Arrhythmia Discrimination Using Support Vector Machine

被引：0
|
作者：
Rani, Monika [1 ]
Ekta [1 ]
Devi, Reeta [1 ]
机构：
[1] Kurukshetra Univ, UIET, Kurukshetra, Haryana, India
来源：
PROCEEDINGS OF 4TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMPUTING AND CONTROL (ISPCC 2K17) | 2017年
关键词：
Arrhythmia; ECG; Wavelet Transform; features; SVM;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper support vector machine (SVM) classifier is developed for the classification of two types of arrhythmias i.e. premature ventricular contraction (PVC) and atrial premature contraction (APC). Discrete wavelet transform (DWT) is used for feature extraction of the ECG signal. For the classification purpose MIT-BIH arrhythmia database is used from the physionet.org. The aim of the work is to develop a technique which classifies the arrhythmia with higher accuracy. MATLAB 7.8.0(R2009a) is used for the simulation purpose.
引用
收藏
页码：283 / 287
页数：5
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