A universal ECG signal classification system using the wavelet transform

Abstract

The electrocardiograph (ECG) is one of the most successful medical diagnostic tools. The ECG can show, roughly speaking, all types of heart disordersthat appear as ECG signal arrhythmias or problems with the rate or rhythm of thehuman heartbeat. In this paper, a universal ECG signal arrhythmia classificationsystem is proposed. The proposed system is based on using the wavelet transformin two of its known forms, namely, the discrete wavelet transform (DWT) andthe wavelet packet transform (WPT), or a combination thereof. The purpose ofthe research reported herein is to find out a universal classification system; in thesense of providing a capability for simultaneous classification of all types of known heart arrhythmias. Three algorithms based on the wavelet transform are tested for different wavelet levels, wavelet functions, training and testing ratios, and elapsed times. We rank these algorithms according to the elapsed times needed for their processing over the whole loop of the eight different arrhythmia classes. This ranking nominates the WPT-based algorithm to be the most superior method among the competing methods. A different ranking according to successful recognition rates assigns priority instead to the method combining the WPT and the DWT.