ECG classification using wavelet transform and Discriminant Analysis

Abstract

This paper focuses on two cardiac conditions, the supraventricular ectopy and the ventricular ectopy. Four different mother wavelets are used to produce sets of features. Results shows that each cardiac conditions beat has its own unique characteristics and also decomposition of different mother wavelet produced different degree in discriminative power. The Discriminant Analysis Classifier of different distance metric (linear, quadratic and mahalanobis) are tested. Classification performance mostly reached more than 90% for both individual feature and combined feature classification.