Joint Heart Sound Denoising Using DTCWT and Adaptive Sparsity-assisted Signal Smoothing Algorithm

Jianqiang Hu1,2   , Dafeng Shen1, Lin Chen1, Yu Chen1, Shigen Shen3   , Yan Che2   

  1. School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, P. R. China
    hujianqiang@tsinghua.org.cn
    shendafeng25@gmail.com
    275914270c@gmail.com
    631894828@qq.com
  2. Engineering Research Center for Big Data Application in Private Health Medicine of Fujian Universities, Putian University, Putian, Fujian 351100, P. R. China
    ptucy07@126.com (corresponding author)
  3. School of Information Engineering, Huzhou University, Huzhou 313000, P. R. China
    shigens@zjhu.edu.cn

Abstract

Various unwanted and unavoidable noises corrupt Heart Sound Signals (HSSs). It is strongly required to suppress respiratory sound and ambient noise due to significant reduction of clarity and interpretation of HSSs. In this paper, we propose a joint heart sound denoising using Dual-Tree Complex Wavelet Transform (DTCWT) and Adaptive Sparsity-assisted Signal Smoothing (ASASS) algorithm. In this research, the signal is first decomposed by DTCWT to obtain the multi-scale feature representation of the signal. Subsequently, ASASS suppresses pseudo-Gibbs artifacts around signal boundaries of DTCWT while implementing adaptive thresholding strategies to maximize the Signal-to-Noise Ratio (SNR). Experimental validation on the PhysioNet/CinC 2016 database and Open Access Heart Sound Dataset (OAHS Dataset) demonstrates that the proposed method significantly outperforms existing techniques. Under conditions involving Gaussian white noise (GWN) SNR of 0 dB, the proposed method achieves an SNR of 9.01 dB and a Root Mean Square Error (RMSE) of 0.032, outperforming standalone DTCWT and multiple existing models.

Key words

Heart Sound Signals, Denoising, Adaptive Sparsity-Assisted Signal Smoothing, Dual-Tree Complex Wavelet Transform

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS250828017H

Publication information

Volume 23, Issue 2 (April 2026)
Year of Publication: 2026
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Hu, J., Shen, D., Chen, L., Chen, Y., Shen, S., Che, Y.: Joint Heart Sound Denoising Using DTCWT and Adaptive Sparsity-assisted Signal Smoothing Algorithm. Computer Science and Information Systems, 23(2), 687–706 (2026). https://doi.org/10.2298/CSIS250828017H