Research On Heart Sound Denoising Method Based On CEEMDAN And Optimal Wavelet

• Published in: 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE) pp. 629 - 632
• Main Authors: Xu, Chundong, Li, Haibing, Xin, Pengli
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.01.2022
• Subjects: autocorrelation function; CEEMDAN; Empirical mode decomposition; Filtering algorithms; Heart; heart sound signal; Information filters; Noise measurement; Noise reduction; optimal wavelet; Wavelet analysis
• DOI: 10.1109/ICCECE54139.2022.9712657

For the traditional heart sound denoising algorithm is easy to filter the effective information of heart sound, a method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and optimal wavelet is proposed for heart sound denoising. Firstly, CEEMDAN algorithm is used to decompose the noisy heart sound signal to obtain several Intrinsic Mode Functions (IMF) with different scales. Then, the noisy information of IMF components is analyzed according to the characteristics of autocorrelation function, the noise dominated IMF components are removed, and the aliased IMF components are subjected to optimal wavelet denoising. Finally, the processed IMF component and the remaining IMF component are reconstructed to obtain the denoised heart sound signal. The experimental results show that this method has obvious effect in heart sound denoising, and the signal-to-noise ratio (SNR) and root mean square error (RMSE) are better.