two themes (I and II) were identified. The variation in the acoustic characteristics such as fundamental frequency, range, duration of the sound unit, and the structure of the phrases and themes are discussed. Sound units were recorded from mid-January to mid-March, with a peak in February, when the mean SST is approx. 28 degree C, and no presence was recorded after mid-March. The temporal and thematic structures strongly determine the functions of the humpback whale song form. Given the use of song in the SEAS, this area is possibly used as an active breeding habitat by humpback whales during the winter season.

Effects of different analysis techniques and recording duty cycles on passive acoustic monitoring of killer whales.

PubMed

Riera, Amalis; Ford, John K; Ross Chapman, N

2013-09-01

Killer whales in British Columbia are at risk, and little is known about their winter distribution. Passive acoustic monitoring of their year-round habitat is a valuable supplemental method to traditional visual and photographic surveys. However, long-term acoustic studies of odontocetes have some limitations, including the generation of large amounts of data that require highly time-consuming processing. There is a need to develop tools and protocols to maximize the efficiency of such studies. Here, two types of analysis, real-time and long term spectral averages, were compared to assess their performance at detecting killer whale calls in long-term acoustic recordings. In addition, two different duty cycles, 1/3 and 2/3, were tested. Both the use of long term spectral averages and a lower duty cycle resulted in a decrease in call detection and positive pod identification, leading to underestimations of the amount of time the whales were present. The impact of these limitations should be considered in future killer whale acoustic surveys. A compromise between a lower resolution data processing method and a higher duty cycle is suggested for maximum methodological efficiency.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies

PubMed Central

Puce, Aina; Hämäläinen, Matti S.

2017-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed. PMID:28561761

Evaluation of Sleep by Detrended Fluctuation Analysis of the Heartbeat

NASA Astrophysics Data System (ADS)

Yazawa, Toru; Shimoda, Yukio; Hutapea, Albert M.

2011-08-01

There are already-established methods for investigating biological signals such as rhythmic heartbeats. We used detrended fluctuation analysis (DFA), originally developed by Peng et al. (1995) to check power-law characteristics, because the method can quantify the heart condition numerically. In this article, we studied the heartbeat of sleeping subjects. Our purpose was to test whether DFA is useful to evaluate the subject's wellness of both during being awake and sleeping. This is a challenge to measure sleep without complex/expensive machine, an electro encephalography (EEG). We conducted electrophysiological recording to measure heartbeats during sleep using electrocardiograph with three-leads, one ground electrode and two active electrodes attached to chest. For good recording, a stable baseline must be maintained even when subjects move their body. We needed a tool to ensure long-term steady recording. We thus invented a new electric-circuit designed to produce this desired result. This gadget allowed us to perform heartbeat recording without any drifting baseline. We then were able to detect 100% of heartbeat peaks over the entire period of sleep. Here, we show a case study as empirical evidence that DFA is useful numerical method for quantifying sleep by using the scaling exponents.

Comparing near-regional and local measurements of infrasound from Mount Erebus, Antarctica: Implications for monitoring

NASA Astrophysics Data System (ADS)

Dabrowa, A. L.; Green, D. N.; Johnson, J. B.; Phillips, J. C.; Rust, A. C.

2014-11-01

Local (100 s of metres from vent) monitoring of volcanic infrasound is a common tool at volcanoes characterized by frequent low-magnitude eruptions, but it is generally not safe or practical to have sensors so close to the vent during more intense eruptions. To investigate the potential and limitations of monitoring at near-regional ranges (10 s of km) we studied infrasound detection and propagation at Mount Erebus, Antarctica. This site has both a good local monitoring network and an additional International Monitoring System infrasound array, IS55, located 25 km away. We compared data recorded at IS55 with a set of 117 known Strombolian events that were recorded with the local network in January 2006. 75% of these events were identified at IS55 by an analyst looking for a pressure transient coincident with an F-statistic detection, which identifies coherent infrasound signals. With the data from January 2006, we developed and calibrated an automated signal-detection algorithm based on threshold values of both the F-statistic and the correlation coefficient. Application of the algorithm across IS55 data for all of 2006 identified infrasonic signals expected to be Strombolian explosions, and proved reliable for indicating trends in eruption frequency. However, detectability at IS55 of known Strombolian events depended strongly on the local signal amplitude: 90% of events with local amplitudes > 25 Pa were identified at IS55, compared to only 26% of events with local amplitudes < 25 Pa. Event detection was also affected by considerable variation in amplitude decay rates between the local and near-regional sensors. Amplitudes recorded at IS55 varied between 3% and 180% of the amplitude expected assuming hemispherical spreading, indicating that amplitudes recorded at near-regional ranges to Erebus are unreliable indicators of event magnitude. Comparing amplitude decay rates with locally collected radiosonde data indicates a close relationship between recorded amplitude and lower atmosphere effective sound speed structure. At times of increased sound speed gradient, higher amplitude decay rates are observed, consistent with increased upward refraction of acoustic energy along the propagation path. This study indicates that whilst monitoring activity levels at near-regional ranges can be successful, variable amplitude decay rate means quantitative analysis of infrasound data for eruption intensity and magnitude is not advisable without the consideration of local atmospheric sound speed structure.

Heart sounds analysis using probability assessment.

PubMed

Plesinger, F; Viscor, I; Halamek, J; Jurco, J; Jurak, P

2017-07-31

This paper describes a method for automated discrimination of heart sounds recordings according to the Physionet Challenge 2016. The goal was to decide if the recording refers to normal or abnormal heart sounds or if it is not possible to decide (i.e. 'unsure' recordings). Heart sounds S1 and S2 are detected using amplitude envelopes in the band 15-90 Hz. The averaged shape of the S1/S2 pair is computed from amplitude envelopes in five different bands (15-90 Hz; 55-150 Hz; 100-250 Hz; 200-450 Hz; 400-800 Hz). A total of 53 features are extracted from the data. The largest group of features is extracted from the statistical properties of the averaged shapes; other features are extracted from the symmetry of averaged shapes, and the last group of features is independent of S1 and S2 detection. Generated features are processed using logical rules and probability assessment, a prototype of a new machine-learning method. The method was trained using 3155 records and tested on 1277 hidden records. It resulted in a training score of 0.903 (sensitivity 0.869, specificity 0.937) and a testing score of 0.841 (sensitivity 0.770, specificity 0.913). The revised method led to a test score of 0.853 in the follow-up phase of the challenge. The presented solution achieved 7th place out of 48 competing entries in the Physionet Challenge 2016 (official phase). In addition, the PROBAfind software for probability assessment was introduced.

A Novel Quantitative Method for Diabetic Cardiac Autonomic Neuropathy Assessment in Type 1 Diabetic Mice

PubMed Central

Yang, Bufan; Posada-Quintero, Hugo F.; Siu, Kin L.; Rolle, Marsha; Brink, Peter; Birzgalis, Aija; Moore, Leon C.

2014-01-01

In this work, we used a sensitive and noninvasive computational method to assess diabetic cardiovascular autonomic neuropathy (DCAN) from pulse oximeter (photoplethysmographic; PPG) recordings from mice. The method, which could be easily applied to humans, is based on principal dynamic mode (PDM) analysis of heart rate variability (HRV). Unlike the power spectral density, PDM has been shown to be able to separately identify the activities of the parasympathetic and sympathetic nervous systems without pharmacological intervention. HRV parameters were measured by processing PPG signals from conscious 1.5- to 5-month-old C57/BL6 control mice and in Akita mice, a model of insulin-dependent type 1 diabetes, and compared with the gold-standard Western blot and immunohistochemical analyses. The PDM results indicate significant cardiac autonomic impairment in the diabetic mice in comparison to the controls. When tail-cuff PPG recordings were collected and analyzed starting from 1.5 months of age in both C57/Bl6 controls and Akita mice, onset of DCAN was seen at 3 months in the Akita mice, which persisted up to the termination of the recording at 5 months. Western blot and immunohistochemical analyses also showed a reduction in nerve density in Akita mice at 3 and 4 months as compared to the control mice, thus, corroborating our PDM data analysis of HRV records. Western blot analysis of autonomic nerve proteins corroborated the PPG-based HRV analysis via the PDM approach. In contrast, traditional HRV analysis (based on either the power spectral density or time-domain measures) failed to detect the nerve rarefaction. PMID:25097056

Layering extraction from subsurface radargrams over Greenland and the Martian NPLD by combining wavelet analysis with Hough transforms

NASA Astrophysics Data System (ADS)

Xiong, Si-Ting; Muller, Jan-Peter

2017-04-01

Extracting lines from an imagery is a solved problem in the field of edge detection. Different to images taken by camera, radargrams are a set of radar echo profiles, which record wave energy reflected by subsurface reflectors, at each location of a radar footprint along the satellite's ground track. The radargrams record where there is a dielectric contrast caused by different deposits, and other subsurface features, such as facies, and internal distributions like porosity and fluids. Among the subsurface features, layering is an important one which reflect the sequence of seasonal or yearly deposits on the ground [1-2]. In the field of image processing, line detection methods, such as the Radon Transform or Hough Transform, are able to extract these subsurface layers from rasterised versions of the echograms. However, due to the attenuation of radar waves whilst propagating through geological media, radargrams sometimes suffer from gradient and high background noise. These attributes of radargrams cause errors in detection when conventional line detection methods are directly applied. In this study, we have developed a continuous wavelet analysis technique to be applied directly to the radar echo profiles in a radargram in order to detect segmented lines, and then a conventional line detection method, such as a Hough transform can be applied to connect these segmented lines. This processing chain is tested by using datasets from a radargram acquired by the Multi-channel Coherent Radar Depth Sounder (MCoRDS) on an airborne platform in Greenland and a radargram acquired by the SHAllow RADar (SHARAD) on board the Mars Reconnaissance Orbiter (MRO) [3] over Martian North Polar Layered Deposits (NPLD). Keywords: Subsurface mapping, Radargram, SHARAD, Greenland, Martian NPLD, Subsurface layering, line detection References: [1] Phillips, R. J., et al. "Mars north polar deposits: Stratigraphy, age, and geodynamical response." Science 320.5880 (2008): 1182-1185. [2] Cutts, James A., and Blake H. Lewis. "Models of climate cycles recorded in Martian polar layered deposits." Icarus 50.2 (1982): 216-244. [3] Plaut J J, Picardi G, Safaeinili A, et al. Subsurface radar sounding of the south polar layered deposits of Mars[J]. science, 2007, 316(5821): 92-95. Acknowledgements: Part of the research leading to these results has received funding from the STFC "MSSL Consolidated Grant" ST/K000977/1 and partial support from the European Union's Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement No. 607379 as well as from the China Scholarship Council and the UCL Dean of MAPS fund.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

The effect of recording and analysis bandwidth on acoustic identification of delphinid species.

PubMed

Oswald, Julie N; Rankin, Shannon; Barlow, Jay

2004-11-01

Because many cetacean species produce characteristic calls that propagate well under water, acoustic techniques can be used to detect and identify them. The ability to identify cetaceans to species using acoustic methods varies and may be affected by recording and analysis bandwidth. To examine the effect of bandwidth on species identification, whistles were recorded from four delphinid species (Delphinus delphis, Stenella attenuata, S. coeruleoalba, and S. longirostris) in the eastern tropical Pacific ocean. Four spectrograms, each with a different upper frequency limit (20, 24, 30, and 40 kHz), were created for each whistle (n = 484). Eight variables (beginning, ending, minimum, and maximum frequency; duration; number of inflection points; number of steps; and presence/absence of harmonics) were measured from the fundamental frequency of each whistle. The whistle repertoires of all four species contained fundamental frequencies extending above 20 kHz. Overall correct classification using discriminant function analysis ranged from 30% for the 20-kHz upper frequency limit data to 37% for the 40-kHz upper frequency limit data. For the four species included in this study, an upper bandwidth limit of at least 24 kHz is required for an accurate representation of fundamental whistle contours.

Signal classification using global dynamical models, Part II: SONAR data analysis

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

Kremliovsky, M.; Kadtke, J.

1996-06-01

In Part I of this paper, we described a numerical method for nonlinear signal detection and classification which made use of techniques borrowed from dynamical systems theory. Here in Part II of the paper, we will describe an example of data analysis using this method, for data consisting of open ocean acoustic (SONAR) recordings of marine mammal transients, supplied from NUWC sources. The purpose here is two-fold: first to give a more operational description of the technique and provide rules-of-thumb for parameter choices; and second to discuss some new issues raised by the analysis of non-ideal (real-world) data sets. Themore » particular data set considered here is quite non-stationary, relatively noisy, is not clearly localized in the background, and as such provides a difficult challenge for most detection/classification schemes. {copyright} {ital 1996 American Institute of Physics.}« less

An Analysis of Eruptions Detected by the LMSAL Eruption Patrol

NASA Astrophysics Data System (ADS)

Hurlburt, N. E.; Higgins, P. A.; Jaffey, S.

2014-12-01

Observations of the solar atmosphere reveals a wide range of real and apparent motions, from small scale jets and spicules to global-scale coronal mass ejections. Identifying and characterizing these motions are essential to advance our understanding the drivers of space weather. Automated and visual identifications are used in identifying CMEs. To date, the precursors to these — eruptions near the solar surface — have been identified primarily by visual inspection. Here we report on an analysis of the eruptions detected by the Eruption Patrol, a data mining module designed to automatically identify eruptions from data collected by Solar Dynamics Observatory's Atmospheric Imaging Assembly (SDO/AIA). We describe the module and use it both to explore relations with other solar events recorded in the Heliophysics Event Knowledgebase and to identify and access data collected by the Interface Region Imaging Spectrograph (IRIS) and Solar Optical Telescope (SOT) on Hinode for further analysis.

Record of hospitalizations for ambulatory care sensitive conditions: validation of the hospital information system.

PubMed

Rehem, Tania Cristina Morais Santa Barbara; de Oliveira, Maria Regina Fernandes; Ciosak, Suely Itsuko; Egry, Emiko Yoshikawa

2013-01-01

To estimate the sensitivity, specificity and positive and negative predictive values of the Unified Health System's Hospital Information System for the appropriate recording of hospitalizations for ambulatory care-sensitive conditions. The hospital information system records for conditions which are sensitive to ambulatory care, and for those which are not, were considered for analysis, taking the medical records as the gold standard. Through simple random sampling, a sample of 816 medical records was defined and selected by means of a list of random numbers using the Statistical Package for Social Sciences. The sensitivity was 81.89%, specificity was 95.19%, the positive predictive value was 77.61% and the negative predictive value was 96.27%. In the study setting, the Hospital Information System (SIH) was more specific than sensitive, with nearly 20% of care sensitive conditions not detected. There are no validation studies in Brazil of the Hospital Information System records for the hospitalizations which are sensitive to primary health care. These results are relevant when one considers that this system is one of the bases for assessment of the effectiveness of primary health care.

A statistical approach to bioclimatic trend detection in the airborne pollen records of Catalonia (NE Spain)

NASA Astrophysics Data System (ADS)

Fernández-Llamazares, Álvaro; Belmonte, Jordina; Delgado, Rosario; De Linares, Concepción

2014-04-01

Airborne pollen records are a suitable indicator for the study of climate change. The present work focuses on the role of annual pollen indices for the detection of bioclimatic trends through the analysis of the aerobiological spectra of 11 taxa of great biogeographical relevance in Catalonia over an 18-year period (1994-2011), by means of different parametric and non-parametric statistical methods. Among others, two non-parametric rank-based statistical tests were performed for detecting monotonic trends in time series data of the selected airborne pollen types and we have observed that they have similar power in detecting trends. Except for those cases in which the pollen data can be well-modeled by a normal distribution, it is better to apply non-parametric statistical methods to aerobiological studies. Our results provide a reliable representation of the pollen trends in the region and suggest that greater pollen quantities are being liberated to the atmosphere in the last years, specially by Mediterranean taxa such as Pinus, Total Quercus and Evergreen Quercus, although the trends may differ geographically. Longer aerobiological monitoring periods are required to corroborate these results and survey the increasing levels of certain pollen types that could exert an impact in terms of public health.

Influence analysis for high-dimensional time series with an application to epileptic seizure onset zone detection

PubMed Central

Flamm, Christoph; Graef, Andreas; Pirker, Susanne; Baumgartner, Christoph; Deistler, Manfred

2013-01-01

Granger causality is a useful concept for studying causal relations in networks. However, numerical problems occur when applying the corresponding methodology to high-dimensional time series showing co-movement, e.g. EEG recordings or economic data. In order to deal with these shortcomings, we propose a novel method for the causal analysis of such multivariate time series based on Granger causality and factor models. We present the theoretical background, successfully assess our methodology with the help of simulated data and show a potential application in EEG analysis of epileptic seizures. PMID:23354014

Wave field features of shallow vertical discontinuity and their application in non-destructive detection

USGS Publications Warehouse

Liu, J.; Xia, J.; Luo, Y.; Chen, C.; Li, X.; Huang, Y.

2007-01-01

The geotechnical integrity of critical infrastructure can be seriously compromised by the presence of fractures or crevices. Non-destructive techniques to accurately detect fractures in critical infrastructure such as dams and highways could be of significant benefit to the geotechnical industry. This paper investigates the application of shallow seismic and georadar methods to the detection of a vertical discontinuity using numerical simulations. The objective is to address the kinematical analysis of a vertical discontinuity, determine the resulting wave field characteristics, and provide the basis for determining the existence of vertical discontinuities based on the recorded signals. Simulation results demonstrate that: (1) A reflection from a vertical discontinuity produces a hyperbolic feature on a seismic or georadar profile; (2) In order for a reflection from a vertical discontinuity to be produced, a reflecting horizon below the discontinuity must exist, the offset between source and receiver (x0) must be non-zero, on the same side of the vertical discontinuity; (3) The range of distances from the vertical discontinuity where a reflection event is observed is proportional to its length and to x0; (4) Should the vertical crevice (or fracture) pass through a reflecting horizon, dual hyperbolic features can be observed on the records, and this can be used as a determining factor that the vertical crevice passes through the interface; and (5) diffractions from the edges of the discontinuity can be recorded with relatively smaller amplitude than reflections and their ranges are not constrained by the length of discontinuity. If the length of discontinuity is short enough, diffractions are the dominant feature. Real-world examples show that the shallow seismic reflection method and the georadar method are capable of recording the hyperbolic feature, which can be interpreted as vertical discontinuity. Thus, these methods show some promise as effective non-destructive detection methods for locating vertical discontinuities (e.g., fractures or crevices) in infrastructure such as dams and highway pavement. ?? 2007 Elsevier B.V. All rights reserved.

Raman and Conductivity Analysis of Graphene for Biomedical Applications

PubMed Central

Qiu, Chao; Bennet, Kevin E.; Khan, Tamanna; Ciubuc, John D.; Manciu, Felicia S.

2016-01-01

In this study, we present a comprehensive investigation of graphene’s optical and conductive properties using confocal Raman and a Drude model. A comparative analysis between experimental findings and theoretical predictions of the material’s changes and improvements as it transitioned from three-dimensional graphite is also presented and discussed. Besides spectral recording by Raman, which reveals whether there is a single, a few, or multi-layers of graphene, the confocal Raman mapping allows for distinction of such domains and a direct visualization of material inhomogeneity. Drude model employment in the analysis of the far-infrared transmittance measurements demonstrates a distinct increase of the material’s conductivity with dimensionality reduction. Other particularly important material characteristics, including carrier concentration and time constant, were also determined using this model and presented here. Furthermore, the detection of micromolar concentration of dopamine on graphene surfaces not only proves that the Raman technique facilitates ultrasensitive chemical detection of analytes, besides offering high information content about the biomaterial under study, but also that carbon-based materials are biocompatible and favorable micro-environments for such detection. Such information is valuable for the development of bio-medical sensors, which is the main application envisioned for this analysis. PMID:28774016

Reevaluating Recovery: Perceived Violations and Preemptive Interventions on Emergency Psychiatry Rounds

PubMed Central

Cohen, Trevor; Blatter, Brett; Almeida, Carlos; Patel, Vimla L.

2007-01-01

Objective Contemporary error research suggests that the quest to eradicate error is misguided. Error commission, detection, and recovery are an integral part of cognitive work, even at the expert level. In collaborative workspaces, the perception of potential error is directly observable: workers discuss and respond to perceived violations of accepted practice norms. As perceived violations are captured and corrected preemptively, they do not fit Reason’s widely accepted definition of error as “failure to achieve an intended outcome.” However, perceived violations suggest the aversion of potential error, and consequently have implications for error prevention. This research aims to identify and describe perceived violations of the boundaries of accepted procedure in a psychiatric emergency department (PED), and how they are resolved in practice. Design Clinical discourse from fourteen PED patient rounds was audio-recorded. Excerpts from recordings suggesting perceived violations or incidents of miscommunication were extracted and analyzed using qualitative coding methods. The results are interpreted in relation to prior research on vulnerabilities to error in the PED. Results Thirty incidents of perceived violations or miscommunication are identified and analyzed. Of these, only one medication error was formally reported. Other incidents would not have been detected by a retrospective analysis. Conclusions The analysis of perceived violations expands the data available for error analysis beyond occasional reported adverse events. These data are prospective: responses are captured in real time. This analysis supports a set of recommendations to improve the quality of care in the PED and other critical care contexts. PMID:17329728

A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

NASA Astrophysics Data System (ADS)

Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

2013-08-01

Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.

Observed SWE trends and climate analysis for Northwest Pacific North America: validation for future projection of SWE using the CRCM and VIC

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Bronaugh, D.; Rodenhuis, D.

2008-12-01

Observational databases of snow water equivalent (SWE) have been collected from Alaska, western US states and the Canadian provinces of British Columbia, Alberta, Saskatchewan, and territories of NWT, and the Yukon. These databases were initially validated to remove inconsistencies and errors in the station records, dates or the geographic co-ordinates of the station. The cleaned data was then analysed for historical (1950 to 2006) trend using emerging techniques for trend detection based on (first of the month) estimates for January to June. Analysis of SWE showed spatial variability in the count of records across the six month time period, and this study illustrated differences between Canadian and US (or the north and south) collection. Two different data sets (one gridded and one station) were then used to analyse April 1st records, for which there was the greatest spatial spread of station records for analysis with climate information. Initial results show spatial variability (in both magnitude and direction of trend) for trend results, and climate correlations and principal components indicate different drivers of change in SWE across the western US, Canada and north to Alaska. These results will be used to validate future predictions of SWE that are being undertaken using the Canadian Regional Climate Model (CRCM) and the Variable Infiltration Capacity (VIC) hydrologic model for Western Northern America (CRCM) and British Columbia (VIC).

TargetVue: Visual Analysis of Anomalous User Behaviors in Online Communication Systems.

PubMed

Cao, Nan; Shi, Conglei; Lin, Sabrina; Lu, Jie; Lin, Yu-Ru; Lin, Ching-Yung

2016-01-01

Users with anomalous behaviors in online communication systems (e.g. email and social medial platforms) are potential threats to society. Automated anomaly detection based on advanced machine learning techniques has been developed to combat this issue; challenges remain, though, due to the difficulty of obtaining proper ground truth for model training and evaluation. Therefore, substantial human judgment on the automated analysis results is often required to better adjust the performance of anomaly detection. Unfortunately, techniques that allow users to understand the analysis results more efficiently, to make a confident judgment about anomalies, and to explore data in their context, are still lacking. In this paper, we propose a novel visual analysis system, TargetVue, which detects anomalous users via an unsupervised learning model and visualizes the behaviors of suspicious users in behavior-rich context through novel visualization designs and multiple coordinated contextual views. Particularly, TargetVue incorporates three new ego-centric glyphs to visually summarize a user's behaviors which effectively present the user's communication activities, features, and social interactions. An efficient layout method is proposed to place these glyphs on a triangle grid, which captures similarities among users and facilitates comparisons of behaviors of different users. We demonstrate the power of TargetVue through its application in a social bot detection challenge using Twitter data, a case study based on email records, and an interview with expert users. Our evaluation shows that TargetVue is beneficial to the detection of users with anomalous communication behaviors.

Stable and unstable chromosomal aberrations among Finnish nuclear power plant workers.

PubMed

Lindholm, C

2001-01-01

Twenty nuclear power plant workers with relatively high recorded cumulative doses were studied using FISH chromosome painting and dicentric analysis after solid Giemsa staining. The results indicated that chronic exposure to ionising radiation can be detected on the group level using translocation analysis after chromosome painting, although the mean cumulative dose was approximately 100 mSv. A significant association between translocation frequency and cumulative dose was observed. Variability in the translocation yields among workers with similar recorded doses was large, resulting in a poor correlation between translocation frequencies and documented doses on the individual level. The yields of dicentric and acentric chromosomes were not correlated with the cumulative dose, indicating the inability of unstable aberrations to monitor long-term exposures. It was also shown that the unstable aberrations were not correlated with the most recent annual dose.

A case study on Discrete Wavelet Transform based Hurst exponent for epilepsy detection.

PubMed

Madan, Saiby; Srivastava, Kajri; Sharmila, A; Mahalakshmi, P

2018-01-01

Epileptic seizures are manifestations of epilepsy. Careful analysis of EEG records can provide valuable insight and improved understanding of the mechanism causing epileptic disorders. The detection of epileptic form discharges in EEG is an important component in the diagnosis of epilepsy. As EEG signals are non-stationary, the conventional frequency and time domain analysis does not provide better accuracy. So, in this work an attempt has been made to provide an overview of the determination of epilepsy by implementation of Hurst exponent (HE)-based discrete wavelet transform techniques for feature extraction from EEG data sets obtained during ictal and pre ictal stages of affected person and finally classifying EEG signals using SVM and KNN Classifiers. The The highest accuracy of 99% is obtained using SVM.

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

PubMed

Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity from neurophysiological recordings. Copyright © 2016 Elsevier B.V. All rights reserved.

Algorithms for Lunar Flash Video Search, Measurement, and Archiving

NASA Technical Reports Server (NTRS)

Swift, Wesley; Suggs, Robert; Cooke, Bill

2007-01-01

Lunar meteoroid impact flashes provide a method to estimate the flux of the large meteoroid flux and thus their hazard to spacecraft. Although meteoroid impacts on the Moon have been detected using video methods for over a decade, the difficulty of manually searching hours of video for the rare, extremely brief impact flashes has discouraged the technique's systematic implementation. A prototype has been developed for the purpose of automatically searching lunar video records for impact flashes, eliminating false detections, editing the returned possible flashes, Z and archiving and documenting the results. The theory and organization of the program is discussed with emphasis on the filtering out of several classes of false detections and retaining the brief portions of the raw video necessary for in depth analysis of the flashes detected. Several utilities for measurement, analysis, and location of the flashes on the moon included in the program are demonstrated. Application of the program to a year's worth of lunar observations is discussed along with examples of impact flashes as well as several classes of false impact flashes.

Radiometric Short-Term Fourier Transform analysis of photonic Doppler velocimetry recordings and detectivity limit

NASA Astrophysics Data System (ADS)

Prudhomme, G.; Berthe, L.; Bénier, J.; Bozier, O.; Mercier, P.

2017-01-01

Photonic Doppler Velocimetry is a plug-and-play and versatile diagnostic used in dynamic physic experiments to measure velocities. When signals are analyzed using a Short-Time Fourier Transform, multiple velocities can be distinguished: for example, the velocities of moving particle-cloud appear on spectrograms. In order to estimate the back-scattering fluxes of target, we propose an original approach "PDV Radiometric analysis" resulting in an expression of time-velocity spectrograms coded in power units. Experiments involving micron-sized particles raise the issue of detection limit; particle-size limit is very difficult to evaluate. From the quantification of noise sources, we derive an estimation of the spectrogram noise leading to a detectivity limit, which may be compared to the fraction of the incoming power which has been back-scattered by the particle and then collected by the probe. This fraction increases with their size. At last, some results from laser-shock accelerated particles using two different PDV systems are compared: it shows the improvement of detectivity with respect to the Effective Number of Bits (ENOB) of the digitizer.

Algorithms for Lunar Flash Video Search, Measurement, and Archiving

NASA Technical Reports Server (NTRS)

Swift, Wesley; Suggs, Robert; Cooke, William

2007-01-01

Lunar meteoroid impact flashes provide a method to estimate the flux of the large meteoroid flux and thus their hazard to spacecraft. Although meteoroid impacts on the Moon have been detected using video methods for over a decade, the difficulty of manually searching hours of video for the rare, extremely brief impact flashes has discouraged the technique's systematic implementation. A prototype has been developed for the purpose of automatically searching Lunar video records for impact flashes, eliminating false detections, editing the returned possible flashes, and archiving and documenting the results. The theory and organization of the program is discussed with emphasis on the filtering out of several classes of false detections and retaining the brief portions of the raw video necessary for in depth analysis of the flashes detected. Several utilities for measurement, analysis, and location of the flashes on the moon included in the program are demonstrated. Application of the program to a year's worth of Lunar observations is discussed along with examples of impact flashes as well as several classes of false impact flashes.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

PubMed

Qin, Qin; Li, Jianqing; Yue, Yinggao; Liu, Chengyu

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm

PubMed Central

Qin, Qin

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method. PMID:29104745

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

PubMed Central

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

Evaluation of listener-based anuran surveys with automated audio recording devices

USGS Publications Warehouse

Shearin, A. F.; Calhoun, A.J.K.; Loftin, C.S.

2012-01-01

Volunteer-based audio surveys are used to document long-term trends in anuran community composition and abundance. Current sampling protocols, however, are not region- or species-specific and may not detect relatively rare or audibly cryptic species. We used automated audio recording devices to record calling anurans during 2006–2009 at wetlands in Maine, USA. We identified species calling, chorus intensity, time of day, and environmental variables when each species was calling and developed logistic and generalized mixed models to determine the time interval and environmental variables that optimize detection of each species during peak calling periods. We detected eight of nine anurans documented in Maine. Individual recordings selected from the sampling period (0.5 h past sunset to 0100 h) described in the North American Amphibian Monitoring Program (NAAMP) detected fewer species than were detected in recordings from 30 min past sunset until sunrise. Time of maximum detection of presence and full chorusing for three species (green frogs, mink frogs, pickerel frogs) occurred after the NAAMP sampling end time (0100 h). The NAAMP protocol’s sampling period may result in omissions and misclassifications of chorus sizes for certain species. These potential errors should be considered when interpreting trends generated from standardized anuran audio surveys.

The miniaturized Raman system and detection of traces of life in halite from the Atacama Desert: some considerations for the search for life signatures on Mars.

PubMed

Vítek, Petr; Jehlička, Jan; Edwards, Howell G M; Hutchinson, Ian; Ascaso, Carmen; Wierzchos, Jacek

2012-12-01

Raman spectroscopy is being adopted as a nondestructive instrumentation for the robotic exploration of Mars to search for traces of life in the geological record. Here, miniaturized Raman spectrometers of two different types equipped with 532 and 785 nm lasers for excitation, respectively, were compared for the detection of microbial biomarkers in natural halite from the hyperarid region of the Atacama Desert. Measurements were performed directly on the rock as well as on the homogenized, powdered samples prepared from this material-the effects of this sample preparation and the excitation wavelength employed in the analysis are compared and discussed. From these results, 532 nm excitation was found to be superior for the analysis of powdered specimens due to its high sensitivity toward carotenoids and hence a higher capability for their detection at relatively low concentration in bulk powdered specimens. For the same reason, this wavelength was a better choice for the detection of carotenoids in direct measurements made on the rock samples. The 785 nm excitation wavelength, in contrast, proved to be more sensitive toward the detection of scytonemin.

The 2010 Eyjafjallajökull and 2011 Grimsvötn ash plumes as seen by GPS

NASA Astrophysics Data System (ADS)

Grapenthin, R.; Hreinsdottir, S.; Gudmundsson, M. T.

2015-12-01

The injection of a volcanic plume introduces a dynamic, localized, short-term heterogeneity in the atmosphere. Satellite-imagery based remote sensing techniques provide good spatial coverage for the detection of such plumes, but slow satellite repeat times (>30 minutes) and cloud cover can delay, if not entirely prevent, the detection. GPS, in turn, provides excellent temporal coverage, but requires favorable satellite-station-geometry such that the signal propagates through the plume if it is to be used for plume detection and analysis. Two methods exist to detect / analyze ash plumes with GPS: (a) Ash-heavy plumes result in signal dispersion and hence a lowered signal-to-noise ratio (SNR). A lowered SNR, recorded by some receivers, can provide useful information about the plume, such as location and velocity of ascent. These data can be evaluated directly as they are recorded by the receiver; without the need of solving for a receiver's position. (b) Wet plumes refract the GPS signals piercing the plume and hence induce a propagation delay. When solving for a receiver position GPS analysis tools do not model this localized phase delay effect and solutions for plume-piercing satellites do not fit the data well. This can be exploited for plume analysis such as the estimation of changes to the atmospheric refractivity index. We analyze GPS data of the ~2 month 2010 Eyafjallajökull erption and the week-long 2011 Grímsvötn eruption to infer a first order estimate of plume geometry and its progression. Using SNR and phase delay information, we evaluate the evolution of the partitioning of wet versus dry parts of the plume. During the GPS processing we iteratively solve for phase-delay and position and fix other parameters, hence reducing the mapping of least-squares misfit into position estimates and other parameters. Nearly continuous webcam imagery provides independent observations of first-order plume characteristics for the Eyafjallajökull event.

Assessment of NDE reliability data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Couchman, J. C.; Chang, F. H.; Packman, D. F.

1975-01-01

Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.

Detection of short-term response of the low ionosphere on gamma ray bursts

NASA Astrophysics Data System (ADS)

Nina, Aleksandra; Simić, Saša.; Srećković, Vladimir A.; Popović, Luka Č.

2015-10-01

In this paper, we study the possibility of detection of short-term terrestrial lower ionospheric response to gamma ray bursts (GRBs) using a statistical analysis of perturbations of six very low or low-frequency (VLF/LF) radio signals emitted by transmitters located worldwide and recorded by VLF/LF receiver located in Belgrade (Serbia). We consider a sample of 54 short-lasting GRBs (shorter than 1 min) detected by the Swift satellite during the period 2009-2012. We find that a statistically significant perturbation can be present in the low ionosphere, and reactions on GRBs may be observed immediately after the beginning of the GRB event or with a time delay of 60 s-90 s.

Are pollinating hawk moths declining in the Northeastern United States? An analysis of collection records

PubMed Central

2017-01-01

Increasing attention to pollinators and their role in providing ecosystem services has revealed a paucity of studies on long-term population trends of most insect pollinators in many parts of the world. Because targeted monitoring programs are resource intensive and unlikely to be performed on most insect pollinators, we took advantage of existing collection records to examine long-term trends in northeastern United States populations of 26 species of hawk moths (family Sphingidae) that are presumed to be pollinators. We compiled over 6,600 records from nine museum and 14 private collections that spanned a 112-year period, and used logistic generalized linear mixed models (GLMMs) to examine long-term population trends. We controlled for uneven sampling effort by adding a covariate for list length, the number of species recorded during each sampling event. We found that of the 22 species for which there was sufficient data to assess population trends, eight species declined and four species increased in detection probability (the probability of a species being recorded during each year while accounting for effort, climate, and spatial effects in the GLMMs). Of the four species with too few records to statistically assess, two have disappeared from parts of their ranges. None of the four species with diurnal adults showed a trend in detection probability. Two species that are pests of solanaceous crops declined, consistent with a seven-fold drop in the area planted in tobacco and tomato crops. We found some evidence linking susceptibility to parasitoidism by the introduced fly Compsilura concinnata (Tachinidae) to declines. Moths with larvae that feed on vines and trees, where available evidence indicates that the fly is most likely to attack, had a greater propensity to decline than species that use herbs and shrubs as larval host plants. Species that develop in the spring, before Compsilura populations have increased, did not decline. However, restricting the analysis to hawk moth records from areas outside of a “refuge” area where Compsilura does not occur did not significantly increase the intensity of the declines as would be predicted if Compsilura was the primary cause of declines. Forests have recovered over the study period across most of the northeastern U.S., but this does not appear to have been a major factor because host plants of several of the declining species have increased in abundance with forest expansion and maturation. Climate variables used in the GLMMs were not consistently related to moth detection probability. Hawk moth declines may have ecological effects on both the plants pollinated by these species and vertebrate predators of the moths. PMID:28982152

Optimizing combined GPR, OSL and LiDAR (GOaL) to extract paleoenvironmental records and decipher shoreline evolution

NASA Astrophysics Data System (ADS)

Dougherty, A. J.; Choi, J. H.; Turney, C. S.; Dosseto, A.

2017-12-01

Records of past sea levels, storms, sediment supply and their impacts on the coastline are crucial for projecting likely shoreline changes resulting from anthropogenic warming. High-resolution geophysics, geochronology, and remote sensing techniques offer an optimal way to extract these records and decipher shoreline evolution. These methods include Light Detection and Ranging (LiDAR for imaging barrier morphologies in three dimensions), Ground Penetrating Radar (GPR for detecting paleo-dune, beach and nearshore stratigraphy) and Optically Stimulated Luminescence (OSL for dating deposition of sand grains along paleoshorelines). Each of these teqniques have been applied to coastal research over the decades since they were first introduced. Recently there has been a rapid increase their use since LiDAR became more available, GPR more user-friendly, and OSL more accessible. These methods have the potential to produce both detailed and voluminous datasets that can overwhelm or obscure significant features, such that discrepancies in analysis and/or presentation may lead to erroneous interpretations. In contrast, when utilized correctly on prograded barriers these methods (independently or in various combinations) have produced storm records, constructed sea-level curves, quantified sediment budgets, and deciphered coastal evolution. Therefore, combining the application of GPR, OSL, and LiDAR (GOaL) on one prograded barrier has the potential to generate detailed records of storms, sea level, and sediment supply for that coastline. Obtaining this GOaL hat-trick can provide valuable insights into how these three factors influenced past and future barrier evolution. Here we argue that systematically achieving GOaL hat-tricks on some of the 300+ prograded barriers worldwide would allow us to disentangle local patterns of sediment supply from regional effects of storms or global changes in sea level, allowing direct comparison to climate proxy records. To fully realize this aim requires standardization of methods to optimize results. The impetus for this initiative is to establish a framework for consistent data analysis that maximizes the potential of GOaL to contribute to climate change research and assist coastal communities in mitigating future impacts of global warming.

Detection and Mapping of the September 2017 Mexico Earthquakes Using DAS Fiber-Optic Infrastructure Arrays

NASA Astrophysics Data System (ADS)

Karrenbach, M. H.; Cole, S.; Williams, J. J.; Biondi, B. C.; McMurtry, T.; Martin, E. R.; Yuan, S.

2017-12-01

Fiber-optic distributed acoustic sensing (DAS) uses conventional telecom fibers for a wide variety of monitoring purposes. Fiber-optic arrays can be located along pipelines for leak detection; along borders and perimeters to detect and locate intruders, or along railways and roadways to monitor traffic and identify and manage incidents. DAS can also be used to monitor oil and gas reservoirs and to detect earthquakes. Because thousands of such arrays are deployed worldwide and acquiring data continuously, they can be a valuable source of data for earthquake detection and location, and could potentially provide important information to earthquake early-warning systems. In this presentation, we show that DAS arrays in Mexico and the United States detected the M8.1 and M7.2 Mexico earthquakes in September 2017. At Stanford University, we have deployed a 2.4 km fiber-optic DAS array in a figure-eight pattern, with 600 channels spaced 4 meters apart. Data have been recorded continuously since September 2016. Over 800 earthquakes from across California have been detected and catalogued. Distant teleseismic events have also been recorded, including the two Mexican earthquakes. In Mexico, fiber-optic arrays attached to pipelines also detected these two events. Because of the length of these arrays and their proximity to the event locations, we can not only detect the earthquakes but also make location estimates, potentially in near real time. In this presentation, we review the data recorded for these two events recorded at Stanford and in Mexico. We compare the waveforms recorded by the DAS arrays to those recorded by traditional earthquake sensor networks. Using the wide coverage provided by the pipeline arrays, we estimate the event locations. Such fiber-optic DAS networks can potentially play a role in earthquake early-warning systems, allowing actions to be taken to minimize the impact of an earthquake on critical infrastructure components. While many such fiber-optic networks are already in place, new arrays can be created on demand, using existing fiber-optic telecom cables, for specific monitoring situations such as recording aftershocks of a large earthquake or monitoring induced seismicity.

Action potential propagation recorded from single axonal arbors using multi-electrode arrays.

PubMed

Tovar, Kenneth R; Bridges, Daniel C; Wu, Bian; Randall, Connor; Audouard, Morgane; Jang, Jiwon; Hansma, Paul K; Kosik, Kenneth S

2018-04-11

We report the presence of co-occurring extracellular action potentials (eAPs) from cultured mouse hippocampal neurons among groups of planar electrodes on multi-electrode arrays (MEAs). The invariant sequences of eAPs among co-active electrode groups, repeated co-occurrences and short inter-electrode latencies are consistent with action potential propagation in unmyelinated axons. Repeated eAP co-detection by multiple electrodes was widespread in all our data records. Co-detection of eAPs confirms they result from the same neuron and allows these eAPs to be isolated from all other spikes independently of spike sorting algorithms. We averaged co-occurring events and revealed additional electrodes with eAPs that would otherwise be below detection threshold. We used these eAP cohorts to explore the temperature sensitivity of action potential propagation and the relationship between voltage-gated sodium channel density and propagation velocity. The sequence of eAPs among co-active electrodes 'fingerprints' neurons giving rise to these events and identifies them within neuronal ensembles. We used this property and the non-invasive nature of extracellular recording to monitor changes in excitability at multiple points in single axonal arbors simultaneously over several hours, demonstrating independence of axonal segments. Over several weeks, we recorded changes in inter-electrode propagation latencies and ongoing changes in excitability in different regions of single axonal arbors. Our work illustrates how repeated eAP co-occurrences can be used to extract physiological data from single axons with low electrode density MEAs. However, repeated eAP co-occurrences leads to over-sampling spikes from single neurons and thus can confound traditional spike-train analysis.

Detection of main tidal frequencies using least squares harmonic estimation method

NASA Astrophysics Data System (ADS)

Mousavian, R.; Hossainali, M. Mashhadi

2012-11-01

In this paper the efficiency of the method of Least Squares Harmonic Estimation (LS-HE) for detecting the main tidal frequencies is investigated. Using this method, the tidal spectrum of the sea level data is evaluated at two tidal stations: Bandar Abbas in south of Iran and Workington on the eastern coast of the UK. The amplitudes of the tidal constituents at these two tidal stations are not the same. Moreover, in contrary to the Workington station, the Bandar Abbas tidal record is not an equispaced time series. Therefore, the analysis of the hourly tidal observations in Bandar Abbas and Workington can provide a reasonable insight into the efficiency of this method for analyzing the frequency content of tidal time series. Furthermore, applying the method of Fourier transform to the Workington tidal record provides an independent source of information for evaluating the tidal spectrum proposed by the LS-HE method. According to the obtained results, the spectrums of these two tidal records contain the components with the maximum amplitudes among the expected ones in this time span and some new frequencies in the list of known constituents. In addition, in terms of frequencies with maximum amplitude; the power spectrums derived from two aforementioned methods are the same. These results demonstrate the ability of LS-HE for identifying the frequencies with maximum amplitude in both tidal records.

Real-Time Amperometric Recording of Extracellular H₂O₂ in the Brain of Immunocompromised Mice: An In Vitro, Ex Vivo and In Vivo Characterisation Study.

PubMed

Reid, Caroline H; Finnerty, Niall J

2017-07-08

We detail an extensive characterisation study on a previously described dual amperometric H₂O₂ biosensor consisting of H₂O₂ detection (blank) and degradation (catalase) electrodes. In vitro investigations demonstrated excellent H₂O₂ sensitivity and selectivity against the interferent, ascorbic acid. Ex vivo studies were performed to mimic physiological conditions prior to in vivo deployment. Exposure to brain tissue homogenate identified reliable sensitivity and selectivity recordings up to seven days for both blank and catalase electrodes. Furthermore, there was no compromise in pre- and post-implanted catalase electrode sensitivity in ex vivo mouse brain. In vivo investigations performed in anaesthetised mice confirmed the ability of the H₂O₂ biosensor to detect increases in amperometric current following locally perfused/infused H₂O₂ and antioxidant inhibitors mercaptosuccinic acid and sodium azide. Subsequent recordings in freely moving mice identified negligible effects of control saline and sodium ascorbate interference injections on amperometric H₂O₂ current. Furthermore, the stability of the amperometric current was confirmed over a five-day period and analysis of 24-h signal recordings identified the absence of diurnal variations in amperometric current. Collectively, these findings confirm the biosensor current responds in vivo to increasing exogenous and endogenous H₂O₂ and tentatively supports measurement of H₂O₂ dynamics in freely moving NOD SCID mice.

Multi-Channel Hyperspectral Fluorescence Detection Excited by Coupled Plasmon-Waveguide Resonance

PubMed Central

Du, Chan; Liu, Le; Zhang, Lin; Guo, Jun; Guo, Jihua; Ma, Hui; He, Yonghong

2013-01-01

We propose in this paper a biosensor scheme based on coupled plasmon-waveguide resonance (CPWR) excited fluorescence spectroscopy. A symmetrical structure that offers higher surface electric field strengths, longer surface propagation lengths and depths is developed to support guided waveguide modes for the efficient excitation of fluorescence. The optimal parameters for the sensor films are theoretically and experimentally investigated, leading to a detection limit of 0.1 nM (for a Cy5 solution). Multiplex analysis possible with the fluorescence detection is further advanced by employing the hyperspectral fluorescence technique to record the full spectra for every pixel on the sample plane. We demonstrate experimentally that highly overlapping fluorescence (Cy5 and Dylight680) can be distinguished and ratios of different emission sources can be determined accurately. This biosensor shows great potential for multiplex detections of fluorescence analytes. PMID:24129023

The effect of the quality of vital sign recording on clinical decision making in a regional acute care trauma ward.

PubMed

Keene, Claire M; Kong, Victor Y; Clarke, Damian L; Brysiewicz, Petra

2017-10-01

Recording vital signs is important in the hospital setting and the quality of this documentation influences clinical decision making. The Modified Early Warning Score (MEWS) uses vital signs to categorise the severity of a patient's physiological derangement and illustrates the clinical impact of vital signs in detecting patient deterioration and making management decisions. This descriptive study measured the quality of vital sign recordings in an acute care trauma setting, and used the MEWS to determine the impact the documentation quality had on the detection of physiological derangements and thus, clinical decision making. Vital signs recorded by the nursing staff of all trauma patients in the acute care trauma wards at a regional hospital in South Africa were collected from January 2013 to February 2013. Investigator-measured values taken within 2 hours of the routine observations and baseline patient information were also recorded. A MEWS for each patient was calculated from the routine and investigator-measured observations. Basic descriptive statistics were performed using EXCEL. The details of 181 newly admitted patients were collected. Completion of recordings was 81% for heart rate, 88% for respiratory rate, 98% for blood pressure, 92% for temperature and 41% for GCS. The recorded heart rate was positively correlated with the investigator's measurement (Pearson's correlation coefficient of 0.76); while the respiratory rate did not correlate (Pearson's correlation coefficient of 0.02). In 59% of patients the recorded respiratory rate (RR) was exactly 20 breaths per minute and 27% had a recorded RR of exactly 15. Seven percent of patients had aberrant Glasgow Coma Scale readings above the maximum value of 15. The average MEWS was 2 for both the recorded (MEWS(R)) and investigator (MEWS(I)) vitals, with the range of MEWS(R) 0-7 and MEWS(I) 0-9. Analysis showed 59% of the MEWS(R) underestimated the physiological derangement (scores were lower than the MEWS(I)); 80% of patients had a MEWS(R) requiring 4 hourly checks which was only completed in 2%; 86% of patients had a MEWS(R) of less than three (i.e. not necessitating escalation of care), but 33% of these showed a MEWS(I) greater than three (i.e. actually necessitating escalation of care). Documentation of vital signs aids management decisions, indicating the physiological derangement of a patient and dictating treatment. This study showed that there was a poor quality of vital sign recording in this acute care trauma setting, which led to underestimation of patients' physiological derangement and an inability to detect deteriorating patients. The MEWS could be a powerful tool to empower nurses to become involved in the diagnosis and detection of deteriorating patients, as well as providing a framework to communicate the severity of derangement between health workers. However, it requires a number of strategies to improve the quality of vital sign recording, including continuing education, increasing the numbers of competent staff and administrative changes in vital sign charts. Copyright © 2017. Production and hosting by Elsevier B.V.

White light phase shifting interferometry and color fringe analysis for the detection of contaminants in water

NASA Astrophysics Data System (ADS)

Dubey, Vishesh; Singh, Veena; Ahmad, Azeem; Singh, Gyanendra; Mehta, Dalip Singh

2016-03-01

We report white light phase shifting interferometry in conjunction with color fringe analysis for the detection of contaminants in water such as Escherichia coli (E.coli), Campylobacter coli and Bacillus cereus. The experimental setup is based on a common path interferometer using Mirau interferometric objective lens. White light interferograms are recorded using a 3-chip color CCD camera based on prism technology. The 3-chip color camera have lesser color cross talk and better spatial resolution in comparison to single chip CCD camera. A piezo-electric transducer (PZT) phase shifter is fixed with the Mirau objective and they are attached with a conventional microscope. Five phase shifted white light interferograms are recorded by the 3-chip color CCD camera and each phase shifted interferogram is decomposed into the red, green and blue constituent colors, thus making three sets of five phase shifted intererograms for three different colors from a single set of white light interferogram. This makes the system less time consuming and have lesser effect due to surrounding environment. Initially 3D phase maps of the bacteria are reconstructed for red, green and blue wavelengths from these interferograms using MATLAB, from these phase maps we determines the refractive index (RI) of the bacteria. Experimental results of 3D shape measurement and RI at multiple wavelengths will be presented. These results might find applications for detection of contaminants in water without using any chemical processing and fluorescent dyes.

Feasibility of Using Low-Cost Motion Capture for Automated Screening of Shoulder Motion Limitation after Breast Cancer Surgery.

PubMed

Gritsenko, Valeriya; Dailey, Eric; Kyle, Nicholas; Taylor, Matt; Whittacre, Sean; Swisher, Anne K

2015-01-01

To determine if a low-cost, automated motion analysis system using Microsoft Kinect could accurately measure shoulder motion and detect motion impairments in women following breast cancer surgery. Descriptive study of motion measured via 2 methods. Academic cancer center oncology clinic. 20 women (mean age = 60 yrs) were assessed for active and passive shoulder motions during a routine post-operative clinic visit (mean = 18 days after surgery) following mastectomy (n = 4) or lumpectomy (n = 16) for breast cancer. Participants performed 3 repetitions of active and passive shoulder motions on the side of the breast surgery. Arm motion was recorded using motion capture by Kinect for Windows sensor and on video. Goniometric values were determined from video recordings, while motion capture data were transformed to joint angles using 2 methods (body angle and projection angle). Correlation of motion capture with goniometry and detection of motion limitation. Active shoulder motion measured with low-cost motion capture agreed well with goniometry (r = 0.70-0.80), while passive shoulder motion measurements did not correlate well. Using motion capture, it was possible to reliably identify participants whose range of shoulder motion was reduced by 40% or more. Low-cost, automated motion analysis may be acceptable to screen for moderate to severe motion impairments in active shoulder motion. Automatic detection of motion limitation may allow quick screening to be performed in an oncologist's office and trigger timely referrals for rehabilitation.

Fast EEG spike detection via eigenvalue analysis and clustering of spatial amplitude distribution

NASA Astrophysics Data System (ADS)

Fukami, Tadanori; Shimada, Takamasa; Ishikawa, Bunnoshin

2018-06-01

Objective. In the current study, we tested a proposed method for fast spike detection in electroencephalography (EEG). Approach. We performed eigenvalue analysis in two-dimensional space spanned by gradients calculated from two neighboring samples to detect high-amplitude negative peaks. We extracted the spike candidates by imposing restrictions on parameters regarding spike shape and eigenvalues reflecting detection characteristics of individual medical doctors. We subsequently performed clustering, classifying detected peaks by considering the amplitude distribution at 19 scalp electrodes. Clusters with a small number of candidates were excluded. We then defined a score for eliminating spike candidates for which the pattern of detected electrodes differed from the overall pattern in a cluster. Spikes were detected by setting the score threshold. Main results. Based on visual inspection by a psychiatrist experienced in EEG, we evaluated the proposed method using two statistical measures of precision and recall with respect to detection performance. We found that precision and recall exhibited a trade-off relationship. The average recall value was 0.708 in eight subjects with the score threshold that maximized the F-measure, with 58.6  ±  36.2 spikes per subject. Under this condition, the average precision was 0.390, corresponding to a false positive rate 2.09 times higher than the true positive rate. Analysis of the required processing time revealed that, using a general-purpose computer, our method could be used to perform spike detection in 12.1% of the recording time. The process of narrowing down spike candidates based on shape occupied most of the processing time. Significance. Although the average recall value was comparable with that of other studies, the proposed method significantly shortened the processing time.

Next generation laser-based standoff spectroscopy techniques for Mars exploration.

PubMed

Gasda, Patrick J; Acosta-Maeda, Tayro E; Lucey, Paul G; Misra, Anupam K; Sharma, Shiv K; Taylor, G Jeffrey

2015-01-01

In the recent Mars 2020 Rover Science Definition Team Report, the National Aeronautics and Space Administration (NASA) has sought the capability to detect and identify elements, minerals, and most importantly, biosignatures, at fine scales for the preparation of a retrievable cache of samples. The current Mars rover, the Mars Science Laboratory Curiosity, has a remote laser-induced breakdown spectroscopy (LIBS) instrument, a type of quantitative elemental analysis, called the Chemistry Camera (ChemCam) that has shown that laser-induced spectroscopy instruments are not only feasible for space exploration, but are reliable and complementary to traditional elemental analysis instruments such as the Alpha Particle X-Ray Spectrometer. The superb track record of ChemCam has paved the way for other laser-induced spectroscopy instruments, such as Raman and fluorescence spectroscopy. We have developed a prototype remote LIBS-Raman-fluorescence instrument, Q-switched laser-induced time-resolved spectroscopy (QuaLITy), which is approximately 70 000 times more efficient at recording signals than a commercially available LIBS instrument. The increase in detection limits and sensitivity is due to our development of a directly coupled system, the use of an intensified charge-coupled device image detector, and a pulsed laser that allows for time-resolved measurements. We compare the LIBS capabilities of our system with an Ocean Optics spectrometer instrument at 7 m and 5 m distance. An increase in signal-to-noise ratio of at least an order of magnitude allows for greater quantitative analysis of the elements in a LIBS spectrum with 200-300 μm spatial resolution at 7 m, a Raman instrument capable of 1 mm spatial resolution at 3 m, and bioorganic fluorescence detection at longer distances. Thus, the new QuaLITy instrument fulfills all of the NASA expectations for proposed instruments.

Primary cosmic ray particles with z 35 (VVH particles). [very heavy particle detection by high altitude balloons

NASA Technical Reports Server (NTRS)

Blanford, G. E., Jr.; Friedlander, M. W.; Hoppe, M.; Klarmann, J.; Walker, R. M.; Wefel, J. P.

1972-01-01

Large areas of nuclear emulsions and plastic detectors were exposed to the primary cosmic radiation during high altitude balloon flights. From the analysis of 141 particle tracks recorded during a total exposure of 1.3 x 10 to the 7th power sq m ster.sec., a charge spectrum of the VVH particles has been derived.

Companions to α Orionis

NASA Astrophysics Data System (ADS)

Karovska, M.; Nisenson, P.; Noyes, R. W.; Stachnik, R.

Detection of two close optical companions to the red supergiant a Ori was accomplished using the PAPA detector for data recording, and speckle imaging for image reconstruction. Our analysis favors an interpretation in which the two optical sources are stellar companions to a Ori.The observed time dependent variations of the polarization of a Ori can be interpreted as being due to a systemic asymmetry created by one of the companions.

Sequential Analysis: Hypothesis Testing and Changepoint Detection

DTIC Science & Technology

2014-07-11

it is necessary to estimate in situ the geographical coordinates and other parameters of earthquakes . The standard sensor equipment of a three...components. When an earthquake arises, the sensors begin to record several types of seismic waves (body and surface waves), among which the more important...machines and to increased safety norms. Many structures to be monitored, e.g., civil engineering structures subject to wind and earthquakes , aircraft

The Miniaturized Raman System and Detection of Traces of Life in Halite from the Atacama Desert: Some Considerations for the Search for Life Signatures on Mars

PubMed Central

Jehlička, Jan; Edwards, Howell G.M.; Hutchinson, Ian; Ascaso, Carmen; Wierzchos, Jacek

2012-01-01

Abstract Raman spectroscopy is being adopted as a nondestructive instrumentation for the robotic exploration of Mars to search for traces of life in the geological record. Here, miniaturized Raman spectrometers of two different types equipped with 532 and 785 nm lasers for excitation, respectively, were compared for the detection of microbial biomarkers in natural halite from the hyperarid region of the Atacama Desert. Measurements were performed directly on the rock as well as on the homogenized, powdered samples prepared from this material—the effects of this sample preparation and the excitation wavelength employed in the analysis are compared and discussed. From these results, 532 nm excitation was found to be superior for the analysis of powdered specimens due to its high sensitivity toward carotenoids and hence a higher capability for their detection at relatively low concentration in bulk powdered specimens. For the same reason, this wavelength was a better choice for the detection of carotenoids in direct measurements made on the rock samples. The 785 nm excitation wavelength, in contrast, proved to be more sensitive toward the detection of scytonemin. Key Words: Miniaturized portable Raman—Atacama—Mars—Biomarker detection. Astrobiology 12, 1095–1099. PMID:23151300

Enhancing detection of steady-state visual evoked potentials using individual training data.

PubMed

Wang, Yijun; Nakanishi, Masaki; Wang, Yu-Te; Jung, Tzyy-Ping

2014-01-01

Although the performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) has improved gradually in the past decades, it still does not meet the requirement of a high communication speed in many applications. A major challenge is the interference of spontaneous background EEG activities in discriminating SSVEPs. An SSVEP BCI using frequency coding typically does not have a calibration procedure since the frequency of SSVEPs can be recognized by power spectrum density analysis (PSDA). However, the detection rate can be deteriorated by the spontaneous EEG activities within the same frequency range because phase information of SSVEPs is ignored in frequency detection. To address this problem, this study proposed to incorporate individual SSVEP training data into canonical correlation analysis (CCA) to improve the frequency detection of SSVEPs. An eight-class SSVEP dataset recorded from 10 subjects in a simulated online BCI experiment was used for performance evaluation. Compared to the standard CCA method, the proposed method obtained significantly improved detection accuracy (95.2% vs. 88.4%, p<0.05) and information transfer rates (ITR) (104.6 bits/min vs. 89.1 bits/min, p<0.05). The results suggest that the employment of individual SSVEP training data can significantly improve the detection rate and thereby facilitate the implementation of a high-speed BCI.

Tectonic Tremor along the San Jacinto Fault Zone near Anza, California

NASA Astrophysics Data System (ADS)

Brown, J. R.

2013-12-01

In several tectonic settings where it is observed, low frequency tremor is proven as a useful tool to probe slow fault slip at depth (e.g., southwest Japan, Cascadia, Parkfield). However, tremor is difficult to detect due to its long durations and low amplitudes close to the noise band. This is particularly true in southern California where cultural noise sources are both spatially and temporally pervasive. Visually scanning continuous seismic recordings of the Southern California Seismic Network from 2001-2011 we find three pervasive occurrences of tremor: fall 2001, summer 2005 and summer 2010. In this presentation we focus on our analysis of the summer 2010 tremors on account of the enhanced instrumentation from the EarthScope Plate Boundary Observatory. During summer 2010 we detect ~240 hours of tremor-like signals in vicinity of the San Jacinto fault zone (SJFZ) near Anza. Visual inspection of continuous recordings up to 100 km northeast and southwest of the SJFZ do not record tremor-like signals indicating the source is both weak and local. Tremor is discriminated from other noise sources by calculating their spectral shapes to assure the signals are distinct from local noise sources and earthquakes. Similar to tremor spectra in other settings, the tremor signals in vicinity of the SJFZ are spectrally flat up to 9 Hz. In order to characterize the tremor source, we employ a combination of running autocorrelation and matched-filter techniques to detect and locate low frequency earthquakes (LFE) along the SJFZ one hour at a time. The autocorrelation of the north and vertical components of 14 stations detects over 13500 LFEs. We identify S-wave arrivals using the cross-correlation of 6 s windows for event pairs using the north component. Preliminary analysis of S-waves reveals a localized swarm of LFE epicenters extending 5 to 10 km SE of the Anza Gap with a horizontal error of +/- 4 km. Tremor depths are poorly constrained due to the lack of clear P-wave arrivals. The LFE epicenters reveal a zone of slow slip activity to the SE of the Anza Gap during early summer of 2010.

Automated Studies of Continuing Current in Lightning Flashes

NASA Astrophysics Data System (ADS)

Martinez-Claros, Jose

Continuing current (CC) is a continuous luminosity in the lightning channel that lasts longer than 10 ms following a lightning return stroke to ground. Lightning flashes following CC are associated with direct damage to power lines and are thought to be responsible for causing lightning-induced forest fires. The development of an algorithm that automates continuing current detection by combining NLDN (National Lightning Detection Network) and LEFA (Langmuir Electric Field Array) datasets for CG flashes will be discussed. The algorithm was applied to thousands of cloud-to-ground (CG) flashes within 40 km of Langmuir Lab, New Mexico measured during the 2013 monsoon season. It counts the number of flashes in a single minute of data and the number of return strokes of an individual lightning flash; records the time and location of each return stroke; performs peak analysis on E-field data, and uses the slope of interstroke interval (ISI) E-field data fits to recognize whether continuing current (CC) exists within the interval. Following CC detection, duration and magnitude are measured. The longest observed C in 5588 flashes was 631 ms. The performance of the algorithm (vs. human judgement) was checked on 100 flashes. At best, the reported algorithm is "correct" 80% of the time, where correct means that multiple stations agree with each other and with a human on both the presence and duration of CC. Of the 100 flashes that were validated against human judgement, 62% were hybrid. Automated analysis detects the first but misses the second return stroke in many cases where the second return stroke is followed by long CC. This problem is also present in human interpretation of field change records.

Clinical implementation and failure mode and effects analysis of HDR skin brachytherapy using Valencia and Leipzig surface applicators.

PubMed

Sayler, Elaine; Eldredge-Hindy, Harriet; Dinome, Jessie; Lockamy, Virginia; Harrison, Amy S

2015-01-01

The planning procedure for Valencia and Leipzig surface applicators (VLSAs) (Nucletron, Veenendaal, The Netherlands) differs substantially from CT-based planning; the unfamiliarity could lead to significant errors. This study applies failure modes and effects analysis (FMEA) to high-dose-rate (HDR) skin brachytherapy using VLSAs to ensure safety and quality. A multidisciplinary team created a protocol for HDR VLSA skin treatments and applied FMEA. Failure modes were identified and scored by severity, occurrence, and detectability. The clinical procedure was then revised to address high-scoring process nodes. Several key components were added to the protocol to minimize risk probability numbers. (1) Diagnosis, prescription, applicator selection, and setup are reviewed at weekly quality assurance rounds. Peer review reduces the likelihood of an inappropriate treatment regime. (2) A template for HDR skin treatments was established in the clinic's electronic medical record system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planner as well as increases the detectability of an error. (3) A screen check was implemented during the second check to increase detectability of an error. (4) To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display, facilitating data entry and verification. (5) VLSAs are color coded and labeled to match the electronic medical record prescriptions, simplifying in-room selection and verification. Multidisciplinary planning and FMEA increased detectability and reduced error probability during VLSA HDR brachytherapy. This clinical model may be useful to institutions implementing similar procedures. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Face recognition for criminal identification: An implementation of principal component analysis for face recognition

NASA Astrophysics Data System (ADS)

Abdullah, Nurul Azma; Saidi, Md. Jamri; Rahman, Nurul Hidayah Ab; Wen, Chuah Chai; Hamid, Isredza Rahmi A.

2017-10-01

In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforce thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

Smart Toys Designed for Detecting Developmental Delays

PubMed Central

Rivera, Diego; García, Antonio; Alarcos, Bernardo; Velasco, Juan R.; Ortega, José Eugenio; Martínez-Yelmo, Isaías

2016-01-01

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports. PMID:27879626

Smart Toys Designed for Detecting Developmental Delays.

PubMed

Rivera, Diego; García, Antonio; Alarcos, Bernardo; Velasco, Juan R; Ortega, José Eugenio; Martínez-Yelmo, Isaías

2016-11-20

In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports.

Detectability of the impacts of ozone-depleting substances and greenhouse gases upon stratospheric ozone accounting for nonlinearities in historical forcings

NASA Astrophysics Data System (ADS)

Bandoro, Justin; Solomon, Susan; Santer, Benjamin D.; Kinnison, Douglas E.; Mills, Michael J.

2018-01-01

We perform a formal attribution study of upper- and lower-stratospheric ozone changes using observations together with simulations from the Whole Atmosphere Community Climate Model. Historical model simulations were used to estimate the zonal-mean response patterns (fingerprints) to combined forcing by ozone-depleting substances (ODSs) and well-mixed greenhouse gases (GHGs), as well as to the individual forcing by each factor. Trends in the similarity between the searched-for fingerprints and homogenized observations of stratospheric ozone were compared to trends in pattern similarity between the fingerprints and the internally and naturally generated variability inferred from long control runs. This yields estimated signal-to-noise (S/N) ratios for each of the three fingerprints (ODS, GHG, and ODS + GHG). In both the upper stratosphere (defined in this paper as 1 to 10 hPa) and lower stratosphere (40 to 100 hPa), the spatial fingerprints of the ODS + GHG and ODS-only patterns were consistently detectable not only during the era of maximum ozone depletion but also throughout the observational record (1984-2016). We also develop a fingerprint attribution method to account for forcings whose time evolutions are markedly nonlinear over the observational record. When the nonlinearity of the time evolution of the ODS and ODS + GHG signals is accounted for, we find that the S/N ratios obtained with the stratospheric ODS and ODS + GHG fingerprints are enhanced relative to standard linear trend analysis. Use of the nonlinear signal detection method also reduces the detection time - the estimate of the date at which ODS and GHG impacts on ozone can be formally identified. Furthermore, by explicitly considering nonlinear signal evolution, the complete observational record can be used in the S/N analysis, without applying piecewise linear regression and introducing arbitrary break points. The GHG-driven fingerprint of ozone changes was not statistically identifiable in either the upper- or lower-stratospheric SWOOSH data, irrespective of the signal detection method used. In the WACCM simulations of future climate change, the GHG signal is statistically identifiable between 2020 and 2030. Our findings demonstrate the importance of continued stratospheric ozone monitoring to improve estimates of the contributions of ODS and GHG forcing to global changes in stratospheric ozone.

Prostate cancer localization with endorectal MR imaging and MR spectroscopic imaging: effect of clinical data on reader accuracy.

PubMed

Dhingsa, Rajpal; Qayyum, Aliya; Coakley, Fergus V; Lu, Ying; Jones, Kirk D; Swanson, Mark G; Carroll, Peter R; Hricak, Hedvig; Kurhanewicz, John

2004-01-01

To determine the effect of digital rectal examination findings, sextant biopsy results, and prostate-specific antigen (PSA) levels on reader accuracy in the localization of prostate cancer with endorectal magnetic resonance (MR) imaging and MR spectroscopic imaging. This was a retrospective study of 37 patients (mean age, 57 years) with biopsy-proved prostate cancer. Transverse T1-weighted, transverse high-spatial-resolution, and coronal T2-weighted MR images and MR spectroscopic images were obtained. Two independent readers, unaware of clinical data, recorded the size and location of suspicious peripheral zone tumor nodules on a standardized diagram of the prostate. Readers also recorded their degree of diagnostic confidence for each nodule on a five-point scale. Both readers repeated this interpretation with knowledge of rectal examination findings, sextant biopsy results, and PSA level. Step-section histopathologic findings were the reference standard. Logistic regression analysis with generalized estimating equations was used to correlate tumor detection with clinical data, and alternative free-response receiver operating characteristic (AFROC) curve analysis was used to examine the overall effect of clinical data on all positive results. Fifty-one peripheral zone tumor nodules were identified at histopathologic evaluation. Logistic regression analysis showed awareness of clinical data significantly improved tumor detection rate (P <.02) from 15 to 19 nodules for reader 1 and from 13 to 19 nodules for reader 2 (27%-37% overall) by using both size and location criteria. AFROC analysis showed no significant change in overall reader performance because there was an associated increase in the number of false-positive findings with awareness of clinical data, from 11 to 21 for reader 1 and from 16 to 25 for reader 2. Awareness of clinical data significantly improves reader detection of prostate cancer nodules with endorectal MR imaging and MR spectroscopic imaging, but there is no overall change in reader accuracy, because of an associated increase in false-positive findings. A stricter definition of a true-positive result is associated with reduced sensitivity for prostate cancer nodule detection. Copyright RSNA, 2004

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

Christoph, G.G; Jackson, K.A.; Neuman, M.C.

An effective method for detecting computer misuse is the automatic auditing and analysis of on-line user activity. This activity is reflected in the system audit record, by changes in the vulnerability posture of the system configuration, and in other evidence found through active testing of the system. In 1989 we started developing an automatic misuse detection system for the Integrated Computing Network (ICN) at Los Alamos National Laboratory. Since 1990 this system has been operational, monitoring a variety of network systems and services. We call it the Network Anomaly Detection and Intrusion Reporter, or NADIR. During the last year andmore » a half, we expanded NADIR to include processing of audit and activity records for the Cray UNICOS operating system. This new component is called the UNICOS Real-time NADIR, or UNICORN. UNICORN summarizes user activity and system configuration information in statistical profiles. In near real-time, it can compare current activity to historical profiles and test activity against expert rules that express our security policy and define improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. UNICORN is currently operational on four Crays in Los Alamos` main computing network, the ICN.« less

A wearable, mobile phone-based respiration monitoring system for sleep apnea syndrome detection.

PubMed

Ishida, Ryoichi; Yonezawa, Yoshiharu; Maki, Hiromichi; Ogawa, Hidekuni; Ninomiya, Ishio; Sada, Kouji; Hamada, Shingo; Hahn, Allen W; Caldwell, W Morton

2005-01-01

A new wearable respiration monitoring system has been developed for non-invasive detection of sleep apnea syndrome. The system, which is attached to a shirt, consists of a piezoelectric sensor, a low-power 8-bit single chip microcontroller, EEPROM and a 2.4 GHz low-power transmitting mobile phone (PHS). The piezoelectric sensor, whose electrical polarization voltage is produced by body movements, is installed inside the shirt and closely contacts the patient's chest. The low frequency components of body movements recorded by the sensor are mainly generated by respiration. The microcontroller sequentially stores the movement signal to the EEPROM for 5 minutes and detects, by time-frequency analysis, whether the patient has breathed during that time. When the patient is apneic for 10 sseconds, the microcontroller sends the recorded respiration waveform during and one minute before and after the apnea directly to the hospital server computer via the mobile phone. The server computer then creates apnea "filings" automatically for every patient. The system can be used at home and be self-applied by patients. Moreover, the system does not require any extra equipment such as a personal computer, PDA, or Internet connection.

Detection of cardiac activity using a 5.8 GHz radio frequency sensor.

PubMed

Vasu, V; Fox, N; Brabetz, T; Wren, M; Heneghan, C; Sezer, S

2009-01-01

A 5.8-GHz ISM-Band radio-frequency sensor has been developed for non-contact measurement of respiration and heart rate from stationary and semi-stationary subjects at a distance of 0.5 to 1.5 meters. We report on the accuracy of the heart rate measurements obtained using two algorithmic approaches, as compared to a reference heart rate obtained using a pulse oximeter. Simultaneous Photoplethysmograph (PPG) and non-contact sensor recordings were recorded over fifteen minute periods for ten healthy subjects (8M/2F, ages 29.6 + or - 5.6 yrs) One algorithm is based on automated detection of individual peaks associated with each cardiac cycle; a second algorithm extracts a heart rate over a 60-second period using spectral analysis. Peaks were also extracted manually for comparison with the automated method. The peak-detection methods were less accurate than the spectral methods, but suggest the possibility of acquiring beat by beat data; the spectral algorithms measured heart rate to within + or -10% for the ten subjects chosen. Non-contact measurement of heart rate will be useful in chronic disease monitoring for conditions such as heart failure and cardiovascular disease.

Quantification of larval zebrafish motor function in multiwell plates using open-source MATLAB applications.

PubMed

Zhou, Yangzhong; Cattley, Richard T; Cario, Clinton L; Bai, Qing; Burton, Edward A

2014-07-01

This article describes a method to quantify the movements of larval zebrafish in multiwell plates, using the open-source MATLAB applications LSRtrack and LSRanalyze. The protocol comprises four stages: generation of high-quality, flatly illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB scripts; and implementation of validation controls. The method is reliable, automated and flexible, requires <1 h of hands-on work for completion once optimized and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine the following: positional preference; displacement, velocity and acceleration; and duration and frequency of movement events and rest periods. This approach is widely applicable to the analysis of spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multiwell plate format suitable for high-throughput applications.

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

Data cleaning and management protocols for linked perinatal research data: a good practice example from the Smoking MUMS (Maternal Use of Medications and Safety) Study.

PubMed

Tran, Duong Thuy; Havard, Alys; Jorm, Louisa R

2017-07-11

Data cleaning is an important quality assurance in data linkage research studies. This paper presents the data cleaning and preparation process for a large-scale cross-jurisdictional Australian study (the Smoking MUMS Study) to evaluate the utilisation and safety of smoking cessation pharmacotherapies during pregnancy. Perinatal records for all deliveries (2003-2012) in the States of New South Wales (NSW) and Western Australia were linked to State-based data collections including hospital separation, emergency department and death data (mothers and babies) and congenital defect notifications (babies in NSW) by State-based data linkage units. A national data linkage unit linked pharmaceutical dispensing data for the mothers. All linkages were probabilistic. Twenty two steps assessed the uniqueness of records and consistency of items within and across data sources, resolved discrepancies in the linkages between units, and identified women having records in both States. State-based linkages yielded a cohort of 783,471 mothers and 1,232,440 babies. Likely false positive links relating to 3703 mothers were identified. Corrections of baby's date of birth and age, and parity were made for 43,578 records while 1996 records were flagged as duplicates. Checks for the uniqueness of the matches between State and national linkages detected 3404 ID clusters, suggestive of missed links in the State linkages, and identified 1986 women who had records in both States. Analysis of content data can identify inaccurate links that cannot be detected by data linkage units that have access to personal identifiers only. Perinatal researchers are encouraged to adopt the methods presented to ensure quality and consistency among studies using linked administrative data.

A Novel Application for the Detection of an Irregular Pulse using an iPhone 4S in Patients with Atrial Fibrillation

PubMed Central

McManus, David D.; Lee, Jinseok; Maitas, Oscar; Esa, Nada; Pidikiti, Rahul; Carlucci, Alex; Harrington, Josephine; Mick, Eric; Chon, Ki H.

2012-01-01

Background Atrial fibrillation (AF) is common and associated with adverse health outcomes. Timely detection of AF can be challenging using traditional diagnostic tools. Smartphone use is increasing and may provide an inexpensive and user-friendly means to diagnose AF. Objective To test the hypothesis that a smartphone-based application could detect an irregular pulse from AF. Methods 76 adults with persistent AF were consented for participation in our study. We obtained pulsatile time series recordings before and after cardioversion using an iPhone 4S camera. A novel smartphone application conducted real-time pulse analysis using 2 statistical methods [Root Mean Square of Successive RR Differences (RMSSD/mean); Shannon Entropy (ShE)]. We examined the sensitivity, specificity, and predictive accuracy of both algorithms using the 12-lead electrocardiogram as the gold standard. Results RMSDD/mean and ShE were higher in participants in AF compared with sinus rhythm. The 2 methods were inversely related to AF in regression models adjusting for key factors including heart rate and blood pressure (β coefficients per SD-increment in RMSDD/mean and ShE were −0.20 and −0.35; p<0.001). An algorithm combining the 2 statistical methods demonstrated excellent sensitivity (0.962), specificity (0.975), and accuracy (0.968) for beat-to-beat discrimination of an irregular pulse during AF from sinus rhythm. Conclusions In a prospectively recruited cohort of 76 participants undergoing cardioversion for AF, we found that a novel algorithm analyzing signals recorded using an iPhone 4S accurately distinguished pulse recordings during AF from sinus rhythm. Data are needed to explore the performance and acceptability of smartphone-based applications for AF detection. PMID:23220686

A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation.

PubMed

McManus, David D; Lee, Jinseok; Maitas, Oscar; Esa, Nada; Pidikiti, Rahul; Carlucci, Alex; Harrington, Josephine; Mick, Eric; Chon, Ki H

2013-03-01

Atrial fibrillation (AF) is common and associated with adverse health outcomes. Timely detection of AF can be challenging using traditional diagnostic tools. Smartphone use is increasing and may provide an inexpensive and user-friendly means to diagnoseAF. To test the hypothesis that a smartphone-based application could detect an irregular pulse fromAF. Seventy-six adults with persistent AF were consented for participation in our study. We obtained pulsatile time series recordings before and after cardioversion using an iPhone 4S camera. A novel smartphone application conducted real-time pulse analysis using 2 statistical methods: root mean square of successive RR difference (RMSSD/mean) and Shannon entropy (ShE). We examined the sensitivity, specificity, and predictive accuracy of both algorithms using the 12-lead electrocardiogram as the gold standard. RMSDD/mean and ShE were higher in participants in AF than in those with sinus rhythm. The 2 methods were inversely related to AF in regression models adjusting for key factors including heart rate and blood pressure (beta coefficients per SD increment in RMSDD/mean and ShE were-0.20 and-0.35; P<.001). An algorithm combining the 2 statistical methods demonstrated excellent sensitivity (0.962), specificity (0.975), and accuracy (0.968) for beat-to-beat discrimination of an irregular pulse during AF from sinus rhythm. In a prospectively recruited cohort of 76 participants undergoing cardioversion for AF, we found that a novel algorithm analyzing signals recorded using an iPhone 4S accurately distinguished pulse recordings during AF from sinus rhythm. Data are needed to explore the performance and acceptability of smartphone-based applications for AF detection. Copyright © 2013 Heart Rhythm Society. All rights reserved.

Automatic evaluation of intrapartum fetal heart rate recordings: a comprehensive analysis of useful features.

PubMed

Chudáček, V; Spilka, J; Janků, P; Koucký, M; Lhotská, L; Huptych, M

2011-08-01

Cardiotocography is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO), used routinely since the 1960s by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. We assess the features on a large data set (552 records) and unlike in other published papers we use three-class expert evaluation of the records instead of the pH values. We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. The number of accelerations and decelerations, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.

The Analysis Performance Method Naive Bayes Andssvm Determine Pattern Groups of Disease

NASA Astrophysics Data System (ADS)

Sitanggang, Rianto; Tulus; Situmorang, Zakarias

2017-12-01

Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naïve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naïve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy

Use of near-infrared video recording system for the detection of freeze damaged citrus leaves

NASA Technical Reports Server (NTRS)

Escobar, D. E.; Bowen, R. L.; Gausman, H. W.; Cooper, G. (Principal Investigator)

1982-01-01

A video recording system with a visible light blocking filter to give sensitivity in the 0.78 m to 1.1 m waveband detected freeze-damaged citrus leaves rapidly. With this technique, the time to analyze images can be decreased from about one day for conventional photography to less than one hour for video recording.

Algorithm for identifying and separating beats from arterial pulse records

PubMed Central

Treo, Ernesto F; Herrera, Myriam C; Valentinuzzi, Max E

2005-01-01

Background This project was designed as an epidemiological aid-selecting tool for a small country health center with the general objective of screening out possible coronary patients. Peripheral artery function can be non-invasively evaluated by impedance plethysmography. Changes in these vessels appear as good predictors of future coronary behavior. Impedance plethysmography detects volume variations after simple occlusive maneuvers that may show indicative modifications in arterial/venous responses. Averaging of a series of pulses is needed and this, in turn, requires proper determination of the beginning and end of each beat. Thus, the objective here is to describe an algorithm to identify and separate out beats from a plethysmographic record. A secondary objective was to compare the output given by human operators against the algorithm. Methods The identification algorithm detected the beat's onset and end on the basis of the maximum rising phase, the choice of possible ventricular systolic starting points considering cardiac frequency, and the adjustment of some tolerance values to optimize the behavior. Out of 800 patients in the study, 40 occlusive records (supradiastolic- subsystolic) were randomly selected without any preliminary diagnosis. Radial impedance plethysmographic pulse and standard ECG were recorded digitizing and storing the data. Cardiac frequency was estimated with the Power Density Function and, thereafter, the signal was derived twice, followed by binarization of the first derivative and rectification of the second derivative. The product of the two latter results led to a weighing signal from which the cycles' onsets and ends were established. Weighed and frequency filters are needed along with the pre-establishment of their respective tolerances. Out of the 40 records, 30 seconds strands were randomly chosen to be analyzed by the algorithm and by two operators. Sensitivity and accuracy were calculated by means of the true/false and positive/negative criteria. Synchronization ability was measured through the coefficient of variation and the median value of correlation for each patient. These parameters were assessed by means of Friedman's ANOVA and Kendall Concordance test. Results Sensitivity was 97% and 91% for the two operators, respectively, while accuracy was cero for both of them. The synchronism variability analysis was significant (p < 0.01) for the two statistics, showing that the algorithm produced the best result. Conclusion The proposed algorithm showed good performance as expressed by its high sensitivity. The correlation analysis demonstrated that, from the synchronism point of view, the algorithm performed the best detection. Patients with marked arrhythmic processes are not good candidates for this kind of analysis. At most, they would be singled out by the algorithm and, thereafter, to be checked by an operator. PMID:16095532

Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.

PubMed

Patil, Ajeetkumar; Bhat, Sujatha; Pai, Keerthilatha M; Rai, Lavanya; Kartha, V B; Chidangil, Santhosh

2015-09-08

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper. In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Seismic waveform classification using deep learning

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.

2017-12-01

MyShake is a global smartphone seismic network that harnesses the power of crowdsourcing. It has an Artificial Neural Network (ANN) algorithm running on the phone to distinguish earthquake motion from human activities recorded by the accelerometer on board. Once the ANN detects earthquake-like motion, it sends a 5-min chunk of acceleration data back to the server for further analysis. The time-series data collected contains both earthquake data and human activity data that the ANN confused. In this presentation, we will show the Convolutional Neural Network (CNN) we built under the umbrella of supervised learning to find out the earthquake waveform. The waveforms of the recorded motion could treat easily as images, and by taking the advantage of the power of CNN processing the images, we achieved very high successful rate to select the earthquake waveforms out. Since there are many non-earthquake waveforms than the earthquake waveforms, we also built an anomaly detection algorithm using the CNN. Both these two methods can be easily extended to other waveform classification problems.

Comparison of ambulatory and polysomnographic recording of jaw muscle activity during sleep in normal subjects.

PubMed

Yamaguchi, T; Abe, S; Rompré, P H; Manzini, C; Lavigne, G J

2012-01-01

Clinicians and investigators need a simple and reliable recording device to diagnose or monitor sleep bruxism (SB). The aim of this study was to compare recordings made with an ambulatory electromyographic telemetry recorder (TEL-EMG) with those made with standard sleep laboratory polysomnography with synchronised audio-visual recording (PSG-AV). Eight volunteer subjects without current history of tooth grinding spent one night in a sleep laboratory. Simultaneous bilateral masseter EMG recordings were made with a TEL-EMG and standard PSG. All types of oromotor activity and rhythmic masseter muscle activity (RMMA), typical of SB, were independently scored by two individuals. Correlation and intra-class coefficient (ICC) were estimated for scores on each system. The TEL-EMG was highly sensitive to detect RMMA (0·988), but with low positive predictive value (0·231) because of a high rate of oromotor activity detection (e.g. swallowing and scratching). Almost 72% of false-positive oromotor activity scored with the TEL-EMG occurred during the transient wake period of sleep. A non-significant correlation between recording systems was found (r = 0·49). Because of the high frequency of wake periods during sleep, ICC was low (0·47), and the removal of the influence of wake periods improved the detection reliability of the TEL-EMG (ICC = 0·88). The TEL-EMG is sensitive to detect RMMA in normal subjects. However, it obtained a high rate of false-positive detections because of the presence of frequent oromotor activities and transient wake periods of sleep. New algorithms are needed to improve the validity of TEL-EMG recordings. © 2011 Blackwell Publishing Ltd.

Determination of baseline periods of record for selected streamflow-gaging stations in and near Oklahoma for use in modeling applications

USGS Publications Warehouse

Esralew, Rachel A.

2010-01-01

Use of historical streamflow data from a least-altered period of record can be used in calibration of various modeling applications that are used to characterize least-altered flow and predict the effects of proposed streamflow alteration. This information can be used to enhance water-resources planning. A baseline period of record was determined for selected streamflow-gaging stations that can be used as a calibration dataset for modeling applications. The baseline period of record was defined as a period that is least-altered by anthropogenic activity and has sufficient streamflow record length to represent extreme climate variability. Streamflow data from 171 stations in and near Oklahoma with a minimum of 10 complete water years of daily streamflow record through water year 2007 and drainage areas that were less than 2,500 square miles were considered for use in the baseline period analysis. The first step to determine the least-altered period of record was to evaluate station information by using previous publications, historical station record notes, and information gathered from oral and written communication with hydrographers familiar with selected stations. The second step was to indentify stations that had substantial effects from upstream regulation by evaluating the location and extent of dams in the drainage basin. The third step was (a) the analysis of annual hydrographs and included visual hydrograph analysis for selected stations with 20 or more years of streamflow record, (b) analysis of covariance of double-mass curves, and (c) Kendall's tau trend analysis to detect statistically significant trends in base flow, runoff, total flow, and base-flow index related to anthropogenic activity for selected stations with 15 or more years of streamflow record. A preliminary least-altered period of record for each stream was identified by removing the period of streamflow record when streams were substantially affected by anthropogenic activity. After streamflow record was removed from designation as a least-altered period, stations that did not have at least 10 years of remaining continuous streamflow record were considered to have an insufficient baseline period for modeling applications. An optimum minimum period of record was determined for each of the least-altered periods for each station to ensure a sufficient streamflow record length to provide a representative sample of annual climate variability. An optimum minimum period of 10 years or more was evaluated by analyzing the variability of annual precipitation for selected 5-, 10-, 15-, 25-, and 35-year periods for each of 20 climate divisions that contained stations used in the baseline period analysis. The distribution of annual precipitation was compared for each consecutive overlapping 5-year period to the period 1925-2007 by using a Wilcoxon rank-sum test. The least-altered period of record for stations was also compared to the period 1925-2007 by using a Wilcoxon rank-sum test. The results of this analysis were used to determine how many years of annual precipitation data were needed for the selected period to be statistically similar to the distribution of annual precipitation data for a long-term period, 1925-2007. Minimum optimum periods ranged from 10 to 35 years and varied by climate division. A final baseline period was determined for 111 stations that had a baseline period of at least 10 years of continuous streamflow record after the record-elimination process. A suitable baseline period of record for use in modeling applications could not be identified for 58 of the initial 171 stations because of substantial anthropogenic alteration of the stream or drainage basin and for 2 stations because the least-altered period of record was not representative of annual climate variability. The baseline period for each station was rated ?excellent?, ?good?, ?fair?, ?poor?, or ?no baseline period.? This rating was based on a qualitative evaluation of t

Development of Software for Automatic Analysis of Intervention in the Field of Homeopathy.

PubMed

Jain, Rajesh Kumar; Goyal, Shagun; Bhat, Sushma N; Rao, Srinath; Sakthidharan, Vivek; Kumar, Prasanna; Sajan, Kannanaikal Rappayi; Jindal, Sameer Kumar; Jindal, Ghanshyam D

2018-05-01

To study the effect of homeopathic medicines (in higher potencies) in normal subjects, Peripheral Pulse Analyzer (PPA) has been used to record physiologic variability parameters before and after administration of the medicine/placebo in 210 normal subjects. Data have been acquired in seven rounds; placebo was administered in rounds 1 and 2 and medicine in potencies 6, 30, 200, 1 M, and 10 M was administered in rounds 3 to 7, respectively. Five different medicines in the said potencies were given to a group of around 40 subjects each. Although processing of data required human intervention, a software application has been developed to analyze the processed data and detect the response to eliminate the undue delay as well as human bias in subjective analysis. This utility named Automatic Analysis of Intervention in the Field of Homeopathy is run on the processed PPA data and the outcome has been compared with the manual analysis. The application software uses adaptive threshold based on statistics for detecting responses in contrast to fixed threshold used in manual analysis. The automatic analysis has detected 12.96% higher responses than subjective analysis. Higher response rates have been manually verified to be true positive. This indicates robustness of the application software. The automatic analysis software was run on another set of pulse harmonic parameters derived from the same data set to study cardiovascular susceptibility and 385 responses were detected in contrast to 272 of variability parameters. It was observed that 65% of the subjects, eliciting response, were common. This not only validates the software utility for giving consistent yield but also reveals the certainty of the response. This development may lead to electronic proving of homeopathic medicines (e-proving).

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

PubMed

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

2018-05-11

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

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

Detection and analysis of microseismic events using a Matched Filtering Algorithm (MFA)

NASA Astrophysics Data System (ADS)

Caffagni, Enrico; Eaton, David W.; Jones, Joshua P.; van der Baan, Mirko

2016-07-01

A new Matched Filtering Algorithm (MFA) is proposed for detecting and analysing microseismic events recorded by downhole monitoring of hydraulic fracturing. This method requires a set of well-located template (`parent') events, which are obtained using conventional microseismic processing and selected on the basis of high signal-to-noise (S/N) ratio and representative spatial distribution of the recorded microseismicity. Detection and extraction of `child' events are based on stacked, multichannel cross-correlation of the continuous waveform data, using the parent events as reference signals. The location of a child event relative to its parent is determined using an automated process, by rotation of the multicomponent waveforms into the ray-centred co-ordinates of the parent and maximizing the energy of the stacked amplitude envelope within a search volume around the parent's hypocentre. After correction for geometrical spreading and attenuation, the relative magnitude of the child event is obtained automatically using the ratio of stacked envelope peak with respect to its parent. Since only a small number of parent events require interactive analysis such as picking P- and S-wave arrivals, the MFA approach offers the potential for significant reduction in effort for downhole microseismic processing. Our algorithm also facilitates the analysis of single-phase child events, that is, microseismic events for which only one of the S- or P-wave arrivals is evident due to unfavourable S/N conditions. A real-data example using microseismic monitoring data from four stages of an open-hole slickwater hydraulic fracture treatment in western Canada demonstrates that a sparse set of parents (in this case, 4.6 per cent of the originally located events) yields a significant (more than fourfold increase) in the number of located events compared with the original catalogue. Moreover, analysis of the new MFA catalogue suggests that this approach leads to more robust interpretation of the induced microseismicity and novel insights into dynamic rupture processes based on the average temporal (foreshock-aftershock) relationship of child events to parents.

Modelling spatiotemporal change using multidimensional arrays Meng

NASA Astrophysics Data System (ADS)

Lu, Meng; Appel, Marius; Pebesma, Edzer

2017-04-01

The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical modelling, and extreme event detection methods to model spatiotemporal change. We show how array operations can facilitate expressing these methods, and how the open-source array data management and analytics software SciDB and R can be used to scale the process and make it easily reproducible.

Site-occupancy distribution modeling to correct population-trend estimates derived from opportunistic observations

USGS Publications Warehouse

Kery, M.; Royle, J. Andrew; Schmid, Hans; Schaub, M.; Volet, B.; Hafliger, G.; Zbinden, N.

2010-01-01

Species' assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection-nondetection records) are generated. Within-season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectablity means correcting for observation effort. Second, site-occupancy models are applied directly to the detection-history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site-occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen-science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis. ) and Sparrowhawk (Accipiter nisus. ) and the scarce Rock Thrush (Monticola saxatilis. ) and Wallcreeper (Tichodroma muraria. ). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions. ?? 2010 Society for Conservation Biology.

Endoparasites in the feces of arctic foxes in a terrestrial ecosystem in Canada

PubMed Central

Elmore, Stacey A.; Lalonde, Laura F.; Samelius, Gustaf; Alisauskas, Ray T.; Gajadhar, Alvin A.; Jenkins, Emily J.

2013-01-01

The parasites of arctic foxes in the central Canadian Arctic have not been well described. Canada’s central Arctic is undergoing dramatic environmental change, which is predicted to cause shifts in parasite and wildlife species distributions, and trophic interactions, requiring that baselines be established to monitor future alterations. This study used conventional, immunological, and molecular fecal analysis techniques to survey the current gastrointestinal endoparasite fauna currently present in arctic foxes in central Nunavut, Canada. Ninety-five arctic fox fecal samples were collected from the terrestrial Karrak Lake ecosystem within the Queen Maud Gulf Migratory Bird Sanctuary. Samples were examined by fecal flotation to detect helminths and protozoa, immunofluorescent assay (IFA) to detect Cryptosporidium and Giardia, and quantitative PCR with melt-curve analysis (qPCR-MCA) to detect coccidia. Positive qPCR-MCA products were sequenced and analyzed phylogenetically. Arctic foxes from Karrak Lake were routinely shedding eggs from Toxascaris leonina (63%). Taeniid (15%), Capillarid (1%), and hookworm eggs (2%), Sarcocystis sp. sporocysts 3%), and Eimeria sp. (6%), and Cystoisospora sp. (5%) oocysts were present at a lower prevalence on fecal flotation. Cryptosporidium sp. (9%) and Giardia sp. (16%) were detected by IFA. PCR analysis detected Sarcocystis (15%), Cystoisospora (5%), Eimeria sp., and either Neospora sp. or Hammondia sp. (1%). Through molecular techniques and phylogenetic analysis, we identified two distinct lineages of Sarcocystis sp. present in arctic foxes, which probably derived from cervid and avian intermediate hosts. Additionally, we detected previously undescribed genotypes of Cystoisospora. Our survey of gastrointestinal endoparasites in arctic foxes from the central Canadian Arctic provides a unique record against which future comparisons can be made. PMID:24533320

Detection of Drug Effects on Brain Activity using EEG-P300 with Similar Stimuli

NASA Astrophysics Data System (ADS)

Turnip, Arjon; Dwi Esti, K.; Faizal Amri, M.; Simbolon, Artha I.; Agung Suhendra, M.; IsKandar, Shelly; Wirakusumah, Firman F.

2017-07-01

Drug addiction poses a serious problem to our species. The worry that our significant family might be involved in drug use and are concerned to know how to detect drug use. Examinations of thirty taped EEG recordings were performed. The subjects consist of three group: addictive, methadone treatment (rehabilitation), and control (normal) which 10 subjects for each group. Statistical analysis was performed for the relative frequency of wave bands. The higher average amplitude is obtained from the addiction subjects. In the comparison with the signals source, channels P3 provide slightly higher average amplitude than other channels for all of subjects.

Kinematic Features of Jaw and Lips Distinguish Symptomatic From Presymptomatic Stages of Bulbar Decline in Amyotrophic Lateral Sclerosis.

PubMed

Bandini, Andrea; Green, Jordan R; Wang, Jun; Campbell, Thomas F; Zinman, Lorne; Yunusova, Yana

2018-05-17

The goals of this study were to (a) classify speech movements of patients with amyotrophic lateral sclerosis (ALS) in presymptomatic and symptomatic phases of bulbar function decline relying solely on kinematic features of lips and jaw and (b) identify the most important measures that detect the transition between early and late bulbar changes. One hundred ninety-two recordings obtained from 64 patients with ALS were considered for the analysis. Feature selection and classification algorithms were used to analyze lip and jaw movements recorded with Optotrak Certus (Northern Digital Inc.) during a sentence task. A feature set, which included 35 measures of movement range, velocity, acceleration, jerk, and area measures of lips and jaw, was used to classify sessions according to the speaking rate into presymptomatic (> 160 words per minute) and symptomatic (< 160 words per minute) groups. Presymptomatic and symptomatic phases of bulbar decline were distinguished with high accuracy (87%), relying only on lip and jaw movements. The best features that allowed detecting the differences between early and later bulbar stages included cumulative path of lower lip and jaw, peak values of velocity, acceleration, and jerk of lower lip and jaw. The results established a relationship between facial kinematics and bulbar function decline in ALS. Considering that facial movements can be recorded by means of novel inexpensive and easy-to-use, video-based methods, this work supports the development of an automatic system for facial movement analysis to help clinicians in tracking the disease progression in ALS.

Functional principal component analysis of glomerular filtration rate curves after kidney transplant.

PubMed

Dong, Jianghu J; Wang, Liangliang; Gill, Jagbir; Cao, Jiguo

2017-01-01

This article is motivated by some longitudinal clinical data of kidney transplant recipients, where kidney function progression is recorded as the estimated glomerular filtration rates at multiple time points post kidney transplantation. We propose to use the functional principal component analysis method to explore the major source of variations of glomerular filtration rate curves. We find that the estimated functional principal component scores can be used to cluster glomerular filtration rate curves. Ordering functional principal component scores can detect abnormal glomerular filtration rate curves. Finally, functional principal component analysis can effectively estimate missing glomerular filtration rate values and predict future glomerular filtration rate values.

Photographic Analysis Technique for Assessing External Tank Foam Loss Events

NASA Technical Reports Server (NTRS)

Rieckhoff, T. J.; Covan, M.; OFarrell, J. M.

2001-01-01

A video camera and recorder were placed inside the solid rocket booster forward skirt in order to view foam loss events over an area on the external tank (ET) intertank surface. In this Technical Memorandum, a method of processing video images to allow rapid detection of permanent changes indicative of foam loss events on the ET surface was defined and applied to accurately count, categorize, and locate such events.

Liquid Chromatographic Analysis of Hydraulic Fluids.

DTIC Science & Technology

1979-11-01

chemical mixtures of a petroleum- or nonpetroleum-base stock component formulated with various additives which may be present in trace amounts or...absorb UV radiation near the monitoring wavelength may swamp the detector signal and therefore should be avoided in 1JV detection. The recorder trace of...Also, organic phosphites , thiophosphates, and sulfides are used to inhibit oxidative catalysis by metal ions. The oxidation inhibitor in 6083D-0 is BPC

A PC-based computer package for automatic detection and location of earthquakes: Application to a seismic network in eastern sicity (Italy)

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio; Giampiccolo, Elisabetta; Gresta, Stefano

Few automated data acquisition and processing systems operate on mainframes, some run on UNIX-based workstations and others on personal computers, equipped with either DOS/WINDOWS or UNIX-derived operating systems. Several large and complex software packages for automatic and interactive analysis of seismic data have been developed in recent years (mainly for UNIX-based systems). Some of these programs use a variety of artificial intelligence techniques. The first operational version of a new software package, named PC-Seism, for analyzing seismic data from a local network is presented in Patanè et al. (1999). This package, composed of three separate modules, provides an example of a new generation of visual object-oriented programs for interactive and automatic seismic data-processing running on a personal computer. In this work, we mainly discuss the automatic procedures implemented in the ASDP (Automatic Seismic Data-Processing) module and real time application to data acquired by a seismic network running in eastern Sicily. This software uses a multi-algorithm approach and a new procedure MSA (multi-station-analysis) for signal detection, phase grouping and event identification and location. It is designed for an efficient and accurate processing of local earthquake records provided by single-site and array stations. Results from ASDP processing of two different data sets recorded at Mt. Etna volcano by a regional network are analyzed to evaluate its performance. By comparing the ASDP pickings with those revised manually, the detection and subsequently the location capabilities of this software are assessed. The first data set is composed of 330 local earthquakes recorded in the Mt. Etna erea during 1997 by the telemetry analog seismic network. The second data set comprises about 970 automatic locations of more than 2600 local events recorded at Mt. Etna during the last eruption (July 2001) at the present network. For the former data set, a comparison of the automatic results with the manual picks indicates that the ASDP module can accurately pick 80% of the P-waves and 65% of S-waves. The on-line application on the latter data set shows that automatic locations are affected by larger errors, due to the preliminary setting of the configuration parameters in the program. However, both automatic ASDP and manual hypocenter locations are comparable within the estimated error bounds. New improvements of the PC-Seism software for on-line analysis are also discussed.

Continuous, Large-Scale Processing of Seismic Archives for High-Resolution Monitoring of Seismic Activity and Seismogenic Properties

NASA Astrophysics Data System (ADS)

Waldhauser, F.; Schaff, D. P.

2012-12-01

Archives of digital seismic data recorded by seismometer networks around the world have grown tremendously over the last several decades helped by the deployment of seismic stations and their continued operation within the framework of monitoring earthquake activity and verification of the Nuclear Test-Ban Treaty. We show results from our continuing effort in developing efficient waveform cross-correlation and double-difference analysis methods for the large-scale processing of regional and global seismic archives to improve existing earthquake parameter estimates, detect seismic events with magnitudes below current detection thresholds, and improve real-time monitoring procedures. We demonstrate the performance of these algorithms as applied to the 28-year long seismic archive of the Northern California Seismic Network. The tools enable the computation of periodic updates of a high-resolution earthquake catalog of currently over 500,000 earthquakes using simultaneous double-difference inversions, achieving up to three orders of magnitude resolution improvement over existing hypocenter locations. This catalog, together with associated metadata, form the underlying relational database for a real-time double-difference scheme, DDRT, which rapidly computes high-precision correlation times and hypocenter locations of new events with respect to the background archive (http://ddrt.ldeo.columbia.edu). The DDRT system facilitates near-real-time seismicity analysis, including the ability to search at an unprecedented resolution for spatio-temporal changes in seismogenic properties. In areas with continuously recording stations, we show that a detector built around a scaled cross-correlation function can lower the detection threshold by one magnitude unit compared to the STA/LTA based detector employed at the network. This leads to increased event density, which in turn pushes the resolution capability of our location algorithms. On a global scale, we are currently building the computational framework for double-difference processing the combined parametric and waveform archives of the ISC, NEIC, and IRIS with over three million recorded earthquakes worldwide. Since our methods are scalable and run on inexpensive Beowulf clusters, periodic re-analysis of such archives may thus become a routine procedure to continuously improve resolution in existing global earthquake catalogs. Results from subduction zones and aftershock sequences of recent great earthquakes demonstrate the considerable social and economic impact that high-resolution images of active faults, when available in real-time, will have in the prompt evaluation and mitigation of seismic hazards. These results also highlight the need for consistent long-term seismic monitoring and archiving of records.

ECG signal analysis through hidden Markov models.

PubMed

Andreão, Rodrigo V; Dorizzi, Bernadette; Boudy, Jérôme

2006-08-01

This paper presents an original hidden Markov model (HMM) approach for online beat segmentation and classification of electrocardiograms. The HMM framework has been visited because of its ability of beat detection, segmentation and classification, highly suitable to the electrocardiogram (ECG) problem. Our approach addresses a large panel of topics some of them never studied before in other HMM related works: waveforms modeling, multichannel beat segmentation and classification, and unsupervised adaptation to the patient's ECG. The performance was evaluated on the two-channel QT database in terms of waveform segmentation precision, beat detection and classification. Our waveform segmentation results compare favorably to other systems in the literature. We also obtained high beat detection performance with sensitivity of 99.79% and a positive predictivity of 99.96%, using a test set of 59 recordings. Moreover, premature ventricular contraction beats were detected using an original classification strategy. The results obtained validate our approach for real world application.

Fall prevention walker during rehabilitation

NASA Astrophysics Data System (ADS)

Tee, Kian Sek; E, Chun Zhi; Saim, Hashim; Zakaria, Wan Nurshazwani Wan; Khialdin, Safinaz Binti Mohd; Isa, Hazlita; Awad, M. I.; Soon, Chin Fhong

2017-09-01

This paper proposes on the design of a walker for the prevention of falling among elderlies or patients during rehabilitation whenever they use a walker to assist them. Fall happens due to impaired balance or gait problem. The assistive device is designed by applying stability concept and an accelerometric fall detection system is included. The accelerometric fall detection system acts as an alerting device that acquires body accelerometric data and detect fall. Recorded accelerometric data could be useful for further assessment. Structural strength of the walker was verified via iterations of simulation using finite element analysis, before being fabricated. Experiments were conducted to identify the fall patterns using accelerometric data. The design process and detection of fall pattern demonstrates the design of a walker that could support the user without fail and alerts the helper, thus salvaging the users from injuries due to fall and unattended situation.

Presence and seasonal variation of deep diving foraging odontocetes around Kauai, Hawaii using remote autonomous acoustic recorders.

PubMed

Au, Whitlow W L; Giorli, Giacomo; Chen, Jessica; Copeland, Adrienne; Lammers, Marc O; Richlen, Michael; Jarvis, Susan; Morrissey, Ronald; Moretti, David

2014-01-01

Ecological acoustic recorders (EARs) were moored off the bottom in relatively deep depths (609-710 m) at five locations around the island of Kauai. Initially, the EARs had an analog-to-digital sample rate of 64 kHz with 30-s recordings every 5 min. After the second deployment the sampling rate was increased to 80 kHz in order to better record beaked whale biosonar signals. The results of the 80 kHz recording are discussed in this manuscript and are the results of three deployments over a year's period (January 2010 to January 2011). Five categories of the biosonar signal detection of deep diving odontocetes were created, short-finned pilot whales, sperm whales, beaked whales, Risso's dolphins, and unknown dolphins. During any given day, at least one species of these deep diving odontocetes were detected. On many days, several species were detected. The biosonar signals of short-finned pilot whales were detected the most often with approximately 30% of all the signals, followed by beaked and sperm whales approximately 22% and 21% of all clicks, respectively. The seasonal patterns were not very strong except in the SW location with distinct peak in detection during the months of April-June 2010 period.

Physical principles of neutron-gamma materials monitoring

NASA Astrophysics Data System (ADS)

Pekarskii, G. Sh.

1986-03-01

The physical principles of secondary radiation methods in nondestructive testing are discussed. Among the techniques considered are: neutron activation analysis (NAA); the induced-radiation method; and quasialbedo recording of secondary gamma-radiation. Emphasis is given to the neutron-gamma method which consists of exposing test material to a neutron flux and recording the secondary gamma-radiation by means of a spectrometer. The limitations of the method in detecting local inhomogeneous defects (filled pores cracks, and inclusions) in metal layers and multicomponents materials are described, and some advantages of the method over NAA are discussed. Formulas are derived for estimating the optimum density of the gamma-ray flux which is received by the detector.

Physical principles of neutron-gamma materials monitoring

NASA Astrophysics Data System (ADS)

Pekarskii, G. Sh.

1985-07-01

The physical principles of secondary radiation methods in nondestructive testing are discussed. Among the techniques considered are: neutron activation analysis (NAA); the induced-radiation method; and quasialbedo recording of secondary gamma-radiation. Emphasis is given to the neutron-gamma method which consists of exposing test material to a neutron flux and recording the secondary gamma-radiation by means of a spectrometer. The limitations of the method in detecting local inhomogeneous defects (filled pores cracks, and inclusions) in metal layers and multicomponents materials are described, and some advantages of the method over NAA are discussed. Formulas are derived for estimating the optimum density of the gamma-ray flux which is received by the detector.

Detection of Hepatozoon felis in Ticks Collected from Free-Ranging Amur Tigers ( Panthera tigris altaica), Russian Far East, 2002-12.

PubMed

Thomas, Lindsay H; Seryodkin, Ivan V; Goodrich, John M; Miquelle, Dale G; Birtles, Richard J; Lewis, John C M

2016-07-01

We collected 69 ticks from nine, free-ranging Amur tigers ( Panthera tigris altaica) between 2002 and 2011 and investigated them for tick-borne pathogens. DNA was extracted using alkaline digestion and PCR was performed to detect apicomplexan organisms. Partial 18S rDNA amplification products were obtained from 14 ticks from four tigers, of which 13 yielded unambiguous nucleotide sequence data. Comparative sequence analysis revealed all 13 partial 18S rDNA sequences were most similar to those belonging to strains of Hepatozoon felis (>564/572 base-pair identity, >99% sequence similarity). Although this tick-borne protozoon pathogen has been detected in wild felids from many parts of the world, this is the first record from the Russian Far East.

Path length entropy analysis of diastolic heart sounds.

PubMed

Griffel, Benjamin; Zia, Mohammad K; Fridman, Vladamir; Saponieri, Cesare; Semmlow, John L

2013-09-01

Early detection of coronary artery disease (CAD) using the acoustic approach, a noninvasive and cost-effective method, would greatly improve the outcome of CAD patients. To detect CAD, we analyze diastolic sounds for possible CAD murmurs. We observed diastolic sounds to exhibit 1/f structure and developed a new method, path length entropy (PLE) and a scaled version (SPLE), to characterize this structure to improve CAD detection. We compare SPLE results to Hurst exponent, Sample entropy and Multiscale entropy for distinguishing between normal and CAD patients. SPLE achieved a sensitivity-specificity of 80%-81%, the best of the tested methods. However, PLE and SPLE are not sufficient to prove nonlinearity, and evaluation using surrogate data suggests that our cardiovascular sound recordings do not contain significant nonlinear properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

Path Length Entropy Analysis of Diastolic Heart Sounds

PubMed Central

Griffel, B.; Zia, M. K.; Fridman, V.; Saponieri, C.; Semmlow, J. L.

2013-01-01

Early detection of coronary artery disease (CAD) using the acoustic approach, a noninvasive and cost-effective method, would greatly improve the outcome of CAD patients. To detect CAD, we analyze diastolic sounds for possible CAD murmurs. We observed diastolic sounds to exhibit 1/f structure and developed a new method, path length entropy (PLE) and a scaled version (SPLE), to characterize this structure to improve CAD detection. We compare SPLE results to Hurst exponent, Sample entropy and Multi-scale entropy for distinguishing between normal and CAD patients. SPLE achieved a sensitivity-specificity of 80%–81%, the best of the tested methods. However, PLE and SPLE are not sufficient to prove nonlinearity, and evaluation using surrogate data suggests that our cardiovascular sound recordings do not contain significant nonlinear properties. PMID:23930808

Cardiovascular and respiratory dynamics during normal and pathological sleep

NASA Astrophysics Data System (ADS)

Penzel, Thomas; Wessel, Niels; Riedl, Maik; Kantelhardt, Jan W.; Rostig, Sven; Glos, Martin; Suhrbier, Alexander; Malberg, Hagen; Fietze, Ingo

2007-03-01

Sleep is an active and regulated process with restorative functions for physical and mental conditions. Based on recordings of brain waves and the analysis of characteristic patterns and waveforms it is possible to distinguish wakefulness and five sleep stages. Sleep and the sleep stages modulate autonomous nervous system functions such as body temperature, respiration, blood pressure, and heart rate. These functions consist of a sympathetic tone usually related to activation and to parasympathetic (or vagal) tone usually related to inhibition. Methods of statistical physics are used to analyze heart rate and respiration to detect changes of the autonomous nervous system during sleep. Detrended fluctuation analysis and synchronization analysis and their applications to heart rate and respiration during sleep in healthy subjects and patients with sleep disorders are presented. The observed changes can be used to distinguish sleep stages in healthy subjects as well as to differentiate normal and disturbed sleep on the basis of heart rate and respiration recordings without direct recording of brain waves. Of special interest are the cardiovascular consequences of disturbed sleep because they present a risk factor for cardiovascular disorders such as arterial hypertension, cardiac ischemia, sudden cardiac death, and stroke. New derived variables can help to find indicators for these health risks.

Automatic detection of confusion in elderly users of a web-based health instruction video.

PubMed

Postma-Nilsenová, Marie; Postma, Eric; Tates, Kiek

2015-06-01

Because of cognitive limitations and lower health literacy, many elderly patients have difficulty understanding verbal medical instructions. Automatic detection of facial movements provides a nonintrusive basis for building technological tools supporting confusion detection in healthcare delivery applications on the Internet. Twenty-four elderly participants (70-90 years old) were recorded while watching Web-based health instruction videos involving easy and complex medical terminology. Relevant fragments of the participants' facial expressions were rated by 40 medical students for perceived level of confusion and analyzed with automatic software for facial movement recognition. A computer classification of the automatically detected facial features performed more accurately and with a higher sensitivity than the human observers (automatic detection and classification, 64% accuracy, 0.64 sensitivity; human observers, 41% accuracy, 0.43 sensitivity). A drill-down analysis of cues to confusion indicated the importance of the eye and eyebrow region. Confusion caused by misunderstanding of medical terminology is signaled by facial cues that can be automatically detected with currently available facial expression detection technology. The findings are relevant for the development of Web-based services for healthcare consumers.

Serial 3-dimensional computed tomography and a novel method of volumetric analysis for the evaluation of the osteo-odonto-keratoprosthesis.

PubMed

Sipkova, Zuzana; Lam, Fook Chang; Francis, Ian; Herold, Jim; Liu, Christopher

2013-04-01

To assess the use of serial computed tomography (CT) in the detection of osteo-odonto-lamina resorption in osteo-odonto-keratoprosthesis (OOKP) and to investigate the use of new volumetric software, Advanced Lung Analysis software (3D-ALA; GE Healthcare), for detecting changes in OOKP laminar volume. A retrospective assessment of the radiological databases and hospital records was performed for 22 OOKP patients treated at the National OOKP referral center in Brighton, United Kingdom. Three-dimensional surface reconstructions of the OOKP laminae were performed using stored CT data. For the 2-dimensional linear analysis, the linear dimensions of the reconstructed laminae were measured, compared with original measurements taken at the time of surgery, and then assigned a CT grade based on a predetermined resorption grading scale. The volumetric analysis involved calculating the laminar volumes using 3D-ALA. The effectiveness of 2-dimensional linear analysis, volumetric analysis, and clinical examination in detecting laminar resorption was compared. The mean change in laminar volume between the first and second scans was -6.67% (range, +10.13% to -24.86%). CT grades assigned to patients based on laminar dimension measurements remained the same, despite significant changes in laminar volumes. Clinical examination failed to identify 60% of patients who were found to have resorption on volumetric analysis. Currently, the detection of laminar resorption relies on clinical examination and the measurement of laminar dimensions on the 2- and 3-dimensional radiological images. Laminar volume measurement is a useful new addition to the armamentarium. It provides an objective tool that allows for a precise and reproducible assessment of laminar resorption.

Disease Risk Analysis and Post-Release Health Surveillance for a Reintroduction Programme: the Pool Frog Pelophylax lessonae.

PubMed

Sainsbury, A W; Yu-Mei, R; Ågren, E; Vaughan-Higgins, R J; Mcgill, I S; Molenaar, F; Peniche, G; Foster, J

2017-10-01

There are risks from disease in undertaking wild animal reintroduction programmes. Methods of disease risk analysis have been advocated to assess and mitigate these risks, and post-release health and disease surveillance can be used to assess the effectiveness of the disease risk analysis, but results for a reintroduction programme have not to date been recorded. We carried out a disease risk analysis for the reintroduction of pool frogs (Pelophylax lessonae) to England, using information gained from the literature and from diagnostic testing of Swedish pool frogs and native amphibians. Ranavirus and Batrachochytrium dendrobatidis were considered high-risk disease threats for pool frogs at the destination site. Quarantine was used to manage risks from disease due to these two agents at the reintroduction site: the quarantine barrier surrounded the reintroduced pool frogs. Post-release health surveillance was carried out through regular health examinations of amphibians in the field at the reintroduction site and collection and examination of dead amphibians. No significant health or disease problems were detected, but the detection rate of dead amphibians was very low. Methods to detect a higher proportion of dead reintroduced animals and closely related species are required to better assess the effects of reintroduction on health and disease. © 2016 Blackwell Verlag GmbH.

Computerized wheeze detection in young infants: comparison of signals from tracheal and chest wall sensors.

PubMed

Puder, Lia C; Wilitzki, Silke; Bührer, Christoph; Fischer, Hendrik S; Schmalisch, Gerd

2016-12-01

Computerized wheeze detection is an established method for objective assessment of respiratory sounds. In infants, this method has been used to detect subclinical airway obstruction and to monitor treatment effects. The optimal location for the acoustic sensors, however, is unknown. The aim of this study was to evaluate the quality of respiratory sound recordings in young infants, and to determine whether the position of the sensor affected computerized wheeze detection. Respiratory sounds were recorded over the left lateral chest wall and the trachea in 112 sleeping infants (median postmenstrual age: 49 weeks) on 129 test occasions using an automatic wheeze detection device (PulmoTrack ® ). Each recording lasted 10 min and the recordings were stored. A trained clinician retrospectively evaluated the recordings to determine sound quality and disturbances. The wheeze rates of all undisturbed tracheal and chest wall signals were compared using Bland-Altman plots. Comparison of wheeze rates measured over the trachea and the chest wall indicated strong correlation (r  ⩾  0.93, p  <  0.001), with a bias of 1% or less and limits of agreement of within 3% for the inspiratory wheeze rate and within 6% for the expiratory wheeze rate. However, sounds from the chest wall were more often affected by disturbances than sounds from the trachea (23% versus 6%, p  <  0.001). The study suggests that in young infants, a better quality of lung sound recordings can be obtained with the tracheal sensor.

Analysis of bioelectric records and fabrication of phototype sleep analysis equipment

NASA Technical Reports Server (NTRS)

Kellaway, P.

1972-01-01

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

Strategies to increase patient safety in Hemodialysis: Application of the modal analysis system of errors and effects (FEMA system).

PubMed

Arenas Jiménez, María Dolores; Ferre, Gabriel; Álvarez-Ude, Fernando

Haemodialysis (HD) patients are a high-risk population group. For these patients, an error could have catastrophic consequences. Therefore, systems that ensure the safety of these patients in an environment with high technology and great interaction of the human factor is a requirement. To show a systematic working approach, reproducible in any HD unit, which consists of recording the complications and errors that occurred during the HD session; defining which of those complications could be considered adverse event (AE), and therefore preventable; and carrying out a systematic analysis of them, as well as of underlying real or potential errors, evaluating their severity, frequency and detection; as well as establishing priorities for action (Failure Mode and Effects Analysis system [FMEA systems]). Retrospective analysis of the graphs of all HD sessions performed during one month (October 2015) on 97 patients, analysing all recorded complications. The consideration of these complications as AEs was based on a consensus among 13 health professionals and 2 patients. The severity, frequency and detection of each AE was evaluated by the FMEA system. We analysed 1303 HD treatments in 97 patients. A total of 383 complications (1 every 3.4 HD treatments) were recorded. Approximately 87.9% of them was deemed AEs and 23.7% complications related with patients' underlying pathology. There was one AE every 3.8 HD treatments. Hypertension and hypotension were the most frequent AEs (42.7 and 27.5% of all AEs recorded, respectively). Vascular-access related AEs were one every 68.5 HD treatments. A total of 21 errors (1 every 62 HD treatments), mainly related to the HD technique and to the administration of prescribed medication, were registered. The highest risk priority number, according to the FMEA, corresponded to errors related to patient body weight; dysfunction/rupture of the catheter; and needle extravasation. HD complications are frequent. Consideration of some of them as AEs could improve safety by facilitating the implementation of preventive measures. The application of the FMEA system allows stratifying real and potential errors in dialysis units and acting with the appropriate degree of urgency, developing and implementing the necessary preventive and improvement measures. Copyright © 2017 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

On impact damage detection and quantification for CFRP laminates using structural response data only

NASA Astrophysics Data System (ADS)

Sultan, M. T. H.; Worden, K.; Pierce, S. G.; Hickey, D.; Staszewski, W. J.; Dulieu-Barton, J. M.; Hodzic, A.

2011-11-01

The overall purpose of the research is to detect and attempt to quantify impact damage in structures made from composite materials. A study that uses simplified coupon specimens made from a Carbon Fibre-Reinforced Polymer (CFRP) prepreg with 11, 12 and 13 plies is presented. PZT sensors were placed at three separate locations in each test specimen to record the responses from impact events. To perform damaging impact tests, an instrumented drop-test machine was used and the impact energy was set to cover a range of 0.37-41.72 J. The response signals captured from each sensor were recorded by a data acquisition system for subsequent evaluation. The impacted specimens were examined with an X-ray technique to determine the extent of the damaged areas and it was found that the apparent damaged area grew monotonically with impact energy. A number of simple univariate and multivariate features were extracted from the sensor signals recorded during impact by computing their spectra and calculating frequency centroids. The concept of discordancy from the statistical discipline of outlier analysis is employed in order to separate the responses from non-damaging and damaging impacts. The results show that the potential damage indices introduced here provide a means of identifying damaging impacts from the response data alone.

Evoking Blinks with Natural Stimulation and Detecting Them with a Noninvasive Optical Device: A Simple, Inexpensive Method for Use with Freely Moving Animals

PubMed Central

Weiss, Craig; Disterhoft, John F.

2008-01-01

Many laboratories studying eyeblinks in unanesthetized rodents use a periorbital shock to evoke the blink. The stimulus is typically delivered via a tether and usually obliterates detection of a full unconditioned response with electromyographic (EMG) recording. Here we describe the adapter we have used successfully for several years to deliver puffs of air to the cornea of freely moving rats during our studies of eyeblink conditioning. The stimulus evokes an unconditioned response that can be recorded without affecting the EMG signal. This allows a complete analysis of the unconditioned response which is important for studies examining reflex modification or the effect of drugs, genetic manipulations, or aging on the unconditioned blink reflex. We also describe an infrared reflective sensor that can be added to the tether to minimize the number of wires that need to be implanted around the eye, and which is relatively immune to electrical artifacts associated with a periorbital shock stimulus or other devices powered by alternating current. The responses recorded simultaneously by EMG wires and the optical sensor appear highly correlated and demonstrate that the optical sensor can measure responses that might otherwise be lost due to electrical interference from a shock stimulus. PMID:18598716

Climate Events and Cycles During the Last Glacial-Interglacial Transition

NASA Astrophysics Data System (ADS)

Lee, Eun Hee; Lee, Dae-Young; Park, Mi-Young

2017-09-01

During the last glacial-interglacial transition, there were multiple intense climatic events such as the Bølling-Allerød warming and Younger Dryas cooling. These events show abrupt and rapid climatic changes. In this study, the climate events and cycles during this interval are examined through wavelet analysis of Arctic and Antarctic ice-core 18O and tropical marine 14C records. The results show that periods of 1383-1402, 1029-1043, 726-736, 441-497 and 202-247 years are dominant in the Arctic region, whereas periods of 1480, 765, 518, 311, and 207 years are prominent in the Antarctic TALDICE. In addition, cycles of 1019, 515, and 209 years are distinct in the tropical region. Among these variations, the de Vries cycle of 202-209 years, correlated with variations in solar activity, was detected globally. In particular, this cycle shows a strong signal in the Antarctic between about 13,000 and 10,500 yr before present (BP). In contrast, the Eddy cycle of 1019-1043 years was prominent in Greenland and the tropical region, but was not detected in the Antarctic TALDICE records. Instead, these records showed that the Heinrich cycle of 1480 year was very strong and significant throughout the last glacial-interglacial interval.

Detection of ground motions using high-rate GPS time-series

NASA Astrophysics Data System (ADS)

Psimoulis, Panos A.; Houlié, Nicolas; Habboub, Mohammed; Michel, Clotaire; Rothacher, Markus

2018-05-01

Monitoring surface deformation in real-time help at planning and protecting infrastructures and populations, manage sensitive production (i.e. SEVESO-type) and mitigate long-term consequences of modifications implemented. We present RT-SHAKE, an algorithm developed to detect ground motions associated with landslides, sub-surface collapses, subsidences, earthquakes or rock falls. RT-SHAKE detects first transient changes in individual GPS time series before investigating for spatial correlation(s) of observations made at neighbouring GPS sites and eventually issue a motion warning. In order to assess our algorithm on fast (seconds to minute), large (from 1 cm to meters) and spatially consistent surface motions, we use the 1 Hz GEONET GNSS network data of the Tohoku-Oki MW9.0 2011 as a test scenario. We show the delay of detection of seismic wave arrival by GPS records is of ˜10 seconds with respect to an identical analysis based on strong-motion data and this time delay depends on the level of the time-variable noise. Nevertheless, based on the analysis of the GPS network noise level and ground motion stochastic model, we show that RT-SHAKE can narrow the range of earthquake magnitude, by setting a lower threshold of detected earthquakes to MW6.5-7, if associated with a real-time automatic earthquake location system.

Optimizing collection of adverse event data in cancer clinical trials supporting supplemental indications.

PubMed

Kaiser, Lee D; Melemed, Allen S; Preston, Alaknanda J; Chaudri Ross, Hilary A; Niedzwiecki, Donna; Fyfe, Gwendolyn A; Gough, Jacqueline M; Bushnell, William D; Stephens, Cynthia L; Mace, M Kelsey; Abrams, Jeffrey S; Schilsky, Richard L

2010-12-01

Although much is known about the safety of an anticancer agent at the time of initial marketing approval, sponsors customarily collect comprehensive safety data for studies that support supplemental indications. This adds significant cost and complexity to the study but may not provide useful new information. The main purpose of this analysis was to assess the amount of safety and concomitant medication data collected to determine a more optimal approach in the collection of these data when used in support of supplemental applications. Following a prospectively developed statistical analysis plan, we reanalyzed safety data from eight previously completed prospective randomized trials. A total of 107,884 adverse events and 136,608 concomitant medication records were reviewed for the analysis. Of these, four grade 1 to 2 and nine grade 3 and higher events were identified as drug effects that were not included in the previously established safety profiles and could potentially have been missed using subsampling. These events were frequently detected in subsamples of 400 patients or larger. Furthermore, none of the concomitant medication records contributed to labeling changes for the supplemental indications. Our study found that applying the optimized methodologic approach, described herein, has a high probability of detecting new drug safety signals. Focusing data collection on signals that cause physicians to modify or discontinue treatment ensures that safety issues of the highest concern for patients and regulators are captured and has significant potential to relieve strain on the clinical trials system.

Passive acoustic monitoring to detect spawning in large-bodied catostomids

USGS Publications Warehouse

Straight, Carrie A.; Freeman, Byron J.; Freeman, Mary C.

2014-01-01

Documenting timing, locations, and intensity of spawning can provide valuable information for conservation and management of imperiled fishes. However, deep, turbid or turbulent water, or occurrence of spawning at night, can severely limit direct observations. We have developed and tested the use of passive acoustics to detect distinctive acoustic signatures associated with spawning events of two large-bodied catostomid species (River Redhorse Moxostoma carinatum and Robust Redhorse Moxostoma robustum) in river systems in north Georgia. We deployed a hydrophone with a recording unit at four different locations on four different dates when we could both record and observe spawning activity. Recordings captured 494 spawning events that we acoustically characterized using dominant frequency, 95% frequency, relative power, and duration. We similarly characterized 46 randomly selected ambient river noises. Dominant frequency did not differ between redhorse species and ranged from 172.3 to 14,987.1 Hz. Duration of spawning events ranged from 0.65 to 11.07 s, River Redhorse having longer durations than Robust Redhorse. Observed spawning events had significantly higher dominant and 95% frequencies than ambient river noises. We additionally tested software designed to automate acoustic detection. The automated detection configurations correctly identified 80–82% of known spawning events, and falsely indentified spawns 6–7% of the time when none occurred. These rates were combined over all recordings; rates were more variable among individual recordings. Longer spawning events were more likely to be detected. Combined with sufficient visual observations to ascertain species identities and to estimate detection error rates, passive acoustic recording provides a useful tool to study spawning frequency of large-bodied fishes that displace gravel during egg deposition, including several species of imperiled catostomids.

realfast: Real-time, Commensal Fast Transient Surveys with the Very Large Array

NASA Astrophysics Data System (ADS)

Law, C. J.; Bower, G. C.; Burke-Spolaor, S.; Butler, B. J.; Demorest, P.; Halle, A.; Khudikyan, S.; Lazio, T. J. W.; Pokorny, M.; Robnett, J.; Rupen, M. P.

2018-05-01

Radio interferometers have the ability to precisely localize and better characterize the properties of sources. This ability is having a powerful impact on the study of fast radio transients, where a few milliseconds of data is enough to pinpoint a source at cosmological distances. However, recording interferometric data at millisecond cadence produces a terabyte-per-hour data stream that strains networks, computing systems, and archives. This challenge mirrors that of other domains of science, where the science scope is limited by the computational architecture as much as the physical processes at play. Here, we present a solution to this problem in the context of radio transients: realfast, a commensal, fast transient search system at the Jansky Very Large Array. realfast uses a novel architecture to distribute fast-sampled interferometric data to a 32-node, 64-GPU cluster for real-time imaging and transient detection. By detecting transients in situ, we can trigger the recording of data for those rare, brief instants when the event occurs and reduce the recorded data volume by a factor of 1000. This makes it possible to commensally search a data stream that would otherwise be impossible to record. This system will search for millisecond transients in more than 1000 hr of data per year, potentially localizing several Fast Radio Bursts, pulsars, and other sources of impulsive radio emission. We describe the science scope for realfast, the system design, expected outcomes, and ways in which real-time analysis can help in other fields of astrophysics.

Real-Time Amperometric Recording of Extracellular H2O2 in the Brain of Immunocompromised Mice: An In Vitro, Ex Vivo and In Vivo Characterisation Study

PubMed Central

Reid, Caroline H.; Finnerty, Niall J.

2017-01-01

We detail an extensive characterisation study on a previously described dual amperometric H2O2 biosensor consisting of H2O2 detection (blank) and degradation (catalase) electrodes. In vitro investigations demonstrated excellent H2O2 sensitivity and selectivity against the interferent, ascorbic acid. Ex vivo studies were performed to mimic physiological conditions prior to in vivo deployment. Exposure to brain tissue homogenate identified reliable sensitivity and selectivity recordings up to seven days for both blank and catalase electrodes. Furthermore, there was no compromise in pre- and post-implanted catalase electrode sensitivity in ex vivo mouse brain. In vivo investigations performed in anaesthetised mice confirmed the ability of the H2O2 biosensor to detect increases in amperometric current following locally perfused/infused H2O2 and antioxidant inhibitors mercaptosuccinic acid and sodium azide. Subsequent recordings in freely moving mice identified negligible effects of control saline and sodium ascorbate interference injections on amperometric H2O2 current. Furthermore, the stability of the amperometric current was confirmed over a five-day period and analysis of 24-h signal recordings identified the absence of diurnal variations in amperometric current. Collectively, these findings confirm the biosensor current responds in vivo to increasing exogenous and endogenous H2O2 and tentatively supports measurement of H2O2 dynamics in freely moving NOD SCID mice. PMID:28698470

Revealing climatic variability of the last three millennia in northwestern Iberia using pollen influx data

NASA Astrophysics Data System (ADS)

Desprat, Stéphanie; Sánchez Goñi, María. Fernanda; Loutre, Marie-France

2003-08-01

Climatic variability of the last 3 millennia in NW Iberia has been documented using high-resolution pollen analysis of Vir-18 core, retrieved from the Ría de Vigo (42°14.07‧N, 8°47.37‧W). The depth-age model is based on two accelerator mass spectrometry 14C dates and three historically dated botanical events in Galicia: the expansion of Juglans and Pinus, as well as the introduction of Eucalyptus. During the last 3000 years, the relative pollen record demonstrates the occurrence of an open deciduous oak forest, indicating a humid and temperate climate in northwestern Iberia. Two-step forest reduction since 975 cal BC suggests climate as the main cause rather than major socio-economic changes documented in historical archives. Absolute pollen influx has been compared with instrumental summer and winter temperatures and tentatively used as a proxy of short (decadal-scale) and low-amplitude (˜1°C) temperature variations. This new approach allows us to detect for the first time in NW Iberia the millennial-scale climatic cyclicity suggested by North Atlantic records, challenging the apparent climatic stability reflected by the relative pollen record. The Little Ice Age is recorded as low pollen influx values between 1400 and 1860 cal AD, with a cold maximum at 1700 cal AD (Maunder Minimum). The Roman and Medieval Warm Periods are detected through high pollen influx values at 250 cal BC-450 cal AD and 950-1400 cal AD, respectively.

Development of swine-specific DNA markers for biosensor-based halal authentication.

PubMed

Ali, M E; Hashim, U; Kashif, M; Mustafa, S; Che Man, Y B; Abd Hamid, S B

2012-06-29

The pig (Sus scrofa) mitochondrial genome was targeted to design short (15-30 nucleotides) DNA markers that would be suitable for biosensor-based hybridization detection of target DNA. Short DNA markers are reported to survive harsh conditions in which longer ones are degraded into smaller fragments. The whole swine mitochondrial-genome was in silico digested with AluI restriction enzyme. Among 66 AluI fragments, five were selected as potential markers because of their convenient lengths, high degree of interspecies polymorphism and intraspecies conservatism. These were confirmed by NCBI blast analysis and ClustalW alignment analysis with 11 different meat-providing animal and fish species. Finally, we integrated a tetramethyl rhodamine-labeled 18-nucleotide AluI fragment into a 3-nm diameter citrate-tannate coated gold nanoparticle to develop a swine-specific hybrid nanobioprobe for the determination of pork adulteration in 2.5-h autoclaved pork-beef binary mixtures. This hybrid probe detected as low as 1% pork in deliberately contaminated autoclaved pork-beef binary mixtures and no cross-species detection was recorded, demonstrating the feasibility of this type of probe for biosensor-based detection of pork adulteration of halal and kosher foods.

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Kreider, Gary; Fichter, Thomas

2006-01-01

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG.

PubMed

Orosco, Lorena; Laciar, Eric; Correa, Agustina Garces; Torres, Abel; Graffigna, Juan P

2009-01-01

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

Acoustic occurrence detection of a newly recorded Indo-Pacific humpback dolphin population in waters southwest of Hainan Island, China.

PubMed

Dong, Lijun; Liu, Mingming; Dong, Jianchen; Li, Songhai

2017-11-01

In 2014, Indo-Pacific humpback dolphins were recorded for the first time in waters southwest of Hainan Island, China. In this paper, the temporal occurrence of Indo-Pacific humpback dolphins in this region was detected by stationary passive acoustic monitoring. During the 130-day observation period (from January to July 2016), 1969 click trains produced by Indo-Pacific humpback dolphins were identified, and 262 ten-minute recording bins contained echolocation click trains of dolphins, of which 70.9% were at night and 29.1% were during the day. A diurnal rhythm with a nighttime peak in acoustic detections was found. Passive acoustic detections indicated that the Indo-Pacific humpback dolphins frequently occurred in this area and were detected mainly at night. This information may be relevant to conservation efforts for these dolphins in the near future.

Reliability of recordings of subgingival calculus detected using an ultrasonic device.

PubMed

Corraini, Priscila; López, Rodrigo

2015-04-01

To assess the intra-examiner reliability of recordings of subgingival calculus detected using an ultrasonic device, and to investigate the influence of subject-, tooth- and site-level factors on the reliability of these subgingival calculus recordings. On two occasions, within a 1-week interval, 147 adult periodontitis patients received a full-mouth clinical periodontal examination by a single trained examiner. Duplicate subgingival calculus recordings, in six sites per tooth, were obtained using an ultrasonic device for calculus detection and removal. Agreement was observed in 65 % of the 22,584 duplicate subgingival calculus recordings, ranging 45 % to 83 % according to subject. Using hierarchical modeling, disagreements in the subgingival calculus duplicate recordings were more likely in all other sites than the mid-buccal, and in sites harboring supragingival calculus. Disagreements were less likely in sites with PD ≥  4 mm and with furcation involvement  ≥  degree 2. Bleeding on probing or suppuration did not influence the reliability of subgingival calculus. At the subject-level, disagreements were less likely in patients presenting with the highest and lowest extent categories of the covariate subgingival calculus. The reliability of subgingival calculus recordings using the ultrasound technology is reasonable. The results of the present study suggest that the reliability of subgingival calculus recordings is not influenced by the presence of inflammation. Moreover, subgingival calculus can be more reliably detected using the ultrasound device at sites with higher need for periodontal therapy, i.e., sites presenting with deep pockets and premolars and molars with furcation involvement.

Syndromic surveillance for health information system failures: a feasibility study.

PubMed

Ong, Mei-Sing; Magrabi, Farah; Coiera, Enrico

2013-05-01

To explore the applicability of a syndromic surveillance method to the early detection of health information technology (HIT) system failures. A syndromic surveillance system was developed to monitor a laboratory information system at a tertiary hospital. Four indices were monitored: (1) total laboratory records being created; (2) total records with missing results; (3) average serum potassium results; and (4) total duplicated tests on a patient. The goal was to detect HIT system failures causing: data loss at the record level; data loss at the field level; erroneous data; and unintended duplication of data. Time-series models of the indices were constructed, and statistical process control charts were used to detect unexpected behaviors. The ability of the models to detect HIT system failures was evaluated using simulated failures, each lasting for 24 h, with error rates ranging from 1% to 35%. In detecting data loss at the record level, the model achieved a sensitivity of 0.26 when the simulated error rate was 1%, while maintaining a specificity of 0.98. Detection performance improved with increasing error rates, achieving a perfect sensitivity when the error rate was 35%. In the detection of missing results, erroneous serum potassium results and unintended repetition of tests, perfect sensitivity was attained when the error rate was as small as 5%. Decreasing the error rate to 1% resulted in a drop in sensitivity to 0.65-0.85. Syndromic surveillance methods can potentially be applied to monitor HIT systems, to facilitate the early detection of failures.

Iron meteorite fragment studied by atomic and nuclear analytical methods

NASA Astrophysics Data System (ADS)

Cesnek, Martin; Štefánik, Milan; Kmječ, Tomáš; Miglierini, Marcel

2016-10-01

Chemical and structural compositions of a fragment of Sikhote-Alin iron meteorite were investigated by X-ray fluorescence analysis (XRF), neutron activation analysis (NAA) and Mössbauer spectroscopy (MS). XRF and NAA revealed the presence of chemical elements which are characteristic for iron meteorites. XRF also showed a significant amount of Si and Al on the surface of the fragment. MS spectra revealed possible presence of α-Fe(Ni, Co) phase with different local Ni concentration. Furthermore, paramagnetic singlet was detected in Mössbauer spectra recorded at room temperature and at 4.2 K.

Sideband analysis and seismic detection in a large ring laser

NASA Astrophysics Data System (ADS)

Stedman, G. E.; Li, Z.; Bilger, H. R.

1995-08-01

A ring laser unlocked by the Earth's Sagnac effect has attained a frequency resolution of 1 part in 3 \\times 1021 and a rotational resolution of 300 prad. We discuss both theoretically and experimentally the sideband structure of the Earth rotation-induced spectral line induced in the microhertz-hertz region by frequency modulation associated with extra mechanical motion, such as seismic events. The relative sideband height is an absolute measure of the rotational amplitude of that Fourier component. An initial analysis is given of the ring laser record from the Arthur's Pass-Coleridge seismic event of 18 June 1994.

U.S. data processing for the IRAS project. [by Jet Propulsion Laboratory Scientific Data Analysis System

NASA Technical Reports Server (NTRS)

Duxbury, J. H.

1983-01-01

The JPL's Scientific Data Analysis System (SDAS), which will process IRAS data and produce a catalogue of perhaps a million infrared sources in the sky, as well as other information for astronomical records, is described. The purposes of SDAS are discussed, and the major SDAS processors are shown in block diagram. The catalogue processing is addressed, mentioning the basic processing steps which will be applied to raw detector data. Signal reconstruction and conversion to astrophysical units, source detection, source confirmation, data management, and survey data products are considered in detail.

In utero eyeball development study by magnetic resonance imaging.

PubMed

Brémond-Gignac, D S; Benali, K; Deplus, S; Cussenot, O; Ferkdadji, L; Elmaleh, M; Lassau, J P

1997-01-01

The aim of this study was to measure fetal ocular development and to determine a growth curve by means of measurements in utero. Fetal ocular development was recorded by analysis of the results of magnetic resonance imaging (MRI). An anatomic study allowed definition of the best contrasted MRI sequences for calculation of the ocular surface. Biometric analysis of the values of the ocular surface in the neuro-ocular plane in 35 fetuses allowed establishment of a linear model of ocular growth curve in utero. Evaluation of ocular development may allow the detection and confirmation of malformational ocular anomalies such as microphthalmia.

One Way of Testing a Distributed Processor

NASA Technical Reports Server (NTRS)

Edstrom, R.; Kleckner, D.

1982-01-01

Launch processing for Space Shuttle is checked out, controlled, and monitored with new system. Entire system can be exercised by two computer programs--one in master console and other in each of operations consoles. Control program in each operations console detects change in status and begins task initiation. All of front-end processors are exercised from consoles through common data buffer, and all data are logged to processed-data recorder for posttest analysis.

Sensor Management for Tactical Surveillance Operations

DTIC Science & Technology

2007-11-01

active and passive sonar for submarine and tor- pedo detection, and mine avoidance. [range, bearing] range 1.8 km to 55 km Active or Passive AN/SLQ-501...finding (DF) unit [bearing, classification] maximum range 1100 km Passive Cameras (day- light/ night- vision) ( video & still) Record optical and...infrared still images or motion video of events for near-real time assessment or long term analysis and archiving. Range is limited by the image resolution

Evaluation of auto incident recording system (AIRS).

DOT National Transportation Integrated Search

2005-05-01

The Auto Incident Recording System (AIRS) is a sound-actuated video recording system. It automatically records potential incidents when activated by sound (horns, clashing metal, squealing tires, etc.). The purpose is to detect patterns of crashes at...

Comparison of enterovirus detection in cerebrospinal fluid with Bacterial Meningitis Score in children

PubMed Central

Pires, Frederico Ribeiro; Franco, Andréia Christine Bonotto Farias; Gilio, Alfredo Elias; Troster, Eduardo Juan

2017-01-01

ABSTRACT Objective To measure the role of enterovirus detection in cerebrospinal fluid compared with the Bacterial Meningitis Score in children with meningitis. Methods A retrospective cohort based on analysis of medical records of pediatric patients diagnosed as meningitis, seen at a private and tertiary hospital in São Paulo, Brazil, between 2011 and 2014. Excluded were patients with critical illness, purpura, ventricular shunt or recent neurosurgery, immunosuppression, concomitant bacterial infection requiring parenteral antibiotic therapy, and those who received antibiotics 72 hours before lumbar puncture. Results The study included 503 patients. Sixty-four patients were excluded and 94 were not submitted to all tests for analysis. Of the remaining 345 patients, 7 were in the Bacterial Meningitis Group and 338 in the Aseptic Meningitis Group. There was no statistical difference between the groups. In the Bacterial Meningitis Score analysis, of the 338 patients with possible aseptic meningitis (negative cultures), 121 of them had one or more points in the Bacterial Meningitis Score, with sensitivity of 100%, specificity of 64.2%, and negative predictive value of 100%. Of the 121 patients with positive Bacterial Meningitis Score, 71% (86 patients) had a positive enterovirus detection in cerebrospinal fluid. Conclusion Enterovirus detection in cerebrospinal fluid was effective to differentiate bacterial from viral meningitis. When the test was analyzed together with the Bacterial Meningitis Score, specificity was higher when compared to Bacterial Meningitis Score alone. PMID:28767914

Analysis of the cyanolichen Lichina pygmaea metabolites using in situ DART-MS: from detection to thermochemistry of mycosporine serinol.

PubMed

Le Pogam, Pierre; Legouin, Béatrice; Le Lamer, Anne-Cécile; Boustie, Joël; Rondeau, David

2015-03-01

Direct Analysis in Real Time DART-HRMS is here first applied to the detection of molecules from a lichen, Lichina pygmaea. The aim was to propose an innovative method of in situ detection of lichen secondary metabolites using the possibilities of elemental composition determination available when a DART source is interfaced with a TOF analyzer. Three kinds of samples have been submitted to DART ionization, i.e. an intact thallus, a powder obtained from the crushed lichen and an aqueous extract. In situ analysis of crushed lichen, yields an extensive chemical profile, comparable to what is obtained from the aqueous extract, comprising both major polar metabolites described in literature along with some other signals that could correspond to potentially unknown metabolites. One of the detected secondary metabolites, mycosporine serinol, underwent a dehydration reaction prior to its transfer in the gas-phase by DART ionization. The consideration of the thermal transfers involved in the DART ionization process and the possibility to record time-dependent mass spectra through the use of the TOF analyzer allowed establishing Arrhenius plots of this water molecule loss to obtain associated thermodynamic quantities. The low values of corresponding activation enthalpy (Δr‡Hm° of the order of 25 kJ mol(-1)) enabled formulating some assumption regarding a possible role of such metabolites in the lichen. Copyright © 2015 John Wiley & Sons, Ltd.

Preoperative lymphoscintigraphy and tumor histologic grade are associated with surgical detection of the sentinel lymph node.

PubMed

Arias Ortega, M; Torres Sousa, M Y; González García, B; Pardo García, R; González López, A; Delgado Portela, M

2014-01-01

To study which variables involved in the process of selective sentinel node biopsy (SSNB) influence the intraoperative detection of the sentinel lymph node. This was a prospective cross-sectional study in 210 patients (mean age, 54 years) diagnosed with breast cancer who underwent SSNB. We recorded clinical, radiological, radioisotope administration, surgical, and histological data as well as follow-up data. We did a descriptive analysis of the data and an associative analysis using multivariable regression. Deep injection alone was the most common route of radioisotope administration (72.7%). Most lesions were palpable (57.1%), presented as nodules (67.1%), measured less than 2 cm in diameter (64.8%), were located in the upper outer quadrant (49.1%), were ductal carcinomas (85.7%), were accompanied by infiltration (66.2%), and had a histologic grade of differentiation of ii (44.8%). Preoperative scintigraphy detected the sentinel node in 97.6% of cases and 95.7% were detected during the operation. One axillary relapse was observed. In the associative study, the variables "preoperative lymphoscintigraphy" and "histologic grade of differentiation of the tumor" were significantly associated with the detection of the sentinel lymph node during the operation. The probability of not detecting the sentinel lymph node during the surgical intervention is higher in patients with high histologic grade tumors or in patients in whom preoperative lymphoscintigraphy failed to detect the sentinel node. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

NASA Astrophysics Data System (ADS)

Chatterjee, Subhasri; Das, Nandan K.; Kumar, Satish; Mohapatra, Sonali; Pradhan, Asima; Panigrahi, Prasanta K.; Ghosh, Nirmalya

2013-02-01

Multi-resolution analysis on the spatial refractive index inhomogeneities in the connective tissue regions of human cervix reveals clear signature of multifractality. We have thus developed an inverse analysis strategy for extraction and quantification of the multifractality of spatial refractive index fluctuations from the recorded light scattering signal. The method is based on Fourier domain pre-processing of light scattering data using Born approximation, and its subsequent analysis through Multifractal Detrended Fluctuation Analysis model. The method has been validated on several mono- and multi-fractal scattering objects whose self-similar properties are user controlled and known a-priori. Following successful validation, this approach has initially been explored for differentiating between different grades of precancerous human cervical tissues.

Analysis of anthropogenic contributions to record high Australian summer rainfall (2010-2012) using CMIP5 simulations

NASA Astrophysics Data System (ADS)

Lewis, Sophie; Karoly, David

2013-04-01

Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.

Description of the NASA Hypobaric Decompression Sickness Database (1982-1998)

NASA Technical Reports Server (NTRS)

Wessel, J. H., III; Conkin, J.

2008-01-01

The availability of high-speed computers, data analysis software, and internet communication are compelling reasons to describe and make available computer databases from many disciplines. Methods: Human research using hypobaric chambers to understand and then prevent decompression sickness (DCS) during space walks has been conducted at the Johnson Space Center (JSC) from 1982 to 1998. The data are archived in the NASA Hypobaric Decompression Sickness Database, within an Access 2003 Relational Database. Results: There are 548 records from 237 individuals that participated in 31 unique tests. Each record includes physical characteristics, the denitrogenation procedure that was tested, and the outcome of the test, such as the report of a DCS symptom and the intensity of venous gas emboli (VGE) detected with an ultrasound Doppler bubble detector as they travel in the venous blood along the pulmonary artery on the way to the lungs. We documented 84 cases of DCS and 226 cases where VGE were detected. The test altitudes were 10.2, 10.1, 6.5, 6.0, and 4.3 pounds per square inch absolute (psia). 346 records are from tests conducted at 4.3 psia, the operating pressure of the current U.S. space suit. 169 records evaluate the Staged 10.2 psia Decompression Protocol used by the Space Shuttle Program. The mean exposure time at altitude was 242.3 minutes (SD = 80.6), with a range from 120 to 360 minutes. Among our test subjects, 96 records of exposures are females. The mean age of all test subjects was 31.8 years (SD = 7.17), with a range from 20 to 54 years. Discussion: These data combined with other published databases and evaluated with metaanalysis techniques would extend our understanding about DCS. A better understanding about the cause and prevention of DCS would benefit astronauts, aviators, and divers.

Electromyography as a recording system for eyeblink conditioning with functional magnetic resonance imaging.

PubMed

Knuttinen, M-G; Parrish, T B; Weiss, C; LaBar, K S; Gitelman, D R; Power, J M; Mesulam, M-M; Disterhoft, J F

2002-10-01

This study was designed to develop a suitable method of recording eyeblink responses while conducting functional magnetic resonance imaging (fMRI). Given the complexity of this behavioral setup outside of the magnet, this study sought to adapt and further optimize an approach to eyeblink conditioning that would be suitable for conducting event-related fMRI experiments. This method involved the acquisition of electromyographic (EMG) signals from the orbicularis oculi of the right eye, which were subsequently amplified and converted into an optical signal outside of the head coil. This optical signal was converted back into an electrical signal once outside the magnet room. Electromyography (EMG)-detected eyeblinks were used to measure responses in a delay eyeblink conditioning paradigm. Our results indicate that: (1) electromyography is a sensitive method for the detection of eyeblinks during fMRI; (2) minimal interactions or artifacts of the EMG signal were created from the magnetic resonance pulse sequence; and (3) no electromyography-related artifacts were detected in the magnetic resonance images. Furthermore, an analysis of the functional data showed areas of activation that have previously been shown in positron emission tomography studies of human eyeblink conditioning. Our results support the strength of this behavioral setup as a suitable method to be used in association with fMRI.

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.

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

PubMed Central

2017-01-01

Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs. PMID:29065613

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

PubMed

Park, Jeong-Seon; Lee, Sang-Woong; Park, Unsang

2017-01-01

Rapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

Human care system for heart-rate and human-movement trajectory in home and its application to detect mental disease

NASA Astrophysics Data System (ADS)

Hata, Yutaka; Kanazawa, Seigo; Endo, Maki; Tsuchiya, Naoki; Nakajima, Hiroshi

2012-06-01

This paper proposes a heart rate monitoring system for detecting autonomic nervous system by the heart rate variability using an air pressure sensor to diagnose mental disease. Moreover, we propose a human behavior monitoring system for detecting the human trajectory in home by an infrared camera. In day and night times, the human behavior monitoring system detects the human movement in home. The heart rate monitoring system detects the heart rate in bed in night time. The air pressure sensor consists of a rubber tube, cushion cover and pressure sensor, and it detects the heart rate by setting it to bed. It unconstraintly detects the RR-intervals; thereby the autonomic nervous system can be assessed. The autonomic nervous system analysis can examine the mental disease. While, the human behavior monitoring system obtains distance distribution image by an infrared camera. It classifies adult, child and the other object from distance distribution obtained by the camera, and records their trajectories. This behavior, i.e., trajectory in home, strongly corresponds to cognitive disorders. Thus, the total system can detect mental disease and cognitive disorders by uncontacted sensors to human body.

Rear-end vision-based collision detection system for motorcyclists

NASA Astrophysics Data System (ADS)

Muzammel, Muhammad; Yusoff, Mohd Zuki; Meriaudeau, Fabrice

2017-05-01

In many countries, the motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. To increase the safety of motorcyclists and minimize their road fatalities, this paper introduces a vision-based rear-end collision detection system. The binary road detection scheme contributes significantly to reduce the negative false detections and helps to achieve reliable results even though shadows and different lane markers are present on the road. The methodology is based on Harris corner detection and Hough transform. To validate this methodology, two types of dataset are used: (1) self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and (2) online datasets (recorded by placing a camera at the front of a car). This method achieved 95.1% accuracy for the self-recorded dataset and gives reliable results for the rear-end vehicle detections under different road scenarios. This technique also performs better for the online car datasets. The proposed technique's high detection accuracy using a monocular vision camera coupled with its low computational complexity makes it a suitable candidate for a motorbike rear-end collision detection system.

Barriers to Screening and Possibilities for Active Detection of Family Medicine Attendees Exposed to Intimate Partner Violence.

PubMed

Kopčavar Guček, Nena; Petek, Davorina; Švab, Igor; Selič, Polona

2016-03-01

In 1996 the World Health Organization declared intimate partner violence (IPV) the most important public health problem. Meta-analyses in 2013 showed every third female globally had been a victim of violence. Experts find screening controversial; family medicine is the preferred environment for identifying victims of violence, but barriers on both sides prevent patients from discussing it with doctors. In July 2014, a qualitative study was performed through semi-structured interviews with ten family doctors of different ages and gender, working in rural or urban environments. Sound recordings of the interviews were transcribed, and the record verified. The data were interpreted using content analysis. A coding scheme was developed and later verified and analysed by two independent researchers. The text of the interviews was analysed according to the coding scheme. Two coding schemes were developed: one for screening, and the other for the active detection of IPV. The main themes emerging as barriers to screening were lack of time, staff turnover, inadequate finance, ignorance of a clear definition, poor commitment to screening, obligatory follow-up, risk of deterioration of the doctor-patient relationship, and insincerity on the part of the patient. Additionally, cultural aspects of violence, uncertainty/ helplessness, fear, lack of competence and qualifications, autonomy/negative experience, and passive role/stigma/ fear on the part of the patients were barriers to active detection. All the participating doctors had had previous experience with active detection of IPV and were aware of its importance. Due to several barriers to screening for violence they preferred active detection.

Barriers to Screening and Possibilities for Active Detection of Family Medicine Attendees Exposed to Intimate Partner Violence

PubMed Central

KOPČAVAR GUČEK, Nena; PETEK, Davorina; ŠVAB, Igor; SELIČ, Polona

2016-01-01

Introduction In 1996 the World Health Organization declared intimate partner violence (IPV) the most important public health problem. Meta-analyses in 2013 showed every third female globally had been a victim of violence. Experts find screening controversial; family medicine is the preferred environment for identifying victims of violence, but barriers on both sides prevent patients from discussing it with doctors. Methods In July 2014, a qualitative study was performed through semi-structured interviews with ten family doctors of different ages and gender, working in rural or urban environments. Sound recordings of the interviews were transcribed, and the record verified. The data were interpreted using content analysis. A coding scheme was developed and later verified and analysed by two independent researchers. The text of the interviews was analysed according to the coding scheme. Results Two coding schemes were developed: one for screening, and the other for the active detection of IPV. The main themes emerging as barriers to screening were lack of time, staff turnover, inadequate finance, ignorance of a clear definition, poor commitment to screening, obligatory follow-up, risk of deterioration of the doctor-patient relationship, and insincerity on the part of the patient. Additionally, cultural aspects of violence, uncertainty/ helplessness, fear, lack of competence and qualifications, autonomy/negative experience, and passive role/stigma/ fear on the part of the patients were barriers to active detection. Conclusion All the participating doctors had had previous experience with active detection of IPV and were aware of its importance. Due to several barriers to screening for violence they preferred active detection. PMID:27647084

Local vs. volume conductance activity of field potentials in the human subthalamic nucleus

PubMed Central

Marmor, Odeya; Valsky, Dan; Joshua, Mati; Bick, Atira S; Arkadir, David; Tamir, Idit; Bergman, Hagai; Israel, Zvi

2017-01-01

Subthalamic nucleus field potentials have attracted growing research and clinical interest over the last few decades. However, it is unclear whether subthalamic field potentials represent locally generated neuronal subthreshold activity or volume conductance of the organized neuronal activity generated in the cortex. This study aimed at understanding of the physiological origin of subthalamic field potentials and determining the most accurate method for recording them. We compared different methods of recordings in the human subthalamic nucleus: spikes (300–9,000 Hz) and field potentials (3–100 Hz) recorded by monopolar micro- and macroelectrodes, as well as by differential-bipolar macroelectrodes. The recordings were done outside and inside the subthalamic nucleus during electrophysiological navigation for deep brain stimulation procedures (150 electrode trajectories) in 41 Parkinson’s disease patients. We modeled the signal and estimated the contribution of nearby/independent vs. remote/common activity in each recording configuration and area. Monopolar micro- and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity. However, bipolar macroelectrode recordings inside the subthalamic nucleus can detect locally generated potentials. These results are confirmed by high correspondence between the model predictions and actual correlation of neuronal activity recorded by electrode pairs. Differential bipolar macroelectrode subthalamic field potentials can overcome volume conductance effects and reflect locally generated neuronal activity. Bipolar macroelectrode local field potential recordings might be used as a biological marker of normal and pathological brain functions for future electrophysiological studies and navigation systems as well as for closed-loop deep brain stimulation paradigms. NEW & NOTEWORTHY Our results integrate a new method for human subthalamic recordings with a development of an advanced mathematical model. We found that while monopolar microelectrode and macroelectrode recordings detect field potentials that are considerably affected by common (probably cortical) activity, bipolar macroelectrode recordings inside the subthalamic nucleus (STN) detect locally generated potentials that are significantly different than those recorded outside the STN. Differential bipolar subthalamic field potentials can be used in navigation and closed-loop deep brain stimulation paradigms. PMID:28202569

A microprobe for parallel optical and electrical recordings from single neurons in vivo.

PubMed

LeChasseur, Yoan; Dufour, Suzie; Lavertu, Guillaume; Bories, Cyril; Deschênes, Martin; Vallée, Réal; De Koninck, Yves

2011-04-01

Recording electrical activity from identified neurons in intact tissue is key to understanding their role in information processing. Recent fluorescence labeling techniques have opened new possibilities to combine electrophysiological recording with optical detection of individual neurons deep in brain tissue. For this purpose we developed dual-core fiberoptics-based microprobes, with an optical core to locally excite and collect fluorescence, and an electrolyte-filled hollow core for extracellular single unit electrophysiology. This design provides microprobes with tips < 10 μm, enabling analyses with single-cell optical resolution. We demonstrate combined electrical and optical detection of single fluorescent neurons in rats and mice. We combined electrical recordings and optical Ca²(+) measurements from single thalamic relay neurons in rats, and achieved detection and activation of single channelrhodopsin-expressing neurons in Thy1::ChR2-YFP transgenic mice. The microprobe expands possibilities for in vivo electrophysiological recording, providing parallel access to single-cell optical monitoring and control.

[Immunodetection of bacteriophages by a piezoelectric resonator with lateral electric field].

PubMed

Gulii, O I; Zaitsev, B D; Shikhabudinov, A M; Teplykh, A A; Borodina, I A; Pavlii, S A; Larionova, O S; Fomin, A S; Staroverov, S A; Dykman, L A; Ignatov, O V

2016-01-01

It has been demonstrated that electroacoustic analysis with polyclonal antibodies can be used for bacteriophage detection. The frequency dependences of the real and imaginary parts of electrical impedance of a resonator with a viral suspension with antibodies were shown to be essentially different from the dependences of a resonator with control viral suspension without antibodies. It was shown that ΦAl-Sp59b bacteriophages were detected with the use of antibodies in the presence of foreign virus particles. The ΦAl-Sp59b bacteriophage content in the analyzed suspension was ~1010–106 phages/mL; the time of analysis was no more than 5 min. The optimally informative parameter for obtaining reliable information was the change in the real or imaginary part of electrical impedance at a fixed frequency near the resonance upon the addition of specific antibodies to the analyzed suspension. It was demonstrated that the interaction between bacteriophages and antibodies can be recorded, offering good prospects for the development of a biological sensor for liquid-phase identification and virus detection.

13CO2/12CO2 ratio analysis in exhaled air by lead-salt tunable diode lasers for noninvasive diagnostics in gastroenterology

NASA Astrophysics Data System (ADS)

Stepanov, Eugene V.; Zyrianov, Pavel V.; Miliaev, Valerii A.; Selivanov, Yurii G.; Chizhevskii, Eugene G.; Os'kina, Svetlana; Ivashkin, Vladimir T.; Nikitina, Elena I.

1999-07-01

An analyzer of 13CO2/12CO2 ratio in exhaled air based on lead-salt tunable diode lasers is presented. High accuracy of the carbon isotope ratio detection in exhaled carbon dioxide was achieved with help of very simple optical schematics. It was based on the use of MBE laser diodes operating in pulse mode and on recording the resonance CO2 absorption at 4.2 micrometers . Special fast acquisition electronics and software were applied for spectral data collection and processing. Developed laser system was tested in a clinical train aimed to assessment eradication efficiency in therapy of gastritis associated with Helicobacter pylori infection. Data on the 13C-urea breath test used for P.pylori detection and obtained with tunable diode lasers in the course of the trail was compared with the results of Mass-Spectroscopy analysis and histology observations. The analyzer can be used also for 13CO2/12CO2 ratio detection in exhalation to perform gastroenterology breath test based on using other compounds labeled with stable isotopes.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

Motor current signature analysis method for diagnosing motor operated devices

DOEpatents

Haynes, Howard D.; Eissenberg, David M.

1990-01-01

A motor current noise signature analysis method and apparatus for remotely monitoring the operating characteristics of an electric motor-operated device such as a motor-operated valve. Frequency domain signal analysis techniques are applied to a conditioned motor current signal to distinctly identify various operating parameters of the motor driven device from the motor current signature. The signature may be recorded and compared with subsequent signatures to detect operating abnormalities and degradation of the device. This diagnostic method does not require special equipment to be installed on the motor-operated device, and the current sensing may be performed at remote control locations, e.g., where the motor-operated devices are used in accessible or hostile environments.

Determination of Rare Earth Elements in Geological Samples Using Laser-Induced Breakdown Spectroscopy (LIBS).

PubMed

Bhatt, Chet R; Jain, Jinesh C; Goueguel, Christian L; McIntyre, Dustin L; Singh, Jagdish P

2018-01-01

Laser-induced breakdown spectroscopy (LIBS) was used to detect rare earth elements (REEs) in natural geological samples. Low and high intensity emission lines of Ce, La, Nd, Y, Pr, Sm, Eu, Gd, and Dy were identified in the spectra recorded from the samples to claim the presence of these REEs. Multivariate analysis was executed by developing partial least squares regression (PLS-R) models for the quantification of Ce, La, and Nd. Analysis of unknown samples indicated that the prediction results of these samples were found comparable to those obtained by inductively coupled plasma mass spectrometry analysis. Data support that LIBS has potential to quantify REEs in geological minerals/ores.

Motion detection using extended fractional Fourier transform and digital speckle photography.

PubMed

Bhaduri, Basanta; Tay, C J; Quan, C; Sheppard, Colin J R

2010-05-24

Digital speckle photography is a useful tool for measuring the motion of optically rough surfaces from the speckle shift that takes place at the recording plane. A simple correlation based digital speckle photographic system has been proposed that implements two simultaneous optical extended fractional Fourier transforms (EFRTs) of different orders using only a single lens and detector to simultaneously detect both the magnitude and direction of translation and tilt by capturing only two frames: one before and another after the object motion. The dynamic range and sensitivity of the measurement can be varied readily by altering the position of the mirror/s used in the optical setup. Theoretical analysis and experiment results are presented.

A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings.

PubMed

Vairavan, S; Ulusar, U D; Eswaran, H; Preissl, H; Wilson, J D; Mckelvey, S S; Lowery, C L; Govindan, R B

2016-02-01

We propose a novel computational approach to automatically identify the fetal heart rate patterns (fHRPs), which are reflective of sleep/awake states. By combining these patterns with presence or absence of movements, a fetal behavioral state (fBS) was determined. The expert scores were used as the gold standard and objective thresholds for the detection procedure were obtained using Receiver Operating Characteristics (ROC) analysis. To assess the performance, intraclass correlation was computed between the proposed approach and the mutually agreed expert scores. The detected fHRPs were then associated to their corresponding fBS based on the fetal movement obtained from fetal magnetocardiogaphic (fMCG) signals. This approach may aid clinicians in objectively assessing the fBS and monitoring fetal wellbeing. Copyright © 2015 Elsevier Ltd. All rights reserved.

ECG R-R peak detection on mobile phones.

PubMed

Sufi, F; Fang, Q; Cosic, I

2007-01-01

Mobile phones have become an integral part of modern life. Due to the ever increasing processing power, mobile phones are rapidly expanding its arena from a sole device of telecommunication to organizer, calculator, gaming device, web browser, music player, audio/video recording device, navigator etc. The processing power of modern mobile phones has been utilized by many innovative purposes. In this paper, we are proposing the utilization of mobile phones for monitoring and analysis of biosignal. The computation performed inside the mobile phone's processor will now be exploited for healthcare delivery. We performed literature review on RR interval detection from ECG and selected few PC based algorithms. Then, three of those existing RR interval detection algorithms were programmed on Java platform. Performance monitoring and comparison studies were carried out on three different mobile devices to determine their application on a realtime telemonitoring scenario.

Assessment of NDE Reliability Data

NASA Technical Reports Server (NTRS)

Yee, B. G. W.; Chang, F. H.; Couchman, J. C.; Lemon, G. H.; Packman, P. F.

1976-01-01

Twenty sets of relevant Nondestructive Evaluation (NDE) reliability data have been identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations has been formulated. A model to grade the quality and validity of the data sets has been developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, have been formulated for each NDE method. A comprehensive computer program has been written to calculate the probability of flaw detection at several confidence levels by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. Probability of detection curves at 95 and 50 percent confidence levels have been plotted for individual sets of relevant data as well as for several sets of merged data with common sets of NDE parameters.

Analysis of the Emitted Wavelet of High-Resolution Bowtie GPR Antennas

PubMed Central

Rial, Fernando I.; Lorenzo, Henrique; Pereira, Manuel; Armesto, Julia

2009-01-01

Most Ground Penetrating Radars (GPR) cover a wide frequency range by emitting very short time wavelets. In this work, we study in detail the wavelet emitted by two bowtie GPR antennas with nominal frequencies of 800 MHz and 1 GHz. Knowledge of this emitted wavelet allows us to extract as much information as possible from recorded signals, using advanced processing techniques and computer simulations. Following previously published methodology used by Rial et al. [1], which ensures system stability and reliability in data acquisition, a thorough analysis of the wavelet in both time and frequency domain is performed. Most of tests were carried out with air as propagation medium, allowing a proper analysis of the geometrical attenuation factor. Furthermore, we attempt to determine, for each antenna, a time zero in the records to allow us to correctly assign a position to the reflectors detected by the radar. Obtained results indicate that the time zero is not a constant value for the evaluated antennas, but instead depends on the characteristics of the material in contact with the antenna. PMID:22408523

A comparison of high-frequency noise levels on Cascadia Initiative ocean-bottom seismometers

NASA Astrophysics Data System (ADS)

Hilmo, R.; Wilcock, W. S. D.; Roland, E. C.; Bodin, P.; Connolly, J.

2017-12-01

The Cascadia Initiative (CI) included a four-year deployment of 70 ocean bottom seismometers (OBSs) on the Cascadia subduction zone and the Juan de Fuca plate for the purposes of characterizing seismicity and imaging the Earth's interior. The Cascadia subduction zone megathrust exhibits very low rates of seismicity relative to most other subduction zones, and there is great motivation to understand deformation on the megathrust because of its potential to produce a catastrophic M9 earthquake. An understanding of earthquake detectability of the CI network, based on knowledge of noise levels, could contribute to the interpretation of earthquake catalogs derived from the experiment and aid in the design of future networks. This project is aimed at estimating these thresholds of local earthquake detectability and how they change across the array both geographically and temporally. We characterize background noise levels recorded from 0.1 to 20 Hz with an emphasis on the frequency band used to detect local seismicity ( 3-15 Hz) to understand how noise levels depend on instrument design and environmental parameters including seafloor depth, season and oceanographic conditions. Our initial analysis of 3 weeks of vertical channel data in September, January, and May 2012-2013 shows that noise increase significantly moving from the continental shelf to deeper water. Noise levels at a given depth vary with instrument type but further analysis is required to determine whether this reflects variations in instrumental noise and ground coupling noise or errors in the scaling of the instrument response. There is also a strong seasonality in recorded noise levels at some frequencies, with winter noise levels exceeding spring and fall noise levels by up to 10 decibels in both the microseism band and in the fin whale calling band (15-20 Hz). In contrast, the seasonal noise level in the local seismicity band for a given instrument type and location shows smaller noise variation seasonally. We will extend our analysis to the full four-year data set and consider how variations in noise affect the threshold of earthquake detectability by comparing noise levels with expected body wave amplitudes and seismic catalogues.

Physical deterioration in an acute mental health unit: A quantitative retrospective analysis of medical emergencies.

PubMed

Porter, Joanne E; Cant, Robyn; Missen, Karen; Raymond, Anita; Churchill, Anne

2018-04-27

Nursing management of physical deterioration of patients within acute mental health settings is observed, recorded, and actively managed with the use of standardized Adult Deterioration Detection System (ADDS) charts. Patient deterioration may require the urgent assistance of a hospital rapid response or Medical Emergency Team. A five-and-a-half-year (2011-2016) audit of hospital-wide Medical Emergency Team attendances was conducted in an acute mental health unit of a single large 250 bed regional hospital in Victoria, Australia. Data were extracted from the hospitals' quality and patient safety program, RISKMan, and entered into a statistical data program for analysis. A total of 140 patient records were analysed, and the 'Worried' category (34%, n = 47) was the principle reason for a Medical Emergency Team call in a mental health ward, followed by hypotension (23%, n = 31) and a low Glasgow Coma Score (16%, n = 22). Upon further investigation of the 'Worried' category, the most common conditions recorded were an altered conscious state (22%, n = 9), low oxygen saturation (20%, n = 8), or chest pain (17%, n = 7). Activation of Medical Emergency Team calls predominantly occurred in the daylight morning hours (6am-12md). When data were compared to the general hospital patients, the context of the physiological deterioration of the mental health patients was strikingly similar. Further research is recommended to ascertain the extent and frequency with which staff working in mental health units are performing vital signs monitoring as an essential component of detection of early signs of physiological deterioration. © 2018 Australian College of Mental Health Nurses Inc.

Trend analysis of GIMMS and MODIS NDVI time series for establishing a land degradation neutrality national baseline

NASA Astrophysics Data System (ADS)

Gichenje, Helene; Godinho, Sergio

2017-04-01

Land degradation is a key global environment and development problem that is recognized as a priority by the international development community. The Sustainable Development Goals (SDGs) were adopted by the global community in 2015, and include a goal related to land degradation and the accompanying target to achieve a land degradation-neutral (LDN) world by 2030. The LDN concept encompasses two joint actions of reducing the rate of degradation and increasing the rate of restoration. Using Kenya as the study area, this study aims to develop and test a spatially explicit methodology for assessing and monitoring the operationalization of a land degradation neutrality scheme at the national level. Time series analysis is applied to Normalized Difference Vegetation Index (NDVI) satellite data records, based on the hypothesis that the resulting NDVI residual trend would enable successful detection of changes in vegetation photosynthetic capacity and thus serve as a proxy for land degradation and regeneration processes. Two NDVI data sets are used to identify the spatial and temporal distribution of degraded and regenerated areas: the long term coarse resolution (8km, 1982-2015) third generation Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g data record; and the shorter-term finer resolution (250m, 2001-2015) Moderate Resolution Imaging Spectroradiometer (MODIS) derived NDVI data record. Climate data (rainfall, temperature and soil moisture) are used to separate areas of human-induced vegetation productivity decline from those driven by climate dynamics. Further, weekly vegetation health (VH) indexes (4km, 1982-2015) developed by National Oceanic and Atmospheric Administration (NOAA), are assessed as indicators for early detection and monitoring of land degradation by estimating vegetation stress (moisture, thermal and combined conditions).

Near- and far-field infrasound monitoring in the Mediterranean area

NASA Astrophysics Data System (ADS)

Campus, Paola; Marchetti, Emanuele; Le Pichon, Alexis; Wallenstein, Nicolau; Ripepe, Maurizio; Kallel, Mohamed; Mialle, Pierrick

2013-04-01

The Mediterranean area is characterized by a number of very interesting sources of infrasound signals and offers a promising playground for the development of a deeper understanding of such sources and of the associated propagation models. The progress in the construction and certification of infrasound arrays belonging to the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) in the vicinity of this area has been complemented, in the last decade, by the construction of infrasound arrays established by several European research groups. The University of Florence (UniFi) plays a crucial role for the detection of infrasound signals in the Mediterranean area, having deployed since several years two infrasound arrays on Stromboli and Etna volcanoes, and, more recently, three infrasound arrays in the Alpine area of NW Italy and one infrasound array on the Apennines (Mount Amiata), designed and established in the framework of the ARISE Project. The IMS infrasound arrays IS42 (Graciosa, Azores, Portugal) and IS48 (Kesra, Tunisia) recorded, since the time of their certification, a number of far-field events which can be correlated with some near-field records of the infrasound arrays belonging to UniFi. An analysis of the results and potentialities of infrasound source's detections in near and far-field realized by IS42, IS48 and UniFi arrays in the Mediterranean area, with special focus on volcanic events is presented. The combined results deriving from the analysis of data recorded by the Unifi arrays and by the IS42 and IS48 arrays, in collaboration with the Department of Analyse et Surveillance (CEA/DASE), will generate a synergy which will certainly contribute to the progress of the ARISE Project.

An analysis of periodicities in the 1470 to 1974 Beijing precipitation record

NASA Technical Reports Server (NTRS)

Hameed, S.; Yeh, W. M.; Cess, R. D.; Wang, W. C.; Li, M. T.

1983-01-01

An analyis of a time series consisting of an annual index of dryness/wetness for the years 1470 to 1974 in Beijing, China is presented. Its power spectrum shows that dominant cycles occur with long periods of the order of 80 years. Cycles with periods of 11 and 22 years are weak or non-existent, but a significant signal at 18.7 years (which is also the period of a component of the lunar tide generating force) is detected. The long term variations in Beijing precipitation appear to lag long term (Gleissberg) variations in solar activity by nearly 75 years. A pattern which spans nearly 150 years in the Beijing record is found to be repeated with notable similarity.

Digital data detection and synchronization

NASA Technical Reports Server (NTRS)

Noack, T. L.; Morris, J. F.

1973-01-01

The primary accomplishments have been in the analysis and simulation of receivers and bit synchronizers. It has been discovered that tracking rate effects play, a rather fundamental role in both receiver and synchronizer performance, but that data relating to recorder time-base-error, for the proper characterization of this phenomenon, is in rather short supply. It is possible to obtain operationally useful tape recorder time-base-error data from high signal-to-noise ratio tapes using synchronizers with relatively wideband tracking loops. Low signal-to-noise ratio tapes examined in the same way would not be synchronizable. Additional areas of interest covered are receiver false lock, cycle slipping, and other unusual phenomena, which have been described to some extent in this and earlier reports and simulated during the study.

Multi-sensor investigation of the Sumatran Tsunami: observations and analysis of hydroacoustic, seismic, infrasonic, and tide gauge data

NASA Astrophysics Data System (ADS)

Bhattacharyya, J.; Pulli, J.; Gibson, R.; Upton, Z.

2005-05-01

We present an analysis of the acoustic signals from the December 26, 2004 Sumatra earthquakes, in conjunction with the seismic and tide gauge information from the event. The M9.0 mainshock and its aftershocks were recorded by a suite of seismic sensors around the globe, giving us information on its location and the source process. Recently installed sensor assets in the Indian Ocean have enabled us to study additional features of this significant event. Hydroacoustic signals were recorded by three hydrophone arrays, and the direction finding capability of these arrays allows us to examine the location, time and extent of the T-wave generation process. We detect a clear variation of the back-azimuth that is consistent with the spatial extent of the source rupture. Recordings from nearly co-located seismometers provide insights into the acoustic-to-seismic conversion process for T-waves at islands, along with the variation in signal characteristics with source size. Two separate infrasound arrays detect the atmospheric signals generated by the event, along with additional observations of the seismic surface wave and the T-phase. We will present a comparison of the signals from the mainshock, as a function of location and size, with those from aftershocks and similar events in the nearby region. Our acoustic observations compare favorably with model predictions of wave propagation in the region. For the hydroacoustic data, the azimuth, arrival time, and signal blockage characteristics, from three separate arrays, associate the onset of the signal with the mainshock and with a time extent consistent with the rupture propagation. Our analysis of the T-phase travel times suggests that the seismic-to-acoustic conversion occurs more than 100 km from the epicenter. The infrasound signal's arrival time and signal duration are consistent with both stratospheric and thermospheric propagation from a source region near the mainshock. We use the tide gauge data from stations around the Indian Ocean to identify the arrival time of the Tsunami. The acoustic and seismic signals associated with the earthquakes arrive at the remote stations significantly ahead of the Tsunami. We combine the information from the various sensors to investigate the ability of the acoustic stations to detect the Tsunami.

Automated analysis of cell migration and nuclear envelope rupture in confined environments.

PubMed

Elacqua, Joshua J; McGregor, Alexandra L; Lammerding, Jan

2018-01-01

Recent in vitro and in vivo studies have highlighted the importance of the cell nucleus in governing migration through confined environments. Microfluidic devices that mimic the narrow interstitial spaces of tissues have emerged as important tools to study cellular dynamics during confined migration, including the consequences of nuclear deformation and nuclear envelope rupture. However, while image acquisition can be automated on motorized microscopes, the analysis of the corresponding time-lapse sequences for nuclear transit through the pores and events such as nuclear envelope rupture currently requires manual analysis. In addition to being highly time-consuming, such manual analysis is susceptible to person-to-person variability. Studies that compare large numbers of cell types and conditions therefore require automated image analysis to achieve sufficiently high throughput. Here, we present an automated image analysis program to register microfluidic constrictions and perform image segmentation to detect individual cell nuclei. The MATLAB program tracks nuclear migration over time and records constriction-transit events, transit times, transit success rates, and nuclear envelope rupture. Such automation reduces the time required to analyze migration experiments from weeks to hours, and removes the variability that arises from different human analysts. Comparison with manual analysis confirmed that both constriction transit and nuclear envelope rupture were detected correctly and reliably, and the automated analysis results closely matched a manual analysis gold standard. Applying the program to specific biological examples, we demonstrate its ability to detect differences in nuclear transit time between cells with different levels of the nuclear envelope proteins lamin A/C, which govern nuclear deformability, and to detect an increase in nuclear envelope rupture duration in cells in which CHMP7, a protein involved in nuclear envelope repair, had been depleted. The program thus presents a versatile tool for the study of confined migration and its effect on the cell nucleus.

Design and Validation of a Breathing Detection System for Scuba Divers.

PubMed

Altepe, Corentin; Egi, S Murat; Ozyigit, Tamer; Sinoplu, D Ruzgar; Marroni, Alessandro; Pierleoni, Paola

2017-06-09

Drowning is the major cause of death in self-contained underwater breathing apparatus (SCUBA) diving. This study proposes an embedded system with a live and light-weight algorithm which detects the breathing of divers through the analysis of the intermediate pressure (IP) signal of the SCUBA regulator. A system composed mainly of two pressure sensors and a low-power microcontroller was designed and programmed to record the pressure sensors signals and provide alarms in absence of breathing. An algorithm was developed to analyze the signals and identify inhalation events of the diver. A waterproof case was built to accommodate the system and was tested up to a depth of 25 m in a pressure chamber. To validate the system in the real environment, a series of dives with two different types of workload requiring different ranges of breathing frequencies were planned. Eight professional SCUBA divers volunteered to dive with the system to collect their IP data in order to participate to validation trials. The subjects underwent two dives, each of 52 min on average and a maximum depth of 7 m. The algorithm was optimized for the collected dataset and proved a sensitivity of inhalation detection of 97.5% and a total number of 275 false positives (FP) over a total recording time of 13.9 h. The detection algorithm presents a maximum delay of 5.2 s and requires only 800 bytes of random-access memory (RAM). The results were compared against the analysis of video records of the dives by two blinded observers and proved a sensitivity of 97.6% on the data set. The design includes a buzzer to provide audible alarms to accompanying dive buddies which will be triggered in case of degraded health conditions such as near drowning (absence of breathing), hyperventilation (breathing frequency too high) and skip-breathing (breathing frequency too low) measured by the improper breathing frequency. The system also measures the IP at rest before the dive and indicates with flashing light-emitting diodes and audible alarm the regulator malfunctions due to high or low IP that may cause fatal accidents during the dive by preventing natural breathing. It is also planned to relay the alarm signal to underwater and surface rescue authorities by means of acoustic communication.

T-phase and tsunami pressure waveforms recorded by near-source IMS water-column hydrophone triplets during the 2015 Chile earthquake

NASA Astrophysics Data System (ADS)

Matsumoto, H.; Haralabus, G.; Zampolli, M.; Özel, N. M.

2016-12-01

Underwater acoustic signal waveforms recorded during the 2015 Chile earthquake (Mw 8.3) by the hydrophones of hydroacoustic station HA03, located at the Juan Fernandez Islands, are analyzed. HA03 is part of the Comprehensive Nuclear-Test-Ban Treaty International Monitoring System. The interest in the particular data set stems from the fact that HA03 is located only approximately 700 km SW from the epicenter of the earthquake. This makes it possible to study aspects of the signal associated with the tsunamigenic earthquake, which would be more difficult to detect had the hydrophones been located far from the source. The analysis shows that the direction of arrival of the T phase can be estimated by means of a three-step preprocessing technique which circumvents spatial aliasing caused by the hydrophone spacing, the latter being large compared to the wavelength. Following this preprocessing step, standard frequency-wave number analysis (F-K analysis) can accurately estimate back azimuth and slowness of T-phase signals. The data analysis also shows that the dispersive tsunami signals can be identified by the water-column hydrophones at the time when the tsunami surface gravity wave reaches the station.

Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants

PubMed Central

Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

2016-01-01

The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants. PMID:27304876

Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants.

PubMed

Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

2016-01-01

The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants.

Decadal Seasonal Shifts of Precipitation and Temperature in TRMM and AIRS Data

NASA Technical Reports Server (NTRS)

Savtchenko, Andrey; Huffman, George; Meyer, David; Vollmer, Bruce

2018-01-01

We present results from an analysis of seasonal phase shifts in the global precipitation and surface temperatures. We use data from the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Algorithm (TMPA), and the Atmospheric Infrared Sounder (AIRS) on Aqua satellite, all hosted at NASA Goddard Earth Science Data and Information Services Center (GES DISC). We explore the information content and data usability by first aggregating daily grids from the entire records of both missions to pentad (5-day) series which are then processed using Singular Value Decomposition approach. A strength of this approach is the normalized principal components that can then be easily converted from real to complex time series. Thus, we can separate the most informative, the seasonal, components and analyze unambiguously for potential seasonal phase drifts. TMPA and AIRS records represent correspondingly 20 and 15 years of data, which allows us to run simple “phase learning†from the first 5 years of records and use it as reference. The most recent 5 years are then phase-compared with the reference. We demonstrate that the seasonal phase of global precipitation and surface temperatures has been stable in the past two decades. However, a small global trend of delayed precipitation, and earlier arrival of surface temperatures seasons, are detectable at 95% confidence level. Larger phase shifts are detectable at regional level, in regions recognizable from the Eigen vectors to having strong seasonal patterns. For instance, in Central North America, including the North American Monsoon region, confident phase shifts of 1-2 days per decade are detected at 95% confidence level. While seemingly symbolic, these shifts are indicative of larger changes in the Earth Climate System. We thus also demonstrate a potential usability scenario of Earth Science Data Records curated at the NASA GES DISC in partnership with Earth Science Missions.

A Long-Term BCI Study With ECoG Recordings in Freely Moving Rats.

PubMed

Costecalde, Thomas; Aksenova, Tetiana; Torres-Martinez, Napoleon; Eliseyev, Andriy; Mestais, Corinne; Moro, Cecile; Benabid, Alim Louis

2018-02-01

Brain Computer Interface (BCI) studies are performed in an increasing number of applications. Questions are raised about electrodes, data processing and effectors. Experiments are needed to solve these issues. To develop a simple BCI set-up to easier studies for improving the mathematical tools to process the ECoG to control an effector. We designed a simple BCI using transcranial electrodes (17 screws, three mechanically linked to create a common reference, 14 used as recording electrodes) to record Electro-Cortico-Graphic (ECoG) neuronal activities in rodents. The data processing is based on an online self-paced non-supervised (asynchronous) BCI paradigm. N-way partial least squares algorithm together with Continuous Wavelet Transformation of ECoG recordings detect signatures related to motor activities. Signature detection in freely moving rats may activate external effectors during a behavioral task, which involved pushing a lever to obtain a reward. After routine training, we showed that peak brain activity preceding a lever push (LP) to obtain food reward was located mostly in the cerebellar cortex with a higher correlation coefficient, suggesting a strong postural component and also in the occipital cerebral cortex. Analysis of brain activities provided a stable signature in the high gamma band (∼180Hz) occurring within 1500 msec before the lever push approximately around -400 msec to -500 msec. Detection of the signature from a single cerebellar cortical electrode triggers the effector with high efficiency (68% Offline and 30% Online) and rare false positives per minute in sessions about 30 minutes and up to one hour (∼2 online and offline). In summary, our results are original as compared to the rest of the literature, which involves rarely rodents, a simple BCI set-up has been developed in rats, the data show for the first time long-term, up to one year, unsupervised online control of an effector. © 2017 International Neuromodulation Society.

Inter-ictal spike detection using a database of smart templates.

PubMed

Lodder, Shaun S; Askamp, Jessica; van Putten, Michel J A M

2013-12-01

Visual analysis of EEG is time consuming and suffers from inter-observer variability. Assisted automated analysis helps by summarizing key aspects for the reviewer and providing consistent feedback. Our objective is to design an accurate and robust system for the detection of inter-ictal epileptiform discharges (IEDs) in scalp EEG. IED Templates are extracted from the raw data of an EEG training set. By construction, the templates are given the ability to learn by searching for other IEDs within the training set using a time-shifted correlation. True and false detections are remembered and classifiers are trained for improving future predictions. During detection, trained templates search for IEDs in the new EEG. Overlapping detections from all templates are grouped and form one IED. Certainty values are added based on the reliability of the templates involved. For evaluation, 2160 templates were used on an evaluation dataset of 15 continuous recordings containing 241 IEDs (0.79/min). Sensitivities up to 0.99 (7.24fp/min) were reached. To reduce false detections, higher certainty thresholds led to a mean sensitivity of 0.90 with 2.36fp/min. By using many templates, this technique is less vulnerable to variations in spike morphology. A certainty value for each detection allows the system to present findings in a more efficient manner and simplifies the review process. Automated spike detection can assist in visual interpretation of the EEG which may lead to faster review times. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Congruence analysis of point clouds from unstable stereo image sequences

NASA Astrophysics Data System (ADS)

Jepping, C.; Bethmann, F.; Luhmann, T.

2014-06-01

This paper deals with the correction of exterior orientation parameters of stereo image sequences over deformed free-form surfaces without control points. Such imaging situation can occur, for example, during photogrammetric car crash test recordings where onboard high-speed stereo cameras are used to measure 3D surfaces. As a result of such measurements 3D point clouds of deformed surfaces are generated for a complete stereo sequence. The first objective of this research focusses on the development and investigation of methods for the detection of corresponding spatial and temporal tie points within the stereo image sequences (by stereo image matching and 3D point tracking) that are robust enough for a reliable handling of occlusions and other disturbances that may occur. The second objective of this research is the analysis of object deformations in order to detect stable areas (congruence analysis). For this purpose a RANSAC-based method for congruence analysis has been developed. This process is based on the sequential transformation of randomly selected point groups from one epoch to another by using a 3D similarity transformation. The paper gives a detailed description of the congruence analysis. The approach has been tested successfully on synthetic and real image data.

What proportions of focal liver lesions detected by unenhanced ultrasound are inconclusive?

PubMed Central

Willits, Iain; Burn, Julie; Cole, Helen; Hoare, Tim

2014-01-01

In August 2012, the National Institute for Health and Care Excellence produced positive diagnostics guidance on the ultrasound contrast agent SonoVue®, but recommended further research involving an estimation of the proportion of unenhanced ultrasound scans reporting, but not characterising, focal liver lesions, particularly in cirrhotic livers. Patient records from the Radiology Information System of an acute hospital trust were progressively filtered based on categorical fields and keywords in the free text reports, to obtain ultrasound records including the liver that were appropriate for manual analysis. In total, 21,731 records referred from general practice or out-patient clinics were analysed. Patients described as having cirrhosis were analysed as a subgroup. After automatic exclusion of records considered likely to be negative, 5812 records were manually read and categorised as focal liver lesion inconclusive, benign or malignant. In the general practice cohort of 9175 records, 746 reported the presence of one or more focal liver lesions, with 18.4% (95% CI 15.7% to 21.3%) of these records mentioning an inconclusive focal liver lesion. In the out-patient cohort of 12,556 records, 1437 reported one or more focal liver lesions, and 29.4% (95% CI 26.9% to 32.0%) of these were inconclusive. Cirrhosis was reported in 10.8% of the out-patient scans that also reported a focal liver lesion, and 47.4% (95% CI 39.3% to 55.6%) of these scans had an inconclusive focal liver lesion, compared with 27.3% (95% CI 24.9% to 29.8%) that were inconclusive in non-cirrhotic livers (odds ratio 2.4; 95% CI 1.7 to 3.4). This retrospective study indicates that unenhanced ultrasound scans, in which a focal liver lesion is detected, are frequently inconclusive, with the probability of an inconclusive scan being greater in out-patient than general practice referrals. Inconclusive focal liver lesions were also reported in greater proportions of cirrhotic than non-cirrhotic livers. The results of this research will inform future updates of National Institute for Health and Care Excellence diagnostics guidance. PMID:25949268

Spatiotemporal activity patterns detected from single cell measurements from behaving animals

NASA Astrophysics Data System (ADS)

Villa, Alessandro E. P.; Tetko, Igor V.

1999-03-01

Precise temporal patterning of activity within and between neurons has been predicted on theoretical grounds, and found in the spike trains of neurons recorded from anesthetized and conscious animals, in association with sensor stimuli and particular phases of task performance. However, the functional significance of such patterning in the generation of behavior has not been confirmed. We recorded from multiple single neurons in regions of rat auditory cortex during the waiting period of a Go/NoGo task. During this time the animal waited for an auditory signal with high cognitive load. Of note is the fact that neural activity during the period analyzed was essentially stationary, with no event related variability in firing. Detected patterns therefore provide a measure of brain state that could not be addressed by standard methods relying on analysis of changes in mean discharge rate. The possibility is discussed that some patterns might reflect a preset bias to a particular response, formed in the waiting period. Others patterns might reflect a state of prior preparation of appropriate neural assemblies for analyzing a signal that is expected but of unknown behavioral valence.

Valid screening questions useful to diagnose hand and forearm eczema are available in the Spanish language, a new tool for global research.

PubMed

Martí-Margarit, Anna; Manresa, Josep M; Herdman, Mike; Pujol, Ramon; Serra, Consol; Flyvholm, Mary-Ann; Giménez-Arnau, Ana M

2015-04-01

Hand eczema is an impacting cutaneous disease. Globally valid tools that help to diagnose hand and forearm eczema are required. To validate the questions to detect hand and/or forearm eczema included in the "Nordic Occupational Skin Questionnaire" (NOSQ-2002) in the Spanish language. A prospective pilot study was conducted with 80 employees of a cleaning company and a retrospective one involving 2,546 individuals. The responses were analysed for sensitivity, specificity and positive and negative predictive values. The final diagnosis according to the patients' hospital records, the specialty care records and the physical examination was taken as gold standard. The Dermatology Life Quality Index (DLQI) was also evaluated. Sensitivity and specificity, in a worst case scenario (WC) combining both questions, were 96.5% and 66.7%, respectively, and in a per protocol (PP) analysis, were 96.5% and 75.2%. The questions validated detected eczema effectively, making this tool suitable for use e.g. in multicentre epidemiological studies or clinical trials.