title: Objective research of auscultation signals in Traditional Chinese Medicine based on wavelet packet energy and support vector machine.
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.
authors.affiliation: Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China. jjyan@ecust.edu.cn
authors.forename: Jianjun
authors.initials: J
authors.lastname: Yan
authors.forename: Xiaojing
authors.initials: X
authors.lastname: Shen
authors.forename: Yiqin
authors.initials: Y
authors.lastname: Wang
authors.forename: Fufeng
authors.initials: F
authors.lastname: Li
authors.forename: Chunming
authors.initials: C
authors.lastname: Xia
authors.forename: Rui
authors.initials: R
authors.lastname: Guo
authors.forename: Chunfeng
authors.initials: C
authors.lastname: Chen
authors.forename: Qingwei
authors.initials: Q
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001314:Auscultation / Q000379:methods*; D019277:Entropy; D006801:Humans; D008516:Medicine, Chinese Traditional / Q000379:methods*; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted