Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal

作者：

Highlights：

• Classification of normal, CAD, MI and CHF classes using ECG beat is proposed

• CWT transform is performed on ECG beat

• Contourlet and shearlet transforms are performed on scalogram

• First and second order statistical features are extracted

• Obtained an accuracy of 99.55% using contourlet transform

摘要

•Classification of normal, CAD, MI and CHF classes using ECG beat is proposed•CWT transform is performed on ECG beat•Contourlet and shearlet transforms are performed on scalogram•First and second order statistical features are extracted•Obtained an accuracy of 99.55% using contourlet transform

论文关键词：Coronary artery disease,Myocardial infarction,Congestive heart failure,Electrocardiogram,Continuous wavelet transform,Contourlet and shearlet transforms

论文评审过程：Received 31 March 2017, Revised 16 June 2017, Accepted 17 June 2017, Available online 21 June 2017, Version of Record 24 July 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.06.026