基于CEEMD的心音信号小波包去噪算法研究

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (9) : 192-198.

论文

董利超，郭兴明，郑伊能

作者信息 +

Wavelet packet de-noising algorithm for heart sound signals based on CEEMD

DONG Lichao, GUO Xingming, ZHENG Yineng

Author information +

文章历史 +

摘要

针对传统心音去噪方法易将其部分高频有用信息作为噪声滤除而造成滤波后的心音信号失真及信息丢失的问题，提出了一种基于互补总体经验模态分解(CEEMD)的小波包变换去噪算法。首先通过互补总体经验模态分解将心音信号分解为从高频到低频的不同固有模态函数分量(IMFs)，并利用自相关函数客观界定信号的模态分量范围；然后对噪声主导模态分量和混叠模态分量采用小波包变换进行滤波提取有用信息后，与剩余固有模态分量进行重构得到去噪后的信号。实验结果表明，改进的算法不仅可以去除心音中的噪声成分，明显改善心音信号的信噪比和均方根误差，而且能够有效保留信号的高频有用信息，且在不同噪声水平下的去噪性能均优于传统算法，鲁棒性较好。

Abstract

In this study, a wavelet packet denoising algorithm based on complementary ensemble empirical mode decomposition(CEEMD) was proposed to solve the problem that traditional denoising methods of heart sounds generally eliminate high frequency information and thereby cause signal distortion. Firstly, heart sounds were decomposed into different intrinsic mode functions (IMFs) with CEEMD, and autocorrelation function was utilized to define the range of mode components objectively. Then, the useful information was extracted from noise dominant mode components and mixing mode components using wavelet packet transform and used for reconstruction of the denoised signal with the remaining IMFs.The results showed that the proposed method could not only improve the denoising indexs (SNR and RMSE) significantly afer denoising, but also effectively preserve high-frequency useful information of the signal, have better denoising performance under different noise levels compared with traditional algorithms and better robustness.

导出引用

董利超，郭兴明，郑伊能. 基于CEEMD的心音信号小波包去噪算法研究[J]. 振动与冲击, 2019, 38(9): 192-198

DONG Lichao, GUO Xingming, ZHENG Yineng. Wavelet packet de-noising algorithm for heart sound signals based on CEEMD[J]. Journal of Vibration and Shock, 2019, 38(9): 192-198

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