Automatic Heart Disease Detection by Classification of Ventricular Arrhythmias on ECG Using Machine Learning
作者机构：Department of Computer Science and Information TechnologyUniversity of SargodhaSargodha40100Pakistan School of Systems and TechnologyUniversity of Management and TechnologyLahore54782Pakistan COMSAT University IslamabadWah CampusWah CanttPakistan College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of ICT ConvergenceSoonchunhyang UniversityAsan31538Korea Department of Computer ScienceHITEC University TaxilaPakistan
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2022年第71卷第4期
页 面：17-33页
核心收录：
学科分类：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)] 10[医学]
基 金：This research was supported by the MSIT(Ministry of Science and ICT) Korea under the ICAN(ICT Challenge and Advanced Network of HRD)program(IITP-2021-2020-0-01832)supervised by the IITP(Institute of Information&Communications Technology Planning&Evaluation)and the Soonchunhyang University Research Fund
主 题：Heart disease signals preprocessing detection machine learning
摘 要：This paper focuses on detecting diseased signals and arrhythmias classification into two classes:ventricular tachycardia and premature ventricular *** sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick *** proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency(IF).Once a signal taken from a patient is detected,then the classifier takes that signal as input and classifies the target disease by predicting the class *** applying the classifier,templates are designed separately for ventricular tachycardia and premature ventricular *** of a given signal with both the templates are computed in the spectral *** empirical analysis reveals precisions for the detector and the applied classifier are 100%and 77.27%,***,instantaneous frequency analysis provides a benchmark that IF of a normal signal ranges from 0.8 to 1.1 Hz whereas IF range for ventricular tachycardia and premature ventricular contraction is 0.08–0.6 *** indicates a serious loss of high-frequency contents in the spectrum,implying that the heart’s overall activity is slowed *** study may help medical practitioners in detecting the heart disease type based on signal analysis.
维普期刊数据库