文献类型：期刊文献

英文题名：Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine

作者：Yan, Jian-Jun[1];Guo, Rui[2];Wang, Yi-Qin[2];Liu, Guo-Ping[2];Yan, Hai-Xia[2];Xia, Chun-Ming[1];Shen, Xiaojing[1]

机构：[1]E China Univ Sci & Technol, Ctr Mechatron Engn, Shanghai 200237, Peoples R China;[2]Shanghai Univ Chinese Tradit Med, Lab Informat Access & Synth TCM Diagnost 4, Shanghai 201203, Peoples R China

年份：2014

卷号：2014

外文期刊名：EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000336142800001)】；

基金：This work was supported by the National Natural Science Foundation of China under Grant nos. 81302913, 81270050, 30901897, 81173199, and 30701072.

语种：英文

摘要：This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform(WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered.