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Sample records for resting ecg analysis

  1. Cloud-ECG for real time ECG monitoring and analysis.

    PubMed

    Xia, Henian; Asif, Irfan; Zhao, Xiaopeng

    2013-06-01

    Recent advances in mobile technology and cloud computing have inspired numerous designs of cloud-based health care services and devices. Within the cloud system, medical data can be collected and transmitted automatically to medical professionals from anywhere and feedback can be returned to patients through the network. In this article, we developed a cloud-based system for clients with mobile devices or web browsers. Specially, we aim to address the issues regarding the usefulness of the ECG data collected from patients themselves. Algorithms for ECG enhancement, ECG quality evaluation and ECG parameters extraction were implemented in the system. The system was demonstrated by a use case, in which ECG data was uploaded to the web server from a mobile phone at a certain frequency and analysis was performed in real time using the server. The system has been proven to be functional, accurate and efficient. PMID:23261079

  2. Risk stratifying asymptomatic aortic stenosis: role of the resting 12-lead ECG.

    PubMed

    Greve, Anders M

    2014-02-01

    Despite being routinely performed in the clinical follow-up of asymptomatic AS patients, little or no evidence describes the prognostic value of ECG findings in asymptomatic AS populations. This PhD thesis examined the correlates of resting 12-lead ECG variables with echocardiographic measures of AS severity and cardiovascular outcomes in the till date largest cohort (n=1,563) of asymptomatic patients with mild-to-moderate AS. Most importantly, this PhD thesis demonstrated that QRS-duration adds independent predictive value of sudden cardiac death and that the additional presence of ECG LVH/strain for fixed AS severity represents a lethal risk attribute. Finally, ECG abnormalities displayed low/moderate concordance with echocardiographic parameters. This argues that the ECG should be regarded as a separate tool for obtaining prognostically important information. Treatment was not randomized by ECG findings, future studies should therefore examine if and which ECG variables should elicit closer follow-up and/or earlier intervention to improve prognosis in asymptomatic AS populations. PMID:24495893

  3. 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).

  4. Independent component analysis of parameterized ECG signals.

    PubMed

    Tanskanen, Jarno M A; Viik, Jari J; Hyttinen, Jari A K

    2006-01-01

    Independent component analysis (ICA) of measured signals yields the independent sources, given certain fulfilled requirements. Properly parameterized signals provide a better view to the considered system aspects, while reducing the amount of data. It is little acknowledged that appropriately parameterized signals may be subjected to ICA, yielding independent components (ICs) displaying more clearly the investigated properties of the sources. In this paper, we propose ICA of parameterized signals, and demonstrate the concept with ICA of ST and R parameterizations of electrocardiogram (ECG) signals from ECG exercise test measurements from two coronary artery disease (CAD) patients. PMID:17945912

  5. A Computer Language for ECG Contour Analysis

    PubMed Central

    McConnochie, John W.

    1982-01-01

    The purpose of this paper is to demonstrate contructively that criteria for ECG contour analysis can be interpreted directly by a computer. Thereby, the programming task is greatly reduced. Direct interpretation is achieved by the creation of a computer language that is well-suited for the expression of such criteria. Further development of the language is planned.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  7. Preprocessing and analysis of the ECG signals

    NASA Astrophysics Data System (ADS)

    Zhu, Jianmin; Zhang, Xiaolan; Wang, Zhongyu; Wang, Xiaoling

    2008-10-01

    According to the request of automatic analysis and depressing high frequency interference of the ECG signals, this paper applies low-pass filter to preprocess ECG signals, and proposes a QRS complex detection method based on wavelet transform, which takes advantage of Marr wavelet to decompose and filter the ECG signals with Mallat algorithm, using the relationship between wavelet transform and signal singularity to detect QRS complex with amplitude threshold method in scale 3, and to detect P wave and R wave in scale 4. Meanwhile, compositive detection method is used for re-detection, thus to improving the detection accuracy ratio. At last, records from ECG database of MIT/BIH which is widely accepted in the world are used to test the algorithm. And the result shows that correction detecting ratio under this algorithm has been more than 99.8 percent. The detection method in this paper is simple and running fast, and is easy to be realized in the real-time detecting system using for clinical diagnosis.

  8. Multiprocessor system for Holter tape analysis (ECG)

    SciTech Connect

    Feldman, C.L.; Hubelbank, M.; Valvo, V.; Lane, B.

    1983-01-01

    Although techniques for recording and analyzing longterm ambulatory ECGS have been in existence for more than 20 years, the clinical usefulness and frequency of application of the technique continue to grow at an extraordinary rate. To meet the need for faster, more efficient processing of Holter tapes and the growing requirement that the analysis of the tape be quantitatively accurate, a new Holter analysis system has been developed. This system is built around two LSI11 microprocessors and a special purpose byte processor which incorporates an AMD 2903 bit slice chip. It includes 30 MB of mass storage and an impact printer with alphanumeric and graphic capabilities. In a test which included 55 separate readings of 34 12- or 24-hour tapes, correlations with hand counts of vpbs was greater than .99. The system processes either cassette or reel-to-reel tapes at 120* with simultaneous print/process capabilities, has a variety of user interactive displays to assure continuous operator validation, is remarkably nonfatiguing to operate, and automatically produces reports with tables, graphs, and sample ECG strips. 8 references.

  9. ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Kaur, Inderbir; Rajni, Rajni; Marwaha, Anupma

    2016-06-01

    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.

  10. 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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  12. ECG Feature Extraction using Time Frequency Analysis

    NASA Astrophysics Data System (ADS)

    Nair, Mahesh A.

    The proposed algorithm is a novel method for the feature extraction of ECG beats based on Wavelet Transforms. A combination of two well-accepted methods, Pan Tompkins algorithm and Wavelet decomposition, this system is implemented with the help of MATLAB. The focus of this work is to implement the algorithm, which can extract the features of ECG beats with high accuracy. The performance of this system is evaluated in a pilot study using the MIT-BIH Arrhythmia database.

  13. ECG signals denoising using wavelet transform and independent component analysis

    NASA Astrophysics Data System (ADS)

    Liu, Manjin; Hui, Mei; Liu, Ming; Dong, Liquan; Zhao, Zhu; Zhao, Yuejin

    2015-08-01

    A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.

  14. 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

  15. The use of the SPSA method in ECG analysis.

    PubMed

    Gerencsér, László; Kozmann, György; Vágó, Zsuzsanna; Haraszti, Kristóf

    2002-10-01

    The classification, monitoring, and compression of electrocardiogram (ECG) signals recorded of a single patient over a relatively long period of time is considered. The particular application we have in mind is high-resolution ECG analysis, such as late potential analysis, morphology changes in QRS during arrythmias, T-wave alternants, or the study of drug effects on ventricular activation. We propose to apply a modification of a classical method of cluster analysis or vector quantization. The novelty of our approach is that we use a new distortion measure to quantify the distance of two ECG cycles, and the class-distortion measure is defined using a min-max criterion. The new class-distortion-measure is much more sensitive to outliers than the usual distortion measures using average-distance. The price of this practical advantage is that computational complexity is significantly increased. The resulting nonsmooth optimization problem is solved by an adapted version of the simultaneous perturbation stochastic approximation (SPSA) method of. The main idea is to generate a smooth approximation by a randomization procedure. The viability of the method is demonstrated on both simulated and real data. An experimental comparison with the widely used correlation method is given on real data. PMID:12374333

  16. 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

  17. Analysis of ECG from pole-zero models.

    PubMed

    Murthy, I S; Prasad, G S

    1992-07-01

    A complete solution to the fundamental problem of ECG analysis, viz., delineation of the signal into its component waves, is proposed from a system theoretic point of view. The discrete cosine transform of a bell shaped biphasic function is approximated mathematically by a system function with two poles and two zeros, i.e., of order (2, 2). Using this concept as the basis, a pole-zero model of suitable order is derived from the discrete cosine transform (DCT) of the given signal using Steiglitz-McBride method. This model is expanded into a unique set of partial fractions each of order (2, 2), and a biphasic function is recovered from each one of these fractions in the inverse process. Each of the P and T waves usually requires only one biphasic function, while the QRS complex needs two or at most three such fractions. A one-to-one relationship between the pole pattern in the z-plane and component wave pattern in the time signal is established. Results of analysis of continuous strips of ECG show that the delineated component waves are in excellent agreement with the original waves both qualitatively and quantitatively. The method is robust for the analysis of signals with artifacts of various kinds, independent of the sampling rate used, and is free from ad hoc back and forth search procedures. PMID:1516941

  18. 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

  19. Mouse ECG findings in aging, with conduction system affecting drugs and in cardiac pathologies: Development and validation of ECG analysis algorithm in mice.

    PubMed

    Merentie, Mari; Lipponen, Jukka A; Hedman, Marja; Hedman, Antti; Hartikainen, Juha; Huusko, Jenni; Lottonen-Raikaslehto, Line; Parviainen, Viktor; Laidinen, Svetlana; Karjalainen, Pasi A; Ylä-Herttuala, Seppo

    2015-12-01

    Mouse models are extremely important in studying cardiac pathologies and related electrophysiology, but very few mouse ECG analysis programs are readily available. Therefore, a mouse ECG analysis algorithm was developed and validated. Surface ECG (lead II) was acquired during transthoracic echocardiography from C57Bl/6J mice under isoflurane anesthesia. The effect of aging was studied in young (2-3 months), middle-aged (14 months) and old (20-24 months) mice. The ECG changes associated with pharmacological interventions and common cardiac pathologies, that is, acute myocardial infarction (AMI) and progressive left ventricular hypertrophy (LVH), were studied. The ECG raw data were analyzed with an in-house ECG analysis program, modified specially for mouse ECG. Aging led to increases in P-wave duration, atrioventricular conduction time (PQ interval), and intraventricular conduction time (QRS complex width), while the R-wave amplitude decreased. In addition, the prevalence of arrhythmias increased during aging. Anticholinergic atropine shortened PQ time, and beta blocker metoprolol and calcium-channel blocker verapamil increased PQ interval and decreased heart rate. The ECG changes after AMI included early JT elevation, development of Q waves, decreased R-wave amplitude, and later changes in JT/T segment. In progressive LVH model, QRS complex width was increased at 2 and especially 4 weeks timepoint, and also repolarization abnormalities were seen. Aging, drugs, AMI, and LVH led to similar ECG changes in mice as seen in humans, which could be reliably detected with this new algorithm. The developed method will be very useful for studies on cardiovascular diseases in mice. PMID:26660552

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

    PubMed Central

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

    2016-01-01

    Background: 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. Materials and Methods: 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. Results: 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. Conclusion: 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. PMID:27583239

  1. The use of the Hilbert transform in ECG signal analysis.

    PubMed

    Benitez, D; Gaydecki, P A; Zaidi, A; Fitzpatrick, A P

    2001-09-01

    This paper presents a new robust algorithm for QRS detection using the first differential of the ECG signal and its Hilbert transformed data to locate the R wave peaks in the ECG waveform. Using this method, the differentiation of R waves from large, peaked T and P waves is achieved with a high degree of accuracy. In addition, problems with baseline drift, motion artifacts and muscular noise are minimised. The performance of the algorithm was tested using standard ECG waveform records from the MIT-BITH Arrhythmia database. An average detection rate of 99.87%, a sensitivity (Se) of 99.94% and a positive prediction (+P) of 99.93% have been achieved against study records from the MIT-BITH Arrhythmia database. A detection error rate of less than 0.8% was achieved in every study case. The reliability of the proposed detector compares very favorably with published results for other QRS detectors. PMID:11535204

  2. Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

    PubMed Central

    Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

    2015-01-01

    Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

  3. A robust approach for ECG-based analysis of cardiopulmonary coupling.

    PubMed

    Zheng, Jiewen; Wang, Weidong; Zhang, Zhengbo; Wu, Dalei; Wu, Hao; Peng, Chung-Kang

    2016-07-01

    Deriving respiratory signal from a surface electrocardiogram (ECG) measurement has advantage of simultaneously monitoring of cardiac and respiratory activities. ECG-based cardiopulmonary coupling (CPC) analysis estimated by heart period variability and ECG-derived respiration (EDR) shows promising applications in medical field. The aim of this paper is to provide a quantitative analysis of the ECG-based CPC, and further improve its performance. Two conventional strategies were tested to obtain EDR signal: R-S wave amplitude and area of the QRS complex. An adaptive filter was utilized to extract the common component of inter-beat interval (RRI) and EDR, generating enhanced versions of EDR signal. CPC is assessed through probing the nonlinear phase interactions between RRI series and respiratory signal. Respiratory oscillations presented in both RRI series and respiratory signals were extracted by ensemble empirical mode decomposition for coupling analysis via phase synchronization index. The results demonstrated that CPC estimated from conventional EDR series exhibits constant and proportional biases, while that estimated from enhanced EDR series is more reliable. Adaptive filtering can improve the accuracy of the ECG-based CPC estimation significantly and achieve robust CPC analysis. The improved ECG-based CPC estimation may provide additional prognostic information for both sleep medicine and autonomic function analysis. PMID:27118307

  4. A Hierarchical Method for Removal of Baseline Drift from Biomedical Signals: Application in ECG Analysis

    PubMed Central

    Luo, Yurong; Hargraves, Rosalyn H.; Bai, Ou; Qi, Xuguang; Ward, Kevin R.; Pfaffenberger, Michael Paul

    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. PMID:23766720

  5. Efficient ECG signal analysis using wavelet technique for arrhythmia detection: an ANFIS approach

    NASA Astrophysics Data System (ADS)

    Khandait, P. D.; Bawane, N. G.; Limaye, S. S.

    2010-02-01

    This paper deals with improved ECG signal analysis using Wavelet Transform Techniques and employing subsequent modified feature extraction for Arrhythmia detection based on Neuro-Fuzzy technique. This improvement is based on suitable choice of features in evaluating and predicting life threatening Ventricular Arrhythmia . Analyzing electrocardiographic signals (ECG) includes not only inspection of P, QRS and T waves, but also the causal relations they have and the temporal sequences they build within long observation periods. Wavelet-transform is used for effective feature extraction and Adaptive Neuro-Fuzzy Inference System (ANFIS) is considered for the classifier model. In a first step, QRS complexes are detected. Then, each QRS is delineated by detecting and identifying the peaks of the individual waves, as well as the complex onset and end. Finally, the determination of P and T wave peaks, onsets and ends is performed. We evaluated the algorithm on several manually annotated databases, such as MIT-BIH Arrhythmia and CSE databases, developed for validation purposes. Features based on the ECG waveform shape and heart beat intervals are used as inputs to the classifiers. The performance of the ANFIS model is evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the ECG signals. Cross validation is used to measure the classifier performance. A testing classification accuracy of 95.13% is achieved which is a significant improvement.

  6. 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

  7. Rescaled range analysis of resting respiration

    NASA Astrophysics Data System (ADS)

    Hoop, Bernard; Kazemi, Homayoun; Liebovitch, Larry

    1993-01-01

    Fluctuations in resting depth of breathing (tidal volume) at constant breathing rate in the anesthetized adult rat exhibit fractal properties when analyzed by a rescaled range method characterized by a mean (±SD) exponent H=0.83±0.02 and 0.92±0.03 with and without sighs, respectively, for up to 400 breaths. Values of H determined from shuffled tidal volumes and simulated tidal volumes taken randomly from a Gaussian distribution of mean and variance approximating that of the actual data are consistent with the expected value of H=0.5 for an independent random process with finite variances. An empirical description is proposed to predict the change in H with length of time record.

  8. 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.

  9. 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.

  10. 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. PMID:24808843

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

    PubMed Central

    Muller, Angela M.; Meyer, Martin

    2014-01-01

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

  12. Scale invariance analysis of the premature ECG signals

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Cheng, Keqiang

    2012-06-01

    The multifractal detrended fluctuation analysis and detrending moving average algorithm were introduced in detail and applied to the study of the multifractal characteristics of the normal signals, the atrial premature beat (APB) signals and the premature ventricular contraction (PVC) signals. By analyzing the generalized Hurst exponents, Renyi exponents and multifractal spectrum and comparing the relation of h∼h(q) for original signals and their shuffled time series, the result indicated that the three signals have multifractality and present long-range correlation in a certain range. According to the mean value of Δα, we found that the strength of the multifractality is varying. The PVC signals is the strongest, and the Normal signals is the weakest. It is useful for clinical practice of medicine to distinguish APB signals with PVC signals.

  13. Recording of ECG signals on a portable MiniDisc recorder for time and frequency domain heart rate variability analysis.

    PubMed

    Norman, S E; Eager, R A; Waran, N K; Jeffery, L; Schroter, R C; Marlin, D J

    2005-01-17

    Analysis of heart rate variability (HRV) is a non-invasive technique useful for investigating autonomic function in both humans and animals. It has been used for research into both behaviour and physiology. Commercial systems for human HRV analysis are expensive and may not have sufficient flexibility for appropriate analysis in animals. Some heart rate monitors have the facility to provide inter-beat interval (IBI), but verification following collection is not possible as only IBIs are recorded, and not the raw electrocardiogram (ECG) signal. Computer-based data acquisition and analysis systems such as Po-Ne-Mah and Biopac offer greater flexibility and control but have limited portability. Many laboratories and veterinary surgeons have access to ECG machines but do not have equipment to record ECG signals for further analysis. The aim of the present study was to determine whether suitable HRV data could be obtained from ECG signals recorded onto a MiniDisc (MD) and subsequently digitised and analysed using a commercial data acquisition and analysis package. ECG signals were obtained from six Thoroughbred horses by telemetry. A split BNC connecter was used to allow simultaneous digitisation of analogue output from the ECG receiver unit by a computerised data acquisition system (Po-Ne-Mah) and MiniDisc player (MZ-N710, Sony). Following recording, data were played back from the MiniDisc into the same input channel of the data acquisition system as previously used to record the direct ECG. All data were digitised at a sampling rate of 500 Hz. IBI data were analysed in both time and frequency domains and comparisons between direct recorded and MiniDisc data were made using Bland-Altman analysis. Despite some changes in ECG morphology due to loss of low frequency content (primarily below 5 Hz) following MiniDisc recording, there was minimal difference in IBI or time or frequency domain analysis between the two recording methods. The MiniDisc offers a cost

  14. Data processing of exercise ECG's

    NASA Astrophysics Data System (ADS)

    Pahlm, Olle; Sornmo, Leif

    1987-02-01

    Computer processing of exercise ECG's is a well-established technique which aims at improving the signal-to-noise ratio of the ECG for more accurate measurements. In this way the interpretation of the ECG response to exercise is facilitated. This brief review considers the problems pertinent to signal processing in exercise ECG analysis and provides an overview of algorithms employed by research groups as well as manufacturers. The clinical utility of computer measurements and criteria for ECG changes in patients with suspected coronary artery disease is treated.

  15. 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. PMID:26558395

  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. PMID:8835841

  17. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    PubMed

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies. PMID:27075850

  18. [1st experience on the use of an automatic ECG analysis in a large industrial plant in Erfurt].

    PubMed

    Giegler, I; Grossmann, K; Knorre, M; Reissmann, H C; Rübesam, M

    1977-10-01

    By means of a device system consisting of constituents of the SW-production and own developmental works in the factory Kombinat VEB Umformtechnik (combinate nationally owned enterprise transformation technology) for the first time ECG serial examinations were performed with the help of the mechanical ECG-analysis. The corrected orthogonal system of Frank with 3 leads served as deviation system. The ECG-registration was independently performed by function nurses. 1,720 male and female workers of this factory at the age of 21 to 59 years served as test persons. The ECG-registration lasted 20 sec., the whole time of examination including the changing of clothes and the way from the working place to the examination room did not last more than 4 to 8 min. As diagnosis programme served that one developed by Pipberger. The mechanical analysis resulted in 74.4% in a normal course of the electrocardiographic current curve. Among the pathological or abnormal ECGs (25.6%) prevailed the vegetative-functional heart diseases with 92%. Then followed the chronic ischaemic heart diseases with 7.9% and the hypertension with 5.1%. Diseases of the heart and the blood circulation established for the first time referred to 8.9%. Of them 5% needed control and 3.9% needed therapy. PMID:595717

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

    PubMed Central

    2013-01-01

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

  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. 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.

  2. 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. PMID:21095640

  3. A Randomized Trial of Intrapartum Fetal ECG ST-Segment Analysis

    PubMed Central

    Belfort, Michael A.; Saade, George R.; Thom, Elizabeth; Blackwell, Sean C.; Reddy, Uma M.; Thorp, John M.; Tita, Alan T.N.; Miller, Russell S.; Peaceman, Alan M.; McKenna, David S.; Chien, Edward K.S.; Rouse, Dwight J.; Gibbs, Ronald S.; El-Sayed, Yasser Y.; Sorokin, Yoram; Caritis, Steve N.; VanDorsten, J. Peter

    2015-01-01

    BACKGROUND It is unclear whether using fetal electrocardiographic (ECG) ST-segment analysis as an adjunct to conventional intrapartum electronic fetal heart-rate monitoring modifies intrapartum and neonatal outcomes. METHODS We performed a multicenter trial in which women with a singleton fetus who were attempting vaginal delivery at more than 36 weeks of gestation and who had cervical dilation of 2 to 7 cm were randomly assigned to “open” or “masked” monitoring with fetal ST-segment analysis. The masked system functioned as a normal fetal heart-rate monitor. The open system displayed additional information for use when uncertain fetal heart-rate patterns were detected. The primary outcome was a composite of intrapartum fetal death, neonatal death, an Apgar score of 3 or less at 5 minutes, neonatal seizure, an umbilical-artery blood pH of 7.05 or less with a base deficit of 12 mmol per liter or more, intubation for ventilation at delivery, or neonatal encephalopathy. RESULTS A total of 11,108 patients underwent randomization; 5532 were assigned to the open group, and 5576 to the masked group. The primary outcome occurred in 52 fetuses or neonates of women in the open group (0.9%) and 40 fetuses or neonates of women in the masked group (0.7%) (relative risk, 1.31; 95% confidence interval, 0.87 to 1.98; P = 0.20). Among the individual components of the primary outcome, only the frequency of a 5-minute Apgar score of 3 or less differed significantly between neonates of women in the open group and those in the masked group (0.3% vs. 0.1%, P = 0.02). There were no significant between-group differences in the rate of cesarean delivery (16.9% and 16.2%, respectively; P = 0.30) or any operative delivery (22.8% and 22.0%, respectively; P = 0.31). Adverse events were rare and occurred with similar frequency in the two groups. CONCLUSIONS Fetal ECG ST-segment analysis used as an adjunct to conventional intrapartum electronic fetal heart-rate monitoring did not improve

  4. 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.

  5. 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. PMID:10688326

  6. 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,…

  7. A technique to evaluate the performance of computerized ECG analysis systems.

    PubMed

    Teppner, U; Lobodzinski, S; Neubert, D; Laks, M M

    1987-10-01

    No objective method to test computerized ECG systems has been available. Until now, tests have been conducted separately for instrumentation and algorithms. Hence, to facilitate objective verification and testing of modern computerized ECG equipment, a dedicated high resolution, low noise instrument (an "electronic test patient") has been developed. The purpose of this communication is to describe this new instrument and its electrocardiographic database. The instrument is designed not to cause any disturbances to the original ECG signals in the frequency range from 0 to 1 kHz. The input channels accommodating standard 12-lead and 3-lead Frank systems are sampled simultaneously at 10 kHz each with 90 dB dynamic range. The overall RMS noise figure of the instrument is 1 microV. The integral part of the instrument is a high resolution, high bandwidth minidatabase consisting of selected A-type and B-type verified electrocardiograms such as infarctions, ventricular hypertrophies, atrial fibrillations, etc. The minidatabase was collected with the aid of a computerized ECG system, which has a program for searching for specific electrocardiographic diagnosis. Each database record consists of simultaneous electrocardiographic signals of all standard leads and Frank leads, and a validated diagnostic report. A system under test is typically connected via its patient cable to the analog output of the instrument. The testing is performed with reference to the validated ECG from the database. In that way, our minidatabase is compatible with any electrocardiographic system. The only similar database assembled for testing purposes is that of the CSE group.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:3694104

  8. 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.

  9. 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.

  10. 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

  11. Development of a new signal processing algorithm based on independent component analysis for single channel ECG data.

    PubMed

    Lee, J; Lee, K J; Yoo, S K

    2004-01-01

    In this paper, we proposed a new signal processing algorithm based on independent component analysis (ICA) for single channel ECG data. For the application ICA to single channel data, mixed (multi-channel) signals are constructed by adding some delay to original data. By ICA, signal enhancement is acquired. For validation of usefulness of this signal, QRS complex detection was accompanied. In QRS detection process, Hilbert transform and wavelet transform were used and good QRS detection efficacy was obtained. Furthermore, a signal, which could not be filtered properly using existing algorithm, also had better signal enhancement. In future, we need to study on the algorithm optimization and simplification. PMID:17271650

  12. Long-term ECG in ambulatory clinical practice. Analysis and 2-year follow-up of 100 patients studied with a portable ECG tape recorder.

    PubMed

    Johansson, B W

    1977-01-01

    A portable tape recorder for long-term ECG monitoring is described. Its light weight (500 g) and small size (138 X 115 X 39 mm) make its usage in routine clinical practice a practical proposition. The most important application has been in the differential diagnosis of Adams--Strokes syndrome. The results from the first 100 patients with a 2-yr follow-up are presented. The importance of GCG recording during the patients' relevant subjective symptoms is stressed. The mean duration of recording was 2.8 days. In the 28 patients with histories which fitted the symptoms of Adams--Stokes syndrome this diagnosis was confirmed by an arrhythmia recorded simultaneously with the symptoms. In 36 other patients with a similar history the diagnosis was excluded becase of a normal ECG during subjective symptoms. Of the 28 patients with Adams--Stokes sydrome, bradyarrhthmia was the causal factor in 20 patients and these had a pacemaker implanted, whereas the remaining 8 patients had a tachyarrhythmia, which wa treated with antiarrhythmic drugs. The 2-yrs follow-up revealed an improvement and a disappearance of the Adams--Stokes attack in all the patients with an implanted pacemaker. In several of the 36 patients in whom Adams--Stokes syndrome could not be confirmed the syncopal attacks disappeared spontaneously. A large number of arrhythmias, including ventricular and supraventricular tachycardia, 2nd degree AV block and sinus bradycardia were observed during symptom-free intervals in these 36 patients. The introduction of long-term ECG recording routinely in patients with dizziness and syncope of unknown reason has resulted in an increase of the number of patients with a confirmed diagnosis of the Adams--Stokes syndrome, and it has contributed to an increase in the incidence of pacemaker implantation in Malmö from 130 per million inhabitants in 1971 to 220 in 1973, and 1974, respectively. PMID:837958

  13. 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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Schulz-Bruenken, Barbara; Pelikan, Erich

    1996-04-01

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

  16. A Sequential Procedure for Individual Identity Verification Using ECG

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Israel, Steven A.

    2009-12-01

    The electrocardiogram (ECG) is an emerging novel biometric for human identification. One challenge for the practical use of ECG as a biometric is minimizing the time needed to acquire user data. We present a methodology for identity verification that quantifies the minimum number of heartbeats required to authenticate an enrolled individual. The approach rests on the statistical theory of sequential procedures. The procedure extracts fiducial features from each heartbeat to compute the test statistics. Sampling of heartbeats continues until a decision is reached—either verifying that the acquired ECG matches the stored credentials of the individual or that the ECG clearly does not match the stored credentials for the declared identity. We present the mathematical formulation of the sequential procedure and illustrate the performance with measured data. The initial test was performed on a limited population, twenty-nine individuals. The sequential procedure arrives at the correct decision in fifteen heartbeats or fewer in all but one instance and in most cases the decision is reached with half as many heartbeats. Analysis of an additional 75 subjects measured under different conditions indicates similar performance. Issues of generalizing beyond the laboratory setting are discussed and several avenues for future investigation are identified.

  17. 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. PMID:9034668

  18. Comprehensive multilevel in vivo and in vitro analysis of heart rate fluctuations in mice by ECG telemetry and electrophysiology.

    PubMed

    Fenske, Stefanie; Pröbstle, Rasmus; Auer, Franziska; Hassan, Sami; Marks, Vanessa; Pauza, Danius H; Biel, Martin; Wahl-Schott, Christian

    2016-01-01

    The normal heartbeat slightly fluctuates around a mean value; this phenomenon is called physiological heart rate variability (HRV). It is well known that altered HRV is a risk factor for sudden cardiac death. The availability of genetic mouse models makes it possible to experimentally dissect the mechanism of pathological changes in HRV and its relation to sudden cardiac death. Here we provide a protocol that allows for a comprehensive multilevel analysis of heart rate (HR) fluctuations. The protocol comprises a set of techniques that include in vivo telemetry and in vitro electrophysiology of intact sinoatrial network preparations or isolated single sinoatrial node (SAN) cells. In vitro preparations can be completed within a few hours, with data acquisition within 1 d. In vivo telemetric ECG requires 1 h for surgery and several weeks for data acquisition and analysis. This protocol is of interest to researchers investigating cardiovascular physiology and the pathophysiology of sudden cardiac death. PMID:26658468

  19. 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

  20. Resting Metabolic Rate Analysis in Chronic Hemiparesis Patients

    PubMed Central

    de Sant’Anna, Mauricio; Eboli, Leonardo Coelho; Silva, Julio Guilherme; dos Santos, Alan Gomes; Lourenço, Michele; Moreno, Adalgiza Mafra; de Freitas, Gabriel Rodriguez; Orsini, Marco

    2014-01-01

    The objective of the present study was to compare resting metabolic rate (RMR) of chronic hemiparetic patients to sedentary health individuals. The sample was composed of 16 individuals, that were divided into two groups. The first group had eight hemiparetic patients and the second group was formed by eight sedentary individuals. To access and analyze the gases information a VO2000 analyzer was used. The following variables were measured: VO2, VCO2, VE, QR, grams of fat (GrFAT), grams of carbohydrate. RMR was calculated based on Weir’s equation. There was a significant shift on ventilation variables: VE (P<0.0003), VO2 (P<0.0004) and VCO2 (P<0.0001) on hemiparetic individuals group when compared to control group. When the energetic substrate used behavior is observed, it shows that fat consumption (represented by GrFAT) is higher on the hemiparetic group when compared to controls (P<0.0001) significant differences were observed for RMR between groups (P<0.0001). RMR showed a correlation to VO2 on the hemiparetic group (r=0.9277, P=0.0022). To sum up, it was observed through the results that individuals with hemiparesis as a sequel of stroke showed a RMR larger than normal individuals. PMID:25568736

  1. Resting metabolic rate analysis in chronic hemiparesis patients.

    PubMed

    de Sant'Anna, Mauricio; Eboli, Leonardo Coelho; Silva, Julio Guilherme; Dos Santos, Alan Gomes; Lourenço, Michele; Moreno, Adalgiza Mafra; de Freitas, Gabriel Rodriguez; Orsini, Marco

    2014-10-23

    The objective of the present study was to compare resting metabolic rate (RMR) of chronic hemiparetic patients to sedentary health individuals. The sample was composed of 16 individuals, that were divided into two groups. The first group had eight hemiparetic patients and the second group was formed by eight sedentary individuals. To access and analyze the gases information a VO2000 analyzer was used. The following variables were measured: VO2, VCO2, VE, QR, grams of fat (GrFAT), grams of carbohydrate. RMR was calculated based on Weir's equation. There was a significant shift on ventilation variables: VE (P<0.0003), VO2 (P<0.0004) and VCO2 (P<0.0001) on hemiparetic individuals group when compared to control group. When the energetic substrate used behavior is observed, it shows that fat consumption (represented by GrFAT) is higher on the hemiparetic group when compared to controls (P<0.0001) significant differences were observed for RMR between groups (P<0.0001). RMR showed a correlation to VO2 on the hemiparetic group (r=0.9277, P=0.0022). To sum up, it was observed through the results that individuals with hemiparesis as a sequel of stroke showed a RMR larger than normal individuals. PMID:25568736

  2. The importance of bioimpedance (BIA) analysis and Cardio Tens (24-h ABPM and ECG) monitoring in the dialysis programme.

    PubMed

    Löcsey, L; Szlanka, B; Ménes, I; Kövér, A; Vitai, E; Malkócs, Z; Keresztes, P; Paragh, G

    1999-01-01

    The authors performed bioimpedance analysis and Cardio Tens (24-h ABPM and ECG) monitoring in 66 patients (28 males, 38 females) treated in the chronic haemodialysis programme. They investigated the correlations between the body weights before, during and after dialysis, the changes of the water compartments and fat body weight, and the recorded values of blood pressure and ECG alterations. On the basis of the measurements by this non-invasive method it is concluded that, as a result of dialysis and ultrafiltration, the total body weight and total body water are decreasing in a greater extent in men than in women. By gradually decreasing the body weight, the optimal dry weight could be attained, which resulted in the reduction of blood pressure or even normotension. In the course of dialysis the values of bioimpedance and bioreactance increase. The intradialytic hypotensive indispositions were accompanied by a significant reduction of bioreactance (n = 16). The BMI, total body weight and total body water hyperlipidaemic, hypalbuminic patients with treatment-resistant hypertension are considerably larger than those of the patients with normal blood pressure (p<0.01). During Cardio Tens monitoring 53% of the patients proved to be dippers, 47% of whom had ST depression, while in 73% of the non-dippers ischaemic alterations were encountered together with high hyperbaric impact values. The total body weights and total water compartments of patients returning to dialysis with an excess body weight of more than 3.5 kg were significantly larger than of patients who were cooperative and had no oedemas. In the last hour of dialysis and during the following few hours, arrhythmias and ST depressions of the cardiovascularly instable patients appeared more frequently. The total water compartments of these patients are significantly larger than normotensive, normolipaemic patients with appropriate serum albumin concentrations. The importance of the BIA and Cardio Tens monitoring

  3. Application of statistical energy analysis to the design of crew rest compartments

    NASA Astrophysics Data System (ADS)

    Gmerek, Mark M.

    2002-11-01

    Longer flight times for modern commercial aircraft have led to the need for crew rest compartments. Noise levels in the crew rest compartments must be conducive to proper rest and recuperation. Statistical Energy Analysis (SEA) has been used to develop a 777 crew rest compartment design that achieves appropriate noise levels at acceptable weight and cost. In this paper the design of a 777 overhead crew rest compartment is outlined using SEA design tools and methods. Noise data were gathered in flight to distinguish airplane source components and develop model inputs. Crew rest panels, the airplane fuselage, and acoustic volumes were modeled as SEA subsystems by taking into account geometry, material properties, modulus, and damping. A model was built, excited with inputs, and analyzed to determine energy flow paths and acoustic pressure at receiver locations. Prospective add-on treatments were then assessed to engineer an effective noise control package. The model development was supplemented by laboratory sound transmission loss testing of individual components. The good agreement between the laboratory tests and individual SEA models of the components increased confidence in the approach. Once the crew rest was installed on the airplane, the measured in-flight noise levels closely matched the SEA estimates.

  4. 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

  5. Reliability analysis of the resting state can sensitively and specifically identify the presence of Parkinson disease.

    PubMed

    Skidmore, F M; Yang, M; Baxter, L; von Deneen, K M; Collingwood, J; He, G; White, K; Korenkevych, D; Savenkov, A; Heilman, K M; Gold, M; Liu, Y

    2013-07-15

    Parkinson disease (PD) is characterized by a number of motor and behavioral abnormalities that could be considered deficits of a "no task" or "resting" state, including resting motor findings and defects in emerging from a resting state (e.g., resting tremor, elevated resting tone, abulia, akinesia, apathy). PET imaging, and recently, the MRI technique of continuous arterial spin labeling (CASL) have shown evidence of changes in metabolic patterns in individuals with PD. The purpose of this study was to learn if the presence of PD could be "predicted" based on resting fluctuations of the BOLD signal. Participants were 15 healthy controls, 14 subjects with PD, and 1 subject who presented as a control but later developed PD. The amplitude of the low frequency fluctuation (ALFF) was used as an index of brain activity level in the resting state. Participants with PD using this index showed a reliable decrease in activity in a number of regions, including the supplementary motor cortex, the mesial prefrontal cortex, the right middle frontal gyrus, and the left cerebellum (lobule VII/VIII) as well as increased activity in the right cerebellum (lobule IV/V). Using a cross validation approach we term "Reliability Mapping of Regional Differences" (RMRD) to analyze our sample, we were able to reliably distinguish participants with PD from controls with 92% sensitivity and 87% specificity. Our "pre-diagnostic" subject segregated in our analysis with the PD group. These results suggest that resting fMRI should be considered for development as a biomarker and analytical tool for evaluation of PD. PMID:21924367

  6. 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.

  7. [Functional connectivity analysis of the brain network using resting-state FMRI].

    PubMed

    Hayashi, Toshihiro

    2011-12-01

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. PMID:22147450

  8. 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.

  9. 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

  10. 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%. PMID:26568954

  11. Troubleshooting the ECG.

    PubMed

    Hatlestad, Dan

    2003-09-01

    Improper ECG monitoring is dangerous to patient care. Artifact in ECG monitoring can be annoying, costly and produce delays in proper care. Understanding the technical sources of artifact and care in the application of monitoring electrodes can significantly reduce or even eliminate the problem. Critical to the success of ECG monitoring are the technical aspects of proper equipment selection, preventive maintenance, and timely and rapid application to the patient, all to deliver the highest quality patient care. Just as critical is the prehospital clinician's understanding of equipment capabilities and limitations. Take time to read and understand the operator's manual for the ECG monitor/defibrillator in use in your ambulance. The ECG offers invaluable diagnostic information to EMS clinicians. With recent technological advances, today's ECG monitors provide even greater ease and versatility, which results in enhanced patient monitoring. Many factors can affect the quality of the ECG trace and therefore must be controlled in order to gain the most accurate and meaningful reading. Electrode placement and selection, as well as site preparation, are key considerations when applying and monitoring a patient's ECG. PMID:14503159

  12. 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. PMID:23021814

  13. Scientific and clinical evidence for the use of fetal ECG ST segment analysis (STAN).

    PubMed

    Steer, Philip J; Hvidman, Lone Egly

    2014-06-01

    Fetal electrocardiogram waveform analysis has been studied for many decades, but it is only in the last 20 years that computerization has made real-time analysis practical for clinical use. Changes in the ST segment have been shown to correlate with fetal condition, in particular with acid-base status. Meta-analysis of randomized trials (five in total, four using the computerized system) has shown that use of computerized ST segment analysis (STAN) reduces the need for fetal blood sampling by about 40%. However, although there are trends to lower rates of low Apgar scores and acidosis, the differences are not statistically significant. There is no effect on cesarean section rates. Disadvantages include the need for amniotic membranes to be ruptured so that a fetal scalp electrode can be applied, and the need for STAN values to be interpreted in conjunction with detailed fetal heart rate pattern analysis. PMID:24597897

  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. 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

  16. 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.

  17. G-language genome analysis environment with REST and SOAP web service interfaces.

    PubMed

    Arakawa, Kazuharu; Kido, Nobuhiro; Oshita, Kazuki; Tomita, Masaru

    2010-07-01

    G-language genome analysis environment (G-language GAE) contains more than 100 programs that focus on the analysis of bacterial genomes, including programs for the identification of binding sites by means of information theory, analysis of nucleotide composition bias and the distribution of particular oligonucleotides, calculation of codon bias and prediction of expression levels, and visualization of genomic information. We have provided a collection of web services for these programs by utilizing REST and SOAP technologies. The REST interface, available at http://rest.g-language.org/, provides access to all 145 functions of the G-language GAE. These functions can be accessed from other online resources. All analysis functions are represented by unique universal resource identifiers. Users can access the functions directly via the corresponding universe resource locators (URLs), and biological web sites can readily embed the functions by simply linking to these URLs. The SOAP services, available at http://www.g-language.org/wiki/soap/, provide language-independent programmatic access to 77 analysis programs. The SOAP service Web Services Definition Language file can be readily loaded into graphical clients such as the Taverna workbench to integrate the programs with other services and workflows. PMID:20439313

  18. ECG variable cine: computer program for presentation of temporal changes in ECG variables over different number of ECG leads.

    PubMed

    Viik, J; Vänttinen, H; Malmivuo, J

    2000-10-01

    The analysis of exercise electrocardiogram (ECG) is based on the alteration of the measured variables in the detection of coronary artery disease (CAD). In its existing form the analysis of the exercise ECG is laborious and requires much time. The temporal analysis of the ECG variable and the comparison between different phases of the exercise test is difficult and time consuming, especially the simultaneous examination of the variables over several leads. In this article we present a computer program, ECG Variable Cine, for the visualization of the temporal changes of values of exercise ECG variables over the selected ECG lead system. The program includes the stationary 3-D presentation for the variables' alteration simultaneously in all selected leads over the time of exercise test. In addition, the program determines two parameters; the average value of the variable over the selected leads at every sample moment, and the chronotropic index, a parameter that indicates heart rate response to exercise. According to the results the average value of ST-segment deviation at the end of the exercise over the leads and chronotropic index are clinically more competent than the maximum value of ST-segment depression in the detection of CAD. PMID:10960747

  19. Cardiac effects of sertindole and quetiapine: analysis of ECGs from a randomized double-blind study in patients with schizophrenia.

    PubMed

    Nielsen, Jimmi; Matz, Jørgen; Mittoux, Aurelia; Polcwiartek, Christoffer; Struijk, Johannes J; Toft, Egon; Kanters, Jørgen K; Graff, Claus

    2015-03-01

    The QT interval is the most widely used surrogate marker for predicting TdP; however, several alternative surrogate markers, such as Tpeak-Tend (TpTe) and a quantitative T-wave morphology combination score (MCS) have emerged. This study investigated the cardiac effects of sertindole and quetiapine using the QTc interval and newer surrogate markers. Data were derived from a 12 week randomized double-blind study comparing flexible dosage of sertindole 12-20mg and quetiapine 400-600mg in patients with schizophrenia. ECGs were recorded digitally at baseline and after 3, 6 and 12 weeks. Between group effects were compared by using a mixed effect model, whereas assessment within group was compared by using a paired t-test. Treatment with sertindole was associated with QTcF and QTcB interval prolongation and an increase in MCS, T-wave asymmetry, T-wave flatness and TpTe. The mean increase in QTcF from baseline to last observation was 12.1ms for sertindole (p<0.001) and -0.5ms for quetiapine (p=0.8). Quetiapine caused no increase in MCS, T-wave asymmetry, T-wave flatness or TpTe compared to baseline. In the categorical analysis, there were 11 patients (9.6%) receiving quetiapine who experienced more than 20ms QTcF prolongation compared with 36 patients (33.3%) in the sertindole group. Sertindole (12-20mg) was associated with moderate QTc prolongation and worsening of T-wave morphology in a study population of patients with schizophrenia. Although, quetiapine (400-600mg) did not show worsening of repolarization measures some individual patients did experience significant worsening of repolarization. Clinical Trials NCT00654706. PMID:25583364

  20. 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.

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

    PubMed Central

    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. PMID:23720616

  2. Effect of ST segment measurement point on performance of exercise ECG analysis.

    PubMed

    Lehtinen, R; Sievänen, H; Turjanmaa, V; Niemelä, K; Malmivuo, J

    1997-10-10

    To evaluate the effect of ST-segment measurement point on diagnostic performance of the ST-segment/heart rate (ST/HR) hysteresis, the ST/HR index, and the end-exercise ST-segment depression in the detection of coronary artery disease, we analysed the exercise electrocardiograms of 347 patients using ST-segment depression measured at 0, 20, 40, 60 and 80 ms after the J-point. Of these patients, 127 had and 13 had no significant coronary artery disease according to angiography, 18 had no myocardial perfusion defect according to technetium-99m sestamibi single-photon emission computed tomography, and 189 were clinically 'normal' having low likelihood of coronary artery disease. Comparison of areas under the receiver operating characteristic curves showed that the discriminative capacity of the above diagnostic variables improved systematically up to the ST-segment measurement point of 60 ms after the J-point. As compared to analysis at the J-point (0 ms), the areas based on the 60-ms point were 89 vs. 84% (p=0.0001) for the ST/HR hysteresis, 83 vs. 76% (p<0.0001) for the ST/HR index, and 76 vs. 61% (p<0.0001) for the end-exercise ST depression. These findings suggest that the ST-segment measurement at 60 ms after the J-point is the most reasonable point of choice in terms of discriminative capacity of both the simple and the heart rate-adjusted indices of ST depression. Moreover, the ST/HR hysteresis had the best discriminative capacity independently of the ST-segment measurement point, the observation thus giving further support to clinical utility of this new method in the detection of coronary artery disease. PMID:9363740

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

    PubMed Central

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

    2015-01-01

    Background 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. Methods 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. Results 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. Conclusions 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. PMID:25496316

  4. 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.

  5. A statistical index for early diagnosis of ventricular arrhythmia from the trend analysis of ECG phase-portraits.

    PubMed

    Cappiello, Grazia; Das, Saptarshi; Mazomenos, Evangelos B; Maharatna, Koushik; Koulaouzidis, George; Morgan, John; Puddu, Paolo Emilio

    2015-01-01

    In this paper, we propose a novel statistical index for the early diagnosis of ventricular arrhythmia (VA) using the time delay phase-space reconstruction (PSR) technique, from the electrocardiogram (ECG) signal. Patients with two classes of fatal VA-with preceding ventricular premature beats (VPBs) and with no VPBs-have been analysed using extensive simulations. Three subclasses of VA with VPBs viz. ventricular tachycardia (VT), ventricular fibrillation (VF) and VT followed by VF are analyzed using the proposed technique. Measures of descriptive statistics like mean (µ), standard deviation (σ), coefficient of variation (CV = σ/µ), skewness (γ) and kurtosis (β) in phase-space diagrams are studied for a sliding window of 10 beats of the ECG signal using the box-counting technique. Subsequently, a hybrid prediction index which is composed of a weighted sum of CV and kurtosis has been proposed for predicting the impending arrhythmia before its actual occurrence. The early diagnosis involves crossing the upper bound of a hybrid index which is capable of predicting an impending arrhythmia 356 ECG beats, on average (with 192 beats standard deviation) before its onset when tested with 32 VA patients (both with and without VPBs). The early diagnosis result is also verified using a leave one out cross-validation (LOOCV) scheme with 96.88% sensitivity, 100% specificity and 98.44% accuracy. PMID:25500749

  6. 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

  7. 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

  8. 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. PMID:26106217

  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. Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

    PubMed

    Veer, Ilya M; Beckmann, Christian F; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J; Aleman, André; van Buchem, Mark A; van der Wee, Nic J; Rombouts, Serge A R B

    2010-01-01

    Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder. PMID:20941370

  11. Independent Component Analysis of Resting State Activity in Pediatric Obsessive-Compulsive Disorder

    PubMed Central

    Gruner, Patricia; Vo, An; Argyelan, Miklos; Ikuta, Toshikazu; Degnan, Andrew J.; John, Majnu; Peters, Bart D.; Malhotra, Anil K.; Uluğ, Aziz M.; Szeszko, Philip R.

    2014-01-01

    Obsessive-compulsive disorder (OCD) is an often severely disabling illness with onset generally in childhood or adolescence. Little is known, however, regarding the pattern of brain resting state activity in OCD early in the course of illness. We therefore examined differences in brain resting state activity in patients with pediatric OCD compared to healthy volunteers and their clinical correlates. Twenty-three pediatric OCD patients and 23 healthy volunteers (age range 9–17), matched for sex, age, handedness, and IQ completed a resting state functional magnetic resonance imaging exam at 3T. Patients completed the Children’s Yale Brown Obsessive Scale. Data were decomposed into 36 functional networks using spatial group independent component analysis (ICA) and logistic regression was used to identify the components that yielded maximum group separation. Using ICA we identified 3 components that maximally separated the groups: a middle frontal/dorsal anterior cingulate network, an anterior/posterior cingulate network, and a visual network yielding an overall group classification of 76.1% (sensitivity = 78.3% and specificity = 73.9%). Independent component expression scores were significantly higher in patients compared to healthy volunteers in the middle frontal/dorsal anterior cingulate and the anterior/posterior cingulate networks, but lower in patients within the visual network. Higher expression scores in the anterior/posterior cingulate network correlated with greater severity of compulsions among patients. These findings implicate resting state fMRI abnormalities within the cingulate cortex and related control regions in the pathogenesis and phenomenology of OCD early in the course of the disorder and prior to extensive pharmacologic intervention. PMID:24867148

  12. 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.

  13. 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.

  14. Advances and Pitfalls in the Analysis and Interpretation of Resting-State FMRI Data

    PubMed Central

    Cole, David M.; Smith, Stephen M.; Beckmann, Christian F.

    2010-01-01

    The last 15 years have witnessed a steady increase in the number of resting-state functional neuroimaging studies. The connectivity patterns of multiple functional, distributed, large-scale networks of brain dynamics have been recognised for their potential as useful tools in the domain of systems and other neurosciences. The application of functional connectivity methods to areas such as cognitive psychology, clinical diagnosis and treatment progression has yielded promising preliminary results, but is yet to be fully realised. This is due, in part, to an array of methodological and interpretative issues that remain to be resolved. We here present a review of the methods most commonly applied in this rapidly advancing field, such as seed-based correlation analysis and independent component analysis, along with examples of their use at the individual subject and group analysis levels and a discussion of practical and theoretical issues arising from this data ‘explosion’. We describe the similarities and differences across these varied statistical approaches to processing resting-state functional magnetic resonance imaging signals, and conclude that further technical optimisation and experimental refinement is required in order to fully delineate and characterise the gross complexity of the human neural functional architecture. PMID:20407579

  15. An unusual ECG pattern in restrictive cardimyopathy

    PubMed Central

    Selvaganesh, M.; Arul, A.S.; Balasubramanian, S.; Ganesan, N.; Naina Mohammed, S.; Sivakumar, G.S.; Veeramani, S.R.; Jeyasingh, P.; Sathishkumar, S.; Selvaraju, S.

    2015-01-01

    Restrictive cardiomyopathy is the least common type of primary cardiomyopathies. Electrocardiographic recording is abnormal in 99% of patients with RCM. Biatrial enlargement, obliquely elevated ST segment with notched or biphasic late peaking T waves are considered characteristic ECG finding. Significant ST depression with T inversion mimicking subendocardial ischemia has also been reported in patients with RCM and is even suggested as a predictor of sudden cardiac death. We noted a similar ECG pattern in a 16 yr girl with Idiopathic restrictive cardiomyopathy. Coronaries were normal, stress perfusion imaging did not show any perfusion defect. This diffuse resting ST depression with T inversion in precordial & inferior leads along with ST elevation in aVR was persistent for more than six months. PMID:26304570

  16. An unusual ECG pattern in restrictive cardimyopathy.

    PubMed

    Selvaganesh, M; Arul, A S; Balasubramanian, S; Ganesan, N; Naina Mohammed, S; Sivakumar, G S; Veeramani, S R; Jeyasingh, P; Sathishkumar, S; Selvaraju, S

    2015-01-01

    Restrictive cardiomyopathy is the least common type of primary cardiomyopathies. Electrocardiographic recording is abnormal in 99% of patients with RCM. Biatrial enlargement, obliquely elevated ST segment with notched or biphasic late peaking T waves are considered characteristic ECG finding. Significant ST depression with T inversion mimicking subendocardial ischemia has also been reported in patients with RCM and is even suggested as a predictor of sudden cardiac death. We noted a similar ECG pattern in a 16 yr girl with Idiopathic restrictive cardiomyopathy. Coronaries were normal, stress perfusion imaging did not show any perfusion defect. This diffuse resting ST depression with T inversion in precordial & inferior leads along with ST elevation in aVR was persistent for more than six months. PMID:26304570

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

    PubMed Central

    2014-01-01

    Background 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. Methods Design: prospective, observational, cross-sectional study. Setting: Clinical Physiology, University Hospital. Patients: 108 consecutive patients referred for ambiguous palpitations or dizziness/presyncope. Interventions: 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. Main outcome measures: Significant arrhythmias: atrial fibrillation (AF), paroxysmal supraventricular tachycardia (PSVT), atrioventricular (AV) block II–III, sinus arrest (SA), wide complex tachycardia (WCT). Results 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

  18. 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

  19. 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.

  20. 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.

  1. Free vibration analysis of magneto-electro-thermo-elastic nanobeams resting on a Pasternak foundation

    NASA Astrophysics Data System (ADS)

    Jandaghian, A. A.; Rahmani, O.

    2016-03-01

    In this study, free vibration analysis of magneto-electro-thermo-elastic (METE) nanobeams resting on a Pasternak foundation is investigated based on nonlocal theory and Timoshenko beam theory. Coupling effects between electric, magnetic, mechanical and thermal loading are considered to derive the equations of motion and distribution of electrical potential and magnetic potential along the thickness direction of the METE nanobeam. The governing equations and boundary conditions are obtained using the Hamilton principle and discretized via the differential quadrature method (DQM). Numerical results reveal the effects of the nonlocal parameter, magneto-electro-thermo-mechanical loading, Winkler spring coefficients, Pasternak shear coefficients and height-to-length ratio on the vibration characteristics of METE nanobeams. It is observed that the natural frequency is dependent on the magnetic, electric, temperature, elastic medium, small-scale coefficient, and height-to-length ratio. These results are useful in the mechanical analysis and design of smart nanostructures constructed from magneto-electro-thermo-elastic materials.

  2. 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.

  3. 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

  4. 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. PMID:26207740

  5. 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.

  6. Functional connectivity at rest is sensitive to individual differences in executive function: A network analysis.

    PubMed

    Reineberg, Andrew E; Banich, Marie T

    2016-08-01

    Graph theory provides a means to understand the nature of network characteristics and connectivity between specific brain regions. Here it was used to investigate whether the network characteristics of the brain at rest are associated with three dimensions thought to underlie individual differences in executive function (EF)-common EF, shifting-specific EF, and updating-specific EF (Miyake and Friedman [2012]). To do so, both an a priori analysis focused mainly on select frontoparietal regions previously linked to individual differences in EF as well as a whole-brain analysis were performed. The findings indicated that individual differences in each of the three dimensions of EF were associated with specific patterns of resting-state connectivity both in a priori and other brain regions. More specifically, higher common EF was associated with greater integrative (i.e., more hublike) connectivity of cuneus and supplementary motor area but less integrative function of lateral frontal nodes and left temporal lobe nodes. Higher shifting-specific EF was associated with more hublike motor-related nodes and cingulo-opercular nodes. Higher updating-specific EF was associated with less hublike lateral and medial frontoparietal nodes. In general, these results suggested that higher ability in each of these three dimensions of EF was not solely characterized by the connectivity characteristics of frontoparietal regions. The pattern was complicated in that higher EF was associated with the connectivity profile of nodes outside of the traditional frontoparietal network, as well as with less hublike or centrality characteristics of some nodes within the frontoparietal network. Hum Brain Mapp 37:2959-2975, 2016. © 2016 Wiley Periodicals, Inc. PMID:27167614

  7. Test-retest Stability Analysis of Resting Brain Activity Revealed by BOLD fMRI

    PubMed Central

    Li, Zhengjun; Kadivar, Aniseh; Pluta, John; Dunlop, John; Wang, Ze

    2012-01-01

    Purpose To assess test-retest stability of four fMRI-derived resting brain activity metrics: the seed-region-based functional connectivity (SRFC), independent component analysis (ICA)-derived network-based FC (NTFC), regional homogeneity (ReHo), and the amplitude of low frequency fluctuation (ALFF). Methods Simulations were used to assess the sensitivity of SRFC, ReHo, and ALFF to noise interference. Repeat resting blood-oxygen-level-dependent (BOLD) fMRI were acquired from 32 healthy subjects. The intra-class correlation coefficient (ICC) was used to assess the stability of the 4 metrics. Results Random noise yielded small random SRFC, small but consistent ReHo and ALFF. A neighborhood size greater than 20 voxels should be used for calculating ReHo in order to reduce the noise interference. Both the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC)-based SRFC were reproducible in more spatially extended regions than ICA NTFC. The two regional spontaneous brain activity (SBA) measures, ReHo and ALFF, showed test-retest reproducibility in almost the whole grey matter. Conclusion SRFC, ReHo, and ALFF are robust to random noise interference. The neighborhood size for calculating ReHo should be larger than 20 voxels. ICC>0.5 and cluster size>11 should be used to assess the ICC maps for ACC/PCC SRFC, ReHo and ALFF. BOLD fMRI-based SBA can be reliably measured using ACC/PCC SRFC, ReHo and ALFF after two months. PMID:22535702

  8. 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. PMID:25570031

  9. 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.

  10. 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

  11. 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'. PMID:25982737

  12. 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

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

    PubMed

    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

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

    PubMed

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

    2016-04-01

    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. PMID:27007947

  15. 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

  16. Assessing ECG signal quality indices to discriminate ECGs with artefacts from pathologically different arrhythmic ECGs.

    PubMed

    Daluwatte, C; Johannesen, L; Galeotti, L; Vicente, J; Strauss, D G; Scully, C G

    2016-08-01

    False and non-actionable alarms in critical care can be reduced by developing algorithms which assess the trueness of an arrhythmia alarm from a bedside monitor. Computational approaches that automatically identify artefacts in ECG signals are an important branch of physiological signal processing which tries to address this issue. Signal quality indices (SQIs) derived considering differences between artefacts which occur in ECG signals and normal QRS morphology have the potential to discriminate pathologically different arrhythmic ECG segments as artefacts. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied previously reported ECG SQIs in the scientific literature to differentiate ECG segments with artefacts from arrhythmic ECG segments. We found that the ability of SQIs to discriminate between ECG artefacts and arrhythmic ECG varies based on arrhythmia type since the pathology of each arrhythmic ECG waveform is different. Therefore, to reduce the risk of SQIs classifying arrhythmic events as noise it is important to validate and test SQIs with databases that include arrhythmias. Arrhythmia specific SQIs may also minimize the risk of misclassifying arrhythmic events as noise. PMID:27454007

  17. 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.

  18. 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).

  19. 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

  20. Allometry of ECG waves in mammals.

    PubMed

    Günther, B; Morgado, E

    1997-01-01

    The present allometric study deals with the duration of three electrocardiographic intervals (PQ, QRS, QT) and their relationships with the corresponding cardiac cycle length (R-R interval) in mammals across a wide body mass range. The numerical values of the different ECG intervals were obtained from Grauwiler's (1965) monograph on the subject. Because the corresponding body masses were not given by this author, Heusner's (1991) data on basal metabolic rate as function of body mass were used to establish the most likely body mass figure for each case, based on the taxonomic identity between the corresponding specimens. On the other hand, in a recent study we established the "duality" of physiological times (Günther & Morgado, 1996) and, therefore, we adopted this novel approach to investigate the ECG intervals and their relationships with the R-R interval (heart rate reciprocal). Considering that the anatomy and physiology of auricles and ventricles are different (spheroids versus quasi-cylinders), and that excitation (sino-atrial node and His-Purkinje's system) and contraction processes can be described either by Euclidean or fractal geometries, only a quantitative analysis of the different ECG waves could resolve the dilemma. From the present preliminary study we can conclude that fractal geometry is prevalent with regard to ECG intervals. PMID:9711327

  1. Novel electrodes for underwater ECG monitoring.

    PubMed

    Reyes, Bersain A; Posada-Quintero, Hugo F; Bales, Justin R; Clement, Amanda L; Pins, George D; Swiston, Albert; Riistama, Jarno; Florian, John P; Shykoff, Barbara; Qin, Michael; Chon, Ki H

    2014-06-01

    We have developed hydrophobic electrodes that provide all morphological waveforms without distortion of an ECG signal for both dry and water-immersed conditions. Our electrode is comprised of a mixture of carbon black powder (CB) and polydimethylsiloxane (PDMS). For feasibility testing of the CB/PDMS electrodes, various tests were performed. One of the tests included evaluation of the electrode-to-skin contact impedance for different diameters, thicknesses, and different pressure levels. As expected, the larger the diameter of the electrodes, the lower the impedance and the difference between the large sized CB/PDMS and the similarly-sized Ag/AgCl hydrogel electrodes was at most 200 kΩ, in favor of the latter. Performance comparison of CB/PDMS electrodes to Ag/AgCl hydrogel electrodes was carried out in three different scenarios: a dry surface, water immersion, and postwater immersion conditions. In the dry condition, no statistical differences were found for both the temporal and spectral indices of the heart rate variability analysis between the CB/PDMS and Ag/AgCl hydrogel (p > 0.05) electrodes. During water immersion, there was significant ECG amplitude reduction with CB/PDMS electrodes when compared to wet Ag/AgCl electrodes kept dry by their waterproof adhesive tape, but the reduction was not severe enough to obscure the readability of the recordings, and all morphological waveforms of the ECG signal were discernible even when motion artifacts were introduced. When water did not penetrate tape-wrapped Ag/AgCl electrodes, high fidelity ECG signals were observed. However, when water penetrated the Ag/AgCl electrodes, the signal quality degraded to the point where ECG morphological waveforms were not discernible. PMID:24845297

  2. Variable threshold method for ECG R-peak detection.

    PubMed

    Kew, Hsein-Ping; Jeong, Do-Un

    2011-10-01

    In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis. PMID:21695499

  3. A critical appraisal of the evidence for using cardiotocography plus ECG ST interval analysis for fetal surveillance in labor. Part I: the randomized controlled trials

    PubMed Central

    Olofsson, Per; Ayres-de-Campos, Diogo; Kessler, Jörg; Tendal, Britta; Yli, Branka M; Devoe, Lawrence

    2014-01-01

    We reappraised the five randomized controlled trials that compared cardiotocography plus ECG ST interval analysis (CTG+ST) vs. cardiotocography. The numbers enrolled ranged from 5681 (Dutch randomized controlled trial) to 799 (French randomized controlled trial). The Swedish randomized controlled trial (n = 5049) was the only trial adequately powered to show a difference in metabolic acidosis, and the Plymouth randomized controlled trial (n = 2434) was only powered to show a difference in operative delivery for fetal distress. There were considerable differences in study design: the French randomized controlled trial used different inclusion criteria, and the Finnish randomized controlled trial (n = 1483) used a different metabolic acidosis definition. In the CTG+ST study arms, the larger Plymouth, Swedish and Dutch trials showed lower operative delivery and metabolic acidosis rates, whereas the smaller Finnish and French trials showed minor differences in operative delivery and higher metabolic acidosis rates. We conclude that the differences in outcomes are likely due to the considerable differences in study design and size. This will enhance heterogeneity effects in any subsequent meta-analysis. PMID:24797452

  4. 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

  5. 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

  6. 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

  7. Red population of Abell 1314 : A rest-frame narrowband photometric evolutionary analysis

    NASA Astrophysics Data System (ADS)

    Sreedhar, Yuvraj Harsha

    2014-06-01

    Red sequence galaxies form with an intense burst of star formation in the early universe to evolve passively into massive, metal rich, old galaxies at z ˜ 0. But Abell 1314 (z=0.034) is found to host almost all red sequence galaxy members - identified using the mz index, classified using the Principle Component Analysis technique and SDSS colour correlations - some of which show properties of low-mass, star forming, and metal rich galaxies. The variably spread Intra-Cluster Medium (ICM) near the core forms a vital part in influencing the evolution of these members. To study their evolution, I correlated different parameters of the rest-frame narrowband photometry and the derived luminosity-weighted mean Single Stellar Population model ages and metallicities. The study finds the member galaxies evolve differently in three different sections of the cluster: 1. the region of ≤ 200 kpc hosts passively evolving old, massive systems which accumulate mass by dry, minor mergers, 2. the zone between 200-500 kpc shows stripped systems (or in the process of being gas stripped) by ram pressure with moderate star formation history, 3. the outer regions (≥ 500 kpc) show low-mass red objects with blue, star forming Butcher-Oemler galaxy like colours. This sort of environmental condition is known to harbour hybrid systems, like, the pseudo bulges, blue sequence E/S0 and Butcher-Oemler like satellite cluster galaxies. Overall, the cluster is found to be poor, quiescent with galaxies to have formed by the monolithic structure formation in the early universe and are now evolving with mergers and gas stripping processes by ram pressure.

  8. 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).

  9. [ECG mapping in clinical practice].

    PubMed

    Boudík, F; Aschermann, M; Anger, Z

    2002-12-01

    First the authors present a review of important cornerstones in the history of the electrocardiogram (ECG) and ECG mapping. The first to describe the electric cardiac field based on twenty ECGs was A.D. Waller in 1889. The decisive cornerstone for practical use was the introduction of a string galvanometer in 1901 by W. Einthoven and his triaxial lead system. Another very important cornerstone in the development of ECG were the findings of F.N. Wilson. Merits as regards the development and application of ECG mapping are due to B. Taccardi. Workers of the Second Medical Clinic in Prague enhanced after 15 years of studies and comparison of ECG maps with coronarographic findings in subjects with ischaemic heart disease (IHD) and microvascular coronary dysfunction (syndrome X--SyX) substantially the specificity of this method in impaired myocardial vascularization. Better diagnosis was achieved by introduction of diagnostic tests which influence coronary vascularization such as e.g. hyperventilation, as well as other tests. After their application progression of chronic myocardial ischaemia occurs, e.g. by the mechanism of the "steal phenomenon" or restriction of the microcirculation after hyperventilation in patients with SyX. Furthermore the authors present examples of ECG maps after PTCA, after application of diagnostic tests in IHD and SyX and also regression of myocardial ischaemia after marked reduction of total cholesterol. PMID:12744039

  10. Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting-state functional connectivity.

    PubMed

    van den Heuvel, Martijn P; Scholtens, Lianne H; Turk, Elise; Mantini, Dante; Vanduffel, Wim; Feldman Barrett, Lisa

    2016-09-01

    The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large-scale region-to-region resting-state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M1 ) and inhibitory (GABAA , M2 ) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting-state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting-state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting-state fMRI connectivity patterns at the global system's level of connectome organization. Hum Brain Mapp 37:3103-3113, 2016. © 2016 Wiley Periodicals, Inc. PMID:27207489

  11. An Analysis of Principals' Ethical Decision Making Using Rest's Four Component Model of Moral Behavior.

    ERIC Educational Resources Information Center

    Klinker, JoAnn Franklin; Hackmann, Donald G.

    High school principals confront ethical dilemmas daily. This report describes a study that examined how MetLife/NASSP secondary principals of the year made ethical decisions conforming to three dispositions from Standard 5 of the ISLLC standards and whether they could identify processes used to reach those decisions through Rest's Four Component…

  12. Capacitive measurement of ECG for ubiquitous healthcare.

    PubMed

    Lim, Yong Gyu; Lee, Jeong Su; Lee, Seung Min; Lee, Hong Ji; Park, Kwang Suk

    2014-11-01

    The technology for measuring ECG using capacitive electrodes and its applications are reviewed. Capacitive electrodes are built with a high-input-impedance preamplifier and a shield on their rear side. Guarding and driving ground are used to reduce noise. An analysis of the intrinsic noise shows that the thermal noise caused by the resistance in the preamplifier is the dominant factor of the intrinsic noise. A fully non-contact capacitive measurement has been developed using capacitive grounding and applied to a non-intrusive ECG measurement in daily life. Many ongoing studies are examining how to enhance the quality and ease of applying electrodes, thus extending their applications in ubiquitous healthcare from attached-on-object measurements to wearable or EEG measurements. PMID:25052344

  13. Analysis of resting salivation rate in patients with amyotrophic lateral sclerosis using tracheostomy invasive ventilation.

    PubMed

    Matsuda, Chiharu; Shimizu, Toshio; Nakayama, Yuki; Haraguchi, Michiko; Mochizuki, Yoko; Hakuta, Chiyoko; Taira, Masato; Numayama, Takaya; Kinoshita, Masanobu

    2016-07-28

    Patients with amyotrophic lateral sclerosis (ALS) often suffer from salivation problems such as drooling and dry mouth. We examined resting salivation rate cross-sectionally in 66 advanced ALS patients with tracheostomy invasive ventilation using a cotton roll method, and investigated clinical factors associated with salivation rate. Resting salivation rate in the patients was well preserved (median value 0.6 g/min), and was significantly more increased in patients with impairment of jaw movement (P = 0.007) or mouth opening (P = 0.003) than in patients with less impairment, and in patients with the mouth being constantly open ≥ 10 mm in rostrocaudal length than in patients with < 10 mm. These data indicate that salivation rate was increased with progression of dysfunction of voluntary jaw movement. Appropriate oral care is required in advanced ALS patients to maintain their oral hygiene and to avoid penetration of saliva into the airway. PMID:27356730

  14. ECG data compression by modeling.

    PubMed Central

    Madhukar, B.; Murthy, I. S.

    1992-01-01

    This paper presents a novel algorithm for data compression of single lead Electrocardiogram (ECG) data. The method is based on Parametric modeling of the Discrete Cosine Transformed ECG signal. Improved high frequency reconstruction is achieved by separately modeling the low and the high frequency regions of the transformed signal. Differential Pulse Code Modulation is applied on the model parameters to obtain a further increase in the compression. Compression ratios up to 1:40 were achieved without significant distortion. PMID:1482940

  15. Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death

    PubMed Central

    Skinner, James E; Meyer, Michael; Nester, Brian A; Geary, Una; Taggart, Pamela; Mangione, Antoinette; Ramalanjaona, George; Terregino, Carol; Dalsey, William C

    2009-01-01

    Objective: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD). Background: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are independent risk factors for AD in post-myocardial infarction (post-MI) cohorts. Indices based on nonlinear deterministic models have superior predictability in retrospective data. Methods: Patients were enrolled (N = 397) in three emergency departments upon presenting with chest pain and were determined to be at low-to-high risk of acute MI (>7%). Brief ECGs were recorded (15 min) and R-R intervals assessed by three nonlinear algorithms (PD2i, DFA, and ApEn) and four conventional linear-stochastic measures (SDNN, MNN, 1/f-Slope, LF/HF). Out-of-hospital AD was determined by modified Hinkle–Thaler criteria. Results: All-cause mortality at one-year follow-up was 10.3%, with 7.7% adjudicated to be AD. The sensitivity and relative risk for predicting AD was highest at all time-points for the nonlinear PD2i algorithm (p ≤0.001). The sensitivity at 30 days was 100%, specificity 58%, and relative risk >100 (p ≤0.001); sensitivity at 360 days was 95%, specificity 58%, and relative risk >11.4 (p ≤0.001). Conclusions: Heartbeat analysis by the time-dependent nonlinear PD2i algorithm is comparatively the superior test. PMID:19707283

  16. Graph-Based Network Analysis of Resting-State Functional MRI

    PubMed Central

    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. PMID:20589099

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

    SciTech Connect

    Gibson, R.S. )

    1989-08-01

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

  18. The future of remote ECG monitoring systems.

    PubMed

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

    2016-09-01

    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

  19. 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

  20. Artificial gravity training reduces bed rest-induced cardiovascular deconditioning.

    PubMed

    Stenger, Michael B; Evans, Joyce M; Knapp, Charles F; Lee, Stuart M C; Phillips, Tiffany R; Perez, Sondra A; Moore, Alan D; Paloski, William H; Platts, Steven H

    2012-02-01

    We studied 15 men (8 treatment, 7 control) before and after 21 days of 6º head-down tilt to determine whether daily, 1-h exposures to 1.0 G(z) (at the heart) artificial gravity (AG) would prevent bed rest-induced cardiovascular deconditioning. Testing included echocardiographic analysis of cardiac function, plasma volume (PV), aerobic power (VO(2)pk) and cardiovascular and neuroendocrine responses to 80º head-up tilt (HUT). Data collected during HUT were ECG, stroke volume (SV), blood pressure (BP) and blood for catecholamines and vasoactive hormones. Heart rate (HR), cardiac output (CO), total peripheral resistance, and spectral power of BP and HR were calculated. Bed rest decreased PV, supine and HUT SV, and indices of cardiac function in both groups. Although PV was decreased in control and AG after bed rest, AG attenuated the decrease in orthostatic tolerance [pre- to post-bed rest change; control: -11.8 ± 2.0, AG: -6.0 ± 2.8 min (p = 0.012)] and VO(2)pk [pre- to post-bed rest change; control: -0.39 ± 0.11, AG: -0.17 ± 0.06 L/min (p = 0.041)]. AG prevented increases in pre-tilt levels of plasma renin activity [pre- to post-bed rest change; control: 1.53 ± 0.23, AG: -0.07 ± 0.34 ng/mL/h (p = 0.001)] and angiotensin II [pre- to post-bed rest change; control: 3.00 ± 1.04, AG: -0.63 ± 0.81 pg/mL (p = 0.009)] and increased HUT aldosterone [post-bed rest; control: 107 ± 30 pg/mL, AG: 229 ± 68 pg/mL (p = 0.045)] and norepinephrine [post-bed rest; control: 453 ± 107, AG: 732 ± 131 pg/mL (p = 0.003)]. We conclude that AG can mitigate some aspects of bed rest-induced cardiovascular deconditioning, including orthostatic intolerance and aerobic power. Mechanisms of improvement were not cardiac-mediated, but likely through improved sympathetic responsiveness to orthostatic stress. PMID:21626041

  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. PMID:27484657

  2. Effects of lorazepam on cardiac vagal tone during rest and mental stress: assessment by means of spectral analysis.

    PubMed

    Tulen, J H; Mulder, G; Pepplinkhuizen, L; Man in 't Veld, A J; van Steenis, H G; Moleman, P

    1994-02-01

    Dose-dependent effects of intravenously administered lorazepam on haemodynamic fluctuations were studied by means of spectral analysis, in order to elucidate sympathetic and parasympathetic components in cardiovascular control during situations of rest and mental stress after benzodiazepine administration. In a double-blind randomized cross-over study, nine male volunteers participated in two sessions: a placebo and lorazepam session. During these sessions, the subjects repeatedly performed a 10-min version of the Stroop Color Word Test (CWT), with 10 min of rest between the CWTs. Lorazepam was administered before each rest period in increasing doses of 0.0, 0.06, 0.13, 0.25 and 0.5 mg (total cumulative dose: 0.94 mg). During the placebo session the subjects received five placebo injections. For five of the nine subjects the lorazepam session was their first session. Heat rate (HR), blood pressure (BP) and respiration were recorded continuously. Power spectra were calculated per 2.5-min periods for HR, systolic (SBP) and diastolic BP (DBP). Spectral density was assessed for three frequency bands: low (LFB: 0.02-0.06 Hz), mid (MFB: 0.07-0.14 Hz) and high (HFB: 0.15-0.40 Hz). During the consecutive periods of rest, lorazepam induced a dose-dependent decrease in HR, and a dose-dependent increase in LFB, MFB and HFB power of HR, but lorazepam had no effect on BP. The effects were significant after 0.44 mg lorazepam for HR and HFB power, and after 0.94 mg lorazepam for the HR fluctuations in the LFB and MFB. Lorazepam did not influence the cardiovascular responses to the CWT.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7846210

  3. 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

  4. 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

  5. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  7. Neurobiological changes of schizotypy: evidence from both volume-based morphometric analysis and resting-state functional connectivity.

    PubMed

    Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-xia; Cheung, Eric F C; Pantelis, Christos; Chan, Raymond C K

    2015-03-01

    The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional network analysis were conducted. Individuals with high schizotypy showed reduced gray matter (GM) density in the insula and the dorsolateral prefrontal gyrus. The graph theoretical analysis showed that individuals with high schizotypy showed similar global properties in their functional networks as low schizotypy individuals. Several hubs of the functional network were identified in both groups, including the insula, the lingual gyrus, the postcentral gyrus, and the rolandic operculum. More hubs in the frontal lobe and fewer hubs in the occipital lobe were identified in individuals with high schizotypy. By comparing the functional connectivity between clusters with abnormal GM density and the whole brain, individuals with high schizotypy showed weaker functional connectivity between the left insula and the putamen, but stronger connectivity between the cerebellum and the medial frontal gyrus. Taken together, our findings suggest that individuals with high schizotypy present changes in terms of GM and resting-state functional connectivity, especially in the frontal lobe. PMID:25533270

  8. Neurobiological Changes of Schizotypy: Evidence From Both Volume-Based Morphometric Analysis and Resting-State Functional Connectivity

    PubMed Central

    Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-xia; Cheung, Eric F. C.; Pantelis, Christos; Chan, Raymond C. K.

    2015-01-01

    The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional network analysis were conducted. Individuals with high schizotypy showed reduced gray matter (GM) density in the insula and the dorsolateral prefrontal gyrus. The graph theoretical analysis showed that individuals with high schizotypy showed similar global properties in their functional networks as low schizotypy individuals. Several hubs of the functional network were identified in both groups, including the insula, the lingual gyrus, the postcentral gyrus, and the rolandic operculum. More hubs in the frontal lobe and fewer hubs in the occipital lobe were identified in individuals with high schizotypy. By comparing the functional connectivity between clusters with abnormal GM density and the whole brain, individuals with high schizotypy showed weaker functional connectivity between the left insula and the putamen, but stronger connectivity between the cerebellum and the medial frontal gyrus. Taken together, our findings suggest that individuals with high schizotypy present changes in terms of GM and resting-state functional connectivity, especially in the frontal lobe. PMID:25533270

  9. 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

  10. [The design of handheld fast ECG detector].

    PubMed

    Shi, Bo; Zhang, Genxuan; Tsau, Young

    2013-03-01

    A new handheld fast ECG detector based on low gain amplifier, the high resolution analog to digital converter, the real-time digital filter, fast P-QRS-T wave detection and abstraction algorithm was designed. The results showed that the ECG detector can meet the requirements of fast detecting heart rate and ECG P-QRS-T waveforms. PMID:23777065

  11. EEG Resting State Functional Connectivity Analysis in Children with Benign Epilepsy with Centrotemporal Spikes

    PubMed Central

    Adebimpe, Azeez; Aarabi, Ardalan; Bourel-Ponchel, Emilie; Mahmoudzadeh, Mahdi; Wallois, Fabrice

    2016-01-01

    In this study, we investigated changes in functional connectivity (FC) of the brain networks in patients with benign epilepsy with centrotemporal spikes (BECTS) compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA). We investigated FC between 84 Brodmann areas using lagged phase synchronization (LPS) in four frequency bands (δ, θ, α, and β). We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β LPS values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the β band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands. PMID:27065797

  12. Analysis of changes in pulmonary functions at rest following humidity changes.

    PubMed

    Kim, Jae Hyun; Hyong, In Hyouk

    2015-04-01

    [Purpose] The purpose of this study was to compare the effect of humidity changes on the values of pulmonary function at rest. [Subjects and Methods] This study was conducted with 30 young adults (9 males, 21 females; mean age 19.4 years). Participants' mean height was 165.1 cm, and their mean weight was 60.2 kg. The experimental setting was a laboratory in which temperature was fixed at 25 °C. Using a humidifier, relative humidity was successively to adjusted 25%, 50%, and 90%, and pulmonary were measured functions at each level. Using a spirometer, forced vital capacity (FVC), forced expiratory volume in one second (FEV1), expiratory reserve volume (ERV), and tidal volume (TV) were measured, and the results were compared and analyzed. [Results] Controlling for temperature, FVC and FEV1 showed statistically significant differences among different levels of relative humidity, but FEV1/FVC, TV, and ERV showed no significant difference. [Conclusion] In the case of exercises that require large respiration volumes, such as aerobic exercises or exercise load tests, it is recommended that higher than normal humidity levels should be maintained. PMID:25995557

  13. A comparative fine structural and phylogenetic analysis of resting cysts in oligotrich and hypotrich Spirotrichea (Ciliophora)

    PubMed Central

    Foissner, Wilhelm; Müller, Helga; Agatha, Sabine

    2010-01-01

    So far, neither morphology nor gene sequences have provided a reliable classification of halteriid and hypotrichid spirotrichs. Thus, we performed a comparative study on the fine structure of the resting cysts in some representative species, viz., the oligotrichs Halteria grandinella and Pelagostrombidium fallax and the oxytrichid hypotrichs Laurentiella strenua, Steinia sphagnicola, and Oxytricha granulifera. Main results include: (i) there are three different, very likely non-homologous cyst surface ornamentations, viz., spines (generated by the ectocyst), thorns (generated by the mesocyst), and lepidosomes (produced in the cytoplasm); (ii) Halteria has a perilemma; (iii) Halteria, Meseres and Pelagostrombidium have fibrous lepidosomes, while those of Oxytricha are tubular; (iv) the cyst wall structure of Pelagostrombidium and Strombidium is distinctly different from that of halteriids and oxytrichids, which are rather similar in this respect; (v) cyst ornamentation does not provide a reliable phylogenetic signal in oxytrichid hypotrichs because ectocyst spines occur in both flexible and rigid genera. The new observations and literature data were used to investigate the phylogeny of the core Spirotrichea. The Hennigian argumentation scheme and computer algorithms showed that the spirotrichs are bound together by the macronuclear reorganization band, the subepiplasmic microtubule basket, and the apokinetal stomatogenesis. The Hypotrichida and Oligotrichida are united by a very strong synapomorphy, viz., the perilemma, not found in any other member of the phylum. Halteriid and oligotrichid spirotrichs form a sister group supported by as many as 13 apomorphies. Thus, the molecular data, which classify the halteriids within the core hypotrichs, need to be reconsidered. PMID:17766095

  14. EEG Resting State Functional Connectivity Analysis in Children with Benign Epilepsy with Centrotemporal Spikes.

    PubMed

    Adebimpe, Azeez; Aarabi, Ardalan; Bourel-Ponchel, Emilie; Mahmoudzadeh, Mahdi; Wallois, Fabrice

    2016-01-01

    In this study, we investigated changes in functional connectivity (FC) of the brain networks in patients with benign epilepsy with centrotemporal spikes (BECTS) compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA). We investigated FC between 84 Brodmann areas using lagged phase synchronization (LPS) in four frequency bands (δ, θ, α, and β). We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β LPS values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the β band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands. PMID:27065797

  15. Complexity Analysis of Resting State Magnetoencephalography Activity in Traumatic Brain Injury Patients

    PubMed Central

    Xu, Duo; Roskos, Tyler; Stout, Jeff; Kull, Lynda; Cheng, Xi; Whitson, Diane; Boomgarden, Erich; Gfeller, Jeffrey; Bucholz, Richard D.

    2013-01-01

    Abstract Diagnosis of mild traumatic brain injuries (TBIs) has been difficult because of the absence of obvious focal brain lesions, using conventional computed tomography (CT) or magnetic resonance imaging (MRI) scans, in a large percentage of TBIs. One useful measure that can characterize potential tissue and neural network damage objectively is Lempel–Ziv complexity (LZC) applied to magnetoencephalography (MEG) signals. LZC is a model-independent estimator of system complexity that estimates the number of different patterns in a sequence. We hypothesized that because of the potential network damage, TBIs would show a reduced level of complexity in regions that are impaired. We included 18 healthy controls and 18 military veterans with TBI in the study. Resting state MEG data were acquired, and the LZCs were analyzed across the whole brain. Our results indicated reduced complexity in multiple brain areas in TBI patients relative to the healthy controls. In addition, we detected several neuropsychological measures associated with motor responses, visual perception, and memory, correlated with LZC, which likely explains some of the cognitive deficits in TBI patients. PMID:23692211

  16. 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. PMID:26524138

  17. 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.

  18. 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.

  19. Compartmental analysis of technetium-99m-teboroxime kinetics employing fast dynamic SPECT at rest and stress

    SciTech Connect

    Chiao, P.C.; Ficaro, E.P.; Dayaniki, F.

    1994-08-01

    The authors have examined the feasibility of compartmental analysis of {sup 99m}Tc-teboroxime kinetics in measuring physiological changes in response to adenosine-induced coronary vasodilation. To evaluate the effect of tracer recirculation on {sup 99m}Tc-teboroxime kinetics in the myocardium, they also compared compartmental analysis with washout analysis (monoexponertial fitting), which does not account for this effect. Eight healthy male volunteers were imaged using fast dynamic SPECT protocols (5 sec per tomographic image) at rest and during adenosine infusion. A two-compartment model was used and compartmental parameters K1 and k2 (characterizing the diffusion of {sup 99m}Tc-teboroxime from the blood to the myocardium and from the myocardium to the blood, respectively) were fitted from myocardial time-activity curves and left ventricular input functions. Both K1 and washout estimates for the whole left ventricular myocardium changed significantly in response to coronary vasodilation. Mean stress-to-rest (S/R) ratios were almost two times higher for K1 (S/R = 2.7 {plus_minus} 1.1) than for washout estimates (S/R = 1.5 {plus_minus} 0.3). Estimation of K1 for all local regions, except the septal wall, is feasible because variations in K1 estimates for all local regions, except the septum during stress, are comparable with those for the global region. The authors conclude that quantitative compartmental analysis of {sup 99m}Tc-teboroxime kinetics provides a sensitive indicator for changes in response to adenosine-induced coronary vasodilation. 39 refs., 7 figs., 1 tab.

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

    PubMed

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

    2015-11-01

    In this study, we present a method for measuring functional magnetic resonance imaging (fMRI) signal complexity using fuzzy approximate entropy (fApEn) and compare it with the established sample entropy (SampEn). Here we use resting state fMRI dataset of 86 healthy adults (41 males) with age ranging from 19 to 85 years. We expect the complexity of the resting state fMRI signals measured to be consistent with the Goldberger/Lipsitz model for robustness where healthier (younger) and more robust systems exhibit more complexity in their physiological output and system complexity decrease with age. The mean whole brain fApEn demonstrated significant negative correlation (r = -0.472, p<0.001) with age. In comparison, SampEn produced a non-significant negative correlation (r = -0.099, p = 0.367). fApEn also demonstrated a significant (p < 0.05) negative correlation with age regionally (frontal, parietal, limbic, temporal and cerebellum parietal lobes). There was no significant correlation regionally between the SampEn maps and age. These results support the Goldberger/Lipsitz model for robustness and have shown that fApEn is potentially a sensitive new method for the complexity analysis of fMRI data. PMID:26475494

  1. [An improved wavelet threshold algorithm for ECG denoising].

    PubMed

    Liu, Xiuling; Qiao, Lei; Yang, Jianli; Dong, Bin; Wang, Hongrui

    2014-06-01

    Due to the characteristics and environmental factors, electrocardiogram (ECG) signals are usually interfered by noises in the course of signal acquisition, so it is crucial for ECG intelligent analysis to eliminate noises in ECG signals. On the basis of wavelet transform, threshold parameters were improved and a more appropriate threshold expression was proposed. The discrete wavelet coefficients were processed using the improved threshold parameters, the accurate wavelet coefficients without noises were gained through inverse discrete wavelet transform, and then more original signal coefficients could be preserved. MIT-BIH arrythmia database was used to validate the method. Simulation results showed that the improved method could achieve better denoising effect than the traditional ones. PMID:25219225

  2. ECG low QRS voltage and wide QRS complex predictive of centenarian 360-day mortality.

    PubMed

    Szewieczek, Jan; Gąsior, Zbigniew; Duława, Jan; Francuz, Tomasz; Legierska, Katarzyna; Batko-Szwaczka, Agnieszka; Hornik, Beata; Janusz-Jenczeń, Magdalena; Włodarczyk, Iwona; Wilczyński, Krzysztof

    2016-04-01

    We examined the electrocardiographic (ECG) findings of centenarians and associated them with >360-day survival. Physical and functional assessment, resting electrocardiogram and laboratory tests were performed on 86 study participants 101.9 ± 1.2 years old (mean ± SD) (70 women, 16 men) and followed for at least 360 days. Centenarian ECGs were assessed for left ventricular hypertrophy (LVH) according to the Romhilt-Estes score, Sokolow-Lyon criteria and Cornell voltage criteria which were positive for 12.8, 6.98, and 10.5 % of participants, respectively. Fifty-two study participants (60 %) survived ≥360 days. Multivariate logistic regression analysis revealed a negative relationship between 360-day survival and the following: R II <0.45 mV adjusted for CRP (odds ratio (OR) = 0.108, 95 % confidence interval (CI) = 0.034-0.341, P < .001), R aVF < 0.35 mV adjusted for CRP (OR = 0.151, 95 % CI = 0.039-0.584, P < .006), Sokolow-Lyon voltage <1.45 mV adjusted for CRP (OR = 0.178, 95 % CI = 0.064-0.492, P = .001), QRS ≥90 ms adjusted for CRP (OR = 0.375, 95 % CI = 0.144-0.975, P = .044), and Romhilt-Estes score ≥5 points adjusted for sex and Barthel Index (OR = 0.459, 95 % CI = 0.212-0.993, P = .048) in single variable ECG models. QRS voltage correlated positively with systolic and pulse pressure, serum vitamin B12 level, sodium, calcium, phosphorous, TIMP-1, and eGFR. QRS voltage correlated negatively with BMI, WHR, serum leptin, IL-6, TNF-α, and PAI-1 levels. QRS complex duration correlated positively with CRP; QTc correlated positively with TNF-α. Results suggest that Romhilt-Estes LVH criteria scores ≥5 points, low ECG QRS voltages (Sokolow-Lyon voltage <1.45 mV), and QRS complexes ≥90 ms are predictive of centenarian 360-day mortality. PMID:27039197

  3. 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.

  4. 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. PMID:23708767

  5. [The athletes' ECG and the exercise related sudden cardiac death].

    PubMed

    Trachsel, Lukas-Daniel; Wilhelm, Matthias

    2015-05-01

    Regular physical activity induces structural, electrical and functional cardiac adaptations. The main challenge for the athletes' physician is to distinguish abnormal structural changes of the heart from training-induced adaptations (so-called “athlete's heart”). In athletes with underlying cardiac disease, physical activity may be a trigger, not the cause of exercise-induced tachyarrhythmia's and sudden cardiac death (SCD). To identify athletes with cardiac diseases and increased risk for an SCD, the European society of cardiology (ESC) recommends a pre-participation screening in elite athletes which was adopted by the Swiss society of sports medicine. The screening includes a specific medical history, cardiac auscultation and a resting ECG. Due to the high number of false-positive cases of athletes' ECGs based on traditional criteria, the ESC assessment criteria were adjusted to account for training-related changes of the ECG. The sensitivity and especially the specificity could be improved in the “revised Seattle criteria” in 2014. During the last years main attention has been shifted to the early repolarization pattern: additionally to (endurance-) training there is a clear association with male gender, ethnicity, changes in autonomic nervous system activity and high QRS-voltage criteria PMID:26098068

  6. ECG-ELECTRODE INDUCED HYPOPIGMENTATION.

    PubMed

    Tripi, Paul A; Parthasarathy, Supraja N; Honda, Kord

    2016-06-01

    Skin reactions following the application of electrocardiography (ECG) electrodes have been reported in adults and children, and are postulated to result from contact with the conductive gel or adhesive used on the electrodes. Although contact dermatitis is the usual cause of such reactions, contact depigmentation or hypopigmentation may also occur. We report a case of hypopigmentation in a healthy boy following continuous electrocardiography monitoring during general anesthesia for dental rehabilitation. PMID:27487645

  7. 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.

  8. [Continuous ECG recording for freely moving patients].

    PubMed

    Shi, Bo; Liu, Shengyang; Chen, Jianfang; Zhang, Genxuan; Tsau, Young

    2013-04-01

    As more and more people are becoming aged in China and many of them tend to suffer from chronic cardiac problems, the long-term dynamic cardiac monitoring for freely moving patients becomes essential. A new design for continuous ECG recording on the freely moving patients at home and/or at work is proposed here. It is miniature in size, using digital technologies of the low gain amplifier, the high resolution analog to digital converter and the real-time digital filter that features > 100dB input signal dynamic range (ISDR), > 100dB common-mode rejection ratio (CMRR), and < 5microV (RMS) internal noise. The device works continuously more than 24 hours with a pair of AAA batteries, and is capable of storing the recorded data into a storage card. The preliminary tests showed that the P-QRS-T waveforms were captured and displayed smoothly in resting, walking, and activities, making the device useful in monitoring and analyzing for the patients on the move. PMID:23858751

  9. GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia

    PubMed Central

    Rytty, Riikka; Nikkinen, Juha; Paavola, Liisa; Abou Elseoud, Ahmed; Moilanen, Virpi; Visuri, Annina; Tervonen, Osmo; Renton, Alan E.; Traynor, Bryan J.; Kiviniemi, Vesa; Remes, Anne M.

    2013-01-01

    Functional MRI studies have revealed changes in default-mode and salience networks in neurodegenerative dementias, especially in Alzheimer's disease (AD). The purpose of this study was to analyze the whole brain cortex resting state networks (RSNs) in patients with behavioral variant frontotemporal dementia (bvFTD) by using resting state functional MRI (rfMRI). The group specific RSNs were identified by high model order independent component analysis (ICA) and a dual regression technique was used to detect between-group differences in the RSNs with p < 0.05 threshold corrected for multiple comparisons. A y-concatenation method was used to correct for multiple comparisons for multiple independent components, gray matter differences as well as the voxel level. We found increased connectivity in several networks within patients with bvFTD compared to the control group. The most prominent enhancement was seen in the right frontotemporal area and insula. A significant increase in functional connectivity was also detected in the left dorsal attention network (DAN), in anterior paracingulate—a default mode sub-network as well as in the anterior parts of the frontal pole. Notably the increased patterns of connectivity were seen in areas around atrophic regions. The present results demonstrate abnormal increased connectivity in several important brain networks including the DAN and default-mode network (DMN) in patients with bvFTD. These changes may be associated with decline in executive functions and attention as well as apathy, which are the major cognitive and neuropsychiatric defects in patients with frontotemporal dementia. PMID:23986673

  10. 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

  11. 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

  12. Autoadaptivity and optimization in distributed ECG interpretation.

    PubMed

    Augustyniak, Piotr

    2010-03-01

    This paper addresses principal issues of the ECG interpretation adaptivity in a distributed surveillance network. In the age of pervasive access to wireless digital communication, distributed biosignal interpretation networks may not only optimally solve difficult medical cases, but also adapt the data acquisition, interpretation, and transmission to the variable patient's status and availability of technical resources. The background of such adaptivity is the innovative use of results from the automatic ECG analysis to the seamless remote modification of the interpreting software. Since the medical relevance of issued diagnostic data depends on the patient's status, the interpretation adaptivity implies the flexibility of report content and frequency. Proposed solutions are based on the research on human experts behavior, procedures reliability, and usage statistics. Despite the limited scale of our prototype client-server application, the tests yielded very promising results: the transmission channel occupation was reduced by 2.6 to 5.6 times comparing to the rigid reporting mode and the improvement of the remotely computed diagnostic outcome was achieved in case of over 80% of software adaptation attempts. PMID:20064764

  13. 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. PMID:24215744

  14. Identification of hypoglycemia and hyperglycemia in type 1 diabetic patients using ECG parameters.

    PubMed

    Nguyen, Linh Lan; Su, Steven; Nguyen, Hung T

    2012-01-01

    Hypoglycemia and Hyperglycemia are both serious diseases related to diabetes mellitus. Among Type 1 Diabetic patients, there are who experience both hypoglycemic and hyperglycemic events. The aim of this study was to identify of hypoglycemia and hyperglycemia based on ECG changes in this population. An ECG Acquisition and Analysis System based on LabVIEW software has been developed for collecting ECG signals and extracting features with abnormal changes. ECG parameters included Heart rate (HR), corrected QT interval (QTeC), PR interval, corrected RT interval (RTC) and corrected TpTe interval (TpTe(C)). Blood glucose levels were used to classify glycemic states in subjects as hypoglycemic state (≤ 60 mml/l, Hypo), as normoglycemic state (80 to 110 mmol/l, Normo), and as hyperglycemic state 150 mml/l, Hyper). The results indicated that hypoglycemic and hyperglycemic states produce significant inverse changes on those ECG parameters. PMID:23366486

  15. 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. PMID:26684565

  16. 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

    2016-08-01

    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. PMID:27295028

  17. A WBAN based cableless ECG acquisition system.

    PubMed

    Pan, Rui; Chua, Dingjuan; Pathmasuntharam, Jaya Shankar; Xu, Yong Ping

    2014-01-01

    A Wireless Body Area Network (WBAN) based 3-lead cableless electrocardiography (ECG) acquisition system is described. To enable truly cableless ECG monitoring, a new ECG measurement configuration and method that acquires ECG signals at individual lead locations referenced to a localized ground is proposed. The synthesized ECG signals are evaluated against the standard wired 3-lead configuration on the same test subject. Average Pearson correlation coefficients of 0.82, 0.95 and 0.86 have been achieved for Lead I, II and III signals respectively, demonstrating a high degree of similarity in the synthesized signals. Measurements are obtained via a custom wireless network platform utilizing a TDMA-based MAC protocol supporting the star topology and a proprietary front-end ECG acquisition system. PMID:25570107

  18. 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

  19. Effects of diet and diet-plus-exercise programs on resting metabolic rate: a meta-analysis.

    PubMed

    Thompson, J L; Manore, M M; Thomas, J R

    1996-03-01

    Studies examining the effects of diet (D) and diet-plus-exercise (DE) programs on resting metabolic rate (RMR) report equivocal results. The purpose of this study was to use meta-analysis to determine if exercise prevents the decrease in RMR observed with dieting. Results from the 22 studies included in this analysis revealed that the majority of studies used female subjects ages 31-45 years, who were fed a relatively low-fat, high-carbohydrate diet of less than 5,023 kJ.day-1. The predominant prescribed exercise was aerobic in nature, 31-60 min in duration, performed 4-5 days per week, and of moderate intensity (51-70% of VO2max). Contrary to what is reported in narrative reviews, RMR decreased significantly with both D and DE programs, and the drop with D was significantly greater than that with DE. In conclusion, the addition of exercise to dietary restriction appears to prevent some of the decrease in RMR observed in premenopausal women. PMID:8653104

  20. A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.

    PubMed

    Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin

    2013-08-01

    It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences. PMID:22614763

  1. 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.

  2. 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. PMID:27185312

  3. Disease Classification and Biomarker Discovery Using ECG Data

    PubMed Central

    Huang, Rong; Zhou, Yingchun

    2015-01-01

    In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA), SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively. PMID:26688816

  4. 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. PMID:22752143

  5. 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. PMID:17203744

  6. 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

  7. 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. PMID:25534118

  8. Optimising diagnostic accuracy with the exercise ECG: opportunities for women and men with stable ischaemic heart disease

    PubMed Central

    Shaw, Leslee J; Xie, Joe X; Phillips, Lawrence M; Goyal, Abhinav; Reynolds, Harmony R; Berman, Daniel S; Picard, Michael H; Bhargava, Balram; Devlin, Gerard; Chaitman, Bernard R

    2016-01-01

    The exercise ECG is an integral part within the evaluation algorithm for diagnosis and risk stratification of patients with stable ischaemic heart disease (SIHD). There is evidence, both older and new, that the exercise ECG can be an effective and cost-efficient option for patients capable of performing at maximal levels of exercise with suitable resting ECG findings. In this review, we will highlight the major dilemmas in interpreting suspected coronary artery disease symptoms in women and identify optimal strategies for employing exercise ECG as a first-line diagnostic test in the SIHD evaluation algorithm. We will highlight current evidence as well as recent guideline statements on this subject. Trial registration number NCT01471522; Pre-results. PMID:27326241

  9. 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

  10. The presupplementary area within the language network: a resting state functional magnetic resonance imaging functional connectivity analysis.

    PubMed

    Ter Minassian, Aram; Ricalens, Emmanuel; Nguyen The Tich, Sylvie; Dinomais, Mickaël; Aubé, Christophe; Beydon, Laurent

    2014-08-01

    The presupplementary motor area (pre-SMA) is involved in volitional selection. Despite the lateralization of the language network and different functions for both pre-SMA, few studies have reported the lateralization of pre-SMA activity and very little is known about the possible lateralization of pre-SMA connectivity. Via functional connectivity analysis, we sought to understand how the language network may be connected to other intrinsic connectivity networks (ICNs) through the pre-SMA. We performed a spatial independent component analysis of resting state functional magnetic resonance imaging in 30 volunteers to identify the language network. Subsequently, we applied seed-to-voxel functional connectivity analyses centered on peaks detected in the pre-SMA. Three signal peaks were detected in the pre-SMA. The left rostral pre-SMA intrinsic connectivity network (LR ICN) was left lateralized in contrast to bilateral ICNs associated to right pre-SMA peaks. The LR ICN was anticorrelated with the dorsal attention network and the right caudal pre-SMA ICN (RC ICN) anticorrelated with the default mode network. These two ICNs overlapped minimally. In contrast, the right rostral ICN overlapped the LR ICN. Both right ICNs overlapped in the ventral attention network (vATT). The bilateral connectivity of the right rostral pre-SMA may allow right hemispheric recruitment to process semantic ambiguities. Overlap between the right pre-SMA ICNs in vATT may contribute to internal thought to external environment reorientation. Distinct ICNs connected to areas involved in lexico-syntactic selection and phonology converge in the pre-SMA, which may constitute the resolution space of competing condition-action associations for speech production. PMID:24939724

  11. 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.

  12. REST based mobile applications

    NASA Astrophysics Data System (ADS)

    Rambow, Mark; Preuss, Thomas; Berdux, Jörg; Conrad, Marc

    2008-02-01

    Simplicity is the major advantage of REST based webservices. Whereas SOAP is widespread in complex, security sensitive business-to-business aplications, REST is widely used for mashups and end-user centric applicatons. In that context we give an overview of REST and compare it to SOAP. Furthermore we apply the GeoDrawing application as an example for REST based mobile applications and emphasize on pros and cons for the use of REST in mobile application scenarios.

  13. 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. PMID:26853876

  14. 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

  15. Global resting-state fMRI analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder

    PubMed Central

    Anticevic, Alan; Hu, Sien; Zhang, Sheng; Savic, Aleksandar; Billingslea, Eileen; Wasylink, Suzanne; Repovs, Grega; Cole, Michael W.; Bednarski, Sarah; Krystal, John H.; Bloch, Michael H.; Li, Chiang-shan R.; Pittenger, Christopher

    2013-01-01

    Background Obsessive-compulsive disorder (OCD) is associated with regional hyperactivity in cortico-striatal circuits. However, the large-scale patterns of abnormal neural connectivity remain uncharacterized. Resting-state functional connectivity (rs-fcMRI) studies have shown altered connectivity within the implicated circuitry, but they have used seed-driven approaches wherein a circuit of interest is defined a priori. This limits their ability to identify network abnormalities beyond the prevailing framework. This limitation is particularly problematic within the prefrontal cortex (PFC), which is large and heterogeneous and where a priori specification of seeds is therefore difficult. A hypothesis-neutral data-driven approach to the analysis of connectivity is vital. Method We analyzed rs-fcMRI data collected at 3T in 27 OCD patients and 66 matched controls using a recently developed data-driven global brain connectivity (GBC) method, both within the PFC and across the whole brain. Results We found clusters of decreased connectivity in the left lateral PFC in both whole-brain and PFC-restricted analyses. Increased GBC was found in the right putamen and left cerebellar cortex. Within ROIs in the basal ganglia and thalamus, we identified increased GBC in dorsal striatum and anterior thalamus, which was reduced in patients on medication. The ventral striatum/nucleus accumbens exhibited decreased global connectivity, but increased connectivity specifically with the ventral anterior cingulate cortex in subjects with OCD. Conclusion These findings identify previously uncharacterized PFC and basal ganglia dysconnectivity in OCD and reveal differentially altered GBC in dorsal and ventral striatum. Results highlight complex disturbances in PFC networks, which could contribute to disrupted cortical-striatal-cerebellar circuits in OCD. PMID:24314349

  16. 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

  17. 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

  18. Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification.

    PubMed

    Owis, Mohamed I; Abou-Zied, Ahmed H; Youssef, Abou-Bakr M; Kadah, Yasser M

    2002-07-01

    We present a study of the nonlinear dynamics of electrocardiogram (ECG) signals for arrhythmia characterization. The correlation dimension and largest Lyapunov exponent are used to model the chaotic nature of five different classes of ECG signals. The model parameters are evaluated for a large number of real ECG signals within each class and the results are reported. The presented algorithms allow automatic calculation of the features. The statistical analysis of the calculated features indicates that they differ significantly between normal heart rhythm and the different arrhythmia types and, hence, can be rather useful in ECG arrhythmia detection. On the other hand, the results indicate that the discrimination between different arrhythmia types is difficult using such features. The results of this work are supported by statistical analysis that provides a clear outline for the potential uses and limitations of these features. PMID:12083309

  19. 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. PMID:27118009

  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. 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

  2. [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. PMID:27197497

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  4. 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

  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. 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.

  7. Broadband noise suppression and feature identification of ECG waveforms using mathematical morphology and embedding theorem.

    PubMed

    Ji, T Y; Wu, Q H

    2013-12-01

    The paper presents an adaptive morphological filter developed using multiscale mathematical morphology (MM) to reject broadband noise from ECG signals without affecting the feature waveforms. As a pre-processing procedure, the adaptive morphological filter cleans an ECG signal to prepare it for further analysis. The noiseless ECG signal is embedded within a two-dimensional phase space to form a binary image and the identification of the feature waveforms is carried out based on the information presented by the image. The classification of the feature waveforms is implemented by an adaptive clustering technique according to the geometric information represented by the image in the phase space. Simulation studies on ECG records from the MIT-BIH and BIDMC databases have demonstrated the effectiveness and accuracy of the proposed methods. PMID:24094825

  8. 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.

  9. ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA.

    PubMed

    Abbaspour, Sara; Lindén, Maria; Gholamhosseini, Hamid

    2015-01-01

    This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum. PMID:25980853

  10. A 24-HOUR AMBULATORY ECG MONITORING IN ASSESSMENT OF QT INTERVAL DURATION AND DISPERSION IN ROWERS WITH PHYSIOLOGICAL MYOCARDIAL HYPERTROPHY

    PubMed Central

    Kim, Z.F.; Bilalova, R.R.; Tsibulkin, N.A.; Almetova, R.R.; Mudarisova, R.R.; Ahmetov, I.I.

    2013-01-01

    Myocardial hypertrophy (MH) due to cardiac pathology is characterized by an increase in QT interval duration and dispersion, while the findings for exercise-induced myocardial hypertrophy are contradictory. The majority of published research findings have not explored this relationship, but there have only been a few conducted studies using 24-hour ECG monitoring. The aim of the study was to determine the QT interval duration and dispersion in short-term and 24-hour ECG in endurance athletes with myocardial hypertrophy and without it. Methods: A total of 26 well-trained rowers underwent a resting 12-lead ECG, 24-hour ECG monitoring and echocardiography. Results: Athletes with MH (n = 7) at rest did not show any increase in QTc interval duration and dispersion, or mean and maximal QTc duration in Holter monitoring compared to athletes without MH (n = 19). Left ventricular mass was not significantly correlated with any QTc characteristics. Furthermore, athletes with MH had significantly longer mean QT (P = 0.01) and maximal QT (P = 0.018) intervals in Holter monitoring and higher 24-hour heart rate variability indexes due to stronger vagal effects. Conclusions: The present study demonstrated that athlete's heart syndrome with myocardial hypertrophy as a benign phenomenon does not lead to an increase in QT interval duration, or increases in maximal and mean duration in a 24-hour ECG. An increase in QT interval duration in athletes may have an autonomic nature. PMID:24744494

  11. Respiratory Motion Detection and Correction in ECG-Gated SPECT: a New Approach

    PubMed Central

    Bitarafan, Ahmad; Rajabi, Hossein; Gruy, Bernhard; Rustgou, Feridoon; Sharafi, Ali Akbar; Firoozabady, Hasan; Yaghoobi, Nahid; Malek, Hadi; Pirich, Christian; Langesteger, Werner

    2008-01-01

    Objective Gated myocardial perfusion single-photon emission computed tomography (GSPECT) has been established as an accurate and reproducible diagnostic and prognostic technique for the assessment of myocardial perfusion and function. Respiratory motion is among the major factors that may affect the quality of myocardial perfusion imaging (MPI) and consequently the accuracy of the examination. In this study, we have proposed a new approach for the tracking of respiratory motion and the correction of unwanted respiratory motion by the use of respiratory-cardiac gated-SPECT (RC-GSPECT). In addition, we have evaluated the use of RC-GSPECT for quantitative and visual assessment of myocardial perfusion and function. Materials and Methods Twenty-six patients with known or suspected coronary artery disease (CAD)-underwent two-day stress and rest 99mTc-Tetrofosmin myocardial scintigraphy using both conventional GSPECT and RC-GSPECT methods. The respiratory signals were induced by use of a CT real-time position management (RPM) respiratory gating interface. A PIO-D144 card, which is transistor-transistor logic (TTL) compatible, was used as the input interface for simultaneous detection of both ECG and respiration signals. Results A total of 26 patients with known or suspected CAD were examined in this study. Stress and rest myocardial respiratory motion in the vertical direction was 8.8-16.6 mm (mean, 12.4 ± 2.9 mm) and 7.8-11.8 mm (mean, 9.5 ± 1.6 mm), respectively. The percentages of tracer intensity in the inferior, inferoseptal and septal walls as well as the inferior to lateral (I/L) uptake ratio was significantly higher with the use of RC-GSPECT as compared to the use of GSPECT (p < 0.01). In a left ventricular ejection fraction (LVEF) correlation analysis between the use of rest GSPECT and RC-GSPECT with echocardiography, better correlation was noted between RC-GSPECT and echocardiography as compared with the use of GSPECT (y = 0.9654x + 1.6514; r = 0.93, p < 0

  12. 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

  13. 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. PMID:25900143

  14. Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation

    NASA Astrophysics Data System (ADS)

    Andreão, Rodrigo Varejão; Boudy, Jérôme

    2006-12-01

    This work aims at providing new insights on the electrocardiogram (ECG) segmentation problem using wavelets. The wavelet transform has been originally combined with a hidden Markov models (HMMs) framework in order to carry out beat segmentation and classification. A group of five continuous wavelet functions commonly used in ECG analysis has been implemented and compared using the same framework. All experiments were realized on the QT database, which is composed of a representative number of ambulatory recordings of several individuals and is supplied with manual labels made by a physician. Our main contribution relies on the consistent set of experiments performed. Moreover, the results obtained in terms of beat segmentation and premature ventricular beat (PVC) detection are comparable to others works reported in the literature, independently of the type of the wavelet. Finally, through an original concept of combining two wavelet functions in the segmentation stage, we achieve our best performances.

  15. Sleep apnea classification using ECG-signal wavelet-PCA features.

    PubMed

    Rachim, Vega Pradana; Li, Gang; Chung, Wan-Young

    2014-01-01

    Sleep apnea is often diagnosed using an overnight sleep test called a polysomnography (PSG). Unfortunately, though it is the gold standard of sleep disorder diagnosis, a PSG is time consuming, inconvenient, and expensive. Many researchers have tried to ameliorate this problem by developing other reliable methods, such as using electrocardiography (ECG) as an observed signal source. Respiratory rate interval, ECG-derived respiration, and heart rate variability analysis have been studied recently as a means of detecting apnea events using ECG during normal sleep, but these methods have performance weaknesses. Thus, the aim of this study is to classify the subject into normal- or apnea-subject based on their single-channel ECG measurement in regular sleep. In this proposed study, ECG is decomposed into five levels using wavelet decomposition for the initial processing to determine the detail coefficients (D3-D5) of the signal. Approximately 15 features were extracted from every minute of ECG. Principal component analysis and a support vector machine are used for feature dimension reduction and classification, respectively. According to classification that been done from a data set consisting of thirty-five patients, the proposed minute-to-minute classifier specificity, sensitivity, and subject-based classification accuracy are 95.20%, 92.65%, and 94.3%, respectively. Furthermore, the proposed system can be used as a basis for future development of sleep apnea screening tools. PMID:25226993

  16. A comparison of single channel fetal ECG extraction methods.

    PubMed

    Behar, Joachim; Johnson, Alistair; Clifford, Gari D; Oster, Julien

    2014-06-01

    The abdominal electrocardiogram (ECG) provides a non-invasive method for monitoring the fetal cardiac activity in pregnant women. However, the temporal and frequency overlap between the fetal ECG (FECG), the maternal ECG (MECG) and noise results in a challenging source separation problem. This work seeks to compare temporal extraction methods for extracting the fetal signal and estimating fetal heart rate. A novel method for MECG cancelation using an echo state neural network (ESN) based filtering approach was compared with the least mean square (LMS), the recursive least square (RLS) adaptive filter and template subtraction (TS) techniques. Analysis was performed using real signals from two databases composing a total of 4 h 22 min of data from nine pregnant women with 37,452 reference fetal beats. The effects of preprocessing the signals was empirically evaluated. The results demonstrate that the ESN based algorithm performs best on the test data with an F1 measure of 90.2% as compared to the LMS (87.9%), RLS (88.2%) and the TS (89.3%) techniques. Results suggest that a higher baseline wander high pass cut-off frequency than traditionally used for FECG analysis significantly increases performance for all evaluated methods. Open source code for the benchmark methods are made available to allow comparison and reproducibility on the public domain data. PMID:24604619

  17. Reading Networks at Rest

    PubMed Central

    Kelly, Clare; Shehzad, Zarrar; Penesetti, Deepak; Castellanos, F. Xavier; Milham, Michael P.

    2010-01-01

    Resting-state functional connectivity (RSFC) approaches offer a novel tool to delineate distinct functional networks in the brain. In the present functional magnetic resonance imaging (fMRI) study, we elucidated patterns of RSFC associated with 6 regions of interest selected primarily from a meta-analysis on word reading (Bolger DJ, Perfetti CA, Schneider W. 2005. Cross-cultural effect on the brain revisited: universal structures plus writing system variation. Hum Brain Mapp. 25: 92–104). In 25 native adult readers of English, patterns of positive RSFC were consistent with patterns of task-based activity and functional connectivity associated with word reading. Moreover, conjunction analyses highlighted the posterior left inferior frontal gyrus and the posterior left middle temporal gyrus (post-LMTG) as potentially important loci of functional interaction among 5 of the 6 reading networks. The significance of the post-LMTG has typically been unappreciated in task-based studies on unimpaired readers but is frequently reported to be a locus of hypoactivity in dyslexic readers and exhibits intervention-induced changes of activity in dyslexic children. Finally, patterns of negative RSFC included not only regions of the so-called default mode network but also regions involved in effortful controlled processes, which may not be required once reading becomes automatized. In conclusion, the current study supports the utility of resting-state fMRI for investigating reading networks and has direct relevance for the understanding of reading disorders such as dyslexia. PMID:20139150

  18. 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.

  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. Accuracy of pulse oximeters in estimating heart rate at rest and during exercise.

    PubMed Central

    Iyriboz, Y; Powers, S; Morrow, J; Ayers, D; Landry, G

    1991-01-01

    Pulse oximeters are being widely used for non-invasive, simultaneous assessment of haemoglobin oxygen saturation. They are reliable, accurate, relatively inexpensive and portable. Pulse oximeters are often used for estimating heart rate at rest and during exercise. However, at present the data available to validate their use as heart rate monitors are not sufficient. We evaluated the accuracy of two oximeters (Radiometer, ear and finger probe; Ohmeda 3700, ear probe) in monitoring heart rate during incremental exercise by comparing the pulse oximeters with simultaneous ECG readings. Data were collected on eight men (713 heart rate readings) during graded cycle ergometer and treadmill exercise to volitional fatigue. Analysis by linear regression revealed that general oximeter readings significantly correlated with those of ECG (r = 0.91, P less than 0.0001). However, comparison of heart rate at each level of work showed that oximeter readings significantly (P less than 0.05) under-estimated rates above 155 beats/min. These results indicate that the use of pulse oximeters as heart rate monitors during strenuous exercise is questionable. This inaccuracy may well originate from the instability of the probes, sweating, other artefacts during exercise, and measurement of different components in the cardiovascular cycle. PMID:1777787

  1. 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.

  2. Resting State Networks and Consciousness

    PubMed Central

    Heine, Lizette; Soddu, Andrea; Gómez, Francisco; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Demertzi, Athena

    2012-01-01

    In order to better understand the functional contribution of resting state activity to conscious cognition, we aimed to review increases and decreases in functional magnetic resonance imaging (fMRI) functional connectivity under physiological (sleep), pharmacological (anesthesia), and pathological altered states of consciousness, such as brain death, coma, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. The reviewed resting state networks were the DMN, left and right executive control, salience, sensorimotor, auditory, and visual networks. We highlight some methodological issues concerning resting state analyses in severely injured brains mainly in terms of hypothesis-driven seed-based correlation analysis and data-driven independent components analysis approaches. Finally, we attempt to contextualize our discussion within theoretical frameworks of conscious processes. We think that this “lesion” approach allows us to better determine the necessary conditions under which normal conscious cognition takes place. At the clinical level, we acknowledge the technical merits of the resting state paradigm. Indeed, fast and easy acquisitions are preferable to activation paradigms in clinical populations. Finally, we emphasize the need to validate the diagnostic and prognostic value of fMRI resting state measurements in non-communicating brain damaged patients. PMID:22969735

  3. Anatomic distribution of culprit lesions in patients with non-ST-segment elevation myocardial infarction and normal ECG

    PubMed Central

    Moustafa, Abdelmoniem; Abi-Saleh, Bernard; El-Baba, Mohammad; Hamoui, Omar

    2016-01-01

    Background 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. Methods 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. Results 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. Conclusions Among patients presenting with NSTEMI, prior history of CAD, male gender and abnormal admission

  4. 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. PMID:25309910

  5. 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

  6. A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

    PubMed

    Chawla, M P S; Verma, H K; Kumar, Vinod

    2008-09-16

    The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed. PMID:17655943

  7. 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

  8. ECG response of koalas to tourists proximity: a preliminary study.

    PubMed

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

    2009-01-01

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

  9. 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.

  10. A Novel Technique for Muscle Onset Detection Using Surface EMG Signals without Removal of ECG Artifacts

    PubMed Central

    Zhou, Ping; Zhang, Xu

    2014-01-01

    Surface electromyogram (EMG) signal from trunk muscles is often contaminated by electrocardiogram (ECG) artifacts. This study presents a novel method for muscle activity onset detection by processing surface EMG against ECG artifacts. The method does not require removal of ECG artifacts from raw surface EMG signals. Instead, it applies the sample entropy (SampEn) analysis to highlight EMG activity and suppress ECG artifacts in the signal complexity domain. A SampEn threshold can then be determined for detection of muscle activity. The performance of the proposed method was examined with different SampEn analysis window lengths, using a series of combinations of “clean” experimental EMG and ECG recordings over a wide range of signal to noise ratios (SNRs) from −10 dB to 10 dB. For all the examined SNRs, the window length of 128 ms yielded the best performance among all the tested lengths. Compared with the conventional amplitude thresholding and integrated profile methods, the SampEn analysis based method achieved significantly better performance, demonstrated as the shortest average latency or error among the three methods (p<0.001 for any of the examined SNRs except 10 dB). PMID:24345857

  11. Robust off-line heartbeat detection using ECG and pressure-signals.

    PubMed

    Hoeben, Bart; Teo, Soo Kng; Yang, Bo; Su, Yi

    2016-01-01

    Artefacts in pressure- and ECG-signals generally arise due to different causes. Therefore, the combined analysis of both signals can increase the effectiveness of heartbeat detection compared to analysis using solely ECG-signals. In this paper, we present an algorithm for heartbeat annotation by combining the analysis of both the pressure- and ECG-signals. The novelties of our algorithm are as follows: (1) development of a new approach for annotating heartbeats using pressure-signals, (2) development of a mechanism that identifies and corrects paced rhythms, and (3) development of a noise detection approach. Our algorithm is tested on the datasets from the extended phase of the Physionet CINC-2014 challenge and produces an overall score of 87.31%. Finally, we put forth several recommendations that could further improve our algorithm. PMID:26641478

  12. 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.

  13. 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

  14. [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. PMID:27066681

  15. Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes

    PubMed Central

    Zeng, Ke; Wang, Yinghua; Ouyang, Gaoxiang; Bian, Zhijie; Wang, Lei; Li, Xiaoli

    2015-01-01

    Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D). Method: In this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed. Results: Main findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band. Conclusions: The brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track

  16. ECG-based detection of body position changes in ischemia monitoring.

    PubMed

    García, José; Aström, Magnus; Mendive, Javier; Laguna, Pablo; Sörnmo, Leif

    2003-06-01

    The purpose of this paper is to analyze and detect changes in body position (BPC) during electrocardiogram (ECG) recording. These changes are often manifested as shifts in the electrical axis and may be misclassified as ischemic changes during ambulatory monitoring. We investigate two ECG signal processing methods for detecting BPCs. Different schemes for feature extraction are used (spatial and scalar), while preprocessing, trend postprocessing and detection are identical. The spatial approach is based on VCG loop rotation angles and the scalar approach is based on the Karhunen-Loève transform (KLT) coefficients. The methods are evaluated on two different databases: a database with annotated BPCs and the STAFF III database with recordings from rest and during angioplasty-induced ischemia but not including BPCs. The angle-based detector results in performance values of detection probability PD = 95%, false alarm probability PF = 3% in the BPC database and false alarm rate in the STAFF III database in control ECGs during rest RF(c) = 2 h(-1) (episodes per hour) and in ischemia recordings during angioplasty RF(a) = 7 h(-1), whereas the KLT-based detector produces values of PD = 89%, PF = 3%, RF(c) = 4 h(-1), and RF(a) = 11 h(-1), respectively. Including information on noise level in the detection process to reduce the number of false alarms, performance values of PD approximately equal to 90%, PF approximately equal to 1%, RF(c) approximately equal to 1 h(-1) and RF(a) approximately equal to 2 h(-1) are obtained with both methods. It is concluded that reliable detection of BPCs may be achieved using the ECG signal and should work in parallel to ischemia detectors. PMID:12814234

  17. 21 CFR 892.1970 - Radiographic ECG/respirator synchronizer.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Radiographic ECG/respirator synchronizer. 892.1970... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1970 Radiographic ECG/respirator synchronizer. (a) Identification. A radiographic ECG/respirator synchronizer is a device intended to be used...

  18. 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

  19. Accurate and consistent automatic seismocardiogram annotation without concurrent ECG.

    PubMed

    Laurin, A; Khosrow-Khavar, F; Blaber, A P; Tavakolian, Kouhyar

    2016-09-01

    Seismocardiography (SCG) is the measurement of vibrations in the sternum caused by the beating of the heart. Precise cardiac mechanical timings that are easily obtained from SCG are critically dependent on accurate identification of fiducial points. So far, SCG annotation has relied on concurrent ECG measurements. An algorithm capable of annotating SCG without the use any other concurrent measurement was designed. We subjected 18 participants to graded lower body negative pressure. We collected ECG and SCG, obtained R peaks from the former, and annotated the latter by hand, using these identified peaks. We also annotated the SCG automatically. We compared the isovolumic moment timings obtained by hand to those obtained using our algorithm. Mean  ±  confidence interval of the percentage of accurately annotated cardiac cycles were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for levels of negative pressure 0, -20, -30, -40, and  -50 mmHg. LF/HF ratios, the relative power of low-frequency variations to high-frequency variations in heart beat intervals, obtained from isovolumic moments were also compared to those obtained from R peaks. The mean differences  ±  confidence interval were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for increasing levels of negative pressure. The accuracy and consistency of the algorithm enables the use of SCG as a stand-alone heart monitoring tool in healthy individuals at rest, and could serve as a basis for an eventual application in pathological cases. PMID:27510446

  20. Exploratory Analysis of Power Spectrum and Functional Connectivity During Resting State in Young Binge Drinkers: A MEG Study.

    PubMed

    Correas, A; Rodriguez Holguín, S; Cuesta, P; López-Caneda, E; García-Moreno, L M; Cadaveira, F; Maestú, F

    2015-05-01

    Binge Drinking (BD) is a pattern of intermittent intensive alcohol intake which has spread among young adults over the last decades. Adolescence constitutes a critical neuromaturation period in which the brain is particularly sensitive to the effects of alcohol. However, little is known about how BD affects the brain activity. This study aimed to characterize the brain's functional organization in BD and non-BD young population by means of analyzing functional connectivity (FC) and relative power spectra (PS) profiles measured with magnetoencephalography (MEG) during eyes-closed resting state. Our sample composed 73 first-year university students (35 BDs and 38 controls). Results showed that the BD subjects displayed a decreased alpha FC in frontal-parietal regions, and conversely, an enhanced FC in the delta, theta and beta bands in fronto-temporal networks. Besides the FC differences, the BD group showed a decreased PS within alpha range and an increased PS within theta range in the brain's occipital region. These differences in FC and PS measurements provide new evidence of the neurophysiological alterations related to the alcohol neurotoxicity and could represent an initial sign of an anomalous neural activity caused by a BD pattern of alcohol consumption during youth. PMID:25753601

  1. Nonlocal vibration analysis of circular double-layered graphene sheets resting on an elastic foundation subjected to thermal loading

    NASA Astrophysics Data System (ADS)

    Ansari, Reza; Torabi, Jalal

    2016-06-01

    Based on the nonlocal elasticity theory, the vibration behavior of circular double-layered graphene sheets (DLGSs) resting on the Winkler- and Pasternak-type elastic foundations in a thermal environment is investigated. The governing equation is derived on the basis of Eringen's nonlocal elasticity and the classical plate theory (CLPT). The initial thermal loading is assumed to be due to a uniform temperature rise throughout the thickness direction. Using the generalized differential quadrature (GDQ) method and periodic differential operators in radial and circumferential directions, respectively, the governing equation is discretized. DLGSs with clamped and simply-supported boundary conditions are studied and the influence of van der Waals (vdW) interaction forces is taken into account. In the numerical results, the effects of various parameters such as elastic medium coefficients, radius-to-thickness ratio, thermal loading and nonlocal parameter are examined on both in-phase and anti-phase natural frequencies. The results show that the thermal load and elastic foundation respectively decreases and increases the fundamental frequencies of DLGSs.

  2. Receiver operating characteristic analysis improves diagnosis by radionuclide ventriculography

    SciTech Connect

    Dickinson, C.Z.; Forman, M.B.; Vaugh, W.K.; Sandler, M.P.; Kronenberg, M.W.

    1985-05-01

    Receiver operating characteristic analysis (ROC) evaluates continuous variables to define diagnostic criteria for the optimal sensitivity (SENS) and specificity (SPEC) of a test. The authors studied exercise-induced chest pain (CP), ST-changes on electrocardiography (ECG) and rest-exercise gated radionuclide ventriculography (RVG) using ROC to clarify the optimal criteria for detecting myocardial ischemia due to coronary artherosclerosis (CAD). The data of 95 consecutive patients studied with coronary angiography, rest-exercise RVG and ECG were reviewed. 77 patients had ''significant'' CAD (greater than or equal to50% lesions). Exercise-induced CP, ECG abnormalities (ST-T shifts) and RVG abnormalities (change in ejection fraction, 2-view regional wall motion change and relative end-systolic volume) were evaluated to define optimal SENS/SPEC of each and for the combined data. ROC curves were constructed by multiple logistic regression (MLR). By MLR, RVG alone was superior to ECG and CP. The combination of all three produced the best ROC curve for the entire group and for clinical subsets based on the number of diseased vessels and the presence or absence of prior myocardial infarction. When CP, ECG and RVG were combined, the optimal SENS/SPEC for detection of single vessel disease was 88/86. The SENS/SPEC for 3 vessel disease was 93/95. Thus, the application of RVG for the diagnosis of myocardial ischemia is improved with the inclusion of ECG and CP data by the use of a multiple logistic regression model. ROC analysis allows clinical application of multiple data for diagnosing CAD at desired SENS/SPEC rather than by arbitrary single-standard criteria.

  3. Foetal ECG recovery using dynamic neural networks.

    PubMed

    Camps-Valls, Gustavo; Martínez-Sober, Marcelino; Soria-Olivas, Emilio; Magdalena-Benedito, Rafael; Calpe-Maravilla, Javier; Guerrero-Martínez, Juan

    2004-07-01

    Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coefficient) and statistical (analysis of variance, ANOVA) measures allows us to select the best recovery model. Finally, finite impulse response (FIR) and gamma neural networks are included in the adaptive noise cancellation (ANC) scheme in order to provide highly non-linear, dynamic capabilities to the recovery model. Neural networks are benchmarked with classical adaptive methods such as the least mean squares (LMS) and the normalized LMS (NLMS) algorithms in simulated and real registers and some conclusions are drawn. For synthetic registers, the most determinant factor in the identification of the models is the foetal-maternal signal-to-noise ratio (SNR). In addition, as the electromyogram contribution becomes more relevant, neural networks clearly outperform the LMS-based algorithm. From the ANOVA test, we found statistical differences between LMS-based models and neural models when complex situations (high foetal-maternal and foetal-noise SNRs) were present. These conclusions were confirmed after doing robustness tests on synthetic registers, visual inspection of the recovered signals and calculation of the recognition rates of foetal R-peaks for real situations. Finally, the best compromise between model complexity and outcomes was provided by the FIR neural network. Both

  4. A critical appraisal of the evidence for using cardiotocography plus ECG ST interval analysis for fetal surveillance in labor. Part II: the meta-analyses

    PubMed Central

    Olofsson, Per; Ayres-de-Campos, Diogo; Kessler, Jörg; Tendal, Britta; Yli, Branka M; Devoe, Lawrence

    2014-01-01

    We appraised the methodology, execution and quality of the five published meta-analyses that are based on the five randomized controlled trials which compared cardiotocography (CTG)+ST analysis to cardiotocography. The meta-analyses contained errors, either created de novo in handling of original data or from a failure to recognize essential differences among the randomized controlled trials, particularly in their inclusion criteria and outcome parameters. No meta-analysis contained complete and relevant data from all five randomized controlled trials. We believe that one randomized controlled trial excluded in two of the meta-analyses should have been included, whereas one randomized controlled trial that was included in all meta-analyses, should have been excluded. After correction of the uncovered errors and exclusion of the randomized controlled trial that we deemed inappropriate, our new meta-analysis showed that CTG+ST monitoring significantly reduces the fetal scalp blood sampling usage (risk ratio 0.64; 95% confidence interval 0.47–0.88), total operative delivery rate (0.93; 0.88–0.99) and metabolic acidosis rate (0.61; 0.41–0.91). PMID:24797318

  5. QRS detection based ECG quality assessment.

    PubMed

    Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter

    2012-09-01

    Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available. PMID:22902864

  6. Human Identification Using Compressed ECG Signals.

    PubMed

    Camara, Carmen; Peris-Lopez, Pedro; Tapiador, Juan E

    2015-11-01

    As a result of the increased demand for improved life styles and the increment of senior citizens over the age of 65, new home care services are demanded. Simultaneously, the medical sector is increasingly becoming the new target of cybercriminals due the potential value of users' medical information. The use of biometrics seems an effective tool as a deterrent for many of such attacks. In this paper, we propose the use of electrocardiograms (ECGs) for the identification of individuals. For instance, for a telecare service, a user could be authenticated using the information extracted from her ECG signal. The majority of ECG-based biometrics systems extract information (fiducial features) from the characteristics points of an ECG wave. In this article, we propose the use of non-fiducial features via the Hadamard Transform (HT). We show how the use of highly compressed signals (only 24 coefficients of HT) is enough to unequivocally identify individuals with a high performance (classification accuracy of 0.97 and with identification system errors in the order of 10(-2)). PMID:26364201

  7. ECG biometric identification: A compression based approach.

    PubMed

    Bras, Susana; Pinho, Armando J

    2015-08-01

    Using the electrocardiogram signal (ECG) to identify and/or authenticate persons are problems still lacking satisfactory solutions. Yet, ECG possesses characteristics that are unique or difficult to get from other signals used in biometrics: (1) it requires contact and liveliness for acquisition (2) it changes under stress, rendering it potentially useless if acquired under threatening. Our main objective is to present an innovative and robust solution to the above-mentioned problem. To successfully conduct this goal, we rely on information-theoretic data models for data compression and on similarity metrics related to the approximation of the Kolmogorov complexity. The proposed measure allows the comparison of two (or more) ECG segments, without having to follow traditional approaches that require heartbeat segmentation (described as highly influenced by external or internal interferences). As a first approach, the method was able to cluster the data in three groups: identical record, same participant, different participant, by the stratification of the proposed measure with values near 0 for the same participant and closer to 1 for different participants. A leave-one-out strategy was implemented in order to identify the participant in the database based on his/her ECG. A 1NN classifier was implemented, using as distance measure the method proposed in this work. The classifier was able to identify correctly almost all participants, with an accuracy of 99% in the database used. PMID:26737619

  8. A Mathematical Model for Segmenting ECG Signals

    NASA Astrophysics Data System (ADS)

    Feier, Horea; Roşu, Doina; Falniţǎ, Lucian; Roşu, Şerban; Pater, Liana

    2010-09-01

    This paper deals with the behavior of the modulus of the continuous wavelet transform (CWT) for some known mother wavelets like the Morlet wavelet and the Mexican Hat. By exploiting these properties, the models presented can behave as a segmentation/ recognition signal processing tool by modeling the temporal structure of the observed surface ECG.

  9. Computer Interpretations of ECGs in Rural Hospitals

    PubMed Central

    Thompson, James M.

    1992-01-01

    Computer-assisted interpretation of electrocardiograms offers theoretical benefits to rural physicians. This study compared computer-assisted interpretations by a rural physician certified to read ECGs with interpretations by the computer alone. The computer interpretation alone could have led to major errors in patient management, but was correct sufficiently often to warrant purchase by small rural hospitals. PMID:21221365

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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