ANALYSIS OF SAVITZKY-GOLAY FILTER FOR BASELINE WANDER CANCELLATION IN ECG USING WAVELETS

Electrocardiogram (ECG) has always been the most basic useful and low cost tool for diagnosis. Various kinds of noises can contaminate the ECG signals which lead to incorrect diagnosis. In this paper a new method is developed for removal of baseline wander based on Daubechies wavelet decomposition using adaptive thresholding techniques and Savitzky-Golay filtering. Here ECG records are taken from non-invasive fetal electrocardiogram database, noise is generated using MATLAB instructions and added to original ECG signal. In fact DWT has the quality of better signal decomposition and thresholding has the ability of removing noise from decomposed signal. If we apply Savitzky-Golay filter further then preserving the peak it can smooth out the signal without much destroying its original property. In this paper we have done a comparative study between our proposed method and conventional wavelet method consisting only Daubechies wavelet decomposition along with thresholding techniques. This comparison is done by evaluating different statistical parameters like mean square error (MSE), signal to interference ratio (SIR) and peak signal to noise ratio (PSNR).