基于小波熵的心音信号去噪算法研究

A heart sound denoising algorithm based on wavelet entropy

心音信号在采集过程中,易受到干扰混入噪声,常采用小波变换进行心音信号的去噪处理。传统的小波阈值去噪,未根据心音和噪声的特性选择阈值,导致去噪效果不甚理想。针对小波阈值选择问题,提出基于小波熵的自适应阈值选择方法。基于小波熵阈值、极大极小阈值和固定阈值,分别对正常心音、第二心音分裂和含S4的心音信号去噪仿真分析。结果表明,在同信噪比条件下,本文算法的输出信噪比较大而均方根误差较低,该算法的去噪效果优于其他两种小波阈值去噪算法。

Wavelet transform is often used to denoise the heart sound signal which readily introduce noise in the acquisition.However,the traditional wavelet threshold cannot select the threshold according to the characteristics of the signal and noise,and the denoising effect is unsatisfactory.Aiming at the problem,an adaptive threshold method based on wavelet entropy is proposed.Split S2 and heart sound with S4 were compared under wavelet entropy threshold,minimaxi threshold and sqtwolog threshold.Simulation results show that the output SNR is the highest and RMSE is the lowest when the input SNR is the same.So the denoising effect of the proposed algorithm is better than the other two wavelet threshold denoising algorithms.