An adaptive method for shrinking of wavelet coefficients for phonocardiogram denoising

Abstract

Noise suppression from the phonocardiogram (PCG) signal is important to improve the diagnostic efficiency. For the PCG signal, Discrete Wavelet Transform (DWT) based denoising method has been used extensively due to its good performance. However, the performance of this method depends on the threshold value and the way to apply it on the wavelet coefficients. Therefore, in this paper, an adaptive method is proposed to estimate the threshold value for the shrinking of the wavelet coefficients of the PCG signal. For this purpose, a new statistical parameter is obtained by incorporating medical domain knowledge about the PCG. The threshold value is estimated based on the statistical analysis of the wavelet coefficients and the present level of noise. Further, to overcome the issues related to existing threshold functions, soft and hard, new threshold functions, mid and non-linear mid are presented. The proposed method is applied to the PCG signal contaminated with simulated white Gaussian noise, red noise, and pink noise. The obtained results of the proposed method are compared with the results of state-of-the-art methods and they show the superiority of the proposed method.