A New ECG Denoising Technique based on WATV and Convex Fused-Lasso

The Electrocardiogram (ECG) signal serves an important role in identifying heart problems, but it is usually distorted by noise, preventing accurate interpretation. Many ECG denoising techniques were proposed in literature. In this paper, a new ECG denoising approach is proposed. It is based on Convex fused lasso Denoising with non-convex regularization and Wavelet/Total Variation (WATV). The performance of this proposed approach is proved by the results obtained from the computations of SNR (Signal to Noise Ratio), the PSNR (Peack SNR), the MSE (Mean Square Error), the Mean Absolute Error (MAE), and the Cross-Correlation (CC). These results are obtained by applying this proposed approach and other three denoising techniques. The latters are WATV based denoising technique, Convex fused lasso denoising with non-convex regularization, and a statistical approach to signal denoising based on data-driven multiscale representation. These results show that the proposed denoising approach outperforms the other three mentioned techniques.