Thesis

QRS detection using wavelet transform

The electrocardiogram (ECG) provides information about the heart. ECG is a biological signal which generally changes its physiological and statistical property with respect to time, tending to be non-stationary signal. For studying such types of signals wavelet transforms are very useful. The most striking waveform when considering the ECG is QRS wave complex which gives the R wave peak which is time-varying. This report describes an algorithm for detection of QRS complex using the Wavelet transform. This detector is reliable to QRS complex morphology and properties which changes with time and also to the noise in the signal. The performance of the Wavelet transform based QRS detector is illustrated by testing ECG signals from MIT Arrhythmia database. We also compare the performance of Wavelet based QRS detector with detectors using Derivative based method. From the comparison, the Wavelet detector exhibited superior performance for different ECG signals like multiform premature ventricular contractions, bigemy and noisy signals.

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