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

Here, aiming at problems of traditional heart sound signals' de-noising method being easy to eliminate parts of high frequency useful information and cause distortion of heart sound signals and loss of information, a wavelet packet de-noising algorithm based on the complementary ensemble empirical mode decomposition (CEEMD) was proposed. Firstly, heart sound signals were decomposed into different intrinsic mode functions (IMFs) with CEEMD. Autocorrelation function was used to objectively define the range of modal components of a signal. Then, the useful information was extracted from noise dominant modal components and aliasing ones using the wavelet packet transformation, and it was used for reconstruction of the de-noised signal together with residual IMFs. The results showed that the proposed method can be used not only to eliminate noise components in heart sounds, and improve heart sounds' ratio of signal to noise and the root mean square error, but also to effectively retain heart sound signals' high-frequency useful information; compared with traditional algorithms, it has better de-noising performance and robustness under different noise levels. © 2019, Editorial Office of Journal of Vibration and Shock. All right reserved.