Chinese Journal of Tissue Engineering Research ›› 2011, Vol. 15 ›› Issue (30): 5615-5619.doi: 10.3969/j.issn.1673-8225.2011.30.026

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Envelope extraction algorithm and phonocardiogram signal application based on wavelet transform

Zhou Su, Judith Diengi Zeyi, Wu Xiao-ming, Huang Yue-shan   

  1. Department of Biomedical Engineering, South China University of Technology, Guangzhou  510006, Guangdong Province, China
  • Received:2011-03-22 Revised:2011-05-12 Online:2011-07-23 Published:2011-07-23
  • Contact: Wu Xiao-ming, Doctor, Professor, Doctoral supervisor, Department of Biomedical Engineering, South China University of Technology, Guangzhou 510006, Guangdong Province, China bmxmwus@scut.edu.cn
  • About author:Zhou Su★, Studying for master’s degree, Department of Biomedical Engineering, South China University of Technology, Guangzhou 510006, Guangdong Province, China zhousuok@163.com
  • Supported by:

    the Guangdong Science and Technology Plan, No. 2007B031302003, 2009B030801004**

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Abstract:

BACKGROUND: The activity of heart valves can be reflected by cardiac sounds, even some heart disease can also find expression in the abnormal heart sounds. So heart sounds analysis has important clinical significance.
OBJECTIVE: Through extraction envelope and analysis of the various features of heart sounds, to detect whether there is noise or not in phonocardiogram signals so as to improve the weakness of traditional auscultation technology such as high dependence on the doctors’ experience and the limited auscultation range.
METHODS: Extraction envelope curve is one of the commonly used methods to analyze heart sounds. A new method based on wavelet transform to extract the heart sound signals envelope was presented, in contrast to the common methods as Hilbert-Huang transform (HHT), mathematical morphology and average Shannon energy. Through practice, the method was proved to contain many advantages: simple algorithm, smooth feature, outstanding feature point.
RESULTS AND CONCLUSION: In order to test the accuracy of discriminating normal and abnormal heart sounds, 35 heart sounds were collected and analyzed. The experiment demonstrated that the accuracy performances were achieved by 95%, which is very useful in many aspects.

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