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Sample records for resting ecg analysis

  1. [Analysis of pacemaker ECGs].

    PubMed

    Israel, Carsten W; Ekosso-Ejangue, Lucy; Sheta, Mohamed-Karim

    2015-09-01

    The key to a successful analysis of a pacemaker electrocardiogram (ECG) is the application of the systematic approach used for any other ECG without a pacemaker: analysis of (1) basic rhythm and rate, (2) QRS axis, (3) PQ, QRS and QT intervals, (4) morphology of P waves, QRS, ST segments and T(U) waves and (5) the presence of arrhythmias. If only the most obvious abnormality of a pacemaker ECG is considered, wrong conclusions can easily be drawn. If a systematic approach is skipped it may be overlooked that e.g. atrial pacing is ineffective, the left ventricle is paced instead of the right ventricle, pacing competes with intrinsic conduction or that the atrioventricular (AV) conduction time is programmed too long. Apart from this analysis, a pacemaker ECG which is not clear should be checked for the presence of arrhythmias (e.g. atrial fibrillation, atrial flutter, junctional escape rhythm and endless loop tachycardia), pacemaker malfunction (e.g. atrial or ventricular undersensing or oversensing, atrial or ventricular loss of capture) and activity of specific pacing algorithms, such as automatic mode switching, rate adaptation, AV delay modifying algorithms, reaction to premature ventricular contractions (PVC), safety window pacing, hysteresis and noise mode. A systematic analysis of the pacemaker ECG almost always allows a probable diagnosis of arrhythmias and malfunctions to be made, which can be confirmed by pacemaker control and can often be corrected at the touch of the right button to the patient's benefit.

  2. [Risk stratification of asymptomatic subjects using resting ECG and stress ECG].

    PubMed

    Möhlenkamp, Stefan; Wieneke, Heinrich; Sack, Stefan; Erbel, Raimund

    2007-08-01

    The resting electrocardiogram (ECG) and stress ECG are established tests in the array of cardiovascular diagnostic modalities. In addition to their diagnostic value for structural heart disease and rhythm disorders, ECGs at rest or during stress also contain prognostically relevant information. Several ECG abnormalities, e.g., left ventricular hypertrophy (LVH), Q waves, ST segment changes, left bundle branch block, atrial fibrillation or QT interval prolongation, were shown to be associated with cardiovascular events. Differences in study design, the cohorts of investigation and morphological definitions of ECG abnormalities may in part be responsible for the abnormalities not being implemented in risk stratification algorithms. The non-ST-segment-related variables in stress testing, e.g., functional capacity, chronotropic (in)competence, heart rate (HR) recovery, and the HR/ST index and slope, could be identified as prognostically relevant markers in population-based studies. For many of these resting and stress ECG-based abnormalities, associations with the extent of subclinical atherosclerosis in persons without established coronary heart disease were observed, indicating a preclinical relationship between epicardial atherosclerosis and myocardial pathology. The resting and the stress ECG provide a number of prognostically relevant indices that can easily be obtained in routine clinical practice, but have thus far found little acceptance for risk stratification of asymptomatic individuals.

  3. Computational Analysis of ECGs

    NASA Astrophysics Data System (ADS)

    Waters, Kevin

    2013-03-01

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

  4. Noninvasive Fetal ECG analysis

    PubMed Central

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

    2014-01-01

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

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

    DTIC Science & Technology

    1992-02-01

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

  6. Benefit of ECG-gated rest and stress N-13 cardiac PET imaging for quantification of LVEF in ischemic patients.

    PubMed

    Peelukhana, Srikara V; Banerjee, Rupak; Kolli, Kranthi K; Fernandez-Ulloa, Mariano; Arif, Imran; Effat, Mohamed; Helmy, Tarek; Kerr, Hanan

    2015-10-01

    ECG-gated rest-stress cardiac PET can lead to simultaneous quantification of both left ventricular ejection fraction and flow impairment. In this study, our aim was to assess the benefit of rest and stress PET ejection fraction (EF) (EFp) in relation to single-photon emission computed tomography (SPECT) EF (EFs) and echocardiography EF (EFe). To this effect, the EFp was compared with EFs and EFe. Further, the relation between rest and stress EFp was also assessed. ECG-gated N-13 ammonia rest and stress PET imaging was performed in 26 patients. EFp values were obtained using gated reconstruction of the data in Flowquant. In 13 patients, EFs and EFe values were obtained through chart review. Correlation, analysis of variance, and Bland-Altman analyses were performed. P values less than 0.05 were used for statistical significance. The rest and stress EFp values correlated significantly (r=0.80 and 0.71, respectively; P<0.05) with EFs values. There was moderate correlation with statistical significance (P<0.05) between the rest and stress EFp and EFe values (r=0.58 and 0.50, respectively). The mean rest and stress EFp values were not significantly different from mean EFs values. Also, the rest EFp and stress EFp values correlated well (r=0.81, P<0.05) and were not significantly different. Bland-Altman analysis showed no significant bias between the rest and stress EFp, and EFs, and EFe values. Rest and stress EFp values obtained through an ECG-gated PET scan can be used for clinical diagnosis in place of conventional methods like SPECT and echocardiography.

  7. Added value of a resting ECG neural network that predicts cardiovascular mortality.

    PubMed

    Perez, Marco V; Dewey, Frederick E; Tan, Swee Y; Myers, Jonathan; Froelicher, Victor F

    2009-01-01

    The resting 12-lead electrocardiogram (ECG) remains the most commonly used test in evaluating patients with suspected cardiovascular disease. Prognostic values of individual findings on the ECG have been reported but may be of limited use. The characteristics of 45,855 ECGs ordered by physician's discretion were first recorded and analyzed using a computerized system. Ninety percent of these ECGs were used to train an artifical neural network (ANN) to predict cardiovascular mortality (CVM) based on 132 ECG and four demographic characteristics. The ANN generated a Resting ECG Neural Network (RENN) score that was then tested in the remaining ECGs. The RENN score was finally assessed in a cohort of 2189 patients who underwent exercise treadmill testing and were followed for CVM. The RENN score was able to better predict CVM compared to individual ECG markers or a traditional Cox regression model in the testing cohort. Over a mean of 8.6 years, there were 156 cardiovascular deaths in the treadmill cohort. Among the patients who were classified as intermediate risk by Duke Treadmill Scoring (DTS), the third tertile of the RENN score demonstrated an adjusted Cox hazard ratio of 5.4 (95% CI 2.0-15.2) compared to the first RENN tertile. The 10-year CVM was 2.8%, 8.6% and 22% in the first, second and third RENN tertiles, respectively. An ANN that uses the resting ECG and demographic variables to predict CVM was created. The RENN score can further risk stratify patients deemed at moderate risk on exercise treadmill testing.

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  9. Principal Component Analysis in ECG Signal Processing

    NASA Astrophysics Data System (ADS)

    Castells, Francisco; Laguna, Pablo; Sörnmo, Leif; Bollmann, Andreas; Roig, José Millet

    2007-12-01

    This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.

  10. A spline framework for ECG analysis.

    PubMed

    Guilak, Farzin G; McNames, James

    2011-01-01

    In this effort we introduce a spline framework for ECG waveform analysis, with initial application to the ECG delineation (segmentation) problem. The framework comprises knot initialization, spline interpolant, error metric, and knot location optimization to parametrically represent the waveform for analysis, classification, or compression. Choice of these constituents is driven by the application of the framework. For our initial application of ECG delineation, we use the framework to identify characteristic points corresponding to waveform onset and offset times, peak values, and junction points. These are represented mathematically as critical points and points of inflection, which serve as knot locations for linear or cubic Hermite interpolants in the framework. Preliminary tests on a limited but diverse set of morphologies from the European ST-T database indicate that the framework obtains knot locations corresponding to characteristic points, and the resultant interpolated waveform represents the original signal well with low mean squared error.

  11. A Mixed Approach Of Automated ECG Analysis

    NASA Astrophysics Data System (ADS)

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

    1982-11-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  13. [Wireless ECG transfer and centralized system of ECG analysis and storage. Experience with easy ECG usage in the Russian Cardiological Research Center].

    PubMed

    2012-01-01

    Methods of wire and wireless ECG remote registration anda centralized system of ECG reception, analysis and storage are outlined in the context of setting up computer case history. Qualitative assessment of an algorithm of computer syndromal diagnosis used in the Easy ECG system is presented. The system comprises an ECG recorder digital amplifier and software. The system is easy to use and is recommended for introduction into wide medical practice.

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

    DTIC Science & Technology

    1985-12-01

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

  15. Preprocessing and Analysis of Digitized ECGs

    NASA Astrophysics Data System (ADS)

    Villalpando, L. E. Piña; Kurmyshev, E.; Ramírez, S. Luna; Leal, L. Delgado

    2008-08-01

    In this work we propose a methodology and programs in MatlabTM that perform the preprocessing and analysis of the derivative D1 of ECGs. The program makes the correction to isoelectric line for each beat, calculates the average cardiac frequency and its standard deviation, generates a file of amplitude of P, Q and T waves, as well as the segments and intervals important of each beat. Software makes the normalization of beats to a standard rate of 80 beats per minute, the superposition of beats is done centering R waves, before and after normalizing the amplitude of each beat. The data and graphics provide relevant information to the doctor for diagnosis. In addition, some results are displayed similar to those presented by a Holter recording.

  16. 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.

  17. Separation and Analysis of Fetal-ECG Signals From Compressed Sensed Abdominal ECG Recordings.

    PubMed

    Da Poian, Giulia; Bernardini, Riccardo; Rinaldo, Roberto

    2016-06-01

    Analysis of fetal electrocardiogram (f-ECG) waveforms as well as fetal heart-rate (fHR) evaluation provide important information about the condition of the fetus during pregnancy. A continuous monitoring of f-ECG, for example using the technologies already applied for adults ECG tele-monitor-ing (e.g., Wireless Body Sensor Networks (WBSNs)), may increase early detection of fetal arrhythmias. In this study, we propose a novel framework, based on compressive sensing (CS) theory, for the compression and joint detection/classification of mother and fetal heart beats. Our scheme is based on the sparse representation of the components derived from independent component analysis (ICA), which we propose to apply directly in the compressed domain. Detection and classification is based on the activated atoms in a specifically designed reconstruction dictionary. Validation of the proposed compression and detection framework has been done on two publicly available datasets, showing promising results (sensitivity S = 92.5 %, P += 92 % , F1 = 92.2 % for the Silesia dataset and S = 78 % , P += 77 %, F1 = 77.5 % for the Challenge dataset A, with average reconstruction quality PRD = 8.5 % and PRD = 7.5 %, respectively). The experiments confirm that the proposed framework may be used for compression of abdominal f-ECG and to obtain real-time information of the fHR, providing a suitable solution for real time, very low-power f-ECG monitoring. To the authors' knowledge, this is the first time that a framework for the low-power CS compression of fetal abdominal ECG is proposed combined with a beat detector for an fHR estimation.

  18. Prediction of severe coronary artery disease using computerized ECG measurements and discriminant function analysis.

    PubMed

    Moussa, I; Rodriguez, M; Froning, J; Froelicher, V F

    1992-01-01

    This study tested the hypothesis that discriminant function analysis of clinical and exercise-test variables including computerized ST measurements could improve the prediction of severe coronary artery disease. Secondary objectives were to demonstrate the effect of digoxin and/or resting electrocardiographic (ECG) abnormalities, and to evaluate the relative importance of ST measurements made during the recovery phase and in the three lead group areas. The design was a retrospective analysis of data collected during exercise testing and coronary angiography. The ECG data were gathered and stored in digital format on optical discs and all ST measurements were made off-line using the authors' own software. Univariate and multivariate analytic methods were used to analyze all pretest characteristics as well as hemodynamic and computerized ECG responses to exercise. A 1,000-bed Veterans Affairs Medical Center served as the setting. The study included 446 male veterans who underwent a sign or symptom limited treadmill exercise test and coronary angiography. Analysis was also performed on a subset of this population formed by excluding patients receiving digoxin or with resting ECGs exhibiting left ventricular hypertrophy or ST depression (n = 328). In the total study population, the authors derived a treadmill score using discriminant function analysis. This score included: (1) the time-slope area in lead V5 during recovery; (2) delta heart rate; (3) angina pectoris during the exercise test; and (4) presence of diagnostic Q waves on the resting ECG. This score was effective in predicting triple vessel/left main disease and outperformed exercise-induced ST depression for predicting severe coronary artery disease. After exclusion of patients with ECGs exhibiting left ventricular hypertrophy or resting ST depression and patients receiving digoxin, discriminant function analysis chose: (1) the time-slope area in lead V5 during recovery and (2) delta heart rate. Exclusion of

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    DTIC Science & Technology

    1985-12-01

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

  3. Predictive value of casual ECG-based resting heart rate compared with resting heart rate obtained from Holter recording.

    PubMed

    Carlson, Nicholas; Dixen, Ulrik; Marott, Jacob L; Jensen, Magnus T; Jensen, Gorm B

    2014-03-01

    Elevated resting heart rate (RHR) is associated with cardiovascular mortality and morbidity. Assessment of heart rate (HR) from Holter recording may afford a more precise estimate of the effect of RHR on cardiovascular risk, as compared to casual RHR. Comparative analysis was carried out in an age-stratified subsample of 131 subjects in the Copenhagen City Heart Study (CCHS). Casual RHR was assessed from electrocardiograms recorded during clinical assessment. Hourly daytime HRs were mapped by Holter recording. Holter RHR was defined as the average of the lowest 3 hourly HRs recorded and mean HR calculated from all daytime HRs. Follow-up was recorded from public registers. Outcome measure was hazard rate for the combined endpoint of cardiovascular mortality, non-fatal heart failure and non-fatal acute myocardial infarction. Comparison of casual RHR, Holter RHR and mean HR by Multivariate Cox regression was performed. A total of 57 composite endpoints occurred during 17.1 years of follow-up. Regression analysis suggests correlation between Casual RHR and Holter RHR. Multivariate Cox regression analysis adjusted for gender and age demonstrated hazard rates of 1.02 (p = 0.079) for casual RHR, 1.04 (p = 0.036*) for Holter RHR, and 1.03 (p = 0.093) for mean HR for each 10 beat increment in HR. In a comparative analysis on the correlation and significance of differing RHR measurement modalities RHR measured by 24-hour Holter recording was found to be marginally superior as a predictor of cardiovascular morbidity and mortality. The results presented here do not however warrant the abandonment of a tested epidemiological variable.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2012-10-01

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

  7. Holter triage ambulatory ECG analysis. Accuracy and time efficiency.

    PubMed

    Cooper, D H; Kennedy, H L; Lyyski, D S; Sprague, M K

    1996-01-01

    Triage ambulatory electrocardiographic (ECG) analysis permits relatively unskilled office workers to submit 24-hour ambulatory ECG Holter tapes to an automatic instrument (model 563, Del Mar Avionics, Irvine, CA) for interpretation. The instrument system "triages" what it is capable of automatically interpreting and rejects those tapes (with high ventricular arrhythmia density) requiring thorough analysis. Nevertheless, a trained cardiovascular technician ultimately edits what is accepted for analysis. This study examined the clinical validity of one manufacturer's triage instrumentation with regard to accuracy and time efficiency for interpreting ventricular arrhythmia. A database of 50 Holter tapes stratified for frequency of ventricular ectopic beats (VEBs) was examined by triage, conventional, and full-disclosure hand-count Holter analysis. Half of the tapes were found to be automatically analyzable by the triage method. Comparison of the VEB accuracy of triage versus conventional analysis using the full-disclosure hand count as the standard showed that triage analysis overall appeared as accurate as conventional Holter analysis but had limitations in detecting ventricular tachycardia (VT) runs. Overall sensitivity, positive predictive accuracy, and false positive rate for the triage ambulatory ECG analysis were 96, 99, and 0.9%, respectively, for isolated VEBs, 92, 93, and 7%, respectively, for ventricular couplets, and 48, 93, and 7%, respectively, for VT. Error in VT detection by triage analysis occurred on a single tape. Of the remaining 11 tapes containing VT runs, accuracy was significantly increased, with a sensitivity of 86%, positive predictive accuracy of 90%, and false positive rate of 10%. Stopwatch-recorded time efficiency was carefully logged during both triage and conventional ambulatory ECG analysis and divided into five time phases: secretarial, machine, analysis, editing, and total time. Triage analysis was significantly (P < .05) more time

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

    PubMed

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

    2009-01-01

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

  9. Debatable issues in automated ECG reporting.

    PubMed

    Macfarlane, Peter W; Mason, Jay W; Kligfield, Paul; Sommargren, Claire E; Drew, Barbara; van Dam, Peter; Abächerli, Roger; Albert, David E; Hodges, Morrison

    2017-09-01

    Although automated ECG analysis has been available for many years, there are some aspects which require to be re-assessed with respect to their value while newer techniques which are worthy of review are beginning to find their way into routine use. At the annual International Society of Computerized Electrocardiology conference held in April 2017, four areas in particular were debated. These were a) automated 12 lead resting ECG analysis; b) real time out of hospital ECG monitoring; c) ECG imaging; and d) single channel ECG rhythm interpretation. One speaker presented the positive aspects of each technique and another outlined the more negative aspects. Debate ensued. There were many positives set out for each technique but equally, more negative features were not in short supply, particularly for out of hospital ECG monitoring. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  11. PDF-ECG in clinical practice: A model for long-term preservation of digital 12-lead ECG data.

    PubMed

    Sassi, Roberto; Bond, Raymond R; Cairns, Andrew; Finlay, Dewar D; Guldenring, Daniel; Libretti, Guido; Isola, Lamberto; Vaglio, Martino; Poeta, Roberto; Campana, Marco; Cuccia, Claudio; Badilini, Fabio

    2017-08-12

    In clinical practice, data archiving of resting 12-lead electrocardiograms (ECGs) is mainly achieved by storing a PDF report in the hospital electronic health record (EHR). When available, digital ECG source data (raw samples) are only retained within the ECG management system. The widespread availability of the ECG source data would undoubtedly permit successive analysis and facilitate longitudinal studies, with both scientific and diagnostic benefits. PDF-ECG is a hybrid archival format which allows to store in the same file both the standard graphical report of an ECG together with its source ECG data (waveforms). Using PDF-ECG as a model to address the challenge of ECG data portability, long-term archiving and documentation, a real-world proof-of-concept test was conducted in a northern Italy hospital. A set of volunteers undertook a basic ECG using routine hospital equipment and the source data captured. Using dedicated web services, PDF-ECG documents were then generated and seamlessly uploaded in the hospital EHR, replacing the standard PDF reports automatically generated at the time of acquisition. Finally, the PDF-ECG files could be successfully retrieved and re-analyzed. Adding PDF-ECG to an existing EHR had a minimal impact on the hospital's workflow, while preserving the ECG digital data. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Using simulated noise to define optimal QT intervals for computer analysis of ambulatory ECG.

    PubMed

    Tikkanen, P E; Sellin, L C; Kinnunen, H O; Huikuri, H V

    1999-01-01

    The ambulatory electrocardiogram (ECG) is an important medical tool, not only for diagnosis of adverse cardiac events, but also to predict the risk of such events occurring. The 24-hour ambulatory ECG has certain problems and drawbacks because the signal is corrupted by noise from various sources and also several other conditions which may alter the ECG morphology. We have developed a Windows based program for the computer analysis of ambulatory ECG which attempts to address these problems. The software includes options for importing ECG data, different methods of waveform analysis, data-viewing, and exporting the extracted time series. In addition, the modular structure allows for flexible maintenance and expansion of the software. The ECG was recorded using a Holter device and oversampled to enhance the fidelity of the low sampling rate of the ambulatory ECG. The influence of different sampling rates on the interval variability were studied. The noise sensitivity of the implemented algorithm was tested with several types of simulated noise and the precision of the interval measurement was reported with SD values. Our simulations showed that, in most of the cases, defining the end of QT interval at the maximum of the T wave gave the most precise measurement. The definition of the onset of the ventricular repolarization duration is most precisely made on the maximum or descending maximal slope of the R wave. We also analyzed some examples of time series from patients using power spectrum estimates in order to validate the low level QT interval variability.

  13. Rest

    PubMed Central

    2015-01-01

    Rest is a health-related phenomenon. Researchers have explored the phenomenon of rest, but further concept development is recommended. The aim of my study was to develop and describe a concept of rest, from interviews with a total of 63 participants about their lived experiences of rest. I performed the developing process in two stages: first with descriptive phenomenology and second with a hermeneutic approach. The concept of rest is comprised of the essences of both rest and “non-rest,” and there is a current movement between these two conditions in peoples’ lives. The essence of rest is being in harmony in motivation, feeling, and action. The essence of non-rest is being in disharmony in motivation, feeling, and action. The essences reveal some meaning constituents. Health care professionals and researchers can use the concept as a frame of reference in health care praxis and in applied research. PMID:28462307

  14. Validation of PC-based Sound Card with Biopac for Digitalization of ECG Recording in Short-term HRV Analysis.

    PubMed

    Maheshkumar, K; Dilara, K; Maruthy, K N; Sundareswaren, L

    2016-07-01

    Heart rate variability (HRV) analysis is a simple and noninvasive technique capable of assessing autonomic nervous system modulation on heart rate (HR) in healthy as well as disease conditions. The aim of the present study was to compare (validate) the HRV using a temporal series of electrocardiograms (ECG) obtained by simple analog amplifier with PC-based sound card (audacity) and Biopac MP36 module. Based on the inclusion criteria, 120 healthy participants, including 72 males and 48 females, participated in the present study. Following standard protocol, 5-min ECG was recorded after 10 min of supine rest by Portable simple analog amplifier PC-based sound card as well as by Biopac module with surface electrodes in Leads II position simultaneously. All the ECG data was visually screened and was found to be free of ectopic beats and noise. RR intervals from both ECG recordings were analyzed separately in Kubios software. Short-term HRV indexes in both time and frequency domain were used. The unpaired Student's t-test and Pearson correlation coefficient test were used for the analysis using the R statistical software. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV. Correlation analysis revealed perfect positive correlation (r = 0.99, P < 0.001) between the values in time and frequency domain obtained by the devices. On the basis of the results of the present study, we suggest that the calculation of HRV values in the time and frequency domains by RR series obtained from the PC-based sound card is probably as reliable as those obtained by the gold standard Biopac MP36.

  15. Appropriate threshold levels of cardiac beat-to-beat variation in semi-automatic analysis of equine ECG recordings.

    PubMed

    Flethøj, Mette; Kanters, Jørgen K; Pedersen, Philip J; Haugaard, Maria M; Carstensen, Helena; Olsen, Lisbeth H; Buhl, Rikke

    2016-11-28

    Although premature beats are a matter of concern in horses, the interpretation of equine ECG recordings is complicated by a lack of standardized analysis criteria and a limited knowledge of the normal beat-to-beat variation of equine cardiac rhythm. The purpose of this study was to determine the appropriate threshold levels of maximum acceptable deviation of RR intervals in equine ECG analysis, and to evaluate a novel two-step timing algorithm by quantifying the frequency of arrhythmias in a cohort of healthy adult endurance horses. Beat-to-beat variation differed considerably with heart rate (HR), and an adaptable model consisting of three different HR ranges with separate threshold levels of maximum acceptable RR deviation was consequently defined. For resting HRs <60 beats/min (bpm) the threshold level of RR deviation was set at 20%, for HRs in the intermediate range between 60 and 100 bpm the threshold was 10%, and for exercising HRs >100 bpm, the threshold level was 4%. Supraventricular premature beats represented the most prevalent arrhythmia category with varying frequencies in seven horses at rest (median 7, range 2-86) and six horses during exercise (median 2, range 1-24). Beat-to-beat variation of equine cardiac rhythm varies according to HR, and threshold levels in equine ECG analysis should be adjusted accordingly. Standardization of the analysis criteria will enable comparisons of studies and follow-up examinations of patients. A small number of supraventricular premature beats appears to be a normal finding in endurance horses. Further studies are required to validate the findings and determine the clinical significance of premature beats in horses.

  16. Use of electrocardiogram (ECG) electrodes for Bioelectrical Impedance Analysis (BIA)

    NASA Astrophysics Data System (ADS)

    Caicedo-Eraso, J. C.; González-Correa, C. H.; González-Correa, C. A.

    2012-12-01

    BIA is a safe, noninvasive, portable and relatively inexpensive method of estimating body composition that is practical and suitable for individual use and large-scale studies. However, the cost of the electrodes recommended by some BIA manufacturers is too high for developing countries; where very often the long and complicated process of importation reduces the time they can be used. The purpose of this study was to evaluate the use of two types of ECG electrodes (2290 and 2228 by 3M®) in BIA measurements to decrease the costs of the test. The results showed that the 2228 ECG electrodes can be used in BIA measurements for adult's body composition assessment. These electrodes are available in the domestic market and their costs are 92% lower than the electrodes recommended by manufacturer. The results show a new cost-benefit relation for BIA method and make this a more accessible tool for individual tests, large-scale researches and studies in the community.

  17. Inclusion of ECG and EEG Analysis in Neural Network Models

    DTIC Science & Technology

    2007-11-02

    important in the diagnosis of numerous diseases , chiefly in cardiology through the use of electrocardiograms, and to a more limited extent, in neurology...these results with other clinical parameters to represent a more comprehensive view of the disease state, using a neural network model...important information for diagnosis and tracking of disease . Electrocardiogram (ECG) results have made major contributions to cardiac diagnosis [1

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

    PubMed

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

    2015-02-01

    Lead V1 is routinely analysed due to its large amplitude AF waveform. V1 correlates strongly with right atrial activity but only moderately with left atrial activity. Posterior lead V9 correlates strongest with left atrial activity. (1) To establish whether surface dominant AF frequency (DAF) calculated using principal component analysis (PCA) of a modified 12-lead ECG (including posterior leads) has a stronger correlation with left atrial activity compared to the standard ECG. (2) To assess the contribution of individual ECG leads to the AF principal component in both ECG configurations. Patients were assigned to modified or standard ECG groups. In the modified ECG, posterior leads V8 and V9 replaced V4 and V6. AF waveform was extracted from one-minute surface ECG recordings using PCA. Surface DAF was correlated with intracardiac DAF from the high right atrium (HRA), coronary sinus (CS) and pulmonary veins (PVs). 96 patients were studied. Surface DAF from the modified ECG did not have a stronger correlation with left atrial activity compared to the standard ECG. Both ECG configurations correlated strongly with HRA, CS and right PVs but only moderately with left PVs. V1 contributed most to the AF principal component in both ECG configurations. Copyright © 2015. Published by Elsevier Ltd.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2013-01-01

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

  1. A new microcomputer-based ECG analysis system.

    PubMed

    Kyle, M C; Klingeman, J D; Conrad, J D; Freis, E D; Pipberger, H V

    1983-09-01

    A new automated ECG system using advances in microprocessor technology and computerized electrocardiography is described. This microcomputer-based system is self-contained and mobile. It acquires both the 12-lead and orthogonal lead (Frank) electrocardiograms and analyzes the latter within minutes. Software includes the program developed in the Veterans Administration which uses advanced statistical classification techniques and a large well-documented patient data base. Diagnostic probabilities are computed using a Bayesian approach. Diagnostic performance has been tested using independent clinical criteria and found to be quite accurate. This system enables the clinician to immediately review the computer's identifications, measurements, and diagnostic classifications and quickly use these results in clinical decision making. Serial comparisons are readily made since all previous recordings are stored on floppy diskettes. The use of microprocessors in this system makes it economically feasible for practicing physicians.

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

    PubMed

    Kuzilek, Jakub; Kremen, Vaclav; Lhotska, Lenka

    2014-01-01

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

  3. Independent component analysis and decision trees for ECG holter recording de-noising.

    PubMed

    Kuzilek, Jakub; Kremen, Vaclav; Soucek, Filip; Lhotska, Lenka

    2014-01-01

    We have developed a method focusing on ECG signal de-noising using Independent component analysis (ICA). This approach combines JADE source separation and binary decision tree for identification and subsequent ECG noise removal. In order to to test the efficiency of this method comparison to standard filtering a wavelet- based de-noising method was used. Freely data available at Physionet medical data storage were evaluated. Evaluation criteria was root mean square error (RMSE) between original ECG and filtered data contaminated with artificial noise. Proposed algorithm achieved comparable result in terms of standard noises (power line interference, base line wander, EMG), but noticeably significantly better results were achieved when uncommon noise (electrode cable movement artefact) were compared.

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

    PubMed

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

    2008-10-01

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

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

    PubMed

    Marker, Ryan J; Maluf, Katrina S

    2014-12-01

    Electromyography (EMG) recordings from the trapezius are often contaminated by the electrocardiography (ECG) signal, making it difficult to distinguish low-level muscle activity from muscular rest. This study investigates the influence of ECG contamination on EMG amplitude and frequency estimations in the upper trapezius during muscular rest and low-level contractions. A new method of ECG contamination removal, filtered template subtraction (FTS), is described and compared to 30 Hz high-pass filter (HPF) and averaged template subtraction (ATS) methods. FTS creates a unique template of each ECG artifact using a low-pass filtered copy of the contaminated signal, which is subtracted from contaminated periods in the original signal. ECG contamination results in an over-estimation of EMG amplitude during rest in the upper trapezius, with negligible effects on amplitude and frequency estimations during low-intensity isometric contractions. FTS and HPF successfully removed ECG contamination from periods of muscular rest, yet introduced errors during muscle contraction. Conversely, ATS failed to fully remove ECG contamination during muscular rest, yet did not introduce errors during muscle contraction. The relative advantages and disadvantages of different ECG contamination removal methods should be considered in the context of the specific motor tasks that require analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  7. Multilead analysis of T-wave alternans in the ECG using principal component analysis.

    PubMed

    Monasterio, Violeta; Laguna, Pablo; Martínez, Juan Pablo

    2009-07-01

    T-wave alternans (TWA) is a cardiac phenomenon associated with the mechanisms leading to sudden cardiac death. Several methods exist to automatically detect and estimate TWA in the ECG on a single-lead basis, and their main drawback is their poor sensitivity to low-amplitude TWA. In this paper, we propose a multilead analysis scheme to improve the detection and estimation of TWA. It combines principal component analysis with a single-lead method based on the generalized likelihood ratio test. The proposed scheme is evaluated and compared to a single-lead scheme by means of a simulation study, in which different types of simulated and physiological noise are considered under realistic conditions. Simulation results show that the multilead scheme can detect TWA with an SNR 30 dB lower and allows the estimation of TWA with an SNR 25 dB lower than the single-lead scheme. The two analysis schemes are also applied to stress test ECG records. Results show that the multilead scheme provides a higher detection power and that TWA detections obtained with this scheme are significantly different in healthy volunteers and ischemic patients, whereas they are not with the single-lead scheme.

  8. Automatic extraction of ECG strips from continuous 12-lead holter recordings for QT analysis at prescheduled versus optimized time points.

    PubMed

    Badilini, Fabio; Vaglio, Martino; Sarapa, Nenad

    2009-01-01

    Continuous 12-lead ECG monitoring (Holter) in early-phase pharmaceutical studies is today widely used as an ideal platform to extract discrete ECGs for analysis. The extraction process is typically performed manually by trained readers using commercial Holter processing systems. Antares, a novel method for automatic 12-lead extraction from continuous Holter recordings applying minimal noise criteria and heart-rate stability conditions is presented. A set of 12-lead Holter recordings from healthy subjects administered with sotalol is used to compare ECG extractions at fixed time points with ECG extractions generated by Antares optimizing noise and heart rate inside 5 minute windows centered around each expected time point of interest. Global, low- and high-frequency noise content of extracted ECGs was significantly reduced via optimized approach by Antares. Heart rate was also slightly reduced (from 69 +/- 13 to 64 +/- 13 bpm, P < 0.05). Similarly, the corrected QT interval from optimized extractions was significantly reduced (QTcB from 414 +/- 32 to 402 +/- 30 ms, P < 0.05). Using only baseline data, and after adjusting for intersubject variability, the standard deviation (SD) of QT intervals was highly reduced with optimized extraction (SD of QTcF from 11 +/- 8 to 7 +/- 2 ms, P < 0.05). Extraction of discrete 12-lead ECG strips from continuous Holter generates less noisy and more stable ECGs leading to more robust QTc data, thereby potentially facilitating the assessment of ECG effects on clinical trials.

  9. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  10. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    PubMed

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  13. Robust human identification using ecg: eigenpulse revisited

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  14. Multichannel ECG data compression based on multiscale principal component analysis.

    PubMed

    Sharma, L N; Dandapat, S; Mahanta, Anil

    2012-07-01

    In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of principal components (PCs) is based on average fractional energy contribution of eigenvalue in a data matrix. Multichannel compression is implemented using uniform quantizer and entropy coding of PCA coefficients. The compressed signal quality is evaluated quantitatively using percentage root mean square difference (PRD), and wavelet energy-based diagnostic distortion (WEDD) measures. Using dataset from CSE multilead measurement library, multichannel compression ratio of 5.98:1 is found with PRD value 2.09% and the lowest WEDD value of 4.19%. Based on, gold standard subjective quality measure, the lowest mean opinion score error value of 5.56% is found.

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

    PubMed

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

    1995-01-01

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

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

    PubMed

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

    1996-06-01

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

  17. 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.

  18. ECG (image)

    MedlinePlus

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

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

    PubMed

    Zhou, Shijie; Zhang, Zichen; Gu, Jason

    2011-01-01

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

  20. Application of Wavelet Based Denoising for T-Wave Alternans Analysis in High Resolution ECG Maps

    NASA Astrophysics Data System (ADS)

    Janusek, D.; Kania, M.; Zaczek, R.; Zavala-Fernandez, H.; Zbieć, A.; Opolski, G.; Maniewski, R.

    2011-01-01

    T-wave alternans (TWA) allows for identification of patients at an increased risk of ventricular arrhythmia. Stress test, which increases heart rate in controlled manner, is used for TWA measurement. However, the TWA detection and analysis are often disturbed by muscular interference. The evaluation of wavelet based denoising methods was performed to find optimal algorithm for TWA analysis. ECG signals recorded in twelve patients with cardiac disease were analyzed. In seven of them significant T-wave alternans magnitude was detected. The application of wavelet based denoising method in the pre-processing stage increases the T-wave alternans magnitude as well as the number of BSPM signals where TWA was detected.

  1. The importance of sleep apnea index determination using 24 h ECG analysis in patients with heart rhythm disorders.

    PubMed

    Grdinić, Aleksandra; Stajić, Zoran; Grdinić, Aleksandar G; Vucinić, Zarko; Krstić, Violeta Randjelović; Drobnjak, Dragan; Bogdanović, Predrag; Djurić, Predrag; Stevanović, Angelina; Rakonjac, Milanko; Petrović, Stanko; Gudelj, Ognjen; Matunović, Radomir

    2014-11-01

    A possible cause of malignant heart rhythm disorders is the syndrome of sleep apnea (periodic cessation of breathing during sleep longer than 10 seconds). Recent 24 h ECG software systems have the option of determination ECG apnea index (AI) based on the change in voltage of QRS complexes. The aim of the study was to determine the significance of AI evaluation in routine 24-hour Holter ECG on a group of 12 patients. We presented a total of 12 consecutive patients with previously documented arrhythmias and the history of breathing disorders during night. They were analyzed by 24 h ECG (Medilog AR 12 plus Darwin), that is able to determine AI. We presented a case series of 12 patients, 8 men and 4 women, mean age 58.75 years and the average AI 5.78. In the whole group there was a trend of increasing prevalence of complex rhythm disorders with increasing of AI and increased frequency of arrhythmias in the night phase vs. day phase. Determination of AI using routine long term (24 h) ECG analysis is important because sleep apnea can be successfully treated as an etiological or contributing factor of arrhythmias.

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

    PubMed

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

    2008-01-01

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

  3. Continuous ECG monitoring for tracking down atrial fibrillation after stroke: Holter or automated analysis strategy?

    PubMed

    Suissa, Laurent; Lachaud, Sylvain; Mahagne, Marie-Hélène

    2014-01-01

    Tracking down atrial fibrillation (AF) in the stroke unit is a relevant challenge for the prevention of recurrent AF-related stroke. The optimal terms of use of continuous ECG monitoring (CEM) are unknown. We compared 24-hour routine Holter ECG with two different CEM analysis strategies for AF detection. We prospectively enrolled consecutive ischemic stroke patients. All AF-naïve patients received CEM during hospitalization. Two methods for reading CEM data were compared: manual analysis using the Holter function (hCEM) and semiautomated analysis using software (aCEM). The McNemar test was used to compare AF detection rates. Of the 362 patients included, 58 (16.0%) were non-AF-naïve patients and 304 were AF-naïve patients. AF-Naïve patients underwent CEM with a median duration of 5.3 days (3.4-9.7). We detected 22 new AF cases (7.2%) with first-24-hour hCEM, 31 (10.2%) with aCEM, and 42 (13.8%) with hCEM. hCEM and aCEM both significantly increased the AF detection rate compared to first-24-hour hCEM. hCEM detected more new AF cases than aCEM (+3.6%, p = 0.003). In stroke patients, early and prolonged aCEM and hCEM both increase the AF detection rate compared to first-24-hour hCEM. hCEM gives the best AF detection rate. We suggest that in aCEM, detection based only on the ventricular rhythm analysis explains its lower specificity and sensitivity. © 2014 S. Karger AG, Basel.

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

    PubMed

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

    1996-03-01

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

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

    PubMed Central

    Muller, Angela M.; Meyer, Martin

    2014-01-01

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

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

    PubMed

    Muller, Angela M; Meyer, Martin

    2014-01-01

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

  7. WaveformECG: A Platform for Visualizing, Annotating, and Analyzing ECG Data

    PubMed Central

    Winslow, Raimond L.; Granite, Stephen; Jurado, Christian

    2017-01-01

    The electrocardiogram (ECG) is the most commonly collected data in cardiovascular research because of the ease with which it can be measured and because changes in ECG waveforms reflect underlying aspects of heart disease. Accessed through a browser, WaveformECG is an open source platform supporting interactive analysis, visualization, and annotation of ECGs. PMID:28642673

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

    PubMed

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

    2000-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

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

    2013-01-01

    Current guidelines recommend early reperfusion therapy for ST-elevation myocardial infarction (STEMI) within 90 min of first medical encounter. Telecardiology entails the use of advanced communication technologies to transmit the prehospital 12-lead electrocardiogram (ECG) to offsite cardiologists for early triage to the cath lab; which has been shown to dramatically reduce door-to-balloon time and total mortality. However, hospitals often find adopting ECG transmission technologies very challenging. The current review identifies seven major technical challenges of prehospital ECG transmission, including: paramedics inconvenience and transport delay; signal noise and interpretation errors; equipment malfunction and transmission failure; reliability of mobile phone networks; lack of compliance with the standards of digital ECG formats; poor integration with electronic medical records; and costly hardware and software pre-requisite installation. Current and potential solutions to address each of these technical challenges are discussed in details and include: automated ECG transmission protocols; annotatable waveform-based ECGs; optimal routing solutions; and the use of cloud computing systems rather than vendor-specific processing stations. Nevertheless, strategies to monitor transmission effectiveness and patient outcomes are essential to sustain initial gains of implementing ECG transmission technologies. © 2013.

  11. High-frequency QRS analysis compared to conventional ST-segment analysis in patients with chest pain and normal ECG referred for exercise tolerance test.

    PubMed

    Conti, Alberto; Alesi, Andrea; Aspesi, Giovanna; De Bernardis, Niccolò; Bianchi, Simone; Coppa, Alessandro; Donnini, Chiara; Grifoni, Caterina; Becucci, Alessandro; Casula, Claudia

    2015-01-01

    The novel analysis of high-frequency QRS components (HFQRS-analysis) has been proposed in patients with chest pain (CP) and normal electrocardiography (ECG) referred for exercise tolerance test (ex-ECG). The aim of the study was to compare the diagnostic value of ex-ECG with ex-HFQRS-analysis. Patients with CP and normal ECG, troponin, and echocardiography were considered. All patients underwent ex-ECG for conventional ST-segment-analysis and ex-HFQRS-analysis. A decrease ≥ 50% of the HFQRS signal intensity recorded in at least 2 contiguous leads was considered an index of ischemia, as ST-segment depression ≥ 2 mm or ≥ 1 mm and CP on ex-ECG. Exclusion criteria were: QRS duration ≥ 120 ms and inability to exercise. End-point: The composite of coronary stenosis ≥ 70% or acute coronary syndrome, revascularization, cardiovascular death at 3-month follow-up. Three-hundred thirty-seven patients were enrolled (age 60 ± 15 years). The percent-age of age-adjusted maximal predicted heart rate was 89 ± 10 beat per minute and the maximal systolic blood pressure was 169 ± 23 mm Hg. Nineteen patients achieved the end-point. In multivariate analysis, both ex-ECG and ex-HFQRS were predictors of the end-point. The ex-HFQRS-analysis showed higher sensitivity (63% vs. 26%; p < 0.05), lower specificity (68% vs. 95%; p < 0.001), and comparable negative predictive value (97% vs. 96%; p = 0.502) when compared to ex-ECG-analysis. Receiver operator characteristics analysis showed the incremental diagnostic value of HFQRS (area: 0.655, 95% CI 0.60-0.71) over conventional ex-ECG (0.608, CI 0.55-0.66) and CP score (0.530, CI 0.48-0.59), however without statistical significance in pairwise comparison by C-statistic. In patients with CP submitted to ex-ECG, the novel ex-HFQRS-analysis shows a valuable incremental diagnostic value over ST-segment-analysis.

  12. Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation.

    PubMed

    Lankveld, Theo; de Vos, Cees B; Limantoro, Ione; Zeemering, Stef; Dudink, Elton; Crijns, Harry J; Schotten, Ulrich

    2016-05-01

    Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF. The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors. We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV. During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG. ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

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

    PubMed

    Miranda-Cid, Alejandro; Alvarado-Serrano, Carlos

    2010-01-01

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

  14. Fetal ECG Extraction From Maternal Body Surface Measurement Using Independent Component Analysis

    DTIC Science & Technology

    2001-10-25

    vector x(t) is created by (1) and the results are showed in Fig. 3. C. Signal Collection A pregnant Holstein cow , having gestation period of 177 days...if only the heart rate is required in this case. B. Measured Signals Original measured signals from a pregnant Holstein cow is showed in Fig. 6. Top...cutaneous electrodes on the body surface of a maternal cow . Measured signals are the mixtures of components including maternal ECG, foetal ECG and random

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

    NASA Astrophysics Data System (ADS)

    Orosco, L.; Laciar, E.

    2007-11-01

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

  16. Inter-lead correlation analysis for automated detection of cable reversals in 12/16-lead ECG.

    PubMed

    Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger

    2016-10-01

    A crucial factor for proper electrocardiogram (ECG) interpretation is the correct electrode placement in standard 12-lead ECG and extended 16-lead ECG for accurate diagnosis of acute myocardial infarctions. In the context of optimal patient care, we present and evaluate a new method for automated detection of reversals in peripheral and precordial (standard, right and posterior) leads, based on simple rules with inter-lead correlation dependencies. The algorithm for analysis of cable reversals relies on scoring of inter-lead correlations estimated over 4s snapshots with time-coherent data from multiple ECG leads. Peripheral cable reversals are detected by assessment of nine correlation coefficients, comparing V6 to limb leads: (I, II, III, -I, -II, -III, -aVR, -aVL, -aVF). Precordial lead reversals are detected by analysis of the ECG pattern cross-correlation progression within lead sets (V1-V6), (V4R, V3R, V3, V4), and (V4, V5, V6, V8, V9). Disturbed progression identifies the swapped leads. A test-set, including 2239 ECGs from three independent sources-public 12-lead (PTB, CSE) and proprietary 16-lead (Basel University Hospital) databases-is used for algorithm validation, reporting specificity (Sp) and sensitivity (Se) as true negative and true positive detection of simulated lead swaps. Reversals of limb leads are detected with Se = 95.5-96.9% and 100% when right leg is involved in the reversal. Among all 15 possible pairwise reversals in standard precordial leads, adjacent lead reversals are detected with Se = 93.8% (V5-V6), 95.6% (V2-V3), 95.9% (V3-V4), 97.1% (V1-V2), and 97.8% (V4-V5), increasing to 97.8-99.8% for reversals of anatomically more distant electrodes. The pairwise reversals in the four extra precordial leads are detected with Se = 74.7% (right-sided V4R-V3R), 91.4% (posterior V8-V9), 93.7% (V4R-V9), and 97.7% (V4R-V8, V3R-V9, V3R-V8). Higher true negative rate is achieved with Sp > 99% (standard 12-lead ECG), 81.9% (V4R-V3R), 91

  17. [ECG monitoring in full-term infants. Analysis of the rhythm and variability of heart rate].

    PubMed

    Pandolfi, M; Falsini, G; Lazzerini, S; Giani, I; Rosati, C; Mantini, G; Grazzini, M

    1993-01-01

    Heart Rate (HR) and Heart Rate Variability (HRV) depend on the neural control to the heart. HRV can be measured from 24-hours function. Little information is available on cardiac rhythm and on autonomic nervous control to the heart at birth. The aims of the study weew: 1) to study the cardiac rhythm in healthy newborn babies; 2) to asses the normal values for HRV at birth. We studied 20 full term healthy newborn babies. Newborns underwent 24-hours ECG-Holter monitoring. Analysis was performed by a 750 A Del Mar Avionics Analyzer. We determined: Heart Rate (HR), number of extrasystoles, Standard Deviation of all R-R intervals over 24 hours (SDNN) and mean hourly HRV (HRVM). Results about HRV were matched with those of 50 healthy adults. 1) Average HR in the newborn babies was 108 (range: 55-198); we found high prevalence of supraventricular extrasystoles. 2) We determined reference value for HRV. SDNN was 55 +/- 17 ms in newborns. SDNN of adults was 132 +/- 25 ms (44% higher than in newborns; p < 0.001). HRVM was 46 +/- 14 ms in newborns and 76 +/- 14 ms (p < 0.001). 1) Larger intervals of HR in newborn babies compared to literature data and an high prevalence of supraventricular arrhythmias in full term healthy newborn babies. 2) Reference values for HRV in newborn babies. The low values of HRV confirm the immaturity of autonomic cardiac control.

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

    NASA Astrophysics Data System (ADS)

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

    2008-06-01

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

  19. Accurate ECG Diagnosis of Atrial Tachyarrhythmias Using Quantitative Analysis: A Prospective Diagnostic and Cost-Effectiveness Study

    PubMed Central

    Krummen, David E.; Patel, Mitul; Nguyen, Hong; Ho, Gordon; Kazi, Dhruv S.; Clopton, Paul; Holland, Marian C.; Greenberg, Scott L.; Feld, Gregory K.; Faddis, Mitchell N.; Narayan, Sanjiv M.

    2010-01-01

    Introduction Optimal atrial tachyarrhythmia management is facilitated by accurate ECG interpretation, yet typical atrial flutter (AFl) may present without sawtooth F-waves or RR regularity, and atrial fibrillation (AF) may be difficult to separate from atypical AFl or rapid focal atrial tachycardia (AT). We analyzed whether improved diagnostic accuracy using a validated analysis tool significantly impacts costs and patient care. Methods and Results We performed a prospective, blinded, multicenter study using a novel quantitative computerized algorithm to identify atrial tachyarrhythmia mechanism from the surface ECG in patients referred for electrophysiology study (EPS). In 122 consecutive patients (age 60±12 years) referred for EPS, 91 sustained atrial tachyarrhythmias were studied. ECGs were also interpreted by 9 physicians from 3 specialties for comparison and to allow healthcare system modeling. Diagnostic accuracy was compared to the diagnosis at EPS. A Markov model was used to estimate the impact of improved arrhythmia diagnosis. We found 13% of typical AFl ECGs had neither sawtooth flutter waves nor RR regularity, and were misdiagnosed by the majority of clinicians (0/6 correctly diagnosed by consensus visual interpretation) but correctly by quantitative analysis in 83% (5/6, p=0.03). AF diagnosis was also improved through use of the algorithm (92%) vs visual interpretation (primary care: 76%, p<0.01). Economically, we found that these improvements in diagnostic accuracy resulted in an average cost-savings of $1,303 and 0.007 quality-adjusted-life-years per patient. Conclusions Typical AFl and AF are frequently misdiagnosed using visual criteria. Quantitative analysis improves diagnostic accuracy and results in improved healthcare costs and patient outcomes. PMID:20522152

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

    ERIC Educational Resources Information Center

    Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

    2015-01-01

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

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

    ERIC Educational Resources Information Center

    Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

    2015-01-01

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

  2. Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?

    PubMed

    Mahdiani, Shadi; Jeyhani, Vala; Peltokangas, Mikko; Vehkaoja, Antti

    2015-01-01

    With the worldwide growth of mobile wireless technologies, healthcare services can be provided at anytime and anywhere. Usage of wearable wireless physiological monitoring system has been extensively increasing during the last decade. These mobile devices can continuously measure e.g. the heart activity and wirelessly transfer the data to the mobile phone of the patient. One of the significant restrictions for these devices is usage of energy, which leads to requiring low sampling rate. This article is presented in order to investigate the lowest adequate sampling frequency of ECG signal, for achieving accurate enough time domain heart rate variability (HRV) parameters. For this purpose the ECG signals originally measured with high 5 kHz sampling rate were down-sampled to simulate the measurement with lower sampling rate. Down-sampling loses information, decreases temporal accuracy, which was then restored by interpolating the signals to their original sampling rates. The HRV parameters obtained from the ECG signals with lower sampling rates were compared. The results represent that even when the sampling rate of ECG signal is equal to 50 Hz, the HRV parameters are almost accurate with a reasonable error.

  3. Cardiovascular evaluation, including resting and exercise electrocardiography, before participation in competitive sports: cross sectional study

    PubMed Central

    Capalbo, Andrea; Pucci, Nicola; Giuliattini, Jacopo; Condino, Francesca; Alessandri, Flavio; Abbate, Rosanna; Gensini, Gian Franco; Califano, Sergio

    2008-01-01

    Objective To evaluate the clinical usefulness of complete preparticipation cardiovascular screening in a large cohort of sports participants. Design Cross sectional study of data over a five year period. Setting Institute of Sports Medicine in Florence, Italy. Participants 30 065 (23 570 men) people seeking to obtain clinical eligibility for competitive sports. Main outcome measures Results of resting and exercise 12 lead electrocardiography. Results Resting 12 lead ECG patterns showed abnormalities in 1812 (6%) participants, with the most common abnormalities (>80%) concerning innocent ECG changes. Exercise ECG showed an abnormal pattern in 1459 (4.9%) participants. Exercise ECG showed cardiac anomalies in 1227 athletes with normal findings on resting ECG. At the end of screening, 196 (0.6%) participants were considered ineligible for competitive sports. Among the 159 participants who were disqualified at the end of the screening for cardiac reasons, a consistent proportion (n=126, 79.2%) had shown innocent or negative findings on resting 12 lead ECG but clear pathological alterations during the exercise test. After adjustment for possible confounders, logistic regression analysis showed that age >30 years was significantly associated with an increased risk of being disqualified for cardiac findings during exercise testing. Conclusions Among people seeking to take part in competitive sports, exercise ECG can identify those with cardiac abnormalities. Follow-up studies would show if disqualification of such people would reduce the incidence of CV events among athletes. PMID:18599474

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

    PubMed

    Lehtinen, R

    1999-01-01

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

  5. Beat-to-beat measurement and analysis of the R-T interval in 24 h ECG Holter recordings.

    PubMed

    Speranza, G; Nollo, G; Ravelli, F; Antolini, R

    1993-09-01

    This study assesses the feasibility of beat-to-beat measurement of the R-T interval in Holter ECG recordings. The low sampling rate of the Holter system was increased by a specific interpolating filter, and the precision and accuracy of two T-wave fiducial point (T-wave maximum: Tm, T-wave end: Te) detection algorithms were compared. The results of the validation tests show better performance of the Tm measurement procedure in the presence of high noise levels. The overall process for the beat-to-beat R-T interval measurement was then tested on ECG Holter recordings collected during free and controlled respiration. Finally, the R-Tm and the corresponding R-R intervals were measured on 24 h ECG recordings of healthy subjects and the spectral analysis was applied to the constructed series. Both R-R and R-Tm spectra show two main frequency components (low-frequency approximately 0.1 Hz, high-frequency approximately 0.25 Hz) changing in their power ratios continuously throughout the 24 h period. The method described seems to provide a dynamic index of the sympatho-vagal balance at the ventricle that can be useful for a deeper understanding of ventricular repolarisation duration variability.

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

    PubMed

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

    2014-06-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2005-01-01

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

  9. Competency in ECG Interpretation Among Medical Students

    PubMed Central

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

    2015-01-01

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

  10. Competency in ECG Interpretation Among Medical Students.

    PubMed

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

    2015-11-06

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  12. High-frequency ECG

    NASA Technical Reports Server (NTRS)

    Tragardh, Elin; Schlegel, Todd T.

    2006-01-01

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

  13. Integration of multivariate empirical mode decomposition and independent component analysis for fetal ECG separation from abdominal signals.

    PubMed

    Thanaraj, Palani; Roshini, Mable; Balasubramanian, Parvathavarthini

    2016-11-14

    The fetal electrocardiogram (FECG) signals are essential to monitor the health condition of the baby. Fetal heart rate (FHR) is commonly used for diagnosing certain abnormalities in the formation of the heart. Usually, non-invasive abdominal electrocardiogram (AbECG) signals are obtained by placing surface electrodes in the abdomen region of the pregnant woman. AbECG signals are often not suitable for the direct analysis of fetal heart activity. Moreover, the strength and magnitude of the FECG signals are low compared to the maternal electrocardiogram (MECG) signals. The MECG signals are often superimposed with the FECG signals that make the monitoring of FECG signals a difficult task. Primary goal of the paper is to separate the fetal electrocardiogram (FECG) signals from the unwanted maternal electrocardiogram (MECG) signals. A multivariate signal processing procedure is proposed here that combines the Multivariate Empirical Mode Decomposition (MEMD) and Independent Component Analysis (ICA). The proposed method is evaluated with clinical abdominal signals taken from three pregnant women (N= 3) recorded during the 38-41 weeks of the gestation period. The number of fetal R-wave detected (NEFQRS), the number of unwanted maternal peaks (NMQRS), the number of undetected fetal R-wave (NUFQRS) and the FHR detection accuracy quantifies the performance of our method. Clinical investigation with three test subjects shows an overall detection accuracy of 92.8%. Comparative analysis with benchmark signal processing method such as ICA suggests the noteworthy performance of our method.

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

    PubMed

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

    2013-07-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2017-03-08

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

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

    PubMed

    Bahoura, M; Hassani, M; Hubin, M

    1997-01-01

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

  19. Automated detection of ventricular pre-excitation in pediatric 12-lead ECG.

    PubMed

    Gregg, Richard E; Zhou, Sophia H; Dubin, Anne M

    2016-01-01

    With increased interest in screening of young people for potential causes of sudden death, accurate automated detection of ventricular pre-excitation (VPE) or Wolff-Parkinson-White syndrome (WPW) in the pediatric resting ECG is important. Several recent studies have shown interobserver variability when reading screening ECGs and thus an accurate automated reading for this potential cause of sudden death is critical. We designed and tested an automated algorithm to detect pediatric VPE optimized for low prevalence. Digital ECGs with 12 leads or 15 leads (12-lead plus V3R, V4R and V7) were selected from multiple hospitals and separated into a testing and training database. Inclusion criterion was age less than 16 years. The reference for algorithm detection of VPE was cardiologist annotation of VPE for each ECG. The training database (n=772) consisted of VPE ECGs (n=37), normal ECGs (n=492) and a high concentration of conduction defects, RBBB (n=232) and LBBB (n=11). The testing database was a random sample (n=763). All ECGs were analyzed with the Philips DXL ECG Analysis algorithm for basic waveform measurements. Additional ECG features specific to VPE, mainly delta wave scoring, were calculated from the basic measurements and the average beat. A classifier based on decision tree bootstrap aggregation (tree bagger) was trained in multiple steps to select the number of decision trees and the 10 best features. The classifier accuracy was measured on the test database. The new algorithm detected pediatric VPE with a sensitivity of 78%, a specificity of 99.9%, a positive predictive value of 88% and negative predictive value of 99.7%. This new algorithm for detection of pediatric VPE performs well with a reasonable positive and negative predictive value despite the low prevalence in the general population. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2005-01-01

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

  1. The effectiveness of screening history, physical exam, and ECG to detect potentially lethal cardiac disorders in athletes: a systematic review/meta-analysis.

    PubMed

    Harmon, Kimberly G; Zigman, Monica; Drezner, Jonathan A

    2015-01-01

    The optimal cardiovascular preparticipation screen is debated. The purpose of this study was to perform a systematic review/meta-analysis of evidence comparing screening strategies. PRIMSA guidelines were followed. Electronic databases were searched from January 1996 to November 2014 for articles examining the efficacy of screening with history and physical exam (PE) based on the American Heart Association (AHA) or similar recommendations and electrocardiogram (ECG). Pooled data was analyzed for sensitivity, specificity, false positive rates and positive and negative likelihood ratios. Secondary outcomes included rate of potentially lethal cardiovascular conditions detected with screening and the etiology of pathology discovered. Fifteen articles reporting on 47,137 athletes were reviewed. After meta-analysis the sensitivity and specificity of ECG was 94%/93%, history 20%/94%, and PE 9%/97%. The overall false positive rate of ECG (6%) was less than that of history (8%), or physical exam (10%). Positive likelihood ratios were ECG 14.8, history 3.22 and PE 2.93 and negative likelihood ratios were ECG 0.055, history 0.85, and PE 0.93. There were a total of 160 potentially lethal cardiovascular conditions detected for a rate of 0.3% or 1 in 294. The most common pathology was Wolff-Parkinson-White (67, 42%), Long QT Syndrome (18, 11%), hypertrophic cardiomyopathy (18, 11%), dilated cardiomyopathy (11, 7%), coronary artery disease or myocardial ischemia (9, 6%) and arrhythmogenic right ventricular cardiomyopathy (4, 3%). The most effective strategy for screening for cardiovascular disease in athletes is ECG. It is 5 times more sensitive than history, 10 times more sensitive than physical exam, has higher positive likelihood ratio, lower negative likelihood ratio and a lower false positive rate. 12-lead ECG interpreted using modern criteria should be considered best practice in screening for cardiovascular disease in athletes while the use of history and physical alone as

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

    NASA Astrophysics Data System (ADS)

    Schulz-Bruenken, Barbara; Pelikan, Erich

    1996-04-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  5. [Practical experience about the compatibility of PDF converter in ECG information system].

    PubMed

    Yang, Gang; Lu, Weishi; Zhou, Jiacheng

    2009-11-01

    To find a way to view ECG from different manufacturers in electrocardiogram information system. Different format ECG data were transmitted to ECG center by different ways. Corresponding analysis software was used to make the diagnosis reports in the center. Then we use PDF convert to change all ECG reports into PDF format. The electrocardiogram information system manage these PDF format ECG data for clinic user. The ECG reports form several major ECG manufacturers were transformed to PDF format successfully. In the electrocardiogram information system it is freely to view the ECG figure. PDF format ECG report is a practicable way to solve the compatibility problem in electrocardiogram information system.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  8. High-resolution esophageal long-term ECG allows detailed atrial wave morphology analysis in case of atrial ectopic beats.

    PubMed

    Niederhauser, Thomas; Marisa, Thanks; Haeberlin, Andreas; Goette, Josef; Jacoment, Marcel; Vogel, Rolf

    2012-07-01

    Detection of arrhythmic atrial beats in surface ECGs can be challenging when they are masked by the R or T wave, or do not affect the RR-interval. Here, we present a solution using a high-resolution esophageal long-term ECG that offers a detailed view on the atrial electrical activity. The recorded ECG shows atrial ectopic beats with long coupling intervals, which can only be successfully classified using additional morphology criteria. Esophageal high-resolution ECGs provide this information, whereas surface long-term ECGs show poor atrial signal quality. This new method is a promising tool for the long-term rhythm monitoring with software-based automatic classification of atrial beats.

  9. [Individual prediction by the analysis of preflight ECG data of cardiac function disorders in cosmonauts during standard deorbit after long-term space flights and in the period of postflight observation].

    PubMed

    Kotovskaia, A R; Koloteva, M I; Luk'ianiuk, V Iu; Zhernavkov, A F; Kondratiuk, L L

    2008-01-01

    ECG records of 25 cosmonauts--members of 30 long-term Mir and ISS missions (73- to 197-day long) in the period of 1995-2007 were analyzed. The ECG records were made during medical selection, clinical-physiological investigations (KFO) before launch, insertion and standard descent, and post-flight KFO. No negative trends were discovered in 70% (n=21) of ECG records during insertion and descent of cosmonauts who had not have significant ECG deviations before flight. In 20% of ECG records (n=6) pre-launch individual properties of cardiac rhythm, conduction and end of the ventricular complex became more pronounced in the period of descent persisting after landing. In 10% of ECG records (n=3) the predicted ECG deviations were not found This was the first time when dynamic analysis of ECG records made on the stages of selection and pre-launch training was successful in predicting of 90% (n=27 of 30) of cardiac function deviations during descent. At the start of rehabilitation from long-term missions essentially each of the cosmonauts displayed ECG deviations which were more considerable as compared with the KFO and descent records.

  10. Sleep apnea diagnosis using an ECG Holter device including a nasal pressure (NP) recording: validation of visual and automatic analysis of nasal pressure versus full polysomnography.

    PubMed

    Pépin, Jean-Louis; Defaye, Pascal; Vincent, Elodie; Christophle-Boulard, Sylvain; Tamisier, Renaud; Lévy, Patrick

    2009-06-01

    New simplified techniques for diagnosing sleep apnea should be specially tailored for easy use in cardiologic practice. e dedicated one of the channels of a Holter Electrocardiogram (ECG) device (SpiderView() ELA Medical, France) to nasal pressure (NP) recordings. We also developed an automatic analysis of NP signal providing an apnea-hypopnea index (AHI) for physicians without the know-how in sleep medicine. Thirty-four unselected patients referred for symptoms suggesting sleep apnea underwent a polysomnography (PSG) with simultaneous NP and Holter ECG recordings. An expert blinded to PSG results visually scored the Holter plus NP recordings. The results of the AHI obtained in PSG (AHI-PSG) were compared, respectively, to the AHI-NP obtained by visual analysis and automatic analysis (AHI-NP Auto) of Holter ECG nasal pressure. In 10 randomly selected subjects (development set), the best cut-off on Holter ECG for diagnosing sleep apnea patients as defined by AHI>20/h in PSG was determined at 35 events/h by a receiver operator curve (ROC) analysis. Prospective testing of this threshold was then performed in 19 subjects (test set). For visually scored recordings of Holter ECG plus NP, we obtained a negative predictive value (NPV) of 80% and a positive predictive value (PPV) of 100% for sleep apnea. The area under the ROC curve was 0.97. For the automatic analysis, the NPV was 86% and the PPV value 100%. The area under the ROC curve was 0.85. NP recording using a Holter system is an efficient and easy-to-use tool for screening for sleep-disordered breathing in routine cardiology practice.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  12. Time-resolved resting state fMRI analysis: current status, challenges, and new directions.

    PubMed

    Keilholz, Shella Dawn; Caballero-Gaudes, Cesar; Bandettini, Peter; Deco, Gustavo; Calhoun, Vince D

    2017-09-06

    Time-resolved analysis of resting state fMRI data allows researchers to extract more information about brain function than traditional functional connectivity analysis, yet a number of challenges in data analysis and interpretation remain. This manuscript briefly summarizes common methods for time-resolved analysis and presents some of the pressing issues and opportunities in the field. From there, the discussion moves to the interpretation of the network dynamics observed with resting state fMRI and the role that resting state fMRI can play in elucidating the large-scale organization of brain activity.

  13. ECG signal denoising via empirical wavelet transform.

    PubMed

    Singh, Omkar; Sunkaria, Ramesh Kumar

    2016-12-29

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

  14. Rest and the associated benefits in restorative sleep: a concept analysis.

    PubMed

    Helvig, Ashley; Wade, Sonya; Hunter-Eades, Lee

    2016-01-01

    To report an analysis of the concept of rest. Consistency in the literature to describe the concept and use of rest is limited. Concept analysis may be advantageous in rendering an operational definition in the health care setting. This analysis is important to examine the concept of rest for structure and function to promote an understanding of the phenomenon. Rest is a vital component of restorative sleep which has implications for physical, mental and spiritual well-being. Concept analysis. A literature search was conducted in the following databases: PubMed, CINAHL, Medline, ProQuest and an online Internet search with the majority of articles published between 1995-2015. This concept analysis was implemented using the eight step approach developed by Walker and Avant. In health care, rest incorporates the cessation of activity used to promote physical and mental health. Defining attributes of rest include a pathway to calm, inner tranquillity and mental health; base of support; and stillness. Antecedents for rest are time, suitable environment and willingness. Resulting consequences include renewed physical energy, mental clarity and improved health. Rest is a concept that is used frequently in the discipline of nursing but also in various other disciplines. Rest is a basic necessity for restorative sleep to enhance well-being through the restoration of the body, mind and spirit. Defining the concept of rest in the practice of patient care is necessary for consistent use of the term in the development of holistic, patient-centred therapies. © 2015 John Wiley & Sons Ltd.

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

    PubMed Central

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

    2015-01-01

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

  16. Intermittent short ECG recording is more effective than 24-hour Holter ECG in detection of arrhythmias.

    PubMed

    Hendrikx, Tijn; Rosenqvist, Mårten; Wester, Per; Sandström, Herbert; Hörnsten, Rolf

    2014-04-01

    Many patients report symptoms of palpitations or dizziness/presyncope. These patients are often referred for 24-hour Holter ECG, although the sensitivity for detecting relevant arrhythmias is comparatively low. Intermittent short ECG recording over a longer time period might be a convenient and more sensitive alternative. The objective of this study is to compare the efficacy of 24-hour Holter ECG with intermittent short ECG recording over four weeks to detect relevant arrhythmias in patients with palpitations or dizziness/presyncope. prospective, observational, cross-sectional study. Clinical Physiology, University Hospital. 108 consecutive patients referred for ambiguous palpitations or dizziness/presyncope. All individuals underwent a 24-hour Holter ECG and additionally registered 30-second handheld ECG (Zenicor EKG® thumb) recordings at home, twice daily and when having cardiac symptoms, during 28 days. Significant arrhythmias: atrial fibrillation (AF), paroxysmal supraventricular tachycardia (PSVT), atrioventricular (AV) block II-III, sinus arrest (SA), wide complex tachycardia (WCT). 95 patients, 42 men and 53 women with a mean age of 54.1 years, completed registrations. Analysis of Holter registrations showed atrial fibrillation (AF) in two patients and atrioventricular (AV) block II in one patient (= 3.2% relevant arrhythmias [95% CI 1.1-8.9]). Intermittent handheld ECG detected nine patients with AF, three with paroxysmal supraventricular tachycardia (PSVT) and one with AV-block-II (= 13.7% relevant arrhythmias [95% CI 8.2-22.0]). There was a significant difference between the two methods in favour of intermittent ECG with regard to the ability to detect relevant arrhythmias (P = 0.0094). With Holter ECG, no symptoms were registered during any of the detected arrhythmias. With intermittent ECG, symptoms were registered during half of the arrhythmia episodes. Intermittent short ECG recording during four weeks is more effective in detecting AF and PSVT in

  17. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

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

    PubMed

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

    2007-06-01

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

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

    PubMed Central

    Jekova, Irena; Bortolan, Giovanni

    2015-01-01

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

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

    PubMed

    Jekova, Irena; Bortolan, Giovanni

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed Central

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

    2013-01-01

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

  4. A study on stability analysis of atrial repolarization variability using ARX model in sinus rhythm and atrial tachycardia ECGs.

    PubMed

    Sivaraman, J; Uma, G; Langley, P; Umapathy, M; Venkatesan, S; Palanikumar, G

    2016-12-01

    The interaction between the PTa and PP interval dynamics from the surface ECG is seldom explained. Mathematical modeling of these intervals is of interest in finding the relationship between the heart rate and repolarization variability. The goal of this paper is to assess the bounded input bounded output (BIBO) stability in PTa interval (PTaI) dynamics using autoregressive exogenous (ARX) model and to investigate the reason for causing instability in the atrial repolarization process. Twenty-five male subjects in normal sinus rhythm (NSR) and ten male subjects experiencing atrial tachycardia (AT) were included in this study. Five minute long, modified limb lead (MLL) ECGs were recorded with an EDAN SE-1010 PC ECG system. The number of minute ECGs with unstable segments (Nus) and the frequency of premature activation (PA) (i.e. atrial activation) were counted for each ECG recording and compared between AT and NSR subjects. The instability in PTaI dynamics was quantified by measuring the numbers of unstable segments in ECG data for each subject. The unstable segments in the PTaI dynamics were associated with the frequency of PA. The presence of PA is not the only factor causing the instability in PTaI dynamics in NSR subjects, and it is found that the cause of instability is mainly due to the heart rate variability (HRV). The ARX model showed better prediction of PTa interval dynamics in both groups. The frequency of PA is significantly higher in AT patients than NSR subjects. A more complex model is needed to better identify and characterize healthy heart dynamics. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. ECG telemetry in conscious guinea pigs.

    PubMed

    Ruppert, Sabine; Vormberge, Thomas; Igl, Bernd-Wolfgang; Hoffmann, Michael

    2016-01-01

    During preclinical drug development, monitoring of the electrocardiogram (ECG) is an important part of cardiac safety assessment. To detect potential pro-arrhythmic liabilities of a drug candidate and for internal decision-making during early stage drug development an in vivo model in small animals with translatability to human cardiac function is required. Over the last years, modifications/improvements regarding animal housing, ECG electrode placement, and data evaluation have been introduced into an established model for ECG recordings using telemetry in conscious, freely moving guinea pigs. Pharmacological validation using selected reference compounds affecting different mechanisms relevant for cardiac electrophysiology (quinidine, flecainide, atenolol, dl-sotalol, dofetilide, nifedipine, moxifloxacin) was conducted and findings were compared with results obtained in telemetered Beagle dogs. Under standardized conditions, reliable ECG data with low variability allowing largely automated evaluation were obtained from the telemetered guinea pig model. The model is sensitive to compounds blocking cardiac sodium channels, hERG K(+) channels and calcium channels, and appears to be even more sensitive to β-blockers as observed in dogs at rest. QT interval correction according to Bazett and Sarma appears to be appropriate methods in conscious guinea pigs. Overall, the telemetered guinea pig is a suitable model for the conduct of early stage preclinical ECG assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2017-01-01

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

  7. Nonlinear analysis of the heartbeats in public patient ECGs using an automated PD2i algorithm for risk stratification of arrhythmic death

    PubMed Central

    Skinner, James E; Anchin, Jerry M; Weiss, Daniel N

    2008-01-01

    Heart rate variability (HRV) reflects both cardiac autonomic function and risk of arrhythmic death (AD). Reduced indices of HRV based on linear stochastic models are independent risk factors for AD in post-myocardial infarct cohorts. Indices based on nonlinear deterministic models have a significantly higher sensitivity and specificity for predicting AD in retrospective data. A need exists for nonlinear analytic software easily used by a medical technician. In the current study, an automated nonlinear algorithm, the time-dependent point correlation dimension (PD2i), was evaluated. The electrocardiogram (ECG) data were provided through an National Institutes of Health-sponsored internet archive (PhysioBank) and consisted of all 22 malignant arrhythmia ECG files (VF/VT) and 22 randomly selected arrhythmia files as the controls. The results were blindly calculated by automated software (Vicor 2.0, Vicor Technologies, Inc., Boca Raton, FL) and showed all analyzable VF/VT files had PD2i < 1.4 and all analyzable controls had PD2i > 1.4. Five VF/VT and six controls were excluded because surrogate testing showed the RR-intervals to contain noise, possibly resulting from the low digitization rate of the ECGs. The sensitivity was 100%, specificity 85%, relative risk > 100; p < 0.01, power > 90%. Thus, automated heartbeat analysis by the time-dependent nonlinear PD2i-algorithm can accurately stratify risk of AD in public data made available for competitive testing of algorithms. PMID:18728829

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

    PubMed

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

    2012-01-01

    Computerized electrocardiogram (ECG) acquisition and interpretation may be extremely useful in handling analysis of data from large cohort studies and exploit research on the use of ECG data as prognostic markers for cardiovascular disease. The Moli-sani project (http://www.moli-sani.org) is a population-based cohort study aiming at evaluating the risk factors linked to chronic-degenerative disease with particular regard to cardiovascular disease and cancer and intermediate metabolic phenotypes such as hypertension, diabetes, dyslipidemia, obesity, and metabolic syndrome. Between March 2005 and April 2010, 24 325 people aged 35 years or older, living in the Molise region (Italy), were randomly recruited. A follow-up based on linkage with hospital discharge records and mortality regional registry and reexamination of the cohort is ongoing and will be repeated at prefixed times. Each subject was administered questionnaires on personal and medical history, food consumption, quality of life (FS36), and psychometry. Plasma serum, cellular pellet, and urinary spots were stored in liquid nitrogen. Subjects were measured blood pressure, weight, height, and waist and hip circumferences, and underwent spirometry to evaluate pulmonary diffusion capacity, gas diffusion, and pulmonary volumes. Standard 12-lead resting ECG was performed by a Cardiette ar2100-view electrocardiograph and tracings stored in digital standard communication protocol format for subsequent analysis. The digital ECG database of the Moli-sani project is currently being used to assess the association between physiologic variables and pathophyiosiologic conditions and parameters derived from the ECG signal. This computerized ECG database represents a unique opportunity to identify and assess prognostic factors associated with cardiovascular and metabolic diseases. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Human ECG signal parameters estimation during controlled physical activity

    NASA Astrophysics Data System (ADS)

    Maciejewski, Marcin; Surtel, Wojciech; Dzida, Grzegorz

    2015-09-01

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

  10. Detecting moxifloxacin‐induced QTc prolongation in thorough QT and early clinical phase studies using a highly automated ECG analysis approach

    PubMed Central

    Karnad, Dilip R; Kadam, Pramod; Badilini, Fabio; Damle, Anil; Kothari, Snehal

    2016-01-01

    Background and Purpose Exposure–response (ER) modelling (concentration–QTc analysis) is gaining as much acceptance as the traditional by‐time analysis of the placebo‐adjusted change from baseline in the QTc interval (ΔΔQTcF). It has been postulated that intensive ECG analysis and ER modelling during early‐phase drug development could be a cost‐effective approach of estimating QT liability of a new drug, in a small number of subjects. Experimental Approach We used a highly automated analysis of ECGs from 46 subjects from a crossover thorough QT/QTc study to detect ΔΔQTcF with moxifloxacin. Using these data, we also simulated (bootstrapped) 1000 datasets of a parallel study with eight subjects receiving moxifloxacin and eight others receiving placebo. Key Results The slope from the concentration–QTc analysis for moxifloxacin in 46 subjects was 4.12 ms of ΔΔQTcF per μg‐1 mL‐1; at mean C max of 2.95 μg·mL−1, estimated ΔΔQTcF was 13.4 ms (90% confidence interval 11.3, 15.4 ms). In the 1000 simulated datasets, in 996 datasets, ER modelling showed that the upper bound of the 90% confidence interval for ΔΔQTcF at geometric mean C max exceeded 10 ms. In 895 of these 996 datasets, the slope of the ER relationship was statistically significantly positive. Thus, with a small sample size (eight subjects on active drug and eight on placebo), moxifloxacin‐induced QTc prolongation was demonstrated using ER analysis with statistical power of >80%. Conclusions and Implications Our study adds to the growing body of data supporting intensive ECG collection and analysis in early‐phase studies to estimate QT liability. PMID:26784016

  11. Complex network analysis of resting-state fMRI of the brain.

    PubMed

    Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

    2016-08-01

    Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

  12. The Cardiac Safety Research Consortium ECG database.

    PubMed

    Kligfield, Paul; Green, Cynthia L

    2012-01-01

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

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

    PubMed

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

    2006-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Ragulskaya, Maria; Valeriy, Pipin

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

  15. Wavelets for full reconfigurable ECG acquisition system

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  16. Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis

    PubMed Central

    Lau, W K W; Leung, M-K; Lee, T M C; Law, A C K

    2016-01-01

    Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI. PMID:27115121

  17. Cardiac safety of tiotropium in patients with COPD: a combined analysis of Holter-ECG data from four randomised clinical trials.

    PubMed

    Hohlfeld, J M; Furtwaengler, A; Könen-Bergmann, M; Wallenstein, G; Walter, B; Bateman, E D

    2015-01-01

    Tiotropium is generally well tolerated; however, there has been debate whether antimuscarinics, particularly tiotropium administered via Respimat(®) Soft Mist(™) Inhaler, may induce cardiac arrhythmias in a vulnerable subpopulation with cardiovascular comorbidity. The aim of this study was to provide evidence of the cardiac safety of tiotropium maintenance therapy. Combined analysis of Holter electrocardiogram (ECG) data from clinical trials of tiotropium in chronic obstructive pulmonary disease (COPD). Trials in the Boehringer Ingelheim clinical trials database conducted between 2003 and 2012, involving tiotropium HandiHaler(®) 18 μg and/or tiotropium Respimat(®) (1.25-, 2.5-, 5.0- and 10-μg doses) were reviewed. All trials involving Holter-ECG monitoring during this period were included in the analysis. Men and women aged ≥ 40 years with a smoking history of ≥ 10 pack-years, and a clinical diagnosis of COPD were included. Holter ECGs were evaluated for heart rate (HR), supraventricular premature beats (SVPBs), ventricular premature beats (VPBs) and pauses. Quantitative and categorical end-points were derived for each of the Holter monitoring days. Four trials (n = 727) were included in the analysis. Respimat(®) (1.25-10 μg) or HandiHaler(®) (18 μg) was not associated with changes in HR, SVPBs, VPBs and pauses compared with placebo or the pretreatment baseline period. In terms of cardiac arrhythmia end-points, there was no evidence for an exposure-effect relationship. In this analysis, tiotropium maintenance therapy administered using Respimat(®) (1.25-10 μg) or HandiHaler(®) (18 μg) once daily for periods of up to 48 weeks was well tolerated with no increased risk of cardiac arrhythmia in patients with COPD. © 2014 The Authors. International Journal of Clinical Practice Published by John Wiley & Sons Ltd.

  18. Segmentation of holter ECG waves via analysis of a discrete wavelet-derived multiple skewness-kurtosis based metric.

    PubMed

    Ghaffari, A; Homaeinezhad, M R; Khazraee, M; Daevaeiha, M M

    2010-04-01

    In this study, a simple mathematical-statistical based metric called Multiple Higher Order Moments (MHOM) is introduced enabling the electrocardiogram (ECG) detection-delineation algorithm to yield acceptable results in the cases of ambulatory holter ECG including strong noise, motion artifacts, and severe arrhythmia(s). In the MHOM measure, important geometric characteristics such as maximum value to minimum value ratio, area, extent of smoothness or being impulsive and distribution skewness degree (asymmetry), occult. In the proposed method, first three leads of high resolution 24-h holter data are extracted and preprocessed using Discrete Wavelet Transform (DWT). Next, a sample to sample sliding window is applied to preprocessed sequence and in each slid, mean value, variance, skewness, and kurtosis of the excerpted segment are superimposed called MHOM. The MHOM metric is then used as decision statistic to detect and delineate ECG events. To show advantages of the presented method, it is applied to MIT-BIH Arrhythmia Database, QT Database, and T-Wave Alternans Database and as a result, the average values of sensitivity and positive predictivity Se = 99.95% and P+ = 99.94% are obtained for the detection of QRS complexes, with the average maximum delineation error of 6.1, 4.1, and 6.5 ms for P-wave, QRS complex, and T-wave, respectively showing marginal improvement of detection-delineation performance. In the next step, the proposed method is applied to DAY hospital high resolution holter data (more than 1,500,000 beats including Bundle Branch Blocks--BBB, Premature Ventricular Complex--PVC, and Premature Atrial Complex-PAC) and average values of Se = 99.97% and P+ = 99.95% are obtained for QRS detection. In summary, marginal performance improvement of ECG events detection-delineation process, reliable robustness against strong noise, artifacts, and probable severe arrhythmia(s) of high resolution holter data can be mentioned as important merits and capabilities

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  20. Sparse dictionary learning for resting-state fMRI analysis

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  1. Tremor suppression in ECG

    PubMed Central

    Dotsinsky, Ivan A; Mihov, Georgy S

    2008-01-01

    Background Electrocardiogram recordings are very often contaminated by high-frequency noise usually power-line interference and EMG disturbances (tremor). Specific method for interference cancellation without affecting the proper ECG components, called subtraction procedure, was developed some two decades ago. Filtering out the tremor remains a priori partially successful since it has a relatively wide spectrum, which overlaps the useful ECG frequency band. Method The proposed method for tremor suppression implements the following three procedures. Contaminated ECG signals are subjected to moving averaging (comb filter with linear phase characteristic) with first zero set at 50 Hz to suppress tremor and PL interference simultaneously. The reduced peaks of QRS complexes and other relatively high and steep ECG waves are then restored by an introduced by us procedure called linearly-angular, so that the useful high frequency components are preserved in the range specified by the embedded in the ECG instrument filter, usually up to 125 Hz. Finally, a Savitzky-Golay smoothing filter is applied for supplementary tremor suppression outside the QRS complexes. Results The results obtained show a low level of the residual EMG disturbances together with negligible distortion of the wave shapes regardless of rhythm and morphology changes. PMID:19019218

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

    NASA Astrophysics Data System (ADS)

    Almurshedi, A.; Ismail, A. K.

    2014-11-01

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

  3. An ECG Index of Myocardial Scar Enhances Prediction of Defibrillator Shocks: An Analysis of the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT)

    PubMed Central

    Strauss, David G.; Poole, Jeanne E.; Wagner, Galen S.; Selvester, Ronald H.; Miller, Julie M.; Anderson, Jill; Johnson, George; McNulty, Steven E.; Mark, Daniel B.; Lee, Kerry L.; Bardy, Gust H.; Wu, Katherine C.

    2010-01-01

    Background Only a minority of patients receiving implantable cardioverter-defibrillators (ICDs) for the primary prevention of sudden death receive appropriate shocks, yet almost as many are subjected to inappropriate shocks and device complications. Identifying and quantifying myocardial scar, which forms the substrate for ventricular tachyarrhythmias, may improve risk-stratification. Objective To determine if the absence of myocardial scar detected by novel 12-lead ECG Selvester QRS-scoring criteria identifies patients with low risk for appropriate ICD shocks. Methods We applied QRS-scoring to 797 patients from the ICD arm of the Sudden Cardiac Death in Heart Failure Trial. Patients were followed for a median of 45.5 months for ventricular tachycardia/fibrillation treated by the ICD or sudden tachyarrhythmic death (combined group referred to as VT/VF). Results Increasing QRS-score scar size predicted higher rates of VT/VF. Patients with no scar (QRS-score=0) represented a particularly low-risk cohort with 48% fewer VT/VF events than the rest of the population (absolute difference 11%; hazard ratio 0.52, 95% CI=0.31–0.88). QRS-score scar absence vs. presence remained a significant prognostic factor after controlling for 10 clinically-relevant variables. Combining QRS-score (scar absence vs. presence) with ejection fraction (≥25% vs. <25%) distinguished low-, middle-, and high-risk subgroups with 73% fewer VT/VF events in the low- vs. high-risk group (absolute difference 22%; hazard ratio=0.27, 95% CI=0.12–0.62). Conclusions Patients with no scar by QRS-scoring have significantly fewer VT/VF events. This inexpensive 12-lead ECG tool provides unique, incremental prognostic information and should be considered in risk-stratifying algorithms for selecting patients for ICDs. PMID:20884379

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2017-01-01

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

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

    PubMed

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

    2013-01-01

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

  7. Detection and evaluation of ventricular repolarization alternans: an approach to combined ECG, thoracic impedance, and beat-to-beat heart rate variability analysis.

    PubMed

    Kriščiukaitis, Algimantas; Šimoliūnienė, Renata; Macas, Andrius; Petrolis, Robertas; Drėgūnas, Kęstutis; Bakšytė, Giedrė; Pieteris, Linas; Bertašienė, Zita; Žaliūnas, Remigijus

    2014-01-01

    Beat-to-beat alteration in ventricles repolarization reflected by alternans of amplitude and/or shape of ECG S-T,T segment (TWA) is known as phenomena related with risk of severe arrhythmias leading to sudden cardiac death. Technical difficulties have caused limited its usage in clinical diagnostics. Possibilities to register and analyze multimodal signals reflecting heart activity inspired search for new technical solutions. First objective of this study was to test whether thoracic impedance signal and beat-to-beat heart rate reflect repolarization alternans detected as TWA. The second objective was revelation of multimodal signal features more comprehensively representing the phenomena and increasing its prognostic usefulness. ECG, and thoracic impedance signal recordings made during 24h follow-up of the patients hospitalized in acute phase of myocardial infarction were used for investigation. Signal morphology variations reflecting estimates were obtained by the principal component analysis-based method. Clinical outcomes of patients (survival and/or rehospitalization in 6 and 12 months) were compared to repolarization alternans and heart rate variability estimates. Repolarization alternans detected as TWA was also reflected in estimates of thoracic impedance signal shape and variation in beat-to-beat heart rate. All these parameters showed correlation with clinical outcomes of patients. The strongest significant correlation showed magnitude of alternans in estimates of thoracic impedance signal shape. The features of ECG, thoracic impedance signal and beat-to-beat variability of heart rate, give comprehensive estimates of repolarization alternans, which correlate, with clinical outcomes of the patients and we recommend using them to improve diagnostic reliability. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

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

    PubMed Central

    2010-01-01

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

  10. Hybrid ECG signal conditioner

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Li, Zhuo; Wang, Li

    2009-12-01

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

  12. Recognizing mild cognitive impairment based on network connectivity analysis of resting EEG with zero reference.

    PubMed

    Xu, Peng; Xiong, Xiu Chun; Xue, Qing; Tian, Yin; Peng, Yueheng; Zhang, Rui; Li, Pei Yang; Wang, Yu Ping; Yao, De Zhong

    2014-07-01

    The diagnosis of mild cognitive impairment (MCI) is very helpful for early therapeutic interventions of Alzheimer's disease (AD). MCI has been proven to be correlated with disorders in multiple brain areas. In this paper, we used information from resting brain networks at different EEG frequency bands to reliably recognize MCI. Because EEG network analysis is influenced by the reference that is used, we also evaluate the effect of the reference choices on the resting scalp EEG network-based MCI differentiation. The conducted study reveals two aspects: (1) the network-based MCI differentiation is superior to the previously reported classification that uses coherence in the EEG; and (2) the used EEG reference influences the differentiation performance, and the zero approximation technique (reference electrode standardization technique, REST) can construct a more accurate scalp EEG network, which results in a higher differentiation accuracy for MCI. This study indicates that the resting scalp EEG-based network analysis could be valuable for MCI recognition in the future.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    PubMed

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

    2017-04-01

    The configuration of the human brain system at rest, which is in a transitory phase among multistable states, remains unknown. To investigate the dynamic systems properties of the human brain at rest, we constructed an energy landscape for the state dynamics of the subcortical brain network, a critical center that modulates whole brain states, using resting state fMRI. We evaluated alterations in energy landscapes following perturbation in network parameters, which revealed characteristics of the state dynamics in the subcortical brain system, such as maximal number of attractors, unequal temporal occupations, and readiness for reconfiguration of the system. Perturbation in the network parameters, even those as small as the ones in individual nodes or edges, caused a significant shift in the energy landscape of brain systems. The effect of the perturbation on the energy landscape depended on the network properties of the perturbed nodes and edges, with greater effects on hub nodes and hubs-connecting edges in the subcortical brain system. Two simultaneously perturbed nodes produced perturbation effects showing low sensitivity in the interhemispheric homologous nodes and strong dependency on the more primary node among the two. This study demonstrated that energy landscape analysis could be an important tool to investigate alterations in brain networks that may underlie certain brain diseases, or diverse brain functions that may emerge due to the reconfiguration of the default brain network at rest. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. A Meta-analysis on Resting State High-frequency Heart Rate Variability in Bulimia Nervosa.

    PubMed

    Peschel, Stephanie K V; Feeling, Nicole R; Vögele, Claus; Kaess, Michael; Thayer, Julian F; Koenig, Julian

    2016-09-01

    Autonomic nervous system function is altered in eating disorders. We aimed to quantify differences in resting state vagal activity, indexed by high-frequency heart rate variability comparing patients with bulimia nervosa (BN) and healthy controls. A systematic search of the literature to identify studies eligible for inclusion and meta-analytical methods were applied. Meta-regression was used to identify potential covariates. Eight studies reporting measures of resting high-frequency heart rate variability in individuals with BN (n = 137) and controls (n = 190) were included. Random-effects meta-analysis revealed a sizeable main effect (Z = 2.22, p = .03; Hedge's g = 0.52, 95% CI [0.06;0.98]) indicating higher resting state vagal activity in individuals with BN. Meta-regression showed that body mass index and medication intake are significant covariates. Findings suggest higher vagal activity in BN at rest, particularly in unmedicated samples with lower body mass index. Potential mechanisms underlying these findings and implications for routine clinical care are discussed. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

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

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2009-05-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    PubMed

    Sami, S; Miall, R C

    2013-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  3. Local sparse component analysis for blind source separation: an application to resting state FMRI.

    PubMed

    Vieira, Gilson; Amaro, Edson; Baccala, Luiz A

    2014-01-01

    We propose a new Blind Source Separation technique for whole-brain activity estimation that best profits from FMRI's intrinsic spatial sparsity. The Local Sparse Component Analysis (LSCA) combines wavelet analysis, group-separable regularizers, contiguity-constrained clusterization and principal components analysis (PCA) into a unique spatial sparse representation of FMRI images towards efficient dimensionality reduction without sacrificing physiological characteristics by avoiding artificial stochastic model constraints. The LSCA outperforms classical PCA source reconstruction for artificial data sets over many noise levels. A real FMRI data illustration reveals resting-state activities in regions hard to observe, such as thalamus and basal ganglia, because of their small spatial scale.

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

    PubMed

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    PubMed

    Ramkumar, Pavan; Parkkonen, Lauri; Hyvärinen, Aapo

    2014-02-01

    We developed a data-driven method to spatiotemporally and spectrally characterize the dynamics of brain oscillations in resting-state magnetoencephalography (MEG) data. The method, called envelope spatial Fourier independent component analysis (eSFICA), maximizes the spatial and spectral sparseness of Fourier energies of a cortically constrained source current estimate. We compared this method using a simulated data set against 5 other variants of independent component analysis and found that eSFICA performed on par with its temporal variant, eTFICA, and better than other ICA variants, in characterizing dynamics at time scales of the order of minutes. We then applied eSFICA to real MEG data obtained from 9 subjects during rest. The method identified several networks showing within- and cross-frequency inter-areal functional connectivity profiles which resemble previously reported resting-state networks, such as the bilateral sensorimotor network at ~20Hz, the lateral and medial parieto-occipital sources at ~10Hz, a subset of the default-mode network at ~8 and ~15Hz, and lateralized temporal lobe sources at ~8Hz. Finally, we interpreted the estimated networks as spatiospectral filters and applied the filters to obtain the dynamics during a natural stimulus sequence presented to the same 9 subjects. We observed occipital alpha modulation to visual stimuli, bilateral rolandic mu modulation to tactile stimuli and video clips of hands, and the temporal lobe network modulation to speech stimuli, but no modulation of the sources in the default-mode network. We conclude that (1) the proposed method robustly detects inter-areal cross-frequency networks at long time scales, (2) the functional relevance of the resting-state networks can be probed by applying the obtained spatiospectral filters to data from measurements with controlled external stimulation. © 2013 Elsevier Inc. All rights reserved.

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

    PubMed

    Cucherat, Michel; Borer, Jeffrey S

    2012-07-01

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

  8. Effect of ECG filter settings on J-waves.

    PubMed

    Nakagawa, Mikiko; Tsunemitsu, Chie; Katoh, Sayo; Kamiyama, Yukari; Sano, Nario; Ezaki, Kaori; Miyazaki, Hiroko; Teshima, Yasushi; Yufu, Kunio; Takahashi, Naohiko; Saikawa, Tetsunori

    2014-01-01

    While J-waves were observed in healthy populations, variations in their reported incidence may be partly explicable by the ECG filter setting. We obtained resting 12-lead ECG recordings in 665 consecutive patients and enrolled 112 (56 men, 56 women, mean age 59.3±16.1years) who manifested J-waves on ECGs acquired with a 150-Hz low-pass filter. We then studied the J-waves on individual ECGs to look for morphological changes when 25-, 35-, 75-, 100-, and 150Hz filters were used. The notching observed with the 150-Hz filter changed to slurring (42%) or was eliminated (28%) with the 25-Hz filter. Similarly, the slurring seen with the 150-Hz filter was eliminated on 71% of ECGs recorded with the 25-Hz filter. The amplitude of J-waves was significantly lower with 25- and 35-Hz than 75-, 100-, and 150-Hz filters (p<0.0001). The ECG filter setting significantly affects the J-wave morphology. © 2013.

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

    NASA Astrophysics Data System (ADS)

    Almurshedi, Ahmed; Ismail, Abd Khamim

    2015-04-01

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

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

    PubMed

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

    2012-01-01

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

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

    PubMed Central

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

    2017-01-01

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

  12. Effect of field spread on resting-state MEG functional network analysis: a computational modeling study.

    PubMed

    Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; Van Ede, Freek; Griffa, Alessandra; Hagmann, Patrick; Deco, Gustavo

    2017-09-06

    A popular way to analyze resting-state EEG and MEG data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time-series with the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time-series are mixtures of source activity. It is therefore of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion MRI-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged functional connectivity at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We therefore recommend to use lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.

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

    PubMed

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

    2014-01-01

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

  14. Empirical mode decomposition of the ECG signal for noise removal

    NASA Astrophysics Data System (ADS)

    Khan, Jesmin; Bhuiyan, Sharif; Murphy, Gregory; Alam, Mohammad

    2011-04-01

    Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

  15. Digitalis toxicity: ECG vignette.

    PubMed

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

    2016-09-01

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

  16. Effect of therapeutic hypothermia on the outcomes after out-of-hospital cardiac arrest according to initial ECG rhythm and witnessed status: A nationwide observational interaction analysis.

    PubMed

    Choi, Sae Won; Shin, Sang Do; Ro, Young Sun; Song, Kyoung Jun; Lee, Eui Jung; Ahn, Ki Ok

    2016-03-01

    The use of mild therapeutic hypothermia (TH) in out-of-hospital cardiac arrest (OHCA) with shockable rhythms is recommended and widely used. However, it is unclear whether TH is associated with better outcomes in non-shockable rhythms. This is a retrospective observational study using a national OHCA cohort database composed of emergency medical services (EMS) and hospital data. We included adult EMS-treated OHCA patients of presumed cardiac etiology who were admitted to the hospital during Jan. 2008 to Dec. 2013. Patients without hospital outcome data were excluded. The primary outcome was good neurological outcome at discharge; secondary outcome was survival to discharge. The primary exposure was TH. We compared outcomes between TH and non-TH groups using multivariable logistic regression, adjusting for individual and Utstein factors. Interactions of initial ECG rhythm and witnessed status on the effect of TH on outcomes were tested. There were 11,256 patients in the final analysis. TH was performed in 1703 patients (15.1%). Neurological outcome was better in TH (23.5%) than non-TH (15.0%) (Adjusted OR=1.25, 95% CI 1.05-1.48). The effect of TH on the odds for good neurological outcome was highest in the witnessed PEA group (Adjusted OR=3.91, 95% CI 1.87-8.14). Survival to discharge was significantly higher in the TH group (55.1%) than non-TH (35.9%) (Adjusted OR=1.76, 95% CI 1.56-2.00). In a nationwide observational study, TH is associated with better neurological outcome and higher survival to discharge. The effect of TH is greatest in witnessed OHCA patients with PEA as the initial ECG rhythm. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. Analysis of Intermediates of Steroid Transformations in Resting Cells by Thin-Layer Chromatography (TLC).

    PubMed

    Guevara, Govinda; Perera, Julián; Navarro-Llorens, Juana-María

    2017-01-01

    Thin-layer chromatography (TLC) is a useful and convenient method for the analysis of steroids due to: its simple sample preparation, low time-consuming process, high sensitivity, low equipment investment and capacity to work on many samples simultaneously. Here we describe a TLC easy protocol very useful to analyze steroid molecules derived from a biotransformation carried out in wild-type and mutant resting cells of Rhodococcus ruber strain Chol-4. Following this protocol, we were able to detect the presence or the absence of some well-known intermediates of cholesterol catabolism in Rhodococcus, namely AD, ADD, and 9OHAD.

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    PubMed

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

    2010-07-01

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

  20. Brugada ECG patterns in athletes.

    PubMed

    Chung, Eugene H

    2015-01-01

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

  1. Wireless Smartphone ECG Enables Large-Scale Screening in Diverse Populations.

    PubMed

    Haberman, Zachary C; Jahn, Ryan T; Bose, Rupan; Tun, Han; Shinbane, Jerold S; Doshi, Rahul N; Chang, Philip M; Saxon, Leslie A

    2015-05-01

    The ubiquitous presence of internet-connected phones and tablets presents a new opportunity for cost-effective and efficient electrocardiogram (ECG) screening and on-demand diagnosis. Wireless, single-lead real-time ECG monitoring supported by iOS and android devices can be obtained quickly and on-demand. ECGs can be immediately downloaded and reviewed using any internet browser. We compared the standard 12-lead ECG to the smartphone ECG in healthy young adults, elite athletes, and cardiology clinic patients. Accuracy for determining baseline ECG intervals and rate and rhythm was assessed. In 381 participants, 30-second lead I ECG waveforms were obtained using an iPhone case or iPad. Standard 12-lead ECGs were acquired immediately after the smartphone tracing was obtained. De-identified ECGs were interpreted by automated algorithms and adjudicated by two board-certified electrophysiologists. Both smartphone and standard ECGs detected atrial rate and rhythm, AV block, and QRS delay with equal accuracy. Sensitivities ranged from 72% (QRS delay) to 94% (atrial fibrillation). Specificities were all above 94% for both modalities. Smartphone ECG accurately detects baseline intervals, atrial rate, and rhythm and enables screening in diverse populations. Efficient ECG analysis using automated discrimination and an enhanced smartphone application with notification capabilities are features that can be easily incorporated into the acquisition process. © 2015 Wiley Periodicals, Inc.

  2. Quantitative Analysis of Rest-Activity Patterns in Elderly Postoperative Patients with Delirium: Support for a Theory of Pathologic Wakefulness

    PubMed Central

    Jacobson, Sandra A.; Dwyer, Patrick C.; Machan, Jason T.; Carskadon, Mary A.

    2008-01-01

    Study Objectives: To investigate the feasibility of using wrist actigraphy in a postoperative cohort of elderly patients (delirious versus nondelirious), and to use actigraphy to help characterize diurnal rest-activity patterns in this population. Methods: This was a prospective postoperative study using wrist actigraphy and clinical scales (DRS-R-98 and Mini-Mental State Examination). Actigraphy was continuous for 24 to 72 hours, and scales were completed once daily. DSM-IV-TR criteria were used to diagnose delirium and to separate the sample into delirium and nondelirium groups. Groups were compared at inception (age, sex, time since surgery, number of medications, number of active medical conditions, and presurgical sleep quality). For actigraphy analysis, a 24-hour sample (taken when the DRS-R-98 score was highest) was used for each patient. Statistical analyses were performed on 6 rest-activity parameters to examine group differences. Results: Thirteen patients were studied: 6 with delirium and 7 without delirium. The groups did not differ significantly at inception. Significant group differences were found in diurnal rest-activity patterns: delirious patients showed fewer nighttime minutes resting, fewer minutes resting over 24 hours, greater mean activity at night, and a smaller amplitude of change in activity from day to night. Conclusions: This is the first study to document a significant disruption of the diurnal rest-activity cycle among delirious patients using objective methods and quantitative analysis of activity. Rest and activity consolidation were significantly reduced in delirious patients, as was the amplitude of day-night differences in rest and activity. These findings are consistent with a state of pathologic wakefulness in delirium. Citation: Jacobson SA; Dwyer PC; Machan JT; Carskadon MA. Quantitative analysis of rest-activity patterns in elderly postoperative patients with delirium: support for a theory of pathologic wakefulness. J Clin

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

    PubMed

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

    2016-01-01

    Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  4. Frequency domain analysis of heart rate variability in horses at rest and during exercise.

    PubMed

    Physick-Sheard, P W; Marlin, D J; Thornhill, R; Schroter, R C

    2000-05-01

    The pattern of variation in heart rate on a beat-to-beat basis contains information concerning sympathetic (SNS) and parasympathetic (PNS) contributions to autonomic nervous system (ANS) modulation of heart rate (HR). In the present study, heart period (RR interval) time series data were collected at rest and during 3 different treadmill exercise protocols from 6 Thoroughbred horses. Frequency and spectral power were determined in 3 frequency bands: very low (VLF) 0-< or = 0.01, low (LO) >0.01-< or = 0.07 and high (HI) >0.07-< or = 0.5 cycles/beat. Indicators of sympathetic (SNSI = LO/HI) and parasympathetic (PNSI = HI/TOTAL) activity were calculated. Power in all bands fell progressively with increasing exercise intensity from rest to trot. At the gallop VLF and LO power continued to fall but HI power rose. SNSI rose from rest to walk, then fell with increasing effort and was lowest at the gallop. PNSI fell from rest to walk, then rose and was highest at the gallop. Normalised HI power exceeded combined VLF and LO power at all gaits, with the ratio HI to LO power being lowest at the walk and highest at the gallop. ANS indicators showed considerable inter-horse variation, and varied less consistently than raw power with increasing physical effort. In the horses studied, the relationship between power and HR changed at exercise intensities associated with heart rates above approximately 120-130 beats/min. At this level, humoral and other non-neural mechanisms may become more important than autonomic modulation in influencing heart rate and heart rate variability (HRV). HRV at intense effort may be influenced by respiratory-gait entrainment, energetics of locomotion and work of breathing. HRV analysis in the frequency domain would appear to be of potential value as a noninvasive means of assessing autonomic modulation of heart rate at low exercise intensities, only. The technique may be a sensitive method for assessing exercise response to experimental manipulations

  5. Caffeine and diuresis during rest and exercise: A meta-analysis

    PubMed Central

    Coca, Aitor; Casa, Douglas J.; Antonio, Jose; Green, James M.; Bishop, Phillip A.

    2016-01-01

    Objectives Although ergogenic, acute caffeine ingestion may increase urine volume, prompting concerns about fluid balance during exercise and sport events. This meta-analysis evaluated caffeine induced diuresis in adults during rest and exercise. Design Meta-analysis. Methods A search of three databases was completed on November 1, 2013. Only studies that involved healthy adults and provided sufficient information concerning the effect size (ES) of caffeine ingestion on urine volume were included. Sixteen studies met the inclusion criteria, providing a total of 28 ESs for the meta-analysis. Heterogeneity was assessed using a random-effects model. Results The median caffeine dosage was 300 mg. The overall ES of 0.29 (95% confidence interval (CI) = 0.11-0.48, p = 0.001) corresponds to an increase in urine volume of 109 ± 195 mL or 16.0 ± 19.2% for caffeine ingestion vs. non-caffeine conditions. Subgroup meta-analysis confirmed exercise as a strong moderator: active ES = 0.10, 95% CI = −0.07 to 0.27, p = 0.248 vs. resting ES = 0.54, 95% CI = 0.22–0.85, p = 0.001 (Cochran's Q, p = 0.019). Females (ES = 0.75,95% CI = 0.38–1.13, p< 0.001) were more susceptible to diuretic effects than males (ES = 0.13,95% CI = −0.05 to 0.31, p = 0.158) (Cochran's Q, p = 0.003). Conclusions Caffeine exerted a minor diuretic effect which was negated by exercise. Concerns regarding unwanted fluid loss associated with caffeine consumption are unwarranted particularly when ingestion precedes exercise. PMID:25154702

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  9. The prevalence of abnormal ECG in trained sportsmen

    PubMed Central

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

    2015-01-01

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

  10. ECG Parameters and Exposure to Carbon Ultrafine Particles in Young Healthy Subjects

    PubMed Central

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

    2010-01-01

    The mechanisms underlying the association between air pollution and cardiovascular morbidity and mortality are unknown. This study aimed to determine whether controlled exposure to elemental carbon ultrafine particles (UFP) affects electrocardiogram (ECG) parameters describing heart rate variability; repolarization duration, morphology, and variability; and changes in the ST segment. Two separate controlled studies (12 subjects each) were performed using a crossover design, in which each subject was exposed to filtered air and carbon UFP for 2 hours. The first protocol involved 2 exposures to air and 10 µg/m3 (~ 2 × 106 particles/cm3, count median diameter ~25 nm, geometric standard deviation ~1.6), at rest. The second protocol included 3 exposures to air, 10, and 25 µg/m3 UFP (~ 7 × 106 particles/cm3), with repeated exercise. Each subject underwent a continuous digital 12-lead ECG Holter recording to analyze the above ECG parameters. Repeated measures analysis of variance (ANOVA) was used to compare tested parameters between exposures. The observed responses to UFP exposure were small and generally not significant, although there were trends indicating an increase in parasympathetic tone, which is most likely also responsible for trends toward ST elevation, blunted QTc shortening, and increased variability of T-wave complexity after exposure to UFP. Recovery from exercise showed a blunted response of the parasympathetic system after exposure to UFP in comparison to air exposure. In conclusion, transient exposure to 10–25 µg/m3 ultrafine carbon particles does not cause marked changes in ECG-derived parameters in young healthy subjects. However, trends are observed indicating that some subjects might be susceptible to air pollution, with a response involving autonomic modulation of the heart and repolarization of the ventricular myocardium. PMID:18991063

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

    PubMed

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

    2009-02-01

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

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

    PubMed

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

    1978-07-01

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

  13. Sparse representation-based ECG signal enhancement and QRS detection.

    PubMed

    Zhou, Yichao; Hu, Xiyuan; Tang, Zhenmin; Ahn, Andrew C

    2016-12-01

    Electrocardiogram (ECG) signal enhancement and QRS complex detection is a critical preprocessing step for further heart disease analysis and diagnosis. In this paper, we propose a sparse representation-based ECG signal enhancement and QRS complex detection algorithm. Unlike traditional Fourier or wavelet transform-based methods, which use fixed bases, the proposed algorithm models the ECG signal as the superposition of a few inner structures plus additive random noise, where these structures (referred to here as atoms) can be learned from the input signal or a training set. Using these atoms and their properties, we can accurately approximate the original ECG signal and remove the noise and other artifacts such as baseline wandering. Additionally, some of the atoms with larger kurtosis values can be modified and used as an indication function to detect and locate the QRS complexes in the enhanced ECG signals. To demonstrate the robustness and efficacy of the proposed algorithm, we compare it with several state-of-the-art ECG enhancement and QRS detection algorithms using both simulated and real-life ECG recordings.

  14. Assessing validity and reliability of Resting Metabolic Rate in six gas analysis systems

    PubMed Central

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

    2008-01-01

    The Deltatrac Metabolic Monitor (DTC), one of the most popular indirect calorimetry systems for measuring resting metabolic rate (RMR) in human subjects, is no longer being manufactured. This study compared five different gas analysis systems to the DTC. Resting metabolic rate was measured by the DTC and at least one other instrument at three study sites for a total of 38 participants. The five indirect calorimetry systems included: MedGraphics CPX Ultima, MedGem, Vmax Encore 29 System, TrueOne 2400, and Korr ReeVue. Validity was assessed using paired t-tests to compare means while reliability was assessed by using both paired t-tests and root mean square calculations with F tests for significance. Within-subject comparisons for validity of RMR revealed a significant difference between the DTC and Ultima. Bland-Altman plot analysis showed significant bias with increasing RMR values for the Korr and MedGem. Respiratory exchange ratio (RER) analysis showed a significant difference between the DTC and the Ultima and a trend for a difference with the Vmax (p = 0.09). Reliability assessment for RMR revealed that all instruments had a significantly larger coefficient of variation (CV) (ranging from 4.8% to 10.9%) for RMR compared to the 3.0 % CV for the DTC. Reliability assessment for RER data showed none of the instrument CV’s were significantly larger than the DTC CV. The results were quite disappointing, with none of the instruments equaling the within person reliability of the DTC. The TrueOne and Vmax were the most valid instruments in comparison with the DTC for both RMR and RER assessment. Further testing is needed to identify an instrument with the reliability and validity of the DTC. PMID:19103333

  15. [Evaluation of sleep apnea, detected by 24-hour ECG Holter monitoring analysis in patients with stable coronary artery disease and ischemic heart failure - correlations with clinical data].

    PubMed

    Frączek-Jucha, Magdalena; Rostoff, Paweł; Łach, Jacek; Nessler, Jadwiga; Gackowski, Andrzej

    2017-06-23

    Obstructive sleep apnoea (OSA) is frequently undiagnosed in patients with heart failure (HF) and coronary artery disease (CAD). Simple and widely available screening tests are needed to diagnose patients with SA. Measurements of thoracic impedance and heart rate variability during 24-hour ECG Holter (H-EKG) monitoring allows to calculate estimated apnoea-hypopnoea index (eAHI). The aim of the research was to assess prevalence of OSA evaluated with the use of H-EKG and determination of its clinical relevance in patients with CAD and ischeamic HF. The study groups comprised of: 30 consecutive patients with ischeamic HF with reduced LVEF (HFrEF) (group A) and 30 patients with CAD (group B). Control group (C) comprised of 30 patients with arterial hypertension but no CAD nor HF. H-ECG monitoring was performed and eAHI was calculated. On the basis of AHI result group A was subdivided to subgroups A1 (eAHI <15) and A2 (eAHI ≥15). Study groups differed with eAHI values (27,9±19,9 vs. 21,8±17,3 vs. 15,7±12,2; p=0,022). Post hoc analysis revealed that eAHI in group A was higher in comparison to group C (27,9±19,9 vs. 15,7±12,2; p=0,006). SA prevalence was higher in group A compared to group C (70,0% vs. 40,0%; p=0,019). Significant but weak correlation between eAHI and LVEDD was found (r=0,282; p<0,05). Subgroups A1 and A2 did not differ in terms of clinical and demographical parameters, HF symptoms, LVEF and NT-proBNP levels. OSA coexists more frequently with HF than with arterial hypertension Significant but weak correlation between eAHI and LVEDD was demonstrated. However, in patients with symptomatic ischeamic heart failure eAHI ≥15 was not related to NYHA class, lower LVEF and higher NT-proBNP levels.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2014-08-01

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

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

    SciTech Connect

    Ichinomiya, Osamu; Maruyama, Koichi; Sekine, Kouji

    1995-11-01

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

  20. A Review of Resting-State Electroencephalography Analysis in Disorders of Consciousness

    PubMed Central

    Bai, Yang; Xia, Xiaoyu; Li, Xiaoli

    2017-01-01

    Recently, neuroimaging technologies have been developed as important methods for assessing the brain condition of patients with disorders of consciousness (DOC). Among these technologies, resting-state electroencephalography (EEG) recording and analysis has been widely applied by clinicians due to its relatively low cost and convenience. EEG reflects the electrical activity of the underlying neurons, and it contains information regarding neuronal population oscillations, the information flow pathway, and neural activity networks. Some features derived from EEG signal processing methods have been proposed to describe the electrical features of the brain with DOC. The computation of these features is challenging for clinicians working to comprehend the corresponding physiological meanings and then to put them into clinical applications. This paper reviews studies that analyze spontaneous EEG of DOC, with the purpose of diagnosis, prognosis, and evaluation of brain interventions. It is expected that this review will promote our understanding of the EEG characteristics in DOC.

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

    PubMed

    Niknazar, Mohammad; Rivet, Bertrand; Jutten, Christian

    2013-05-01

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

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

    PubMed

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

    2011-07-01

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

  3. Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG

    PubMed Central

    Skinner, James E; Meyer, Michael; Dalsey, William C; Nester, Brian A; Ramalanjaona, George; O’Neil, Brian J; Mangione, Antoinette; Terregino, Carol; Moreyra, Abel; Weiss, Daniel N; Anchin, Jerry M; Geary, Una; Taggart, Pamela

    2008-01-01

    Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, ∼15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment. PMID:19209249

  4. Piezoelectric extraction of ECG signal

    NASA Astrophysics Data System (ADS)

    Ahmad, Mahmoud Al

    2016-11-01

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

  5. Piezoelectric extraction of ECG signal.

    PubMed

    Ahmad, Mahmoud Al

    2016-11-17

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

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

    PubMed

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

    2004-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  8. [Role of ECG screening and cardiologic examinations in occupational health prevention program for construction workers; results of study in the Province of Bergamo].

    PubMed

    Bigoni, F; Borleri, D; Riva, M M; Bresciani, M; Santini, M; Bancone, C; Mosconi, G

    2012-01-01

    Aim of this study was to estimate prevalence of resting electrocardiogram (ECG) abnormalities in men with high physical work demand, like construction workers and the prevalence of secondary related cardiovascular examinations. Several guidelines for cardiovascular risk management recommend an ECG in patients with cardiovascular risk but there are no clear indications about the frequency of resting ECG during evaluation for fitness for work. The results of our study confirm the presence of age-related ECG abnormalities with a similar stratified prevalence distribution in all age-classes. Our fundings intend to contribute to further discussion in occupational health policies and periodical medical evaluations.

  9. Genome-wide association analysis identifies multiple loci related to resting heart rate

    PubMed Central

    Eijgelsheim, Mark; Newton-Cheh, Christopher; Sotoodehnia, Nona; de Bakker, Paul I.W.; Müller, Martina; Morrison, Alanna C.; Smith, Albert V.; Isaacs, Aaron; Sanna, Serena; Dörr, Marcus; Navarro, Pau; Fuchsberger, Christian; Nolte, Ilja M.; de Geus, Eco J.C.; Estrada, Karol; Hwang, Shih-Jen; Bis, Joshua C.; Rückert, Ina-Maria; Alonso, Alvaro; Launer, Lenore J.; Hottenga, Jouke Jan; Rivadeneira, Fernando; Noseworthy, Peter A.; Rice, Kenneth M.; Perz, Siegfried; Arking, Dan E.; Spector, Tim D.; Kors, Jan A.; Aulchenko, Yurii S.; Tarasov, Kirill V.; Homuth, Georg; Wild, Sarah H.; Marroni, Fabio; Gieger, Christian; Licht, Carmilla M.; Prineas, Ronald J.; Hofman, Albert; Rotter, Jerome I.; Hicks, Andrew A.; Ernst, Florian; Najjar, Samer S.; Wright, Alan F.; Peters, Annette; Fox, Ervin R.; Oostra, Ben A.; Kroemer, Heyo K.; Couper, David; Völzke, Henry; Campbell, Harry; Meitinger, Thomas; Uda, Manuela; Witteman, Jacqueline C.M.; Psaty, Bruce M.; Wichmann, H-Erich; Harris, Tamara B.; Kääb, Stefan; Siscovick, David S.; Jamshidi, Yalda; Uitterlinden, André G.; Folsom, Aaron R.; Larson, Martin G.; Wilson, James F.; Penninx, Brenda W.; Snieder, Harold; Pramstaller, Peter P.; van Duijn, Cornelia M.; Lakatta, Edward G.; Felix, Stephan B.; Gudnason, Vilmundur; Pfeufer, Arne; Heckbert, Susan R.; Stricker, Bruno H.Ch.; Boerwinkle, Eric; O'Donnell, Christopher J.

    2010-01-01

    Higher resting heart rate is associated with increased cardiovascular disease and mortality risk. Though heritable factors play a substantial role in population variation, little is known about specific genetic determinants. This knowledge can impact clinical care by identifying novel factors that influence pathologic heart rate states, modulate heart rate through cardiac structure and function or by improving our understanding of the physiology of heart rate regulation. To identify common genetic variants associated with heart rate, we performed a meta-analysis of 15 genome-wide association studies (GWAS), including 38 991 subjects of European ancestry, estimating the association between age-, sex- and body mass-adjusted RR interval (inverse heart rate) and ∼2.5 million markers. Results with P < 5 × 10−8 were considered genome-wide significant. We constructed regression models with multiple markers to assess whether results at less stringent thresholds were likely to be truly associated with RR interval. We identified six novel associations with resting heart rate at six loci: 6q22 near GJA1; 14q12 near MYH7; 12p12 near SOX5, c12orf67, BCAT1, LRMP and CASC1; 6q22 near SLC35F1, PLN and c6orf204; 7q22 near SLC12A9 and UfSp1; and 11q12 near FADS1. Associations at 6q22 400 kb away from GJA1, at 14q12 MYH6 and at 1q32 near CD34 identified in previously published GWAS were confirmed. In aggregate, these variants explain ∼0.7% of RR interval variance. A multivariant regression model including 20 variants with P < 10−5 increased the explained variance to 1.6%, suggesting that some loci falling short of genome-wide significance are likely truly associated. Future research is warranted to elucidate underlying mechanisms that may impact clinical care. PMID:20639392

  10. Translation of EEG Spatial Filters from Resting to Motor Imagery Using Independent Component Analysis

    PubMed Central

    Wang, Yijun; Wang, Yu-Te; Jung, Tzyy-Ping

    2012-01-01

    Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often use spatial filters to improve signal-to-noise ratio of task-related EEG activities. To obtain robust spatial filters, large amounts of labeled data, which are often expensive and labor-intensive to obtain, need to be collected in a training procedure before online BCI control. Several studies have recently developed zero-training methods using a session-to-session scenario in order to alleviate this problem. To our knowledge, a state-to-state translation, which applies spatial filters derived from one state to another, has never been reported. This study proposes a state-to-state, zero-training method to construct spatial filters for extracting EEG changes induced by motor imagery. Independent component analysis (ICA) was separately applied to the multi-channel EEG in the resting and the motor imagery states to obtain motor-related spatial filters. The resultant spatial filters were then applied to single-trial EEG to differentiate left- and right-hand imagery movements. On a motor imagery dataset collected from nine subjects, comparable classification accuracies were obtained by using ICA-based spatial filters derived from the two states (motor imagery: 87.0%, resting: 85.9%), which were both significantly higher than the accuracy achieved by using monopolar scalp EEG data (80.4%). The proposed method considerably increases the practicality of BCI systems in real-world environments because it is less sensitive to electrode misalignment across different sessions or days and does not require annotated pilot data to derive spatial filters. PMID:22666377

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

    PubMed

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

    2012-11-16

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

  12. Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

    PubMed

    Xiong, Guanglei; Kola, Deeksha; Heo, Ran; Elmore, Kimberly; Cho, Iksung; Min, James K

    2015-08-01

    Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for determination of the physiologic significance of the visualized stenoses. In this paper, we propose a new system to determine the physiologic manifestation of coronary stenoses by assessment of myocardial perfusion from typically acquired CTA images at rest. As a first step, we develop an automated segmentation method to delineate the left ventricle. Both endocardium and epicardium are compactly modeled with subdivision surfaces and coupled by explicit thickness representation. After initialization with five anatomical landmarks, the model is adapted to a target image by deformation increments including control vertex displacements and thickness variations guided by trained AdaBoost classifiers, and regularized by a prior of deformation increments from principal component analysis (PCA). The evaluation using a 5-fold cross-validation demonstrates the overall segmentation error to be 1.00 ± 0.39 mm for endocardium and 1.06 ± 0.43 mm for epicardium, with a boundary contour alignment error of 2.79 ± 0.52. Based on our LV model, two types of myocardial perfusion analyzes have been performed. One is a perfusion network analysis, which explores the correlation (as network edges) pattern of perfusion between all pairs of myocardial segments (as network nodes) defined in AHA 17-segment model. We find perfusion network display different patterns in the normal and disease groups, as divided by whether significant coronary stenosis is present in quantitative coronary angiography (QCA). The other analysis is a clinical validation assessment of the ability of the developed algorithm to predict whether a patient has significant coronary stenosis when referenced to an invasive QCA ground truth standard. By training three machine

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2015-10-01

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

  17. A Novel ECG Eigenvalue Detection Algorithm Based on Wavelet Transform

    PubMed Central

    2017-01-01

    This study investigated an electrocardiogram (ECG) eigenvalue automatic analysis and detection method; ECG eigenvalues were used to reverse the myocardial action potential in order to achieve automatic detection and diagnosis of heart disease. Firstly, the frequency component of the feature signal was extracted based on the wavelet transform, which could be used to locate the signal feature after the energy integral processing. Secondly, this study established a simultaneous equations model of action potentials of the myocardial membrane, using ECG eigenvalues for regression fitting, in order to accurately obtain the eigenvalue vector of myocardial membrane potential. The experimental results show that the accuracy of ECG eigenvalue recognition is more than 99.27%, and the accuracy rate of detection of heart disease such as myocardial ischemia and heart failure is more than 86.7%. PMID:28596962

  18. Computational Electrocardiography: Revisiting Holter ECG Monitoring.

    PubMed

    Deserno, Thomas M; Marx, Nikolaus

    2016-08-05

    Since 1942, when Goldberger introduced the 12-lead electrocardiography (ECG), this diagnostic method has not been changed. After 70 years of technologic developments, we revisit Holter ECG from recording to understanding. A fundamental change is fore-seen towards "computational ECG" (CECG), where continuous monitoring is producing big data volumes that are impossible to be inspected conventionally but require efficient computational methods. We draw parallels between CECG and computational biology, in particular with respect to computed tomography, computed radiology, and computed photography. From that, we identify technology and methodology needed for CECG. Real-time transfer of raw data into meaningful parameters that are tracked over time will allow prediction of serious events, such as sudden cardiac death. Evolved from Holter's technology, portable smartphones with Bluetooth-connected textile-embedded sensors will capture noisy raw data (recording), process meaningful parameters over time (analysis), and transfer them to cloud services for sharing (handling), predicting serious events, and alarming (understanding). To make this happen, the following fields need more research: i) signal processing, ii) cycle decomposition; iii) cycle normalization, iv) cycle modeling, v) clinical parameter computation, vi) physiological modeling, and vii) event prediction. We shall start immediately developing methodology for CECG analysis and understanding.

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

    PubMed

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

    2013-01-15

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

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

    NASA Technical Reports Server (NTRS)

    Gu, Randy J.; Cozzarelli, Francis A.

    1988-01-01

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

  1. Preprocessing of Holter ECGs for analysis of the dynamic interrelations between heart rate and ventricular repolarization duration variabilities.

    PubMed

    Merri, M; Alberti, M; Benhorin, J; Moss, A J

    1990-01-01

    The use of approved commercial digital Holter systems as equipment for data acquisition in cardiologic research presents several potential advantages. In fact, it may provide a standard data acquisition procedure that allows the scientists to concentrate on the data processing phase. As a consequence, it may contribute to the comparability of results among different laboratories. In general, some steps of preprocessing are needed before performing the final analysis on the data. In case of study on the variabilities of the heart rate and the duration of repolarization, preprocessing consists of beat-by-beat measurement time intervals in the 24-hour electrocardiograms. Further preprocessing steps may be required, depending on the particular analysis technique that will be applied to the data. In particular, the present study introduces an operator-free method of preprocessing Holter electrocardiograms for time series analysis of signals related to heart rate variability and variability in the duration of ventricular repolarization.

  2. Human ECG indicators for fast screening and evaluation

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  3. The future of remote ECG monitoring systems

    PubMed Central

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    SciTech Connect

    Gibson, R.S. )

    1989-08-01

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

  6. [Effects of filtering techniques on time-domain analysis of signal-averaged ECG after acute myocardial infarction: a multicenter study, GISS-3 arrhythmia sub-project].

    PubMed

    Del Greco, M; Nollo, G; Disertori, M; Sanna, G; Maggioni, A P; Santoro, E; Tarantino, F; Della Mea, M T; Antolini, R; Micciolo, R

    1996-01-01

    To evaluate the influence of different filtering techniques on the measurement of ventricular late potentials (VLP) the Sottoprogetto Aritmie of GISSI-3 collected signal-averaged ECG (SAECG) from 647 patients. Data were recorded after myocardial infarction (10 +/- 4 days) in 20 Italian Coronary Units. Three main filtering algorithms were used in the different commercial devices: Bidirectional Filter (ART, Aerotel, Fidelity Medical) (BF: 340 Patients), Spectral Filter (Marquette) (SF: 258 Patients) and Del Mar Filter (Del Mar Avionics) (DF: 49 Patients). QRS duration (QRSD), low amplitude signal duration (LAS40) and root mean-square-voltage (RMS40), were measured with various filters set at 40-250 Hz high and low pass frequencies. After correction for clinical variables the measurements of VLP in the three different groups were different. QRSD value obtained by BF (100.6 +/- 13 ms) was shorter than that obtained by SF (109.1 +/- 12 ms). No differences were found in LAS40 and RMS40 values between SF and BF, while DF gave longer LAS40 and lower RMS40 than SF and BF. Residual noise was lower in BF (0.3 +/- 0.1 muV). than in SF and DF (0.5 +/- 0.1 muV). Applying standard criteria DF gave a higher prevalence of VLP (48.9%) than BF (23.8%) and SF (19%) groups. This study demonstrates that the use of different filters produces discordant result on VLP measurements. For correct application of SAECG analysis in risk stratification after myocardial infarction, normal and abnormal values must be specifically established for the different filter techniques.

  7. Diagnostic grade wireless ECG monitoring.

    PubMed

    Garudadri, Harinath; Chi, Yuejie; Baker, Steve; Majumdar, Somdeb; Baheti, Pawan K; Ballard, Dan

    2011-01-01

    In remote monitoring of Electrocardiogram (ECG), it is very important to ensure that the diagnostic integrity of signals is not compromised by sensing artifacts and channel errors. It is also important for the sensors to be extremely power efficient to enable wearable form factors and long battery life. We present an application of Compressive Sensing (CS) as an error mitigation scheme at the application layer for wearable, wireless sensors in diagnostic grade remote monitoring of ECG. In our previous work, we described an approach to mitigate errors due to packet losses by projecting ECG data to a random space and recovering a faithful representation using sparse reconstruction methods. Our contributions in this work are twofold. First, we present an efficient hardware implementation of random projection at the sensor. Second, we validate the diagnostic integrity of the reconstructed ECG after packet loss mitigation. We validate our approach on MIT and AHA databases comprising more than 250,000 normal and abnormal beats using EC57 protocols adopted by the Food and Drug Administration (FDA). We show that sensitivity and positive predictivity of a state-of-the-art ECG arrhythmia classifier is essentially invariant under CS based packet loss mitigation for both normal and abnormal beats even at high packet loss rates. In contrast, the performance degrades significantly in the absence of any error mitigation scheme, particularly for abnormal beats such as Ventricular Ectopic Beats (VEB).

  8. Quantification of the Fragmentation of Rest-Activity Patterns in Elderly Individuals Using a State Transition Analysis

    PubMed Central

    Lim, Andrew S.P.; Yu, Lei; Costa, Madalena D.; Buchman, Aron S.; Bennett, David A.; Leurgans, Sue E.; Saper, Clifford B.

    2011-01-01

    . Citation: Lim ASP; Yu L; Costa MD; Buchman AS; Bennett DA; Leurgans SE; Saper CB. Quantification of the fragmentation of rest-activity patterns in elderly individuals using a state transition analysis. PMID:22043128

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

    PubMed

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

    2014-11-01

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

  10. Dispersion entropy for the analysis of resting-state MEG regularity in Alzheimer's disease.

    PubMed

    Azami, Hamed; Rostaghi, Mostafa; Fernandez, Alberto; Escudero, Javier

    2016-08-01

    Alzheimer's disease (AD) is a progressive degenerative brain disorder affecting memory, thinking, behaviour and emotion. It is the most common form of dementia and a big social problem in western societies. The analysis of brain activity may help to diagnose this disease. Changes in entropy methods have been reported useful in research studies to characterize AD. We have recently proposed dispersion entropy (DisEn) as a very fast and powerful tool to quantify the irregularity of time series. The aim of this paper is to evaluate the ability of DisEn, in comparison with fuzzy entropy (FuzEn), sample entropy (SampEn), and permutation entropy (PerEn), to discriminate 36 AD patients from 26 elderly control subjects using resting-state magnetoencephalogram (MEG) signals. The results obtained by DisEn, FuzEn, and SampEn, unlike PerEn, show that the AD patients' signals are more regular than controls' time series. The p-values obtained by DisEn, FuzEn, SampEn, and PerEn based methods demonstrate the superiority of DisEn over PerEn, SampEn, and PerEn. Moreover, the computation time for the newly proposed DisEn-based method is noticeably less than for the FuzEn, SampEn, and PerEn based approaches.

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

    PubMed

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

    2009-01-02

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

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

    PubMed

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

    2011-12-01

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

  13. Cost analysis of the History, ECG, Age, Risk factors, and initial Troponin (HEART) Pathway randomized control trial.

    PubMed

    Riley, Robert F; Miller, Chadwick D; Russell, Gregory B; Harper, Erin N; Hiestand, Brian C; Hoekstra, James W; Lefebvre, Cedric W; Nicks, Bret A; Cline, David M; Askew, Kim L; Mahler, Simon A

    2017-01-01

    The HEART Pathway is a diagnostic protocol designed to identify low-risk patients presenting to the emergency department with chest pain that are safe for early discharge. This protocol has been shown to significantly decrease health care resource utilization compared with usual care. However, the impact of the HEART Pathway on the cost of care has yet to be reported. We performed a cost analysis of patients enrolled in the HEART Pathway trial, which randomized participants to either usual care or the HEART Pathway protocol. For low-risk patients, the HEART Pathway recommended early discharge from the emergency department without further testing. We compared index visit cost, cost at 30 days, and cardiac-related health care cost at 30 days between the 2 treatment arms. Costs for each patient included facility and professional costs. Cost at 30 days included total inpatient and outpatient costs, including the index encounter, regardless of etiology. Cardiac-related health care cost at 30 days included the index encounter and costs adjudicated to be cardiac-related within that period. Two hundred seventy of the 282 patients enrolled in the trial had cost data available for analysis. There was a significant reduction in cost for the HEART Pathway group at 30 days (median cost savings of $216 per individual), which was most evident in low-risk (Thrombolysis In Myocardial Infarction score of 0-1) patients (median savings of $253 per patient) and driven primarily by lower cardiac diagnostic costs in the HEART Pathway group. Using the HEART Pathway as a decision aid for patients with undifferentiated chest pain resulted in significant cost savings. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Reliability of resting metabolic rate measurements in young adults: Impact of methods for data analysis.

    PubMed

    Sanchez-Delgado, Guillermo; Alcantara, Juan M A; Ortiz-Alvarez, Lourdes; Xu, Huiwen; Martinez-Tellez, Borja; Labayen, Idoia; Ruiz, Jonatan R

    2017-08-05

    A high inter-day reliability is a key factor to analyze the magnitude of change in resting metabolic rate (RMR) after an intervention, and the impact of using different methods for data analysis is not known. The aims of this study were: i) to analyze the impact of methods for data analysis on RMR and respiratory exchange ratio (RER) estimation; ii) to analyze the impact of methods for data analysis on inter-day RMR and RER reliability; iii) to compare inter-day RMR and RER reliability across methods for data analysis in participants who achieved steady state (SS) vs. participants who did not achieve SS. Seventeen young healthy adults completed two 30-min indirect calorimetry (IC) measures on two consecutive mornings, using two metabolic carts each day. Two methods for data analysis were used: i) Selection of a predefined time interval (TI) every 5 min (1-5 min, 6-10 min, 11-15 min, 16-20 min, 21-25 min, 26-30 min); and TI representing the whole measurement period (0-30 min, 5-30 min, 5-25 min); and ii) Methods based on the selection of the most stable period (SSt methods) (3 min SSt, 4 min SSt, 5 min SSt, 10 min SSt). Additionally, participants were classified as those achieving SS (CV < 10% for VO2, VCO2 and VE, and CV < 5% for RER) and those who did not. RMR and RER measurements were lower when following SSt methods than when following TI methods (all P < 0.01). Although no significant differences were found between different lengths of SSt, 5 min SSt presented the lowest RMR. There were no differences on the inter-day reliability across methods for data analysis (TI and SSt) (all P > 0.2), and there was no systematic bias when comparing RMR and RER day 1 and day 2 measurements (all P > 0.1). Inter-day reliability was similar in individuals who achieved the SS and individuals who did not achieve it. The results were consistent independently of the metabolic cart used. The 5 min SSt approach should be the method of choice for analyzing

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

    PubMed

    Senter, Phil; Robins, James H

    2015-01-01

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

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

    PubMed Central

    Senter, Phil; Robins, James H.

    2015-01-01

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

  17. Effect of Smoking on Blood Pressure and Resting Heart Rate: A Mendelian Randomization Meta-Analysis in the CARTA Consortium.

    PubMed

    Linneberg, Allan; Jacobsen, Rikke K; Skaaby, Tea; Taylor, Amy E; Fluharty, Meg E; Jeppesen, Jørgen L; Bjorngaard, Johan H; Åsvold, Bjørn O; Gabrielsen, Maiken E; Campbell, Archie; Marioni, Riccardo E; Kumari, Meena; Marques-Vidal, Pedro; Kaakinen, Marika; Cavadino, Alana; Postmus, Iris; Ahluwalia, Tarunveer S; Wannamethee, S Goya; Lahti, Jari; Räikkönen, Katri; Palotie, Aarno; Wong, Andrew; Dalgård, Christine; Ford, Ian; Ben-Shlomo, Yoav; Christiansen, Lene; Kyvik, Kirsten O; Kuh, Diana; Eriksson, Johan G; Whincup, Peter H; Mbarek, Hamdi; de Geus, Eco J C; Vink, Jacqueline M; Boomsma, Dorret I; Smith, George Davey; Lawlor, Debbie A; Kisialiou, Aliaksei; McConnachie, Alex; Padmanabhan, Sandosh; Jukema, J Wouter; Power, Chris; Hyppönen, Elina; Preisig, Martin; Waeber, Gerard; Vollenweider, Peter; Korhonen, Tellervo; Laatikainen, Tiina; Salomaa, Veikko; Kaprio, Jaakko; Kivimaki, Mika; Smith, Blair H; Hayward, Caroline; Sørensen, Thorkild I A; Thuesen, Betina H; Sattar, Naveed; Morris, Richard W; Romundstad, Pål R; Munafò, Marcus R; Jarvelin, Marjo-Riitta; Husemoen, Lise Lotte N

    2015-12-01

    Smoking is an important cardiovascular disease risk factor, but the mechanisms linking smoking to blood pressure are poorly understood. Data on 141 317 participants (62 666 never, 40 669 former, 37 982 current smokers) from 23 population-based studies were included in observational and Mendelian randomization meta-analyses of the associations of smoking status and smoking heaviness with systolic and diastolic blood pressure, hypertension, and resting heart rate. For the Mendelian randomization analyses, a genetic variant rs16969968/rs1051730 was used as a proxy for smoking heaviness in current smokers. In observational analyses, current as compared with never smoking was associated with lower systolic blood pressure and diastolic blood pressure and lower hypertension risk, but with higher resting heart rate. In observational analyses among current smokers, 1 cigarette/day higher level of smoking heaviness was associated with higher (0.21 bpm; 95% confidence interval 0.19; 0.24) resting heart rate and slightly higher diastolic blood pressure (0.05 mm Hg; 95% confidence interval 0.02; 0.08) and systolic blood pressure (0.08 mm Hg; 95% confidence interval 0.03; 0.13). However, in Mendelian randomization analyses among current smokers, although each smoking increasing allele of rs16969968/rs1051730 was associated with higher resting heart rate (0.36 bpm/allele; 95% confidence interval 0.18; 0.54), there was no strong association with diastolic blood pressure, systolic blood pressure, or hypertension. This would suggest a 7 bpm higher heart rate in those who smoke 20 cigarettes/day. This Mendelian randomization meta-analysis supports a causal association of smoking heaviness with higher level of resting heart rate, but not with blood pressure. These findings suggest that part of the cardiovascular risk of smoking may operate through increasing resting heart rate. © 2015 American Heart Association, Inc.

  18. Effect of Smoking on Blood Pressure and Resting Heart Rate: A Mendelian Randomisation Meta-Analysis in the CARTA Consortium

    PubMed Central

    Linneberg, Allan; Jacobsen, Rikke K.; Skaaby, Tea; Taylor, Amy E.; Fluharty, Meg E.; Jeppesen, Jørgen L.; Bjorngaard, Johan H.; Åsvold, Bjørn O.; Gabrielsen, Maiken E.; Campbell, Archie; Marioni, Riccardo E.; Kumari, Meena; Marques-Vidal, Pedro; Kaakinen, Marika; Cavadino, Alana; Postmus, Iris; Ahluwalia, Tarunveer S.; Wannamethee, S. Goya; Lahti, Jari; Räikkönen, Katri; Palotie, Aarno; Wong, Andrew; Dalgård, Christine; Ford, Ian; Ben-Shlomo, Yoav; Christiansen, Lene; Kyvik, Kirsten O.; Kuh, Diana; Eriksson, Johan G.; Whincup, Peter H.; Mbarek, Hamdi; de Geus, Eco J.C.; Vink, Jacqueline M.; Boomsma, Dorret I.; Smith, George Davey; Lawlor, Debbie A.; Kisialiou, Aliaksei; McConnachie, Alex; Padmanabhan, Sandosh; Jukema, J. Wouter; Power, Chris; Hyppönen, Elina; Preisig, Martin; Waeber, Gerard; Vollenweider, Peter; Korhonen, Tellervo; Laatikainen, Tiina; Salomaa, Veikko; Kaprio, Jaakko; Kivimaki, Mika; Smith, Blair H.; Hayward, Caroline; Sørensen, Thorkild I.A.; Thuesen, Betina H.; Sattar, Naveed; Morris, Richard W.; Romundstad, Pål R.; Munafò, Marcus R.; Jarvelin, Marjo-Riitta; Husemoen, Lise Lotte N.

    2015-01-01

    Background Smoking is an important cardiovascular disease risk factor, but the mechanisms linking smoking to blood pressure are poorly understood. Methods and Results Data on 141,317 participants (62,666 never, 40,669 former, 37,982 current smokers) from 23 population-based studies were included in observational and Mendelian randomisation (MR) meta-analyses of the associations of smoking status and smoking heaviness with systolic and diastolic blood pressure (SBP, DBP), hypertension, and resting heart rate. For the MR analyses, a genetic variant rs16969968/rs1051730 was used as a proxy for smoking heaviness in current smokers. In observational analyses, current as compared with never smoking was associated with lower SBP, DBP, and lower hypertension risk, but with higher resting heart rate. In observational analyses amongst current smokers, one cigarette/day higher level of smoking heaviness was associated with higher (0.21 beats/minute; 95% CI 0.19; 0.24) resting heart rate, and slightly higher DBP (0.05 mmHg; 95% CI 0.02; 0.08) and SBP (0.08 mmHg; 95% CI 0.03; 0.13). However, in MR analyses amongst current smokers, while each smoking increasing allele of rs16969968/rs1051730 was associated with higher resting heart rate (0.36 beats/minute/allele; 95% CI 0.18; 0.54), there was no strong association with DBP, SBP, or hypertension. This would suggest a 7 beats/minute higher heart rate in those who smoke 20 cigarettes/day. Conclusions This MR meta-analysis supports a causal association of smoking heaviness with higher level of resting heart rate, but not with blood pressure. These findings suggest that part of the cardiovascular risk of smoking may operate through increasing resting heart rate. PMID:26538566

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

    PubMed

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

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

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

    PubMed

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

    2012-08-01

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

  1. Network analysis of resting state EEG in the developing young brain: structure comes with maturation.

    PubMed

    Boersma, Maria; Smit, Dirk J A; de Bie, Henrica M A; Van Baal, G Caroline M; Boomsma, Dorret I; de Geus, Eco J C; Delemarre-van de Waal, Henriette A; Stam, Cornelis J

    2011-03-01

    During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths. We used graph theoretical concepts to examine changes in functional brain networks during normal development in young children. Resting-state eyes-closed electroencephalography (EEG) was recorded (14 channels) from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) was calculated in three different frequency bands and between each pair of electrodes to obtain SL-weighted graphs. Mean normalized clustering index, average path length and weight dispersion were calculated to characterize network organization. Repeated measures analysis of variance tested for time and gender effects. For all frequency bands mean SL decreased from 5 to 7 years. Clustering coefficient increased in the alpha band. Path length increased in all frequency bands. Mean normalized weight dispersion decreased in beta band. Girls showed higher synchronization for all frequency bands and a higher mean clustering in alpha and beta bands. The overall decrease in functional connectivity (SL) might reflect pruning of unused synapses and preservation of strong connections resulting in more cost-effective networks. Accordingly, we found increases in average clustering and path length and decreased weight dispersion indicating that normal brain maturation is characterized by a shift from random to more organized small-world functional networks. This developmental process is influenced by gender differences early in development. Copyright © 2010 Wiley-Liss, Inc.

  2. Independent Component Analysis of Resting-State Functional Magnetic Resonance Imaging in Pedophiles.

    PubMed

    Cantor, J M; Lafaille, S J; Hannah, J; Kucyi, A; Soh, D W; Girard, T A; Mikulis, D J

    2016-10-01

    Neuroimaging and other studies have changed the common view that pedophilia is a result of childhood sexual abuse and instead is a neurologic phenomenon with prenatal origins. Previous research has identified differences in the structural connectivity of the brain in pedophilia. To identify analogous differences in functional connectivity. Functional magnetic resonance images were recorded from three groups of participants while they were at rest: pedophilic men with a history of sexual offenses against children (n = 37) and two control groups: non-pedophilic men who committed non-sexual offenses (n = 28) and non-pedophilic men with no criminal history (n = 39). Functional magnetic resonance imaging data were subjected to independent component analysis to identify known functional networks of the brain, and groups were compared to identify differences in connectivity with those networks (or "components"). The pedophilic group demonstrated wide-ranging increases in functional connectivity with the default mode network compared with controls and regional differences (increases and decreases) with the frontoparietal network. Of these brain regions (total = 23), 20 have been identified by meta-analytic studies to respond to sexually relevant stimuli. Conversely, of the brain areas known to be those that respond to sexual stimuli, nearly all emerged in the present data as significantly different in pedophiles. This study confirms the presence of significant differences in the functional connectivity of the brain in pedophilia consistent with previously reported differences in structural connectivity. The connectivity differences detected here and elsewhere are opposite in direction from those associated with anti-sociality, arguing against anti-sociality and for pedophilia as the source of the neuroanatomic differences detected. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2009-01-01

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

  5. Piezoelectric extraction of ECG signal

    PubMed Central

    Ahmad, Mahmoud Al

    2016-01-01

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

  6. Non-contact ECG monitoring

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

  8. Feasibility of in utero telemetric fetal ECG monitoring in a lamb model.

    PubMed

    Hermans, Bart; Lewi, Liesbeth; Jani, Jacques; De Buck, Frederik; Deprest, Jan; Puers, Robert

    2008-01-01

    If fetal ECG (fECG) devices could be miniaturized sufficiently, one could consider their implantation at the time of fetal surgery to allow permanent monitoring of the fetus and timely intervention in the viable period. We set up an experiment to evaluate the feasibility of in utero direct fECG monitoring and telemetric transmission using a small implantable device in a lamb model. A 2-lead miniature ECG sensor (volume 1.9 cm(3); weight 3.9 g) was subcutaneously implanted in 2 fetal lambs at 122 days gestation (range 119-125; term 145 days). The ECG sensor can continuously register and transmit fECG. The signal is captured by an external receiving antenna taped to the maternal abdominal wall. We developed dedicated software running on a commercial laptop for on-line analysis of the transmitted fECG signal. This was a noninterventional study, i.e. daily readings of the fECG signal were done without clinical consequences to the observations. fECG could be successfully registered, transmitted by telemetry and analyzed from the moment of implantation till term birth in one case (24 days). In the second case, unexplained in utero fetal death occurred 12 days after implantation. In this subject, agonal fECG changes were recorded. An implanted miniature (<2 ml) ECG sensor can be used to retrieve, process and transmit continuously a qualitative fECG signal in third-trimester fetal lambs. The telemetric signal could be picked up by an external antenna located within a 20-cm range. In this experiment, this was achieved through taping the external receiver to the maternal abdomen. Any acquired signal could be transmitted to a commercially available laptop that could perform on-line analysis of the signal. (c) 2008 S. Karger AG, Basel.

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

    PubMed Central

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

    2016-01-01

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

  10. Assessment of left ventricular volumes, ejection fraction and mass. Comparison of model-based analysis of ECG-gated (⁹⁹m)Tc-SPECT and ¹⁸F-FDG-PET.

    PubMed

    Khorsand, A; Gyöngyösi, M; Sochor, H; Maurer, G; Karanikas, G; Dudczak, R; Schuster, E; Porenta, G; Graf, S

    2011-01-01

    We compared and delineated possible differences of model-based analysis of ECG-gated SPECT using (⁹⁹m)Tc-sestamibi (Tc-SPECT) with ECG-gated ¹⁸F-fluorodeoxyglucose-PET (FDG-PET) for determination of end-diastolic (EDV) and end-systolic (ESV) cardiac volumes, left ventricular ejection fraction (LVEF), and myocardial mass (LVMM). 24 patients (21 men; age: 54±12years) with coronary artery disease underwent Tc-SPECT and FDG-PET imaging for evaluation of myocardial perfusion and viability. By using model-based analysis EDV, ESV, LVEF and LVMM were calculated from short axis images of both Tc-SPECT and FDG-PET. Left ventricular volumes by Tc-SPECT and FDG-PET were 176±60 ml and 181±59 ml for EDV, and 97±44 ml and 103±45 ml for ESV respectively, LVEF was 47±8% by Tc-SPECT and 45±9% by FDG-PET. The LVMM was 214±40 g (Tc-SPECT) and 202±43 g (FDG-PET) (all p = NS, paired t-test). A significant correlation was observed between Tc-SPECT and FDG-PET imaging for calculation of EDV (r = 0.93), ESV (r = 0.93), LVEF (r = 0.83) and LVMM (r = 0.72). ECG-gated Tc-SPECT and FDG-PET using two tracers with different characteristics (perfusion versus metabolism) showed close agreement concerning measurements of left ventricular volumes, contractile function and myocardial mass by using a model-based analysis.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed

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

    2017-02-01

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

  15. Assessment of atrial fibrillation ablation outcomes with clinic ECG, monthly 24-h Holter ECG, and twice-daily telemonitoring ECG.

    PubMed

    Kimura, Takehiro; Aizawa, Yoshiyasu; Kurata, Naomi; Nakajima, Kazuaki; Kashimura, Shin; Kunitomi, Akira; Nishiyama, Takahiko; Katsumata, Yoshinori; Nishiyama, Nobuhiro; Fukumoto, Kotaro; Tanimoto, Yoko; Fukuda, Keiichi; Takatsuki, Seiji

    2017-03-01

    Differences in the methodologies for evaluating atrial fibrillation (AF) ablation outcomes should be evaluated. In the present study, we compared the AF ablation outcomes among periodic clinic electrocardiography (ECG), 24-h Holter ECG, and telemonitoring ECG to evaluate the differences among these methods. In addition, we evaluated the AF-free survival rate for each method with different durations of the blanking period. A total of 30 AF patients were followed up for 6 months after initial catheter ablation, with clinic ECG on every clinic visit, monthly 24-h Holter ECG, and telemonitoring ECG twice daily and upon symptoms. AF relapse was defined as AF or atrial tachycardia detected with any of the methods. Two patients dropped out of the study, and 28 patients were followed up for 8.8 ± 2.7 months. Patients underwent 3.6 ± 0.8 clinic ECG, 5.1 ± 0.8 Holter ECG, and 273 ± 68 telemonitoring ECG examinations. During the first, second, third, fourth, fifth, and sixth months of follow-up, Holter ECG detected relapses in 11.1, 8.3, 11.5, 15.4, 4.2, and 4.8 % of patients and telemonitoring ECG detected relapses in 32.1, 25.0, 25.0, 17.9, 28.6, and 17.9 % of patients, respectively. When no duration was set for the blanking period, the AF-free survival rate was significantly lower with telemonitoring ECG (46.4 %) than with Holter ECG (78.6 %, P = 0.013) or clinic ECG (85.7 %, P = 0.002). In addition, when the duration of the blanking period was set to 3 months, the AF-free survival rate was significantly lower with telemonitoring ECG than with clinic ECG (92.9 vs. 71.4 %, P = 0.041). The AF ablation outcomes with twice-daily telemonitoring ECG might differ from those with clinic ECG when the duration of the blanking period is 0-3 months. A follow-up based solely on clinic ECG might underestimate AF recurrence.

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2010-01-01

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

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

    PubMed

    Beyramienanlou, Hamed; Lotfivand, Nasser

    2017-01-01

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

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

    PubMed Central

    2017-01-01

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

  20. Examining Intrinsic Thalamic Resting State Networks Using Graph Theory Analysis : Implications for mTBI detection

    DTIC Science & Technology

    2012-08-01

    stroke or severe TBI where clear locations of neurological infarct are visible, the focal abnormalities are often not detected using standard clinical...Instruments, Inc. Minnesota, MN]. Whole brain functional MRI ( fMRI ) data were acquired with an EPI pulse sequence in the sagittal plane (TE/TR = 25...state fMRI task, which was a subset of a larger number of anatomical and functional scans. During the resting state task, subjects were asked to lie

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

    PubMed

    Harris, Patricia R E

    2016-09-01

    The electrocardiogram (ECG) is a well-established diagnostic tool extensively used in clinical settings. Knowledge of cardiac rhythm and mastery of cardiac waveform interpretation are fundamental for intensive care nurses. Recognition of the normal findings for the 12-lead ECG and understanding the significance of changes from baseline in continuous cardiac monitoring are essential steps toward ensuring safe patient care. This article highlights historical developments in electrocardiography, describes the normal resting 12-lead ECG, and discusses the need for continuous cardiac monitoring. In addition, future directions for the ECG are explored briefly. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2006-01-01

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

  3. Noninvasive fetal ECG estimation using adaptive comb filter.

    PubMed

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

    2013-10-01

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

  4. A novel real-time patient-specific seizure diagnosis algorithm based on analysis of EEG and ECG signals using spectral and spatial features and improved particle swarm optimization classifier.

    PubMed

    Nasehi, Saadat; Pourghassem, Hossein

    2012-08-01

    This paper proposes a novel real-time patient-specific seizure diagnosis algorithm based on analysis of electroencephalogram (EEG) and electrocardiogram (ECG) signals to detect seizure onset. In this algorithm, spectral and spatial features are selected from seizure and non-seizure EEG signals by Gabor functions and principal component analysis (PCA). Furthermore, four features based on heart rate acceleration are extracted from ECG signals to form feature vector. Then a neural network classifier based on improved particle swarm optimization (IPSO) learning algorithm is developed to determine an optimal nonlinear decision boundary. This classifier allows to adjust the parameters of the neural network classifier, efficiently. This algorithm can automatically detect the presence of seizures with minimum delay which is an important factor from a clinical viewpoint. The performance of the proposed algorithm is evaluated on a dataset consisting of 154 h records and 633 seizures from 12 patients. The results indicate that the algorithm can recognize the seizures with the smallest latency and higher good detection rate (GDR) than other presented algorithms in the literature.

  5. Association between resting heart rate and coronary artery disease, stroke, sudden death and noncardiovascular diseases: a meta-analysis.

    PubMed

    Zhang, Dongfeng; Wang, Weijing; Li, Fang

    2016-10-18

    Resting heart rate is linked to risk of coronary artery disease, stroke, sudden death and noncardiovascular diseases. We conducted a meta-analysis to assess these associations in general populations and in populations of patients with hypertension or diabetes mellitus. We searched PubMed, Embase and MEDLINE from inception to Mar. 5, 2016. We used a random-effects model to combine study-specific relative risks (RRs). We used restricted cubic splines to assess the dose-response relation. We included 45 nonrandomized prospective cohort studies in the meta-analysis. The multivariable adjusted RR with an increment of 10 beats/min in resting heart rate was 1.12 (95% confidence interval [CI] 1.09-1.14) for coronary artery disease, 1.05 (95% CI 1.01-1.08) for stroke, 1.12 (95% CI 1.02-1.24) for sudden death, 1.16 (95% CI 1.12-1.21) for noncardiovascular diseases, 1.09 (95% CI 1.06-1.12) for all types of cancer and 1.25 (95% CI 1.17-1.34) for noncardiovascular diseases excluding cancer. All of these relations were linear. In an analysis by category of resting heart rate (< 60 [reference], 60-70, 70-80 and > 80 beats/min), the RRs were 0.99 (95% CI 0.93-1.04), 1.08 (95% CI 1.01-1.16) and 1.30 (95% CI 1.19-1.43), respectively, for coronary artery disease; 1.08 (95% CI 0.98-1.19), 1.11 (95% CI 0.98-1.25) and 1.08 (95% CI 0.93-1.25), respectively, for stroke; and 1.17 (95% CI 0.94-1.46), 1.31 (95% CI 1.12-1.54) and 1.57 (95% CI 1.39-1.77), respectively, for noncardiovascular diseases. After excluding studies involving patients with hypertension or diabetes, we obtained similar results for coronary artery disease, stroke and noncardiovascular diseases, but found no association with sudden death. Resting heart rate was an independent predictor of coronary artery disease, stroke, sudden death and noncardiovascular diseases over all of the studies combined. When the analysis included only studies concerning general populations, resting heart rate was not associated with sudden

  6. The influence of physical characteristics on the resting energy expenditure of youth: A meta-analysis.

    PubMed

    Herrmann, Stephen D; McMurray, Robert G; Kim, Youngdeok; Willis, Erik A; Kang, Minsoo; McCurdy, Thomas

    2017-05-06

    To examine the literature on resting energy expenditure (REE) of youth and determine the influence of age, sex, BMI, and body composition on REE. A literature search was conducted using PubMed, BIOSIS Previews, NTIS, EMBASE, MEDLINE, and Pascal databases for studies with data on resting metabolic rate, REE, resting oxygen uptake (or VO2 ) in healthy children, youth, or adolescents (age = 1-18 years). Over 200 publications were identified; sixty-one publications met criteria and were included in the meta-analyses, resulting in 142 study population estimates (totaling 5,397 youth) of REE. Pooled mean was 1414 kcal·day(-1) with a significant and moderate-to-high between-study heterogeneity [Q(140) = 7912.42, P < 0.001; I(2)  = 98.97%]. A significantly greater (P < 0.001) pooled mean kcal·day(-1) was estimated for studies with male participants (1519 kcal·day(-1) ) comparing to studies with female participants (1338 kcal·day(-1) ). Age, height, and body mass resulted in the highest R(2) of 86.4 for males and 83.9% for females. Fat free mass and body mass index (BMI) did not improve total R(2) . These data suggest that using a linear equation including age, height, and body mass to estimate REE based on kcal·day(-1) is more accurate than estimates based on body mass kcal·kg(-1) ·h(-1) . Further, if kcal·kg(-1) ·h(-1) is used, including a quadratic component for the physical characteristics improves the predictive ability of the equation. Regardless of the metric, separate equations should be used for each sex. © 2016 Wiley Periodicals, Inc.

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

    PubMed

    Wang, Jinhui; Zuo, Xinian; He, Yong

    2010-01-01

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

  8. Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

    PubMed

    Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

    2017-11-01

    Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. The evolution of ambulatory ECG monitoring.

    PubMed

    Kennedy, Harold L

    2013-01-01

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

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

    PubMed Central

    2010-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  12. A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits.

    PubMed

    Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

    2017-01-01

    Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

  13. Improvement of IFNγ ELISPOT Performance Following Overnight Resting of Frozen PBMC Samples Confirmed Through Rigorous Statistical Analysis

    PubMed Central

    Santos, Radleigh; Buying, Alcinette; Sabri, Nazila; Yu, John; Gringeri, Anthony; Bender, James; Janetzki, Sylvia; Pinilla, Clemencia; Judkowski, Valeria A.

    2014-01-01

    Immune monitoring of functional responses is a fundamental parameter to establish correlates of protection in clinical trials evaluating vaccines and therapies to boost antigen-specific responses. The IFNγ ELISPOT assay is a well-standardized and validated method for the determination of functional IFNγ-producing T-cells in peripheral blood mononuclear cells (PBMC); however, its performance greatly depends on the quality and integrity of the cryopreserved PBMC. Here, we investigate the effect of overnight (ON) resting of the PBMC on the detection of CD8-restricted peptide-specific responses by IFNγ ELISPOT. The study used PBMC from healthy donors to evaluate the CD8 T-cell response to five pooled or individual HLA-A2 viral peptides. The results were analyzed using a modification of the existing distribution free resampling (DFR) recommended for the analysis of ELISPOT data to ensure the most rigorous possible standard of significance. The results of the study demonstrate that ON resting of PBMC samples prior to IFNγ ELISPOT increases both the magnitude and the statistical significance of the responses. In addition, a comparison of the results with a 13-day preculture of PBMC with the peptides before testing demonstrates that ON resting is sufficient for the efficient evaluation of immune functioning. PMID:25546016

  14. Contributions of facial morphology, age, and gender to EMG activity under biting and resting conditions: a canonical correlation analysis.

    PubMed

    Fogle, L L; Glaros, A G

    1995-08-01

    Theoretical studies suggest that facial morphology may confer a mechanical advantage to particular individuals during force production, but not during rest. However, prior studies on the relationship between facial morphology and EMG suffer from various methodological limitations. We examined the hypothesis that facial morphology variables contribute significantly and meaningfully to the variance in masticatory muscle EMG when subjects produce specific levels of interocclusal force, but not when subjects are at rest. Measures of facial morphology included gonial angle, ramus height, and maxillary height, as determined from lateral cephalograms. EMG data were obtained from surface electrodes placed on masseter and temporalis sites. Subjects (N = 96) sat in a darkened, sound-attenuated room while they watched a seven-minute segment of a movie. EMG activity obtained during the last two minutes was used as a baseline period. Using the central incisors, subjects then provided five different force levels ranging from 6.5 to 48 lb in random order on a bite-force device while EMG data were collected. A canonical correlation analysis, performed on the set of predictor variables (age, gender, and facial morphology measurements) and the set of criterion variables (EMG data), showed a significant canonical correlation between the two variable sets while biting, but not at rest. Age, but not the facial morphology variables, was highly related to the canonical variate.(ABSTRACT TRUNCATED AT 250 WORDS)

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  17. An individual differences analysis of the neurocognitive architecture of the semantic system at rest.

    PubMed

    Mollo, Giovanna; Karapanagiotidis, Theodoros; Bernhardt, Boris C; Murphy, Charlotte E; Smallwood, Jonathan; Jefferies, Elizabeth

    2016-11-01

    Efficient semantic cognition depends on accessing and selecting conceptual knowledge relevant to the current task or context. This study explored the neurocognitive architecture that supports this function by examining how individual variation in functional brain organisation predicts comprehension and semantic generation. Participants underwent resting state functional magnetic resonance imaging (fMRI) and, on separate days, performed written synonym judgement, and letter and category fluency tasks. We found that better synonym judgement for high frequency items was linked to greater functional coupling between posterior fusiform and anterior superior temporal cortex (aSTG), which might index orthographic-to-semantic access. However, stronger coupling between aSTG and ventromedial prefrontal cortex was associated with poor performance on the same trials, potentially reflecting greater difficulty in focussing retrieval on relevant features for high frequency items that appear in a greater range of contexts. Fluency performance was instead linked to variations in the functional coupling of the inferior frontal gyrus (IFG); anterior IFG was more coupled to regions of primary visual cortex for individuals who were good at category fluency, while poor letter fluency was predicted by stronger coupling between posterior IFG and retrosplenial cortex. These results show that individual differences in functional connectivity at rest predict semantic performance and are consistent with a component process account of semantic cognition in which representational information is shaped by control processes to fit the current requirements, in both comprehension and fluency tasks. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2014-01-01

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

  19. Adaptive Fourier decomposition based ECG denoising.

    PubMed

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

    2016-10-01

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

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

    PubMed

    Ibaida, Ayman; Khalil, Ibrahim

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2000-04-01

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

  2. Software-based detection of atrial fibrillation in long-term ECGs.

    PubMed

    Haeberlin, Andreas; Roten, Laurent; Schilling, Manuel; Scarcia, Flavio; Niederhauser, Thomas; Vogel, Rolf; Fuhrer, Juerg; Tanner, Hildegard

    2014-06-01

    Atrial fibrillation (AF) is common and may have severe consequences. Continuous long-term electrocardiogram (ECG) is widely used for AF screening. Recently, commercial ECG analysis software was launched, which automatically detects AF in long-term ECGs. It has been claimed that such tools offer reliable AF screening and save time for ECG analysis. However, this has not been investigated in a real-life patient cohort. To investigate the performance of automatic software-based screening for AF in long-term ECGs. Two independent physicians manually screened 22,601 hours of continuous long-term ECGs from 150 patients for AF. Presence, number, and duration of AF episodes were registered. Subsequently, the recordings were screened for AF by an established ECG analysis software (Pathfinder SL), and its performance was validated against the thorough manual analysis (gold standard). Sensitivity and specificity for AF detection was 98.5% (95% confidence interval 91.72%-99.96%) and 80.21% (95% confidence interval 70.83%-87.64%), respectively. Software-based AF detection was inferior to manual analysis by physicians (P < .0001). Median AF duration was underestimated (19.4 hours vs 22.1 hours; P < .001) and median number of AF episodes was overestimated (32 episodes vs 2 episodes; P < .001) by the software. In comparison to extensive quantitative manual ECG analysis, software-based analysis saved time (2 minutes vs 19 minutes; P < .001). Owing to its high sensitivity and ability to save time, software-based ECG analysis may be used as a screening tool for AF. An additional manual confirmatory analysis may be required to reduce the number of false-positive findings. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

  3. ECG data compression using Jacobi polynomials.

    PubMed

    Tchiotsop, Daniel; Wolf, Didier; Louis-Dorr, Valérie; Husson, René

    2007-01-01

    Data compression is a frequent signal processing operation applied to ECG. We present here a method of ECG data compression utilizing Jacobi polynomials. ECG signals are first divided into blocks that match with cardiac cycles before being decomposed in Jacobi polynomials bases. Gauss quadratures mechanism for numerical integration is used to compute Jacobi transforms coefficients. Coefficients of small values are discarded in the reconstruction stage. For experimental purposes, we chose height families of Jacobi polynomials. Various segmentation approaches were considered. We elaborated an efficient strategy to cancel boundary effects. We obtained interesting results compared with ECG compression by wavelet decomposition methods. Some propositions are suggested to improve the results.

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

    PubMed

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

    2016-01-01

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

  5. FastICA peel-off for ECG interference removal from surface EMG.

    PubMed

    Chen, Maoqi; Zhang, Xu; Chen, Xiang; Zhu, Mingxing; Li, Guanglin; Zhou, Ping

    2016-06-13

    Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference. It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference. The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.

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

    PubMed

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

    2015-09-10

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

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

    PubMed

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

    2015-01-01

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

  8. Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects

    NASA Astrophysics Data System (ADS)

    Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang

    2017-08-01

    Objective. Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. Approach. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. Main results. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. Significance. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.

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

    PubMed Central

    2013-01-01

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

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

    PubMed

    Lu, Yu; Tang, Zi-Hui; Zeng, Fangfang; Li, Yiming; Zhou, Linuo

    2013-11-17

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

  11. Horizontal ECG in acute anterolateral myocardial infarction.

    PubMed

    Erdogan, Okan; Dalkilic, Bahar; Kepez, Alper

    2016-07-01

    The present study aims to compare the amount of ST segment changes recorded by horizontal electrocardiography (hECG) with standard ECG (sECG) in patients with acute anterior and/or lateral ST segment elevation myocardial infarction (STEMI). Consecutive eligible patients (n = 58) who were diagnosed with acute anterior and/or lateral STEMI were included in the study. After recording simultaneous sECG and hECG by placing precordial leads (V3-6) horizontally on the left 4th intercostal space, ST segment changes were compared. The mean ST segment changes (mV) on hECG were significantly higher than sECG in V4 (0.27 ± 0.2 vs. 0.21 ± 0.21, p = 0.001), V5 (0.21 ± 0.17 vs. 0.12 ± 0.16, p < 0.001) and V6 (0.09 ± 0.1 vs. 0.04 ± 0.12, p < 0.001), respectively. When hECG and sECG were compared in patients with BMI < 30 kg/m(2), mean ST segment changes (mV) on hECG were significantly higher than sECG in V4 (0.29 ± 0.21 vs. 0.21 ± 0.24, p = 0.004), V5 (0.22 ± 0.19 vs. 0.13 ± 0.17, p < 0.001) and V6 (0.11 ± 0.11 vs. 0.04 ± 0.11, p < 0.001), respectively. Mean ST segment changes in patients with anterior and/or lateral STEMI were significantly higher and easily detectable on hECG compared with sECG. We suggest that hECG be used in conjunction with sECG to diagnose anterior and lateral wall STEMI in cases of diagnostic doubt.

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

    PubMed

    Cho, Hakyung; Lee, Joo Hyeon

    2015-09-01

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

  13. Metabolic, respiratory, and cardiological measurements during exercise and rest

    NASA Technical Reports Server (NTRS)

    1971-01-01

    Low concentration effects of CO2 on metabolic respiration and circulation were measured during work and at rest. The relationship between heart rate and metabolic rate is examined, as well as calibration procedures, and rate measurement during submaximal and standard exercise tests. Alterations in acid base and electrolytes were found during exhaustive exercise, including changes in ECG and metabolic alkalosis effects.

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

    PubMed

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

    2012-01-01

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

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

    PubMed Central

    Chen, Yuexin; Fan, Zhongjie; Li, Yongjun

    2015-01-01

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

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

    PubMed

    Yang, Chia-Yen; Lin, Ching-Po

    2015-07-01

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

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

    PubMed

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

    2008-11-01

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

  18. A novel algorithm for Bluetooth ECG.

    PubMed

    Pandya, Utpal T; Desai, Uday B

    2012-11-01

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

  19. Atrial fibrillation detection on compressed sensed ECG.

    PubMed

    Da Poian, Giulia; Liu, Chengyu; Bernardini, Riccardo; Rinaldo, Roberto; Clifford, Gari D

    2017-06-27

    Compressive sensing (CS) approaches to electrocardiogram (ECG) analysis provide efficient methods for real time encoding of cardiac activity. In doing so, it is important to assess the downstream effect of the compression on any signal processing and classification algorithms. CS is particularly suitable for low power wearable devices, thanks to its low-complex digital or hardware implementation that directly acquires a compressed version of the signal through random projections. In this work, we evaluate the impact of CS compression on atrial fibrillation (AF) detection accuracy. We compare schemes with data reconstruction based on wavelet and Gaussian models, followed by a P&T-based identification of beat-to-beat (RR) intervals on the MIT-BIH atrial fibrillation database. A state-of-the-art AF detector is applied to the RR time series and the accuracy of the AF detector is then evaluated under different levels of compression. We also consider a new beat detection procedure which operates directly in the compressed domain, avoiding costly signal reconstruction procedures. We demonstrate that for compression ratios up to 30[Formula: see text] the AF detector applied to RR intervals derived from the compressed signal exhibits results comparable to those achieved when employing a standard QRS detector on the raw uncompressed signals, and exhibits only a 2% accuracy drop at a compression ratio of 60%. We also show that the Gaussian-based reconstruction approach is superior in terms of AF detection accuracy, with a negligible drop in performance at a compression ratio  ⩽75%, compared to a wavelet approach, which exhibited a significant drop in accuracy at a compression ratio  ⩾65%. The results suggest that CS should be considered as a plausible methodology for both efficient real time ECG compression (at moderate compression rates) and for offline analysis (at high compression rates).

  20. Sparse SPM: Group Sparse-dictionary learning in SPM framework for resting-state functional connectivity MRI analysis.

    PubMed

    Lee, Young-Beom; Lee, Jeonghyeon; Tak, Sungho; Lee, Kangjoo; Na, Duk L; Seo, Sang Won; Jeong, Yong; Ye, Jong Chul

    2016-01-15

    Recent studies of functional connectivity MR imaging have revealed that the default-mode network activity is disrupted in diseases such as Alzheimer's disease (AD). However, there is not yet a consensus on the preferred method for resting-state analysis. Because the brain is reported to have complex interconnected networks according to graph theoretical analysis, the independency assumption, as in the popular independent component analysis (ICA) approach, often does not hold. Here, rather than using the independency assumption, we present a new statistical parameter mapping (SPM)-type analysis method based on a sparse graph model where temporal dynamics at each voxel position are described as a sparse combination of global brain dynamics. In particular, a new concept of a spatially adaptive design matrix has been proposed to represent local connectivity that shares the same temporal dynamics. If we further assume that local network structures within a group are similar, the estimation problem of global and local dynamics can be solved using sparse dictionary learning for the concatenated temporal data across subjects. Moreover, under the homoscedasticity variance assumption across subjects and groups that is often used in SPM analysis, the aforementioned individual and group analyses using sparse dictionary learning can be accurately modeled by a mixed-effect model, which also facilitates a standard SPM-type group-level inference using summary statistics. Using an extensive resting fMRI data set obtained from normal, mild cognitive impairment (MCI), and Alzheimer's disease patient groups, we demonstrated that the changes in the default mode network extracted by the proposed method are more closely correlated with the progression of Alzheimer's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. ECG-cryptography and authentication in body area networks.

    PubMed

    Zhang, Zhaoyang; Wang, Honggang; Vasilakos, Athanasios V; Fang, Hua

    2012-11-01

    Wireless body area networks (BANs) have drawn much attention from research community and industry in recent years. Multimedia healthcare services provided by BANs can be available to anyone, anywhere, and anytime seamlessly. A critical issue in BANs is how to preserve the integrity and privacy of a person's medical data over wireless environments in a resource efficient manner. This paper presents a novel key agreement scheme that allows neighboring nodes in BANs to share a common key generated by electrocardiogram (ECG) signals. The improved Jules Sudan (IJS) algorithm is proposed to set up the key agreement for the message authentication. The proposed ECG-IJS key agreement can secure data communications over BANs in a plug-n-play manner without any key distribution overheads. Both the simulation and experimental results are presented, which demonstrate that the proposed ECG-IJS scheme can achieve better security performance in terms of serval performance metrics such as false acceptance rate (FAR) and false rejection rate (FRR) than other existing approaches. In addition, the power consumption analysis also shows that the proposed ECG-IJS scheme can achieve energy efficiency for BANs.

  2. Thyroid hormones concentrations and ECG picture in the dog.

    PubMed

    Pasławska, U; Noszczyk-Nowak, A; Kungl, K; Bioły, K; Popiel, J; Nicpoń, J

    2006-01-01

    Disorders of the thyroid gland activity are the most commonly encountered disturbances of endocrine origin in the dog. Hypo- or hyperthyroidism may disturb the function of the cardiovascular system and cause arrhythmias. The aim of this study was to evaluate the influence of thyroid gland activity on electrocardiogram (ECG) picture in the dog by comparing ECG curves of healthy dogs, dogs with hypothyroidism and dogs with cardiac insufficiency caused by endocardiosis of the mitral valve. The study was performed on 38 dogs, patients of the Department of Internal and Parasitic Diseases with Clinic for Horses, Dogs and Cats in Wrocław. The animals were assigned to 3 groups: Group I--control group, 13 clinically healthy dogs; Group II--14 dogs with diagnosed cardiac insufficiency caused by endocardiosis of the mitral valve; Group III--11 dogs with hypothyroidism. Clinical examination of the animals was conducted according to the following pattern: anamnesis, general clinical examination, cardiological examination (ECG, USG of the heart) and laboratory analysis (triacylglycerydes, cholesterol, T3, T4, FT4). In this study, the significant influence of thyroid gland activity on ECG picture of the evaluated dogs was found. In the dogs with hypothyroidism a decrease in the sino-atrial node activity was observed, which led to decreased heart rate. In dogs with hypothyroidism, the innerheart conduction was reduced, which was demonstrated by prolongation of the P wave, QRS complex and the QT interval.

  3. Wearable Noncontact Armband for Mobile ECG Monitoring System.

    PubMed

    Rachim, Vega Pradana; Chung, Wan-Young

    2016-12-01

    One of the best ways to obtain health information is from an electrocardiogram (ECG). Through an ECG, characteristics such as patients' heartbeats, heart conditions, and heart disease can be analyzed. Unfortunately, most available healthcare devices do not provide clinical data such as information regarding patients' heart activities. Many researchers have tried to solve this problem by inventing wearable heart monitoring systems with a chest strap or wristband, but their performances were not feasible for practical applications. Thus, the aim of this study is to build a new system to monitor heart activity through ECG signals. The proposed system consists of capacitive-coupled electrodes embedded in an armband. It is considered to be a reliable, robust, and low-power-transmission ECG monitoring system. The reliability of this system was achieved by the careful placement of sensors in the armband. Bluetooth low energy (BLE) was used as the protocol for data transmission; this protocol was proposed to develop the low-power-transmission system. For robustness, the proposed system is equipped with analysis capabilities-e.g., real-time heartbeat detection and a filter algorithm to ignore distractions from body movements or noise from the environment.

  4. Wearable Noncontact Armband for Mobile ECG Monitoring System.

    PubMed

    Rachim, Vega Pradana; Chung, Wan-Young

    2016-05-18

    One of the best ways to obtain health information is from an electrocardiogram (ECG). Through an ECG, characteristics such as patients' heartbeats, heart conditions, and heart disease can be analyzed. Unfortunately, most available healthcare devices do not provide clinical data such as information regarding patients' heart activities. Many researchers have tried to solve this problem by inventing wearable heart monitoring systems with a chest strap or wristband, but their performances were not feasible for practical applications. Thus, the aim of this study is to build a new system to monitor heart activity through ECG signals. The proposed system consists of capacitive-coupled electrodes embedded in an armband. It is considered to be a reliable, robust, and low-power-transmission ECG monitoring system. The reliability of this system was achieved by the careful placement of sensors in the armband. Bluetooth low energy (BLE) was used as the protocol for data transmission; this protocol was proposed to develop the low-power-transmission system. For robustness, the proposed system is equipped with analysis capabilities-e.g., real-time heartbeat detection and a filter algorithm to ignore distractions from body movements or noise from the environment.

  5. III Lead ECG Pulse Measurement Sensor

    NASA Astrophysics Data System (ADS)

    Thangaraju, S. K.; Munisamy, K.

    2015-09-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

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

    PubMed

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

    2015-11-01

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

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

    PubMed Central

    Sameni, Reza; Clifford, Gari D.

    2010-01-01

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

  9. Usefulness of multichannel Holter ECG recording in the third intercostal space for detecting type 1 Brugada ECG: comparison with repeated 12-lead ECGs.

    PubMed

    Shimeno, Kenji; Takagi, Masahiko; Maeda, Keiko; Tatsumi, Hiroaki; Doi, Atsushi; Yoshiyama, Minoru

    2009-09-01

    Type 1 Brugada ECG is essential for the diagnosis of Brugada syndrome. We aimed to evaluate the usefulness of multichannel Holter ECG recording in the third intercostal space for detecting type 1 Brugada ECG. We enrolled 60 consecutive individuals with type 1 Brugada ECG and 31 individuals with type 2 or 3 Brugada ECG, in the presence or absence of Na+ channel blockers. All individuals underwent 12-lead ECGs recorded in the standard position and the third intercostal space at least 5 times every 3 months (4L-ECGs, 3L-ECGs, respectively) and multichannel Holter ECG. On multichannel Holter ECG, the precordial electrodes were attached at standard positions (4L-Holter) and the third intercostal space (3L-Holter) for leads V1 and V2. Among the 60 individuals, type 1 Brugada ECG in 4L-ECGs, 3L-ECGs, 4L-Holter, and 3L-Holter was detected in 15 (25%), 26 (43.3%), 23 (38.3%), and 33 individuals (55%), respectively, whereas detected in none of the 31 individuals. The documented duration of type 1 Brugada ECG on 3L-Holter was significantly longer than that on 4L-Holter (700 +/- 467 vs 372 +/- 422 min; P = 0.01, 3L-Holter vs 4L-Holter, respectively), and type 1 Brugada ECG was most frequently observed between 6 pm and 12 pm. Neither the presence nor the duration of the appearance of type 1 Brugada ECG differed significantly between symptomatic and asymptomatic individuals. Multichannel Holter ECG recording in the third intercostal space is more sensitive and useful for the diagnosis of type 1 Brugada ECG than repeated 12-lead ECGs or multichannel Holter ECG in the standard position.

  10. Fetal cardiac time intervals in healthy pregnancies - an observational study by fetal ECG (Monica Healthcare System).

    PubMed

    Wacker-Gussmann, Annette; Plankl, Cordula; Sewald, Maria; Schneider, Karl-Theo Maria; Oberhoffer, Renate; Lobmaier, Silvia M

    2017-04-28

    Fetal electrocardiogram (fECG) can detect QRS signals in fetuses from as early as 17 weeks' gestation; however, the technique is limited by the minute size of the fetal signal relative to noise ratio. The aim of this study was to evaluate precise fetal cardiac time intervals (fCTIs) with the help of a newly developed fetal ECG device (Monica Healthcare System). In a prospective manner we included 15-18 healthy fetuses per gestational week from 32 weeks onwards. The small and wearable Monica AN24 monitoring system uses standard ECG electrodes placed on the maternal abdomen to monitor fECG, maternal ECG and uterine electromyogram (EMG). Fetal CTIs were estimated on 1000 averaged fetal heart beats. Detection was deemed successful if there was a global signal loss of less than 30% and an analysis loss of the Monica AN24 signal separation analysis of less than 50%. Fetal CTIs were determined visually by three independent measurements. A total of 149 fECGs were performed. After applying the requirements 117 fECGs remained for CTI analysis. While the onset and termination of P-wave and QRS-complex could be easily identified in most ECG patterns (97% for P-wave, PQ and PR interval and 100% for QRS-complex), the T-wave was detectable in only 41% of the datasets. The CTI results were comparable to other available methods such as fetal magnetocardiography (fMCG). Although limited and preclinical in its use, fECG (Monica Healthcare System) could be an additional useful tool to detect precise fCTIs from 32 weeks' gestational age onwards.

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

    PubMed Central

    Li, Yuechun

    2015-01-01

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

  12. A combined application of lossless and lossy compression in ECG processing and transmission via GSM-based SMS.

    PubMed

    Mukhopadhyay, S K; Mitra, S; Mitra, M

    2015-02-01

    This paper presents a software-based scheme for reliable and robust Electrocardiogram (ECG) data compression and its efficient transmission using Second Generation (2G) Global System for Mobile Communication (GSM) based Short Message Service (SMS). To achieve a firm lossless compression in high standard deviating QRS complex regions and an acceptable lossy compression in the rest of the signal, two different algorithms have been used. The combined compression module is such that it outputs only American Standard Code for Information Interchange (ASCII) characters and, hence, SMS service is found to be most suitable for transmitting the compressed signal. At the receiving end, the ECG signal is reconstructed using just the reverse algorithm. The module has been tested to all the 12 leads of different types of ECG signals (healthy and abnormal) collected from the PTB Diagnostic ECG Database. The compression algorithm achieves an average compression ratio of ∼22.51, without any major alteration of clinical morphology.

  13. Fractal and EMD based removal of baseline wander and powerline interference from ECG signals.

    PubMed

    Agrawal, Sakshi; Gupta, Anubha

    2013-11-01

    This paper presents novel methods for baseline wander removal and powerline interference removal from electrocardiogram (ECG) signals. Baseline wander and clean ECG have been modeled as 1st and 2nd-order fractional Brownian motion (fBm) processes, respectively. This fractal modeling is utilized to propose projection operator based approach for baseline wander removal. Powerline interference is removed by using a hybrid approach of empirical mode decomposition method (EMD) and wavelet analysis. Simulation results are presented to show the efficacy of both the methods. The proposed methods have been shown to preserve ECG shapes characteristic of heart abnormalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Panigrahy, D; Sahu, P K

    2017-02-16

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2016-01-01

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

  18. Pre-hospital ECG manifestations of acute myocardial ischemia are an independent predictor of adverse hospital outcomes

    PubMed Central

    Hemsey, Jessica Zègre; Dracup, Kathleen; Fleischmann, Kirsten; Sommargren, Claire E.; Paul, Steven M.; Drew, Barbara J.

    2013-01-01

    Background Prehospital electrocardiography (PH ECG) is becoming the standard of care for patients activating emergency medical services (EMS) for symptoms of acute coronary syndrome (ACS). Little is known about the prognostic value of ischemia found on PH ECG. Study Objectives The purpose of this study was to determine whether manifestations of acute myocardial ischemia on PH ECG are predictive of adverse hospital outcomes. Methods The study was a retrospective analysis of all PH ECGs recorded in 630 patients who called “911” for symptoms of ACS and were enrolled in a prospective clinical trial. ST-segment monitoring software was added to the PH ECG device with automatic storage and transmission of ECGs to the destination emergency department (ED). Patients’ medical records were reviewed for adverse hospital outcomes. Results In 630 patients who called “911” for ACS symptoms, 270 (42.9%) had PH ECG evidence of ischemia. Overall, 37% of patients with PH ECG ischemia had adverse hospital outcomes compared to 27% of patients without PH ECG ischemia (p< .05). Those with PH ECG ischemia were 1.55 times more likely to have adverse hospital outcomes than those without PH ECG ischemia (CI 1.09–2.21, p<0.05), after controlling for other predictors of adverse hospital outcomes (i.e., age, gender, medical history). Conclusions Evidence of ischemia on PH ECG is an independent predictor of adverse hospital outcomes. ST segment monitoring in the prehospital setting may identify high-risk patients with symptoms of ACS and provide important prognostic information at presentation to the ED. PMID:23357378

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Anishkin, Andriy; Akitake, Bradley; Sukharev, Sergei

    2008-01-01

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

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

    PubMed

    Tripathy, R K; Dandapat, S

    2016-06-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-08-03

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

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

    PubMed

    Cheng, H; Skosnik, P D; Pruce, B J; Brumbaugh, M S; Vollmer, J M; Fridberg, D J; O'Donnell, B F; Hetrick, W P; Newman, S D

    2014-11-01

    Chronic cannabis use can cause cognitive, perceptual and personality alterations, which are believed to be associated with regional brain changes and possible changes in connectivity between functional regions. This study aims to identify the changes from resting state functional magnetic resonance imaging scans. A two-level multi-voxel pattern analysis was proposed to classify male cannabis users from normal controls. The first level analysis works on a voxel basis and identifies clusters for the input of a second level analysis, which works on the functional connectivity between these regions. We found distinct clusters for male cannabis users in the middle frontal gyrus, precentral gyrus, superior frontal gyrus, posterior cingulate cortex, cerebellum and some other regions. Based on the functional connectivity of these clusters, a high overall accuracy rate of 84-88% in classification accuracy was achieved. High correlations were also found between the overall classification accuracy and Barrett Barrett Impulsiveness Scale factor scores of attention and motor. Our result suggests regional differences in the brains of male cannabis users that span from the cerebellum to the prefrontal cortex, which are associated with differences in functional connectivity. © The Author(s) 2014.

  11. Resting heart rate and the risk of type 2 diabetes: A systematic review and dose--response meta-analysis of cohort studies.

    PubMed

    Aune, D; Ó Hartaigh, B; Vatten, L J

    2015-06-01

    High resting heart rate has been associated with increased risk of type 2 diabetes in several studies, but the available data are not consistent and it is unclear if there is a dose-response relationship between resting heart rate and type 2 diabetes risk. We aimed to clarify this association by conducting a systematic review and meta-analysis of published studies. PubMed, Embase and Ovid Medline databases were searched for prospective studies published up until October 11th, 2013. Summary relative risks were estimated using a random effects model. Ten cohort studies with >5628 cases and 119,915 participants were included. The summary RR for high vs. low resting heart rate was 1.83 (95% CI: 1.28-2.60, I(2) = 88%, n = 7), and in the dose-response analysis the summary RR was 1.20 (95% CI: 1.07-1.34, I(2) = 93%, n = 9) for an increase of 10 beats per minute. The heterogeneity was to a large degree explained by two studies. There was evidence of nonlinear associations between resting heart rate (pnonlinearity < 0.0001) and risk of type 2 diabetes. The current meta-analysis indicates a strong positive association between high resting heart rate and the risk of type 2 diabetes. As a non-invasive marker of type 2 diabetes risk, resting heart rate may have potential in the clinical setting, especially for interventions aimed at lowering the risk of type 2 diabetes. Additional studies are needed to clarify the mechanisms that may be responsible for the assoiation between resting heart rate and type 2 diabetes. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Smartphone home monitoring of ECG

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

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

    PubMed

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

    2014-01-01

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

  14. A method for independent component graph analysis of resting-state fMRI.

    PubMed

    Ribeiro de Paula, Demetrius; Ziegler, Erik; Abeyasinghe, Pubuditha M; Das, Tushar K; Cavaliere, Carlo; Aiello, Marco; Heine, Lizette; di Perri, Carol; Demertzi, Athena; Noirhomme, Quentin; Charland-Verville, Vanessa; Vanhaudenhuyse, Audrey; Stender, Johan; Gomez, Francisco; Tshibanda, Jean-Flory L; Laureys, Steven; Owen, Adrian M; Soddu, Andrea

    2017-03-01

    Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. First, ICA was performed at the single-subject level in 15 healthy volunteers using a 3T MRI scanner. The identification of nine networks was performed by a multiple-template matching procedure and a subsequent component classification based on the network "neuronal" properties. Second, for each of the identified networks, the nodes were defined as 1,015 anatomically parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Network graph comparison between the classically constructed network and the nine networks showed significant differences in the auditory and visual medial networks with regard to the average degree and the number of edges, while the visual lateral network showed a significant difference in the small-worldness. This novel approach permits us to take advantage of the well-recognized power of ICA in BOLD signal decomposition and, at the same time, to make use of well-established graph measures to evaluate connectivity differences. Moreover, by providing a graph for each separate network, it can offer the possibility to extract graph measures in a specific way for each network. This increased specificity could be relevant for studying pathological brain activity or altered states of consciousness as induced by anesthesia or sleep, where specific networks are known to be altered in

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

    PubMed

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

    2016-09-08

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

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

    PubMed

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

    2016-04-01

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

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

    PubMed

    Chakrabarti, Dhritiman; Bansal, Sonia

    2016-02-01

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

  18. 'Resting toucher': a time and motion analysis of elite lawn bowls.

    PubMed

    Silk, Aaron J; Hammond, John; Weatherby, Robert P

    2006-01-01

    Whilst numerous investigations have explored the physical demands placed upon competitive sportspeople from a wide array of sports little is known about the physical demands placed on lawn bowlers. The purpose of this study was to ascertain the movement activities of Australian representative singles and pairs players and to determine the frequency and duration of these activities. One match each of two male and two female players (one singles and one pairs player per gender) were videotaped during an international tournament. During playback of the videotaped matches (n = 4), a single observer coded the players' activities into five distinct categories (waiting, walking forward, walking backward, jogging and bowling) using a computerised video editing system (Gamebreaker™ Digital Video Analysis System). Field calibration of players over 30m for forward motions and 15m for the backward motion was performed to allow for the estimation of total distance covered during the match. Heart rate was monitored during each match. The duration of a match was found to be (mean ± SD) 1hr 28 ± 15mins. The total distance covered during each match was 2093 ± 276m. The mean percentage of match time spent in each motion was: waiting, 61.8 ± 9.3%; walking forward, 22.3 ± 5.6%; walking backward, 2.0 ± 0.4%; jogging, 1.1 ± 0.5%; and bowling, 8.5 ± 4.2%. Average heart rate was found to be 57 ± 7% of age-predicted HRmax with a maximum of 78 ± 9% of age-predicted HRmax. The results of this study suggest that playing lawn bowls at an international level requires light-moderate intensity activity similar to that reported for golf. Key PointsThe duration of a lawn bowls match played in sets play was 1hr 28 ± 15mins.The majority (65%) of this time was spent in the motion category "waiting".Players covered more than 2000m during a match with the vast majority (85%) in the form of forward walking.The average heart rate was 107 ± 15 bpm or 57 ± 7% of age-predicted HRmax.The game

  19. Resting Toucher’: A Time and Motion Analysis of Elite Lawn Bowls

    PubMed Central

    Silk, Aaron J.; Hammond, John; Weatherby, Robert P.

    2006-01-01

    Whilst numerous investigations have explored the physical demands placed upon competitive sportspeople from a wide array of sports little is known about the physical demands placed on lawn bowlers. The purpose of this study was to ascertain the movement activities of Australian representative singles and pairs players and to determine the frequency and duration of these activities. One match each of two male and two female players (one singles and one pairs player per gender) were videotaped during an international tournament. During playback of the videotaped matches (n = 4), a single observer coded the players’ activities into five distinct categories (waiting, walking forward, walking backward, jogging and bowling) using a computerised video editing system (Gamebreaker™ Digital Video Analysis System). Field calibration of players over 30m for forward motions and 15m for the backward motion was performed to allow for the estimation of total distance covered during the match. Heart rate was monitored during each match. The duration of a match was found to be (mean ± SD) 1hr 28 ± 15mins. The total distance covered during each match was 2093 ± 276m. The mean percentage of match time spent in each motion was: waiting, 61.8 ± 9.3%; walking forward, 22.3 ± 5.6%; walking backward, 2.0 ± 0.4%; jogging, 1.1 ± 0.5%; and bowling, 8.5 ± 4.2%. Average heart rate was found to be 57 ± 7% of age-predicted HRmax with a maximum of 78 ± 9% of age-predicted HRmax. The results of this study suggest that playing lawn bowls at an international level requires light-moderate intensity activity similar to that reported for golf. Key Points The duration of a lawn bowls match played in sets play was 1hr 28 ± 15mins. The majority (65%) of this time was spent in the motion category “waiting”. Players covered more than 2000m during a match with the vast majority (85%) in the form of forward walking. The average heart rate was 107 ± 15 bpm or 57 ± 7% of age-predicted HRmax

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

    NASA Astrophysics Data System (ADS)

    Kora, Padmavathi; Sri Rama Krishna, K.

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  3. Modest agreement in ECG interpretation limits the application of ECG screening in young athletes.

    PubMed

    Brosnan, Maria; La Gerche, Andre; Kumar, Saurabh; Lo, Wilson; Kalman, Jonathan; Prior, David

    2015-01-01

    Athlete ECG screening has been recommended by several international sporting bodies; however, a number of controversies remain regarding the accuracy of ECG screening. An important component that has not been assessed is the reproducibility of ECG interpretation. The purpose of this study was to assess the variability of ECG interpretation among experienced physicians when screening a large number of athletes. A sports cardiologist, a sports medicine physician, and an electrophysiologist analyzed 440 consecutive screening ECGs from asymptomatic athletes and were asked to classify the ECGs according to the 2010 European Society of Cardiology criteria as normal (or demonstrating training related ECG changes) or abnormal. When an abnormal ECG was identified, they were asked to outline what follow-up investigations they would recommend. The reported prevalence of abnormal ECGs ranged from 13.4% to 17.5%. Agreement on which ECGs were abnormal ranged from poor (κ = 0.297) to moderate (κ = 0.543) between observers. Suggested follow-up investigations were varied, and follow-up costs ranged from an additional A$30-A$129 per screening episode. Neither of the 2 subjects (0.45%) in the cohort with significant pathology diagnosed as a result of screening were identified correctly by all 3 physicians. Even when experienced physicians interpret athletes' ECGs according to current standards, there is significant interobserver variability that results in false-positive and false-negative results, thus reducing the effectiveness and increasing the social and economic cost of screening. Copyright © 2015 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

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

    PubMed

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

    2017-03-01

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

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

    PubMed

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

    2017-03-11

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

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

    PubMed

    Ishikawa, Joji; Ishikawa, Shizukiyo; Kario, Kazuomi

    2015-03-01

    We attempted to evaluate whether subjects who exhibit prolonged corrected QT (QTc) interval (≥440 ms in men and ≥460 ms in women) on ECG, with and without ECG-diagnosed left ventricular hypertrophy (ECG-LVH; Cornell product, ≥244 mV×ms), are at increased risk of stroke. Among the 10 643 subjects, there were a total of 375 stroke events during the follow-up period (128.7±28.1 months; 114 142 person-years). The subjects with prolonged QTc interval (hazard ratio, 2.13; 95% confidence interval, 1.22-3.73) had an increased risk of stroke even after adjustment for ECG-LVH (hazard ratio, 1.71; 95% confidence interval, 1.22-2.40). When we stratified the subjects into those with neither a prolonged QTc interval nor ECG-LVH, those with a prolonged QTc interval but without ECG-LVH, and those with ECG-LVH, multivariate-adjusted Cox proportional hazards analysis demonstrated that the subjects with prolonged QTc intervals but not ECG-LVH (1.2% of all subjects; incidence, 10.7%; hazard ratio, 2.70, 95% confidence interval, 1.48-4.94) and those with ECG-LVH (incidence, 7.9%; hazard ratio, 1.83; 95% confidence interval, 1.31-2.57) had an increased risk of stroke events, compared with those with neither a prolonged QTc interval nor ECG-LVH. In conclusion, prolonged QTc interval was associated with stroke risk even among patients without ECG-LVH in the general population. © 2014 American Heart Association, Inc.

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

    PubMed

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

    2014-08-01

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

  8. Molecular Imaging of Mesothelioma with 99mTc-ECG and 68Ga-ECG

    PubMed Central

    Zhang, Yin-Han; Bryant, Jerry; Kong, Fan-Lin; Yu, Dong-Fang; Mendez, Richard; Edmund Kim, E.; Yang, David J.

    2012-01-01

    We have developed ethylenedicysteine-glucosamine (ECG) as an alternative to 18F-fluoro-2-deoxy-D-glucose (18F-FDG) for cancer imaging. ECG localizes in the nuclear components of cells via the hexosamine biosynthetic pathway. This study was to evaluate the feasibility of imaging mesothelioma with 99mTc-ECG and 68Ga-ECG. ECG was synthesized from thiazolidine-4-carboxylic acid and 1,3,4,6-tetra-O-acetyl-2-amino-D-glucopyranose, followed by reduction in sodium and liquid ammonia to yield ECG (52%). ECG was chelated with 99mTc/tin (II) and 68Ga/69Ga chloride for in vitro and in vivo studies in mesothelioma. The highest tumor uptake of 99mTc-ECG is 0.47 at 30 min post injection, and declined to 0.08 at 240 min post injection. Tumor uptake (%ID/g), tumor/lung, tumor/blood, and tumor/muscle count density ratios for 99mTc-ECG (30–240 min) were 0.47 ± 0.06 to 0.08 ± 0.01; 0.71 ± 0.07 to 0.85 ± 0.04; 0.47 ± 0.03 to 0.51 ± 0.01, and 3.49 ± 0.24 to 5.06 ± 0.25; for 68Ga-ECG (15–60 min) were 0.70 ± 0.06 to 0.92 ± 0.08; 0.64 ± 0.05 to 1.15 ± 0.08; 0.42 ± 0.03 to 0.67 ± 0.07, and 3.84 ± 0.52 to 7.00 ± 1.42; for 18F-FDG (30–180 min) were 1.86 ± 0.22 to 1.38 ± 0.35; 3.18 ± 0.44 to 2.92 ± 0.34, 4.19 ± 0.44 to 19.41 ± 2.05 and 5.75 ± 2.55 to 3.33 ± 0.65, respectively. Tumor could be clearly visualized with 99mTc-ECG and 68Ga-ECG in mesothelioma-bearing rats. 99mTc-ECG and 68Ga-ECG showed increased uptake in mesothelioma, suggesting they may be useful in diagnosing mesothelioma and also monitoring therapeutic response. PMID:22645409

  9. Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

    2017-02-01

    We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    PubMed

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

    2016-06-01

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

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

    PubMed

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

    2013-11-01

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

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

    PubMed

    Sarapa, Nenad

    2007-09-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2008-05-01

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

  16. Characteristic wave detection in ECG signal using morphological transform

    PubMed Central

    Sun, Yan; Chan, Kap Luk; Krishnan, Shankar Muthu

    2005-01-01

    Background Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG). Methods A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative. Results We demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed. Conclusion The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition. PMID:16171531

  17. Resting heart rate, physiological stress and disadvantage in Aboriginal and Torres Strait Islander Australians: analysis from a cross-sectional study.

    PubMed

    Zhang, Alice; Hughes, Jaquelyne T; Brown, Alex; Lawton, Paul D; Cass, Alan; Hoy, Wendy; O'Dea, Kerin; Maple-Brown, Louise J

    2016-02-11

    Lower socioeconomic status has been linked to long-term stress, which can manifest in individuals as physiological stress. The aim was to explore the relationship between low socioeconomic status and physiological stress in Aboriginal and Torres Strait Islander Australians. Using data from the eGFR Study (a cross-sectional study of 634 Indigenous Australians in urban and remote areas of northern and central Australia), we examined associations between resting heart rate and demographic, socioeconomic, and biomedical factors. An elevated resting heart rate has been proposed as a measure of sustained stress activation and was used as a marker of physiological stress. Relationships were assessed between heart rate and the above variables using univariate and multiple regression analyses. We reported a mean resting heart rate of 74 beats/min in the cohort (mean age 45 years). On multiple regression analysis, higher heart rate was found to be independently associated with Aboriginal ethnicity, being a current smoker, having only primary level schooling, higher HbA1c and higher diastolic blood pressure (model R(2) 0.25). Elevated resting heart rate was associated with lower socioeconomic status and poorer health profile in Aboriginal and Torres Strait Islander Australians. Higher resting heart rate may be an indicator of stress and disadvantage in this population at high risk of chronic diseases.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  19. The ECG as decision support in STEMI.

    PubMed

    Ripa, Maria Sejersten

    2012-03-01

    The electrocardiogram (ECG) can be used for determining the presence, location and extent of jeopardized myocardium during acute coronary occlusion. Accordingly, the ECG has become essential in the treatment of patients with acute coronary syndrome (ACS). This thesis aims at optimizing the decision support, provided by the ECG, for choosing the best treatment strategy in the individual patient with ST-segment elevation acute myocardial infarction (STEMI). ECG recorded in the prehospital setting has become the standard of care in many communities, but to achieve the full advantage of this early approach it is important that the ECG is recorded from accurately placed electrodes to produce an ECG that resembles the standard 12-lead ECG. Accurate electrode placement is difficult especially in the acute setting, and we investigated an alternative lead system with fewer electrodes in easily identified positions. We showed that the system produced waveforms similar to the standard 12-lead ECG. However, occasional diagnostic errors were seen, compromising general acceptance of the system. Once the ECG has been recorded a decision regarding triage must be made on the basis of a correct ECG diagnosis. We found that trained paramedics can diagnose STEMI correctly in patients without ECG confounding factors, while the presence of ECG confounding factors decreased their ability substantially. Consequently, since many patients do present with ECG confounding factors, transmission to an on-call cardiologist for an early correct diagnosis is needed. We showed that time to pPCI was reduced by more than 1 hour by transmitting prehospital ECG to a cardiologist's handheld device for diagnosis, triage, and activation of the catheterization laboratory when needed. The optimal treatment strategy is dependent on the duration of ischemia however patient information is often inaccurate. Accordingly, it would be advantageous if the first available ECG can help identify patients who will

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

    PubMed

    Orhan, Umut

    2013-10-01

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

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

    PubMed

    Chen, Yun; Yang, Hui

    2012-09-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-05-13

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

  4. Methods for Improving the Diagnosis of a Brugada ECG Pattern.

    PubMed

    Gottschalk, Byron H; Garcia-Niebla, Javier; Anselm, Daniel D; Glover, Benedict; Baranchuk, Adrian

    2016-03-01

    Brugada syndrome (BrS) is an inherited channelopathy that predisposes individuals to malignant arrhythmias and can lead to sudden cardiac death. The condition is characterized by two electrocardiography (ECG) patterns: the type-1 or "coved" ECG and the type-2 or "saddleback" ECG. Although the type-1 Brugada ECG pattern is diagnostic for the condition, the type-2 Brugada ECG pattern requires differential diagnosis from conditions that produce a similar morphology. In this article, we present a case that is suspicious but not diagnostic for BrS and discuss the application of ECG methodologies for increasing or decreasing suspicion for a diagnosis of BrS. © 2015 Wiley Periodicals, Inc.

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

    PubMed

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

    2014-09-01

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

  6. Automatic pattern recognition in ECG time series.

    PubMed

    Sternickel, Karsten

    2002-05-01

    In this paper, a technique for the automatic detection of any recurrent pattern in ECG time series is introduced. The wavelet transform is used to obtain a multiresolution representation of some example patterns for signal structure extraction. Neural Networks are trained with the wavelet transformed templates providing an efficient detector even for temporally varying patterns within the complete time series. The method is also robust against offsets and stable for signal to noise ratios larger than one. Its reliability was tested on 60 Holter ECG recordings of patients at the Department of Cardiology (University of Bonn). Due to the convincing results and its fast implementation the method can easily be used in clinical medicine. In particular, it solves the problem of automatic P wave detection in Holter ECG recordings.

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

    PubMed

    Sem-Jacobsen, C W

    1976-04-01

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

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

    PubMed

    Takahashi, Tomoko; Ohnuma, Masaaki

    2016-02-01

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

  9. Anatomic distribution of culprit lesions in patients with non-ST-segment elevation myocardial infarction and normal ECG.

    PubMed

    Moustafa, Abdelmoniem; Abi-Saleh, Bernard; El-Baba, Mohammad; Hamoui, Omar; AlJaroudi, Wael

    2016-02-01

    In patients presenting with non-ST-elevation myocardial infarction (NSTEMI), left anterior descending (LAD) coronary artery and three-vessel disease are the most commonly encountered culprit lesions in the presence of ST depression, while one third of patients with left circumflex (LCX) artery related infarction have normal ECG. We sought to determine the predictors of presence of culprit lesion in NSTEMI patients based on ECG, echocardiographic, and clinical characteristics. Patients admitted to the coronary care unit with the diagnosis of NSTEMI between June 2012 and December 2013 were retrospectively identified. Admission ECG was interpreted by an electrophysiologist that was blinded to the result of the coronary angiogram. Patients were dichotomized into either normal or abnormal ECG group. The primary endpoint was presence of culprit lesion. Secondary endpoints included length of stay, re-hospitalization within 60 days, and in-hospital mortality. A total of 118 patients that were identified; 47 with normal and 71 with abnormal ECG. At least one culprit lesion was identified in 101 patients (86%), and significantly more among those with abnormal ECG (91.5% vs. 76.6%, P=0.041).The LAD was the most frequently detected culprit lesion in both groups. There was a higher incidence of two and three-vessel disease in the abnormal ECG group (P=0.041).On the other hand, there was a trend of higher LCX involvement (25% vs. 13.8%, P=0.18) and more normal coronary arteries in the normal ECG group (23.4% vs. 8.5%, P=0.041). On multivariate analysis, prior history of coronary artery disease (CAD) [odds ratio (OR) 6.4 (0.8-52)], male gender [OR 5.0 (1.5-17)], and abnormal admission ECG [OR 3.6 (1.12-12)], were independent predictors of a culprit lesion. There was no difference in secondary endpoints between those with normal and abnormal ECG. Among patients presenting with NSTEMI, prior history of CAD, male gender and abnormal admission ECG were independent predictors of a

  10. Three-class ROC analysis: a sequential decision model developed for the diagnostic task rest-stress myocardial perfusion SPECT imaging

    NASA Astrophysics Data System (ADS)

    He, Xin; Frey, Eric C.

    2008-03-01

    Previously we have developed a decision model for three-class ROC analysis where classification is made three simultaneously, i.e., with a single decision. In this paper, an alternative sequential decision model was developed for the specific three-class diagnostic procedure of rest-stress myocardial perfusion SPECT (MPS) imaging. This sequential decision model was developed based on the fact that sometimes this diagnostic task is performed using a two-step process. First, the stress ( 99m Tc) image is read to determine whether a patient is normal or abnormal based on the presence of a defect in the stress image. If a defect is found, the rest ( 201Tl) image is then read to determine whether this is a reversible defect or a fixed defect based on the presence of defect on the rest image. In fact, in some MPS protocols where sequential stress/rest imaging is performed, the rest imaging is not performed if there is no defect in the stress image. Therefore, the three-class task is decomposed to a sequence of two two-class tasks. For this task we determined, by maximizing the expected utility of both steps of the decision process, that log likelihood ratios were the optimal decision variables and provide the optimal ROC surface under the assumption that incorrect decisions have equal utilities under the same hypothesis. The properties of the sequential decision model were then studied. We found that the sequential decision model shares most of the features of a 2-class ROC curve. While this model was developed in the context of rest-stress MPS, it may have applications to other two-step diagnostic tasks.

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-01-01

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

  13. Fetal electrocardiogram (ECG) for fetal monitoring during labour.

    PubMed

    Neilson, James P

    2015-12-21

    Hypoxaemia during labour can alter the shape of the fetal electrocardiogram (ECG) waveform, notably the relation of the PR to RR intervals, and elevation or depression of the ST segment. Technical systems have therefore been developed to monitor the fetal ECG during labour as an adjunct to continuous electronic fetal heart rate monitoring with the aim of improving fetal outcome and minimising unnecessary obstetric interference. To compare the effects of analysis of fetal ECG waveforms during labour with alternative methods of fetal monitoring. The Cochrane Pregnancy and Childbirth Group's Trials Register (latest search 23 September 2015) and reference lists of retrieved studies. Randomised trials comparing fetal ECG waveform analysis with alternative methods of fetal monitoring during labour. One review author independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. One review author assessed the quality of the evidence using the GRADE approach. Seven trials (27,403 women) were included: six trials of ST waveform analysis (26,446 women) and one trial of PR interval analysis (957 women). The trials were generally at low risk of bias for most domains and the quality of evidence for ST waveform analysis trials was graded moderate to high. In comparison to continuous electronic fetal heart rate monitoring alone, the use of adjunctive ST waveform analysis made no obvious difference to primary outcomes: births by caesarean section (risk ratio (RR) 1.02, 95% confidence interval (CI) 0.96 to 1.08; six trials, 26,446 women; high quality evidence); the number of babies with severe metabolic acidosis at birth (cord arterial pH less than 7.05 and base deficit greater than 12 mmol/L) (average RR 0.72, 95% CI 0.43 to 1.20; six trials, 25,682 babies; moderate quality evidence); or babies with neonatal encephalopathy (RR 0.61, 95% CI 0.30 to 1.22; six trials, 26,410 babies; high quality evidence). There were, however, on average

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  16. A beat-by-beat analysis of cardiovascular responses to dry resting and exercise apnoeas in elite divers.

    PubMed

    Sivieri, Andrea; Fagoni, Nazzareno; Bringard, Aurélien; Capogrosso, Michela; Perini, Renza; Ferretti, Guido

    2015-01-01

    Cardiovascular responses during resting apnoea include three phases: (1) a dynamic phase of rapid changes, lasting at most 30 s; (2) a subsequent steady phase; and (3) a further dynamic phase, with a continuous decrease in heart rate (HR) and an increase in blood pressure. The interpretation was that the end of the steady phase corresponds to the physiological apnoea breaking point. This being so, during exercise apnoeas, the steady phase would be shorter, and the rate of cardiovascular changes in the subsequent unsteady phase would be faster than at rest. To test these hypotheses, we measured beat-by-beat systolic (SBP), diastolic, and mean blood pressures (MBP), HR, and stroke volume (SV) in six divers during dry resting (duration 239.4 ± 51.6 s) and exercise (30 W on cycle ergometer, duration 88.2 ± 20.9 s) maximal apnoeas, and we computed cardiac output ([Formula: see text]) and total peripheral resistance (TPR). Compared to control, at the beginning of resting (R1) and exercising (E1) apnoeas, SBP and MBP decreased and HR increased. SV and [Formula: see text] fell, so that TPR remained unchanged. At rest, HR, SV, [Formula: see text], and SBP were stable during the subsequent phase; this steady phase was missing in exercise apnoeas. Subsequently, at rest (R3) and at exercise (E2), HR decreased and SBP increased continuously. SV returned to control values. Since [Formula: see text] remained unchanged, TPR grew. The lack of steady phase during exercise apnoeas suggests that the conditions determining R3 were already attained at the end of E1. This being so, E2 would correspond to R3.

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

    PubMed Central

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

    2009-01-01

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

  18. ECG response of koalas to tourists proximity: a preliminary study.

    PubMed

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

    2009-10-12

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Lu, Liangliang; Chen, Minya

    2015-11-01

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

  2. The Effects of Exercise on Resting Blood Pressure in Children and Adolescents: A Meta-Analysis of Randomized Controlled Trials

    PubMed Central

    Kelley, George A.; Kelley, Kristi S.; Tran, Zung Vu

    2007-01-01

    Resting blood pressure in children and adolescents can track into adulthood. The purpose of this study was to use the meta-analytic approach to examine the effects of exercise on resting systolic and diastolic blood pressure in children and adolescents. Twelve randomized, controlled trials representing 16 outcomes in 1266 subjects met the inclusion criteria. Reductions in blood pressure were approximately 1% and 3% for resting systolic and diastolic blood pressures, respectively. However, random-effects modeling using 5000 bootstrap confidence intervals revealed that neither result was statistically significant (systolic, X̄±SEM=−1±2; 95% bootstrap confidence intervals=−2 to 0 mm Hg; diastolic, X̄±SEM=−2±1; 95% bootstrap confidence intervals=−3 to 0 mm Hg). The results of this study suggest that short-term exercise does not appear to reduce resting systolic and diastolic blood pressure in children and adolescents. However, a need exists for additional studies, especially in hypertensive children and adolescents. PMID:12624556

  3. ECG Beats Classification Using Mixture of Features

    PubMed Central

    Ari, Samit

    2014-01-01

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

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

    PubMed

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

    2013-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Klump, Jens; Robertson, Jess

    2016-04-01

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

  6. Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to Crystallized IQ and Gender

    PubMed Central

    Pezoulas, Vasileios C.; Zervakis, Michalis; Michelogiannis, Sifis; Klados, Manousos A.

    2017-01-01

    During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high crystallized Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject) using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST) was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results reveal that

  7. Application of higher order cumulant features for cardiac health diagnosis using ECG signals.

    PubMed

    Martis, Roshan Joy; Acharya, U Rajendra; Lim, Choo Min; Mandana, K M; Ray, A K; Chakraborty, Chandan

    2013-08-01

    Electrocardiogram (ECG) is the electrical activity of the heart indicated by P, Q-R-S and T wave. The minute changes in the amplitude and duration of ECG depicts a particular type of cardiac abnormality. It is very difficult to decipher the hidden information present in this nonlinear and nonstationary signal. An automatic diagnostic system that characterizes cardiac activities in ECG signals would provide more insight into these phenomena thereby revealing important clinical information. Various methods have been proposed to detect cardiac abnormalities in ECG recordings. Application of higher order spectra (HOS) features is a seemingly promising approach because it can capture the nonlinear and dynamic nature of the ECG signals. In this paper, we have automatically classified five types of beats using HOS features (higher order cumulants) using two different approaches. The five types of ECG beats are normal (N), right bundle branch block (RBBB), left bundle branch block (LBBB), atrial premature contraction (APC) and ventricular premature contraction (VPC). In the first approach, cumulant features of segmented ECG signal were used for classification; whereas in the second approach cumulants of discrete wavelet transform (DWT) coefficients were used as features for classifiers. In both approaches, the cumulant features were subjected to data reduction using principal component analysis (PCA) and classified using three layer feed-forward neural network (NN) and least square-support vector machine (LS-SVM) classifiers. In this study, we obtained the highest average accuracy of 94.52%, sensitivity of 98.61% and specificity of 98.41% using first approach with NN classifier. The developed system is ready clinically to run on large datasets.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

    Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, “dynamic global signal regression” (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional “static” global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps. PMID:27445751

  10. Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems

    PubMed Central

    Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

    2014-01-01

    Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices. PMID:24409290

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

    PubMed

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

    2006-01-01

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

  12. Simple method for adaptive filtering of motion artifacts in E-textile wearable ECG sensors.

    PubMed

    Alkhidir, Tamador; Sluzek, Andrzej; Yapici, Murat Kaya

    2015-08-01

    In this paper, we have developed a simple method for adaptive out-filtering of the motion artifact from the electrocardiogram (ECG) obtained by using conductive textile electrodes. The textile electrodes were placed on the left and the right wrist to measure ECG through lead-1 configuration. The motion artifact was induced by simple hand movements. The reference signal for adaptive filtering was obtained by placing additional electrodes at one hand to capture the motion of the hand. The adaptive filtering was compared to independent component analysis (ICA) algorithm. The signal-to-noise ratio (SNR) for the adaptive filtering approach was higher than independent component analysis in most cases.

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

    PubMed Central

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

    2015-01-01

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

  14. [Development of multi-function ECG signal generator].

    PubMed

    Cheng, F; Wei, Y X

    2000-07-01

    This paper describes the development of a portable multi-function ECG signal generator, which is based on micro-controller. It uses technique of LCD screen, and realizes man-machine interaction by keyboard. In constructing and disposing data module of the ECG signal, Eigen-heartbeat Code mapping method gets ROM saved greatly. Therefore it can generate all kinds of user-defined ECG signal sequence with no extension of on-board memory chips. This system can also simulate kinds of ECG signals, which have various heart rates and symptoms. It can meet the needs of researching and maintenance of kinds of ECG instruments.

  15. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

    PubMed Central

    Ramkumar, Barathram; Sabarimalai Manikandan, M.

    2017-01-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

  16. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

    PubMed

    Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

    2017-02-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

  17. Hyperkalemia Induced Brugada Phenocopy: A Rare ECG Manifestation

    PubMed Central

    Akbar, Ghulam; Mirrani, Ghazi

    2017-01-01

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

  18. Identifying UMLS concepts from ECG Impressions using KnowledgeMap.

    PubMed

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

    2005-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  20. Relationship between echocardiographic LV mass and ECG based left ventricular voltages in an adolescent population: related or random?

    PubMed

    Czosek, Richard J; Cnota, James F; Knilans, Timothy K; Pratt, Jesse; Guerrier, Karine; Anderson, Jeffrey B

    2014-09-01

    In attempts to detect diseases that may place adolescents at risk for sudden death, some have advocated for population-based screening. Controversy exists over electrocardiography (ECG) screening due to the lack of specificity, cost, and detrimental effects of false positive or extraneous outcomes. Analyze the relationship between precordial lead voltage on ECG and left ventricle (LV) mass by echocardiogram in adolescent athletes. Retrospective cohort analysis of a prospectively obtained population of self-identified adolescent athletes during sports screening with ECG and echocardiogram. Correlation between ECG LV voltages (R wave in V6 [RV6] and S wave in lead V1 [SV1]) was compared to echocardiogram-based measurements of left ventricular mass. Potential effects on ECG voltages by body anthropometrics, including weight, body mass index (BMI), and body surface area were analyzed, and ECG voltages indexed to BMI were compared to LV mass indices to analyze for improved correlation. A total of 659 adolescents enrolled in this study (64% male). The mean age was 15.4 years (14-18). The correlations between LV mass and RV6, SV1, and RV6 + SV1 were all less than 0.20. The false positive rate for abnormal voltages was relatively high (5.5%) but improved if abnormal voltages in both RV6 and SV1 were mandated simultaneously (0%). Indexing ECG voltages to BMI significantly improved correlation to LV mass, though false positive findings were increased (12.9%). There is poor correlation between ECG precordial voltages and echocardiographic LV mass. This relationship is modified by BMI. This finding may contribute to the poor ECG screening characteristics. ©2014 Wiley Periodicals, Inc.

  1. Comparison of ECG-based physiological markers for hypoxia in a preterm ovine model.

    PubMed

    Zwanenburg, Alex; Hermans, Ben Jm; Andriessen, Peter; Niemarkt, Hendrik J; Jellema, Reint K; Ophelders, Daan Rmg; Vullings, Rik; Wolfs, Tim Gam; Kramer, Boris W; Delhaas, Tammo

    2016-06-01

    Current methods for assessing perinatal hypoxic conditions did not improve infant outcomes. Various waveform-based and interval-based ECG markers have been suggested, but not directly compared. We compare performance of ECG markers in a standardized ovine model for fetal hypoxia. Sixty-nine fetal sheep of 0.7 gestation had ECG recorded 4 h before, during, and 4 h after a 25-min period of umbilical cord occlusion (UCO), leading to severe hypoxia. Various ECG markers were calculated, among which were heart rate (HR), HR-corrected ventricular depolarization/repolarization interval (QTc), and ST-segment analysis (STAN) episodic and baseline rise markers, analogue to clinical STAN device alarms. Performance of interval- and waveform-based ECG markers was assessed by correlating predicted and actual hypoxic/normoxic state. Of the markers studied, HR and QTc demonstrated high sensitivity (≥86%), specificity (≥96%), and positive predictive value (PPV) (≥86%) and detected hypoxia in ≥90% of fetuses at 4 min after UCO. In contrast, STAN episodic and baseline rise markers displayed low sensitivity (≤20%) and could not detect severe fetal hypoxia in 65 and 28% of the animals, respectively. Interval-based HR and QTc markers could assess the presence of severe hypoxia. Waveform-based STAN episodic and baseline rise markers were ineffective as markers for hypoxia.

  2. EEG and ECG changes during simulator operation reflect mental workload and vigilance.

    PubMed

    Dussault, Caroline; Jouanin, Jean-Claude; Philippe, Matthieu; Guezennec, Charles-Yannick

    2005-04-01

    Performing mission tasks in a simulator influences many neurophysiological measures. Quantitative assessments of electroencephalography (EEG) and electrocardiography (ECG) have made it possible to develop indicators of mental workload and to estimate relative physiological responses to cognitive requirements. To evaluate the effects of mental workload without actual physical risk, we studied the cortical and cardiovascular changes that occurred during simulated flight. There were 12 pilots (8 novices and 4 experts) who simulated a flight composed of 10 sequences that induced several different mental workload levels. EEG was recorded at 12 electrode sites during rest and flight sequences; ECG activity was also recorded. Subjective tests were used to evaluate anxiety and vigilance levels. Theta band activity was lower during the two simulated flight rest sequences than during visual and instrument flight sequences at central, parietal, and occipital sites (p < 0.05). On the other hand, rest sequences resulted in higher beta (at the C4 site; p < 0.05) and gamma (at the central, parietal, and occipital sites; p < 0.05) power than active segments. The mean heart rate (HR) was not significantly different during any simulated flight sequence, but HR was lower for expert subjects than for novices. The subjective tests revealed no significant anxiety and high values for vigilance levels before and during flight. The different flight sequences performed on the simulator resulted in electrophysiological changes that expressed variations in mental workload. These results corroborate those found during study of real flights, particularly during sequences requiring the heaviest mental workload.

  3. Single frequency RF powered ECG telemetry system

    NASA Technical Reports Server (NTRS)

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

    1979-01-01

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

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

    PubMed

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

    2015-09-01

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

  5. Global and System-Specific Resting-State fMRI Fluctuations Are Uncorrelated: Principal Component Analysis Reveals Anti-Correlated Networks

    PubMed Central

    Carbonell, Felix; Bellec, Pierre

    2011-01-01

    Abstract The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)–based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed

  6. Resting cerebral blood flow

    PubMed Central

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

    2009-01-01

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

  7. Electrical Changes in Resting, Exercise, and Holter Electrocardiography in Fabry Cardiomyopathy.

    PubMed

    Krämer, Johannes; Nordbeck, Peter; Störk, Stefan; Ritter, Christian; Ertl, Georg; Wanner, Christoph; Weidemann, Frank

    2015-10-27

    In Fabry cardiomyopathy, little is known about the interaction between its key feature of myocardial replacement fibrosis and changes in resting, Holter, and exercise electrocardiography (-ECG). Resting ECG, 24-h Holter ECG, and exercise ECG were performed in 95 patients (50 women) with Fabry disease, staged using cardiac magnetic resonance imaging to measure left ventricular fibrosis. With resting ECG, T alterations were seen in patients with cardiac fibrosis, while time intervals and rhythm were unchanged (except for a longer QRS duration in patients with severe fibrosis). All patients with severe fibrosis showed T inversion, ST alteration, or both. With Holter ECG, maximum and minimum heart rate did not differ with fibrosis severity. Patients without fibrotic tissue showed less ventricular premature beats (VPB) (median 5/24 h) compared to those with mild (median 11/24 h) or severe fibrosis (median 115/24 h; P < 0.05, respectively). Fibrosis was a strong predictor of VPB burden (r (2) = 0.5; P < 0.001). During exercise, patients with severe fibrosis had the least increase in systolic blood pressure (sBP) (47 ± 22 mmHg vs. 62 ± 25 mmHg, P < 0.05) and the lowest maximum heart rate (113 ± 18/min; P < 0.05). Patients with mild fibrosis had a high sBP during exercise (198 ± 37 mmHg; P < 0.05). Decreased diastolic blood pressure (>10 mmHg) occurred in some patients with no (3/41) or mild fibrosis (3/34) but not in patients with severe fibrosis (0/20; P < 0.01). Our data suggest that cardiac replacement fibrosis is responsible for repolarization abnormalities on resting ECG and increased VPB with Holter ECG. During exercise ECG, advanced cardiomyopathy is characterized by chronotropic incompetence with limitations on blood pressure and heart rate increase.

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

    PubMed

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

    1996-02-01

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

  9. Intelligent Classification of Heartbeats for Automated Real-Time ECG Monitoring

    PubMed Central

    Park, Juyoung

    2014-01-01

    Abstract Background: The automatic interpretation of electrocardiography (ECG) data can provide continuous analysis of heart activity, allowing the effective use of wireless devices such as the Holter monitor. Materials and Methods: We propose an intelligent heartbeat monitoring system to detect the possibility of arrhythmia in real time. We detected heartbeats and extracted features such as the QRS complex and P wave from ECG signals using the Pan–Tompkins algorithm, and the heartbeats were then classified into 16 types using a decision tree. Results: We tested the sensitivity, specificity, and accuracy of our system against data from the MIT-BIH Arrhythmia Database. Our system achieved an average accuracy of 97% in heartbeat detection and an average heartbeat classification accuracy of above 96%, which is comparable with the best competing schemes. Conclusions: This work provides a guide to the systematic design of an intelligent classification system for decision support in Holter ECG monitoring. PMID:25010717

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

    PubMed

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

    2002-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

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

    PubMed Central

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-01-01

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

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

    PubMed

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-04-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-08-21

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

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

    PubMed

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

    2016-09-16

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  19. Getting the most from venous occlusion plethysmography: proposed methods for the analysis of data with a rest/exercise protocol.

    PubMed

    Wythe, Stephen; Davies, Thomas; Martin, Daniel; Feelisch, Martin; Gilbert-Kawai, Edward

    2015-01-01

    Venous occlusion plethysmography is a simple yet powerful technique for the non-invasive measurement of blood flow. It has been used extensively in both the experimental and clinical settings. The underlying rationale is that when venous outflow from an extremity is occluded, any immediate increase in volume of this compartment must originate from the on-going arterial inflow. Mercury-in-silastic strain gauges are typically used to measure these volume changes, the rates of which are directly proportional to blood flow. When using a simple rest/exercise protocol to provide a local or systemic metabolic stimulus to increase blood flow, current methods for analysing the data obtained are often rather simplistic, solely considering the mean increment in blood flow induced by exercise. Previous methodological considerations have focused mainly on issues of reproducibility and accuracy (for instance, by comparing unilateral and/or bilateral measurements) but rarely on what the recorded traces may actually mean. In this methodological manuscript, we suggest a more detailed approach to processing venous occlusion plethysmography data, one which could provide additional physiological information. Six parameters are described, all of which are easily derived from a simple and reproducible experimental rest/exercise venous occlusion plethysmography protocol.

  20. Effect of dietary nitrate supplementation on metabolic rate during rest and exercise in human: A systematic review and a meta-analysis.

    PubMed

    Pawlak-Chaouch, Mehdi; Boissière, Julien; Gamelin, François X; Cuvelier, Grégory; Berthoin, Serge; Aucouturier, Julien

    2016-02-29

    Recent randomized controlled trials have suggested that dietary nitrate (NO3(-)), found in beetroot and other vegetables, and inorganic NO3(-) salts decrease metabolic rate under resting and exercise conditions. Our aim was therefore to determine from a systematic review and meta-analysis whether dietary NO3(-) supplementation significantly reduces metabolic rate, expressed as oxygen uptake (VO2), under resting and exercise conditions in healthy humans and those with cardiorespiratory diseases. A systematic article search was performed on electronic databases (PubMed, Scopus and Web of Science) from February to March 2015. The inclusion criteria included 1) randomized controlled trials; 2) studies reporting the effect of NO3(-) on VO2 under resting and/or exercise conditions; 3) comparison between dietary NO3(-) supplementation and placebo. Random-effects models were used to calculate the pooled effect size. Twenty nine randomized placebo-controlled trials were included in the systematic review, and 26 of which were included in the meta-analysis. Dietary NO3(-) supplementation significantly decreases VO2 during submaximal intensity exercise [-0.26 (95% IC: -0.38, -0.15), p < 0.01], but not in the sub-analysis of subjects with chronic diseases [-0.09 (95% IC: -0.50, 0.32), p = 0.67]. When data were separately analyzed by submaximal intensity domains, NO3(-) supplementation reduces VO2 during moderate [-0.29 (95% IC: -0.48,-0.10), p < 0.01] and heavy [-0.33 (95% IC: -0.54,-0.12), p < 0.01] intensity exercise. When the studies with the largest effects were excluded from the meta-analysis, there is a trend for a VO2 decrease under resting condition in dietary NO3(-) supplementation [-0.28 (95% IC: -0.62, 0.05), p = 0.10]. Dietary NO3(-) supplementation decreases VO2 during exercise performed in the moderate and heavy intensity domains in healthy subjects. The present meta-analysis did not show any significant effect of dietary NO3(-) supplementation on

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

    PubMed

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

    2015-03-01

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

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

    PubMed

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

    2017-03-15

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

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

    PubMed

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

    2014-04-01

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

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

    PubMed

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

    2016-02-01

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

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

    PubMed Central

    Shourie, Nasrin; Firoozabadi, Mohammad; Badie, Kambiz

    2014-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Filstrup, A. W.

    1973-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  11. Reliability and validity of clinician ECG interpretation for athletes.

    PubMed

    Magee, Charles; Kazman, Joshua; Haigney, Mark; Oriscello, Ralph; DeZee, Kent J; Deuster, Patricia; Depenbrock, Patrick; O'Connor, Francis G

    2014-07-01

    Electrocardiogram (ECG) with preparticipation evaluation (PPE) for athletes remains controversial in the United States and diagnostic accuracy of clinician ECG interpretation is unclear. This study aimed to assess reliability and validity of clinician ECG interpretation using expert-validated ECGs according to the 2010 European Society of Cardiology (ESC) interpretation criteria. This is a blinded, prospective study of diagnostic accuracy of clinician ECG interpretation. Anonymized ECGs were validated for normal and abnormal patterns by blinded expert interpreters according to the ESC interpretation criteria from October 2011 through March 2012. Six pairs of clinician interpreters were recruited from relevant clinical specialties in an academic medical center in March 2012. Each clinician interpreted 85 ECGs according to the ESC interpretation guidelines. Cohen and Fleiss' kappa, sensitivity, and specificity were calculated within specialties and across primary care and cardiology specialty groups. Experts interpreted 189 ECGs yielding a kappa of 0.63, demonstrating "substantial" inter-rater agreement. A total of 85 validated ECGs, including 26 abnormals, were selected for clinician interpretation. The kappa across cardiology specialists was "substantial" and "moderate" across primary care (0.69 vs 0.52, respectively, P < 0.001). Sensitivity and specificity to detect abnormal patterns were similar between cardiology and primary care groups (sensitivity 93.3% vs 81.3%, respectively, P = 0.31; specificity 88.8% vs 89.8%, respectively, P = 0.91). Clinician ECG interpretation according to the ESC interpretation criteria appears to demonstrate limited reliability and validity. Before widespread adoption of ECG for PPE of U.S. athletes, further research of training focused on improved reliability and validity of clinician ECG interpretation is warranted. © 2014 Wiley Periodicals, Inc.

  12. Compressed domain ECG biometric with two-lead features

    NASA Astrophysics Data System (ADS)

    Lee, Wan-Jou; Chang, Wen-Whei

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  14. A nonlinear Bayesian filtering framework for ECG denoising.

    PubMed

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

    2007-12-01

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

  15. Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition

    PubMed Central

    Chang, Kang-Ming

    2010-01-01

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

  16. Resting Heart Rate and Auditory Evoked Potential

    PubMed Central

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

    2015-01-01

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

  17. An awareness approach to analyze ECG streaming data.

    PubMed

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

    2013-04-01

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

  18. 3-lead acquisition using single channel ECG device developed on AD8232 analog front end for wireless ECG application

    NASA Astrophysics Data System (ADS)

    Agung, Mochammad Anugrah; Basari

    2017-02-01

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

  19. Study design and rationale for biomedical shirt-based electrocardiography monitoring in relevant clinical situations: ECG-shirt study.

    PubMed

    Balsam, Paweł; Lodziński, Piotr; Tymińska, Agata; Ozierański, Krzysztof; Januszkiewicz, Łukasz; Główczyńska, Renata; Wesołowska, Katarzyna; Peller, Michał; Pietrzak, Radosław; Książczyk, Tomasz; Borodzicz, Sonia; Kołtowski, Łukasz; Borkowski, Mariusz; Werner, Bożena; Opolski, Grzegorz; Grabowski, Marcin

    2017-08-25

    Today, the main challenge for researchers is to develop new technologies which may help to improve the diagnoses of cardiovascular disease (CVD), thereby reducing healthcare costs and improving the quality of life for patients. This study aims to show the utility of biomedical shirt-based electrocardiography (ECG) monitoring of patients with CVD in different clinical situations using the Nuubo® ECG (nECG) system. An investigator-initiated, multicentre, prospective observational study was carried out in a cardiology (adult and paediatric) and cardiac rehabilitation wards . ECG monitoring was used with the biomedical shirt in the following four independent groups of patients: 1) 30 patients after pulmonary vein isolation (PVI), 2) 30 cardiac resynchronization therapy (CRT) recipients, 3) 120 patients during cardiac rehabilitation after myocardial infarction, and 4) 40 pediatric patients with supraventricular tachycardia (SVT) before electrophysiology study. Approval for all study groups was obtained from the institutional review board. The biomedical shirt captures the electrocardiographic signal via textile electrodes integrated into a garment.The software allows the visualization and analysis of data such as ECG, heart rate, arrhythmia detecting algorithm and relative position of the body is captured by an electronic device. The major advantages of the nECG system are continuous ECG monitoring during daily activities, high quality of ECG recordings, as well as assurance of a proper adherence due to adequate comfort while wearing the shirt. There are only a few studies that have examined wearable systems, especially in pediatric populations. This study is registered in ClinicalTrials.gov: Identifier NCT03068169.

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

    PubMed

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

    2016-04-13

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

  1. Diagnostic ECG classification based on neural networks.

    PubMed

    Bortolan, G; Willems, J L

    1993-01-01

    This study illustrates the use of the neural network approach in the problem of diagnostic classification of resting 12-lead electrocardiograms. A large electrocardiographic library (the CORDA database established at the University of Leuven, Belgium) has been utilized in this study, whose classification is validated by electrocardiographic-independent clinical data. In particular, a subset of 3,253 electrocardiographic signals with single diseases has been selected. Seven diagnostic classes have been considered: normal, left, right, and biventricular hypertrophy, and anterior, inferior, and combined myocardial infarction. The basic architecture used is a feed-forward neural network and the backpropagation algorithm for the training phase. Sensitivity, specificity, total accuracy, and partial accuracy are the indices used for testing and comparing the results with classical methodologies. In order to validate this approach, the accuracy of two statistical models (linear discriminant analysis and logistic discriminant analysis) tuned on the same dataset have been taken as the reference point. Several nets have been trained, either adjusting some components of the architecture of the networks, considering subsets and clusters of the original learning set, or combining different neural networks. The results have confirmed the potentiality and good performance of the connectionist approach when compared with classical methodologies.

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

    PubMed

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

    2014-12-01

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

  3. Comparing QT interval variability of semiautomated and high-precision ECG methodologies in seven thorough QT studies-implications for the power of studies intended for definitive evaluation of a drug's QT effect.

    PubMed

    Meiser, Karin; Jordaan, Pierre; Latypova, Sasha; Darpo, Borje

    2017-01-01

    In studies of drug effects on electrocardiographic parameters, the level of precision in measuring QTc interval changes will influence a study's ability to detect small effects. Variability data from investigational, placebo and moxifloxacin treatments from seven thorough QT studies performed by the same sponsor were analyzed with the objective to compare the performance of two commonly used approaches for ECG interval measurements: semiautomated (SA) and the high-precision QT (HPQT) analysis. Five studies were crossover and two parallel. Harmonized procedures were implemented to ensure similar experimental conditions across studies. ECG replicates were extracted serially from continuous 12-lead recordings at predefined time points from subjects supinely resting. The variability estimates were based on the time-point analysis of change-from-baseline QTcF as the dependent variable for the standard primary analysis of previous thorough QT studies. The residual variances were extracted for each study and ECG technique. High-precision QT resulted in a substantial reduction in ∆QTc variability as compared to SA. A reduction in residual variability or approximately 50% was achieved in both crossover and parallel studies, both for the active comparison (drug vs. placebo) and for assay sensitivity (moxifloxacin vs. placebo) data. High-precision QT technique significantly reduces QT interval variability and thereby the number of subjects needed to exclude small effects in QT studies. Based on this assessment, the sample size required to exclude a QTc effect >10 ms with 90% power is reduced from 35 with SA to 18 with HPQT, if a 3 ms underlying drug effect is assumed. © 2016 Wiley Periodicals, Inc.

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

    PubMed

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

    2012-01-01

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

  5. Analysis of central mechanism of cognitive training on cognitive impairment after stroke: Resting-state functional magnetic resonance imaging study.

    PubMed

    Lin, Zhi-cheng; Tao, Jing; Gao, Yan-lin; Yin, Da-zhi; Chen, A-zhen; Chen, Li-dian

    2014-06-01

    To investigate the central mechanism of cognitive training in patients with stroke, using resting state (RS) functional magnetic resonance imaging (fMRI). Patients with stroke and executive function and memory deficit were randomized to receive computer-assisted cognitive training (treatment group; total 60 h training over 10 weeks) or no training (control group). All participants received neuropsychological assessment and RS fMRI at baseline and 10 weeks. Patients in the treatment group (n = 16) showed increased functional connectivity (FC) of the hippocampus with the frontal lobe (right inferior, right middle, left middle, left inferior and left superior frontal gyrus) and left parietal lobe at 10 weeks compared with baseline. Patients in the control group (n = 18) showed decreased FC of the left hippocampus-right occipital gyrus, and right hippocampus-right posterior lobe of cerebellum and left superior temporal gyrus. Significant correlations were found between improved neuropsychological scores and increased FC of the hippocampus with the frontal lobe and left parietal lobe in the treatment group only. Increased RS FC of the hippocampus with the frontal and parietal lobes may be an important mechanism of cognitive recovery after stroke. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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