Performance Comparison of Windowing Techniques for ECG Signal Enhancement

Abstract

Electrocardiogram (ECG) signal is generally corrupted by various artifacts like baseline wander, power line interference (50/60 Hz) and electromyography noise and these must be removed before diagnosis. The task propounded in this article is removal of low frequency interference i.e. baseline wandering and high frequency noise i.e. electromyography in ECG signal and digital filters are implemented to delete it. The digital filters accomplished are FIR with various windowing methods as of Rectangular, Hann, Blackman, Hamming, and Kaiser. The results received are at order of 300, 450, 600. The signal taken of the MIT-BIH database which contains the normal and abnormal waveforms. The work has been in MATLAB where filters are implemented in FDA Tool. The result received for entire FIR filters with various windows are evaluated the waveforms, power spectrums density, signal to noise ratio (SNR) and means square error (MSE) of the noisy and filtered ECG signals. The filter which shows the excellent outcomes is the Kaiser Window.