PC Based Digital Signal Processing of ECG Signals

Abstract: Due to fast advancement in the technology, scientists and engineers are facing several challenges in solving biomedical problem; Digital Signal Processing has become an essential and effective pedagogical approach to solve a problem of detecting selected arrhythmia conditions from a patient’s electrocardiograph (ECG) signals. Finding arrhythmia characteristics corresponding to Atrial Fibrillation (AF), heart rate variability (HRV), etc., from ECG recording have received considerable attention in recent years. Several advanced signal processing techniques have been applied for cardiac arrhythmia detection using Fourier Transforms, Wavelets, Artificial Neural Networks, Independent Component Analysis, etc. Introducing a simple algorithm for arrhythmia detection can be very useful for better conceptual understanding of signal processing. In this paper, simple methods have been discussed to clean ECG signal corrupted by noise and to extract required parameters for detecting arrhythmia condition. These simple procedures involve using filter techniques, wavelet techniques, algorithms of finding peaks & valleys, local maxima & minima etc, for determining R peaks, R-R intervals and QRS amplitude.

Keywords: ECG, HRV, filter, QRS, lead, MATLAB