A New ECG Denoising Approach based on convex fused-Lasso Denoising with Non-Convex Regularization and Wavelet/Total Variation

Abstract

Abstract In this paper, we propose a new Electrocardiogram (ECG) denoising approach based on Convex fused lasso Denoising with non-convex regularization and Wavelet/Total Variation (WATV). This approach consists at first step of applying the Discrete Wavelet Transform (DWT) to the noisy ECG signal for obtaining a noisy approximation coefficient, cAb1 and a noisy details coefficient, cDb1. The latter is denoised by soft thresholding and we obtain a denoised details coefficient, cDd1. The second step of this approach consists of applying the DWT to cAb1 in order to obtain a noisy approximation coefficient, cAb2 and a noisy details coefficient, cDb2. The latter is denoised by Convex fused lasso denoising with non-convex regularization and we obtain a denoised details coefficient, cDd2. The coefficient, cAb2, is denoised by WATV based denoising technique and we obtain a denoised coefficient, cAd2. The inverse of DWT is then applied to cDd2 and cAd2 in order to obtain a denoised approximation coefficient, cAd1. The inverse of DWT is again applied to cDd1 and cAd1 for obtaining finally a denoised ECG signal. The performance of this proposed approach is proved by the computation of SNR, the PSNR, the MSE, the Mean Absolute Error (MAE), and the Cross-Correlation (CC).