Single Scale CWT Algorithm for ECG Beat Detection for a Portable Monitoring System

Abstract

This paper introduces an algorithm for ECG beat detection for portable monitoring systems using the continuous wavelet transform technique. It uses the Mexican-Hat wavelet as an analyzing wavelet. The central frequency of the corresponding band-pass filter frequency response is chosen to be 32 Hz after performing scale analysis. It relies on the adaptive threshold technique to minimize the number of false positive beats and therefore guarantee robustness against high motion artifact noise levels, it also relies on search back to avoid missing real heart beats and hence obtain a high sensitivity. The algorithm was implemented using MATLAB and has a sensitivity Se = 99.37% and a positive predictivity P+ = 99.83% with the MIT-BIH arrhythmia database. Furthermore, in order to test the performance of the algorithm against motion artifact noise, a noise stress test was performed by adding motion artifact noise to the ECG records of the same database at various signal to noise ratio values. The results of the noise stress test were benchmarked against some existing algorithms in the literature such as Pan and Tompkins and Romero.