R peak Detection for Wireless ECG using DWT and Entropy of coefficients

Abstract

Investigation of patient's electrocardiogram helps to diagnose various heart related diseases. With correct R peak detection in ECG wave, classification of arrhythmia can be carried out accurately. However, accurate R peak detection is a big challenge especially in wireless patient monitoring system. In wireless ECG system, in order to reduce the power consumption; it is desirable to capture ECG at lower sampling rate. This paper proposes an algorithm for R peak detection using discrete wavelet transform in which detailed coefficients are selected based on entropy. The proposed algorithm is validated with MIT-BIH database and its performance is compared with similar work. For MIT-BIH case, positive predictivity and sensitivity for proposed algorithm are 99.85 and 99.73, respectively. Application of proposed algorithm on wireless ECG, acquired at adjustable sampling rate from different subjects using prototype Bluetooth ECG module, shows efficacy of algorithm to detect R peak of ECG with high accuracy.