Wavelet subband dependent thresholding for denoising of phonocardiographic signals

In this paper a wavelet transform based optimum subband thresholding algorithm is proposed. This algorithm is used for denoising of heart sound signals that are highly corrupted by noise. The proposed algorithm applies signal dependent optimum thresholding to all the subbands of the signal. The algorithm is tested against different noise densities of the Phonocardiogram signal (PCG). Experimental results demonstrate that our proposed algorithm can obtain better performances in terms of minimized value of mean square error (MSE). The most significant feature of the denoised signal obtained by this algorithm is that it can be used for accurate diagnosis of cardiovascular diseases.