Does Undecimated Wavelet Transform improve ECG signal denoising compared to Discrete Wavelet Transform?
Undecimated Wavelet Transform provides superior ECG signal denoising with a better balance of smoothness and accuracy compared to traditional Discrete Wavelet Transform.
The Electrocardiogram (ECG) is a technique of recording bioelectric currents generated by the heart which will help clinicians to evaluate the conditions of a patient's heart. So it is very important to get the parameters of ECG signal clear without noise. Many of the wavelet based denoising algorithms use DWT (Discrete Wavelet Transform) in the decomposition stage which is suffering from shift variance. To overcome this in this paper we are proposing the denoising method which uses Undecimated Wavelet Transform to decompose the raw ECG signal and we performed the shrinkage operation to eliminate the noise from the noisy signal. In the shrinkage step we used semi-soft and stein thresholding operators along with traditional hard and soft thresholding operators and verified the suitability of different wavelet families for the denoising of ECG signals. The results proved that the denoised signal using UDWT (Undecimated Discrete Wavelet Transform) have a better balance between smoothness and accuracy than the DWT.
Raj et al. (Fri,) studied this question.
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