Denoising Processing of Heart Sound Signal Based on Wavelet Transform

Abstract

When the heart sounds reach the chest wall surface through mediated tissue, it is prone to generate noise, which can reduce the accuracy of pathological diagnosis. A new denoising method for heart sound signal based on wavelet transform is proposed. First of all, the information signal is transformed by multi-scale wavelet. The wavelet coefficients of each scale indicate a distribution sequence of probability according to the corresponding wavelet entropy threshold to find the maximum entropy of wavelet on certain interval, and the interval is recognized as the leading range of noise. And then, a fixed threshold denoising method is used to adaptively enhance the judgment about absolute value with larger attenuation wavelet coefficients, which can reduce the high frequency sound signal loss and improve the heart sound signal to noise ratio. The denoising simulation experiment is carried out to test the performance. The result shows that the proposed method can improve the output signal to noise ratio of heart sound signal, reducing the influence of noise on the extraction of heart sound signal, and therefore, the noise elimination algorithm has stronger anti-interference ability and superior performance.