文献类型：期刊文献

英文题名：Nonlinear analysis of auscultation signals in traditional chinese medicine using wavelet transform and approximate entropy

作者：Yan, Jianjun[1]; Shen, Yong[1]; Xia, Chunming[1]; Shen, Xiaojing[1]; Shen, Qingwei[1]; Gu, Zhongyan[1]; Wang, Yiqin[2]; Li, Fufeng[2]; Guo, Rui[2]; Chen, Chunfeng[2]; Chen, Lingyun[2]; Yan, Bin[2]

机构：[1] Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China; [2] Center for TCM Information Science and Technology, Shanghai University of TCM, Shanghai 201203, China

年份：2010

外文期刊名：2010 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010

收录：EI(收录号：20103613207048)

语种：英文

外文关键词：Discrete wavelet transforms - Nonlinear analysis - Signal reconstruction - Medicine - Frequency domain analysis

摘要：the purpose of this paper is to analyze the auscultation signals in Traditional Chinese Medicine utilizing discrete wavelet (DWT) and approximate entropy (ApEn). In this paper ApEn is used to quantify pathological voicing in qi-deficiency, yindeficiency and health using the voice samples in the time and frequency domain. Since ApEn is a viable single figure of merit, it has the potential to make assessment of aberrant voicing both more concise and objective than the subjective analysis adopted by speech and language therapists (SALTs). In this paper, in the first stage, voice signal were decomposed into approximation and detail coefficients using DWT. In the second stage, ApEn values of approximation and detail coefficients were computed. Finally, ApEn values among three kinds of samples were analyzed. ? 2010 IEEE.