A Noise Reduction Algorithm of Heart Sound Based on Wavelet Shrinkage

DOI

10.2991/icmmct-17.2017.224How to use a DOI?

Keywords

Heart Sound Signal; Wavelet Shrinkage; Threshold Function; Heuristicthreshold Rule

Abstract

In this paper, a kind of noise reduction algorithm is proposed based on wavelet shrinkage technique to acquire heart sound signal while no distortion. Firstly, Haar, Daubechies, Symlets and Coiflets orthogonal wavelets were studied and according to the statistical results, Coif5 wavelet was chosen for the decomposition and reconstruction of heart sound signal. To get the better noise reduction effects, a smooth and continuous adaptive elastic threshold function was designed for wavelet shrinkage, which could perfectly overcome the discontinuous shortage of hard threshold function, especially under Heursure rule when the SNR was less than 50dB. In addition, the results showed that the energy in each layers of Coif5 wavelet differed significantly among different kinds of heart diseases. So the coif5 wavelet may be suitable for feature extraction of heart sound signal and classifications of pathological heart sounds in future research.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - JingLai Sun
AU  - Hui Yu
AU  - Chunfa Miao
AU  - BoChang Jiang
PY  - 2017/04
DA  - 2017/04
TI  - A Noise Reduction Algorithm of Heart Sound Based on Wavelet Shrinkage
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1130
EP  - 1136
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.224
DO  - 10.2991/icmmct-17.2017.224
ID  - Sun2017/04
ER  -