Wavelet denoising of the electrocardiogram signal based on the corrupted noise estimation
Sid Ahmed Chouakri, Fethi Bereksi-Reguig, Saïd Ahmaidi, Odette Fokapu · 2005
We present in this paper an algorithm of filtering the noisy real ECG signal. The classical wavelet denoising process, based on the Donoho et al. algorithm, at the 4thlevel, appears clearly the P and T waves whereas the R waves undergo considerable distortion. This is due to the interference of the WGN and the free noise ECG detail sequences at level 4. To overcome this drawback, our key idea is to estimate the corrupted WGN and consequently remove the noise interfering R waves at the 4thlevel detail sequence. Our denoising algorithm was applied to a set of the MIT-BIH arrhythmia database ECG records corrupted with a 0 dB WGN which provided an output SNR of around 6 dB and an MSE value of around 0.0011. A comparative analysis using the low pass Butterworth filter and the 4thlevel classical wavelet denoising provides the output SNR values of around 3 dB and MSE value of around 0.0018; which demonstrates the superior performance of our proposed denoising algorithm