Objective research of auscultation signals in Traditional Chinese Medicine based on wavelet packet energy and Support Vector Machine. (11th January 2011)

• Record Type: Journal Article
• Authors: Yan, Jianjun; Shen, Xiaojing; Wang, Yiqin; Li, Fufeng; Xia, Chunming; Guo, Rui; Chen, Chunfeng; Shen, Qingwei
• Is Part Of: International journal of bioinformatics research and applications. Volume 6:Number 5(2010)
• Page Start: 435
• Page End: 448
• Publication Date: 2011-01-11
• Subjects: auscultation signals -- WPE -- wavelet packet energy -- SVM -- support vector machines -- pattern recognition -- bioinformatics -- WPD -- wavelet packet decomposition -- TCM -- traditional Chinese medicine; Bioinformatics -- Periodicals; 570.285
• Languages: English
• ISSNs: 1744-5485

Abstract

This study aims at utilising Wavelet Packet Transform (WPT) and Support Vector Machine (SVM) algorithm to make objective analysis and quantitative research for the auscultation in Traditional Chinese Medicine (TCM) diagnosis. First, Wavelet Packet Decomposition (WPD) at level 6 was employed to split more elaborate frequency bands of the auscultation signals. Then statistic analysis was made based on the extracted Wavelet Packet Energy (WPE) features from WPD coefficients. Furthermore, the pattern recognition was used to distinguish mixed subjects' statistical feature values of sample groups through SVM. Finally, the experimental results showed that the classification accuracies were at a high level.