Nonlinear Analysis of Auscultation Signals in Traditional Chinese Medicine Using Wavelet Transform and Approximate Entropy

被引：0

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] East China Univ Sci & Technol, Ctr Mechatron Engn, Shanghai 200237, Peoples R China

[2] Shanghai Univ, TCM, Ctr TCM Informat Sci & Technol, Shanghai 201203, Peoples R China

来源：

2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010) | 2010年

基金：

中国国家自然科学基金;

关键词：

Auscultation; TCM; ApEn; Wavelet transform;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

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, yin-deficiency 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.

引用

页数：4

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