DocumentCode :
2380099
Title :
Analysis of 903 voice signals of patients with five organs illness and normal persons in traditional Chinese medicine auscultation
Author :
Chen, Chunfeng ; Wang, Yiqin ; Guo, Rui ; Xu, Wenjie ; Yan, Jianjun ; Mao, Siyuan ; Shen, Yong ; Shen, Xiaojing
Author_Institution :
Lab. of Four Diagnostic Inf. of TCM, Shanghai Univ. of Traditional Chinese Med., Shanghai, China
fYear :
2010
fDate :
18-18 Dec. 2010
Firstpage :
745
Lastpage :
748
Abstract :
The purpose of this paper is to provide objective gist for organ differentiation of traditional Chinese medicine (TCM). In this paper, we collected 803 voice signals of patients with five internal organs illness and 100 voice signals of normal persons. We extracted the sample entropy characteristic of each group when embedded dimension was 2. By analyzing the statistics result, we found: (1) the sample entropy characteristic of six groups were significantly different in multiple frequencies (P≤0.05); (2) the sample entropy characteristic of normal group was much lower than that of patients (P≤0.05); (3) the sample entropy characteristic of lung illness group was much higher than that of other illness groups and normal group (P≤0.05). Finally, using the method of sample entropy combined with the Wuyin theory, we have got some objective gist for organ differentiation of TCM auscultation.
Keywords :
bioinformatics; diseases; entropy; lung; medical diagnostic computing; patient diagnosis; speech; Wuyin theory; internal organ illness; lung illness group; organ differentiation; patient voice signals; sample entropy characteristic; traditional Chinese medicine auscultation; Wuyin theory; auscultation; objective; signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
Conference_Location :
Hong, Kong
Print_ISBN :
978-1-4244-8303-7
Electronic_ISBN :
978-1-4244-8304-4
Type :
conf
DOI :
10.1109/BIBMW.2010.5703902
Filename :
5703902
Link To Document :
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