Denoising Processing of Heart Sound Signal Based on Wavelet Transform

2018 IEEE International Conference of Safety Produce Informatization (IICSPI) Pub Date : 2018-12-01 DOI:10.1109/IICSPI.2018.8690516

Y. Yong

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引用次数: 3

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.

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基于小波变换的心音信号去噪处理

心音经介导组织到达胸壁表面时，容易产生杂音，降低病理诊断的准确性。提出了一种基于小波变换的心音信号去噪方法。首先，对信息信号进行多尺度小波变换。每个尺度的小波系数根据相应的小波熵阈值表示概率的分布顺序，以找到小波在某一区间上的最大熵，并将该区间识别为噪声的领先范围。然后，采用固定阈值去噪方法，自适应增强对衰减小波系数较大的绝对值的判断，减少高频声信号的损失，提高心音信噪比。进行了降噪仿真实验，对降噪效果进行了验证。结果表明，该方法可以提高心音信号的输出信噪比，降低噪声对心音信号提取的影响，因此，该消噪算法具有更强的抗干扰能力和优越的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2018 IEEE International Conference of Safety Produce Informatization (IICSPI)

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