[Analysis of EEG based on the complexity measure]

[Analysis of EEG based on the complexity measure] Research Abstract Details 

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[Analysis of EEG based on the complexity measure] Abstract Text:

Pin Wang,Xiaolin Zheng,Chenglin Peng,Weiwei Dong,Yonghong Wang,

EEG represents the electric activity of neurons in human brain; it is of course repeatedly used for studying and analyzing the brain activity and the status of brain function. In this paper, we analyzed the patients' and normal persons' EEG in different physiological state, with the aid of two algorithms as a complexity measure. One is Kc complexity defined by Kaspar and Schuster, the other is a new statistical method to measure complexity sequences-Approximate entropy (ApEn). In our work, we analyzed two groups of persons' EEG. Six subjects in 4 different experimental condition are reported. From the results we can discriminate the different state of brain effectively: normal, being injured, and various thinking state. The result suggests that the two algorithms as a complexity measure could be regarded as valued methods in the study of EEG time series and clinical diagnosis.

[Analysis of EEG based on the complexity measure] Publishing Authors By Initials

P Wang,X Zheng,C Peng,W Dong,Y Wang,

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[Analysis of EEG based on the complexity measure] Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Sheng wu yi xue gong cheng xue za zhi = Journal of

VOLUME: 19

Page Numbers: 229-31

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ISSN: 1001-5515

DAY: 12

MONTH: Jun

YEAR: 2002

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LANGUAGE: chi

NlmUniqueID: 9426398

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AFFILIATION: College of Bioengineering, Chongqing University, Chongqing 400044.

Country: China

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MEDLINETA: Sheng Wu Yi Xue Gong Cheng Xue

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