New Technique of Electrocardiogram Denoising Based on 1d Double-Density Complex DWT and Stationary Bionic Wavelet Transform

In this paper, we propose a new electrocardiogram (ECG) denoising technique based on the application of a 1D double-density complex discrete wavelet transform (DWT) denoising method in the stationary bionic wavelet transform (SBWT) domain. SBWT was introduced in our previous work for speech enhancement. The first step in this proposed ECG denoising technique consists of applying the SBWT to the noisy ECG signal to obtain two noisy wavelet coefficients wtb1 and wtb2. The coefficients wtb1 and wtb2 are, respectively, the details and approximation coefficients. To estimate the level, [Formula: see text], of the additive white noise corrupting the original ECG signal, we use wtb1 which is then thresholded using soft thresholding function. The noisy approximation wtb2 is denoised by using 1D double-density complex DWT denoising method. The latter requires the use of this noise level, [Formula: see text]. The results obtained from SNR computations show the performance of the ECG denoising technique proposed in this work.