Jamal Kh-Madhloom^1,2,*, Mohd Khanapi Abd Ghani¹, Mohd Rizuan Baharon¹

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 493-512, 2021, DOI:10.32604/iasc.2021.015129

Abstract Over the decades, protecting the privacy of a health cloud using the design of a fog computing network is a very important field and will be more important in the near future. Current Internet of Things (IoT) research includes security and privacy due to their extreme importance in any growing technology that involves the implementation of cryptographic Internet communications (ICs) for protected IC applications such as fog computing and cloud computing devices. In addition, the implementation of public-key cryptography for IoT-based DNA sequence testing devices requires considerable expertise. Any key can be broken by using a brute-force attack with ample… More >

Ratha Yeu¹, Namhui Ra², Seong-A Lee³, Yunyoung Nam^4,*

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

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, and in cold water. In… More >

Amjad Gawanmeh^1,3,∗, Usman Pervez², Osman Hasan^2,3

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 model checking, which is a… More >

Xin Liu^1,*, Yujuan Si^1,2, 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, this paper proposes to build… More >

Gyu Ho Choi^a, Jae Hyo Jung^b, Hae Min Moon^c, Youn Tae Kim^b, Sung Bum Pan^c

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 proposed system includes the steps… More >

Yunxiang Zhao¹, Jinyong Cheng^{1, *}, Ping Zhang¹, Xueping Peng²

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

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 classify them. This paper applies… More >

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

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 were seen at our… More >

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 pediatric EPs to… More >

Jun Oyamada¹, Chisato Shimizu¹, Jihoon Kim², Matthew R. Williams^1,3, Eileen Png⁴, Martin L. Hibberd⁴, Adriana H. Tremoulet^1,3, James C. Perry^1,3, Jane C. Burns^1,3

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 T waves… More >

Zhong Liu^1,2, Xinan Wang^1,*, 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 signal, low frequency, large variation,… More >