M. Turnip, A. Dharma, D. Pamungkas, Dwi Esti K. Arjon Turnip
{"title":"An Application of Zero Cross QRS Detection Algorithm of ECG Signals with Various Subject Conditions","authors":"M. Turnip, A. Dharma, D. Pamungkas, Dwi Esti K. Arjon Turnip","doi":"10.1109/INCAE.2018.8579419","DOIUrl":null,"url":null,"abstract":"Interpretation of electrocardiogram (ECG) is one of the main research interests in bio-medical signal processing. The reason for the development of research on this interest are the growth in the heart health care all over the word, on the other hand the growth of digital technology makes it easier to detect disease from bio-signals. An application of support vector machine technique for ECG signals analysis is applied. To evaluate the proposed method, a practical experiment with two conditions of subjects (relax and typing) is conducted. With selected feature, the QRS detection average accuracy of 92.48% is achieved. It can be conclude that the applied method with various raw data provides a good results to diagnose pattern of cardiac arrhythmia disease.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Applied Engineering (ICAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCAE.2018.8579419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Interpretation of electrocardiogram (ECG) is one of the main research interests in bio-medical signal processing. The reason for the development of research on this interest are the growth in the heart health care all over the word, on the other hand the growth of digital technology makes it easier to detect disease from bio-signals. An application of support vector machine technique for ECG signals analysis is applied. To evaluate the proposed method, a practical experiment with two conditions of subjects (relax and typing) is conducted. With selected feature, the QRS detection average accuracy of 92.48% is achieved. It can be conclude that the applied method with various raw data provides a good results to diagnose pattern of cardiac arrhythmia disease.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
