Arrhythmia Prediction on Optimal Features Obtained from the ECG as Images

作     者：Fuad A.M.Al-Yarimi 

作者机构：Department of Computer ScienceKing Khalid UniversityAbhaKingdom of Saudi Arabia 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第44卷第1期

页      面：129-142页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 0802[工学-机械工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

基　　金：The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under Grant Number(R.G.P1/155/40/2019) 

主　　题：ECG records electrocardiogram morphological features(MF) empirical mode decomposition algorithm HOS 

摘      要：A critical component of dealing with heart disease is real-time identifi-cation,which triggers rapid *** main challenge of real-time identification is illustrated here by the rare occurrence of cardiac *** contribu-tions to cardiac arrhythmia prediction using supervised learning approaches gen-erally involve the use of demographic features(electronic health records),signal features(electrocardiogram features as signals),and temporal *** the signal of the electrical activity of the heartbeat is very sensitive to differences between high and low heartbeats,it is possible to detect some of the irregularities in the early stages of *** paper describes the training of supervised learning using features obtained from electrocardiogram(ECG)image to correct the limitations of arrhythmia prediction by using demographic and electrocardio-graphic signal *** experimental study demonstrates the usefulness of the proposed Arrhythmia Prediction by Supervised Learning(APSL)method,whose features are obtained from the image formats of the electrocardiograms used as input.