ECG Signal De-noising using Discrete Wavelet Transform

In this paper, wavelet de-noising method has been examined to eliminate noise from the ECG signal. Different thresholding algorithms are analyzed both theoretically and empirically. Ideal ECG signal and noise corrupted ECG signal are evaluated using MATLAB. Removal of noise because of muscle activity is difficult to handle because of the substantial spectral overlap between the ECG and muscle noise. Averaging techniques have been successfully applied to ECG signal for reduction of baseline wander noise. DWT has good ability to decompose the signal and wavelet thresholding is good in removing noise from decomposed signal. We applied wavelet transform on the input vector, thresholded it, inverse transformed it to finally achieve a signal with very low EMG noise. The analyses of thresholding techniques have been compared based on signal to noise ratio. It is observed that “rigrsure” method gives optimum performance.