A New Technique of ECG Denoising based on LWT and Total Variation Minimization ECG Denoising

Abstract

In this paper we propose a new technique of Electrocardiogram (ECG) denoising. This technique is based on Lifting Wavelet Transform (LWT) and Total variation based denoising technique using majorization-minimization. It consists at the first step in applying the LWT to the noisy ECG signal in order to obtain three noisy coefficients, cA2, cD2 and cD1. The coefficients cD2 and cD1 are respectively the details coefficient at level 2 and the details one at level 1 and are denoised applying soft thresholding and we obtain two denoised coefficients, cDd2 and cDd1. The coefficient cA2 is the approximation one and is denoised applying the Total variation based denoising technique using majorization-minimization and we obtain a denoised coefficient, cAd2. The denoised ECG signal is finally obtained from the application of the LWT inverse ( (LWT) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) to the denoised coefficients., cDd1, cDd2 and cAd2. The performance of the proposed ECG denoising technique is proved by the results obtained from the computation of the Signal to Noise Ratio (SNR), the Peak SNR (PSNR), the Mean Absolute Error (MAE), the Mean Square Error (MSE) and the Cross-Correlation (CC).