Maie Aboghazalah^1,*, Passent El-kafrawy², Abdelmoty M. Ahmed³, Rasha Elnemr⁵, Belgacem Bouallegue³, Ayman El-sayed⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3855-3875, 2024, DOI:10.32604/cmc.2023.039936 - 20 June 2024

Abstract Heart monitoring improves life quality. Electrocardiograms (ECGs or EKGs) detect heart irregularities. Machine learning algorithms can create a few ECG diagnosis processing methods. The first method uses raw ECG and time-series data. The second method classifies the ECG by patient experience. The third technique translates ECG impulses into Q waves, R waves and S waves (QRS) features using richer information. Because ECG signals vary naturally between humans and activities, we will combine the three feature selection methods to improve classification accuracy and diagnosis. Classifications using all three approaches have not been examined till now. Several More >

Elio Caruso^1,*, Silvia Farruggio¹, Alfredo Di Pino¹, Paolo Guccione¹, Mohammadrafie Khorgami²

Congenital Heart Disease, Vol.17, No.5, pp. 551-556, 2022, DOI:10.32604/chd.2022.023711 - 06 September 2022

Abstract We present the case of an infant admitted to our department for a rapid broad complex tachycardia and cardiovascular collapse. The patient was submitted to genetic testing because of a conduction defect at baseline ECG and family history of gene mutation. A new SCN5A gene mutation variant was found leading to diagnosis of sodium-channel dysfunction arrhythmia. More > Graphic Abstract

Ashraf Ahmed¹, Yousef AbuHour^2,*, Ammar El-Hassan¹

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 979-990, 2022, DOI:10.32604/iasc.2022.020726 - 17 November 2021

Abstract The Corona (COVID-19) epidemic has triggered interest in many fields of technology, medicine, science, and politics. Most of the mathematical research in this area focused on analyzing the dynamics of the spread of the virus. In this article, after a review of some current methodologies, a non-linear system of differential equations is developed to model the spread of COVID-19. In order to consider a wide spectrum of scenarios, we propose a susceptible-exposed-infected-quarantined-recovered (SEIQRS)-model which was analyzed to determine threshold conditions for its stability, and the number of infected cases that is an infected person will… More >

Jianbo Xu, Wenxi Chen^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1807-1819, 2022, DOI:10.32604/cmc.2022.021154 - 03 November 2021

Abstract This study proposes a convolutional neural network (CNN)-based identity recognition scheme using electrocardiogram (ECG) at different water temperatures (WTs) during bathing, aiming to explore the impact of ECG length on the recognition rate. ECG data was collected using non-contact electrodes at five different WTs during bathing. Ten young student subjects (seven men and three women) participated in data collection. Three ECG recordings were collected at each preset bathtub WT for each subject. Each recording is 18 min long, with a sampling rate of 200 Hz. In total, 150 ECG recordings and 150 WT recordings were… 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 - 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 >

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 More >