Objective research of auscultation signals in Traditional Chinese Medicine based on wavelet packet energy and Support Vector Machine
by Jianjun Yan, Xiaojing Shen, Yiqin Wang, Fufeng Li, Chunming Xia, Rui Guo, Chunfeng Chen, Qingwei Shen
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 6, No. 5, 2010

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.

Online publication date: Fri, 07-Jan-2011

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