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  • Open Access

    ARTICLE

    Evaluation of Pencil Lead Based Electrodes for Electrocardiogram Monitoring in Hot Spring

    Ratha Yeu1, Namhui Ra2, Seong-A Lee3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1411-1425, 2021, DOI:10.32604/cmc.2020.013761 - 26 November 2020

    Abstract Electrocardiogram (ECG) electrodes are conductive pads applied to the skin to measure cardiac activity. Ag/AgCl electrodes are the commercial product which widely used to obtain ECGs. When monitoring the ECG in a hot spring, Ag/AgCl electrodes must be waterproofed; however, this is time-consuming, and the adhesive may tear the skin on removal. For solving the problem, we developed the carbon pencil lead (CPL) electrodes for use in hot springs. Both CPL and Ag/AgCl electrodes were connected to ECG100C’s cables. The Performance was evaluated in three conditions as following: hot spring water with and without bubble,… More >

  • Open Access

    ARTICLE

    LSTM Neural Network for Beat Classification in ECG Identity Recognition

    Xin Liu1,*, Yujuan Si1,2, Di Wang1

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 341-351, 2020, DOI:10.31209/2019.100000104

    Abstract As a biological signal existing in the human living body, the electrocardiogram (ECG) contains abundantly personal information and fulfils the basic characteristics of identity recognition. It has been widely used in the field of individual identification research in recent years. The common process of identity recognition includes three steps: ECG signals preprocessing, feature extraction and processing, beat classification recognition. However, the existing ECG classification models are sensitive to limitations of database type and extracted features dimension, which makes classification accuracy difficult to improve and cannot meet the needs of practical applications. To tackle the problem,… More >

  • Open Access

    ARTICLE

    ECG Classification Using Deep CNN Improved by Wavelet Transform

    Yunxiang Zhao1, Jinyong Cheng1, *, Ping Zhang1, Xueping Peng2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1615-1628, 2020, DOI:10.32604/cmc.2020.09938 - 30 June 2020

    Abstract Atrial fibrillation is the most common persistent form of arrhythmia. A method based on wavelet transform combined with deep convolutional neural network is applied for automatic classification of electrocardiograms. Since the ECG signal is easily inferred, the ECG signal is decomposed into 9 kinds of subsignals with different frequency scales by wavelet function, and then wavelet reconstruction is carried out after segmented filtering to eliminate the influence of noise. A 24-layer convolution neural network is used to extract the hierarchical features by convolution kernels of different sizes, and finally the softmax classifier is used to More >

  • Open Access

    ARTICLE

    QRS Duration and Outcome Late after Repair of Tetralogy of Fallot: Neurohormonal Activation Differentiates between Mechanical and Electrical Dyssynchrony

    Matthias Schneider*, Miriam Moser, Varius Dannenberg, Andreas Mangold, Robert Schönbauer, Christian Hengstenberg, Harald Gabriel

    Congenital Heart Disease, Vol.15, No.1, pp. 51-58, 2020, DOI:10.32604/CHD.2020.011712 - 17 June 2020

    Abstract Background: Predicting the probability for sudden cardiac death (SCD) and thus evaluation of patients for electrical device therapy and/or ablation is one of the main tasks in clinics for adults with congenital heart disease (ACHD) following repaired tetralogy of Fallot (rTOF) patients. Previous data suggests that QRS complex analysis can help identifying those patients who subsequently suffer from SCD. We hypothesized that a long QRS duration is associated with adverse rhythm events if caused by conduction abnormalities but not if caused by right ventricular remodeling. Methods: A retrospective analysis was performed entailing all rTOF patients who… More >

  • Open Access

    ARTICLE

    User Authentication System Based on Baseline‐corrected ECG for Biometrics

    Gyu Ho Choia, Jae Hyo Jungb, Hae Min Moonc, Youn Tae Kimb, Sung Bum Panc

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 193-204, 2019, DOI:10.31209/2018.100000055

    Abstract Recently, ECG-based user authentication technology, which is strong against forgery and falsification, has been actively studied compared to fingerprint and face authentication. It is impossible to measure the open ECG DB measured with expensive medical equipment in daily living, and the ECG measured with the developed device for easy ECG measurement has much noise. In this paper, we developed a device that easily measures the ECG for user authentication in everyday life, measured the ECG through the development equipment, adjusted the baseline correction of the measured ECG, extracted it from the adjusted ECG do. The More >

  • Open Access

    ARTICLE

    Bifid T waves on the ECG and genetic variation in calcium channel voltage‐dependent beta 2 subunit gene (CACNB2) in acute Kawasaki disease

    Jun Oyamada1, Chisato Shimizu1, Jihoon Kim2, Matthew R. Williams1,3, Eileen Png4, Martin L. Hibberd4, Adriana H. Tremoulet1,3, James C. Perry1,3, Jane C. Burns1,3

    Congenital Heart Disease, Vol.14, No.2, pp. 213-220, 2019, DOI:10.1111/chd.12696

    Abstract Background: We previously described the association of genetic variants in calcium channel genes and susceptibility to Kawasaki disease (KD), an acute, self‐limited vas‐ culitis, and the most common cause of acquired cardiac disease in children. Abnormal repolarization of cardiomyocytes and changes in T wave morphology have been re‐ ported in KD but have not been studied systematically.
    Methods: We analyzed acute and convalescent ECG T wave morphology in two inde‐ pendent cohorts of KD subjects and studied the association between bifid T waves and genetic variants in previously reported genes with SNVs associated with cardiac repolarization.
    Results: Bifid… More >

  • Open Access

    RETRACTION

    RETRACTED: Automatic Arrhythmia Detection Based on Convolutional Neural Networks

    Zhong Liu1,2, Xinan Wang1,*, Kuntao Lu1, David Su3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 497-509, 2019, DOI:10.32604/cmc.2019.04882

    Abstract ECG signal is of great importance in the clinical diagnosis of various heart diseases. The abnormal origin or conduction of excitation is the electrophysiological mechanism leading to arrhythmia, but the type and frequency of arrhythmia is an important indicator reflecting the stability of cardiac electrical activity. In clinical practice, arrhythmic signals can be classified according to the origin of excitation, the frequency of excitation, or the transmission of excitation. Traditional heart disease diagnosis depends on doctors, and it is influenced by doctors' professional skills and the department's specialty. ECG signal has the characteristics of weak More >

  • Open Access

    ARTICLE

    Probabliistic Analysis Of Electrocardiogram (Ecg) Heart Signal

    Amjad Gawanmeh1,3,∗, Usman Pervez2, Osman Hasan2,3

    Computer Systems Science and Engineering, Vol.33, No.1, pp. 21-29, 2018, DOI:10.32604/csse.2018.33.021

    Abstract Electrocardiography (ECG) is a heart signal wave that is recorded using medical sensors, which are normally attached to the human body by the heart. ECG waves have repetitive patterns that can be efficiently used in the diagnosis of heart problems as they carry several characteristics of heart operation. Traditionally, the analysis of ECG waves is done using informal techniques, like simulation, which is in-exhaustive and thus the analysis results may lead to ambiguities and life threatening scenarios in extreme cases. In order to overcome such problems, we propose to analyze ECG heart signals using probabilistic More >

  • Open Access

    ARTICLE

    Utility of incomplete right bundle branch block as an isolated ECG finding in children undergoing initial cardiac evaluation

    Omar Meziab, Dominic J. Abrams, Mark E. Alexander, Laura Bevilacqua, Vassilios Bezzerides, Doug Y. Mah, Edward P. Walsh, John K. Triedman

    Congenital Heart Disease, Vol.13, No.3, pp. 419-427, 2018, DOI:10.1111/chd.12589

    Abstract Objective: This study evaluates the ability of experienced pediatric electrophysiologists (EPs) to reliably classify incomplete right bundle branch block (IRBBB) and assesses its clinical utility as an isolated ECG finding in a group of healthy outpatient children without prior cardiac evaluation.
    Design: We performed a retrospective analysis of all electrocardiographic and echocardiographic records at Boston Children’s Hospital between January 1, 2005, and December 31, 2014. Echocardiographic diagnoses were identified if registered between the date of the index electrocardiogram and the ensuing year. A selected subset of 473 ECGs was subsequently reanalyzed in a blinded manner by six… More >

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