A Novel ECG Beats Classification Scheme Using Differentiated DWT and SVM

被引：0

作者：

Mishra, Premananda ^{[1
]}

Agrawal, Sanjay ^{[1
]}

Panda, Rutuparna ^{[1
]}

机构：

[1] VSSUT, Dept EL & TCE, Burla, India

来源：

IEEE INDICON: 15TH IEEE INDIA COUNCIL INTERNATIONAL CONFERENCE | 2018年

关键词：

Electrocardiogram; Daubechies wavelet transform; spline wavelet; R-peak; QRS; SVM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A lot of research is going on for the analysis of Electrocardiogram signal to study the heart condition. The presence of various noise such as baseline wandering, power line interference, noise due to body part movement makes it difficult for proper diagnosis. A number of methods are proposed in the literature for de-noising of the Electrocardiogram signal. In this paper, a level IV differentiated spline wavelet is used to de-noise the signal. Further, Daubechies wavelet is used to extract the features of the signal to check the abnormalities for subsequent treatment planning. The extracted features are used for classification of Electrocardiogram beats into normal or abnormal beats using SVM classifier. The proposed scheme is tested with MIT-BIH Arrhythmias Database from PhysioNet. The proposed method is compared with three other methods with similar dataset. It is observed that the results obtained are encouraging.

引用

页数：6

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