Nonlinear Analysis of Auscultation Signals in Traditional Chinese Medicine Using Wavelet Transform and Approximate Entropy
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.
Jianjun Yan Chunfeng Chen Lingyun Chen Bin Yan Yong Shen Chunming Xia Xiaojing Shen Qingwei Shen Zhongyan Gu Yiqin Wang Fufeng Li Rui Guo
Center for Mechatronics Engineering East China University of Science and Technology Shanghai 200237, Center for TCM information science and technology Shanghai University of TCM, Shanghai 201203, P.R.C
国际会议
成都
英文
1-4
2010-06-18（万方平台首次上网日期，不代表论文的发表时间）