Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals.

Muhammad Adam,Shu Lih Oh,K. Vidya Sudarshan,Joel E. W. Koh,Yuki Hagiwara,Jen-Hong Tan,Ru San Tan,U. Rajendra Acharya

Computer Methods and Programs in Biomedicine（2018）

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摘要

•Classification of normal, DCM, HCM and MI ECG signals.•Four seconds of ECG segments are used.•Nonlinear features are extracted from DWT decomposition.•Feature selection is done using SFS and ReliefF method.•Obtained accuracy of 99.27% using 15 features with kNN classifier.

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关键词

Cardiovascular disease,Dilated cardiomyopathy,Hypertrophic cardiomyopathy,Myocardial infarction,Electrocardiogram,Discrete wavelet transform

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