Analysis of EEG based on the complexity measure

被引：0
|
作者：
Wang, P [1 ]
Zheng, XL [1 ]
Zheng, EX [1 ]
Dong, WW [1 ]
Wang, YH [1 ]
机构：
[1] Chongqing Univ, Coll Bioengn, Chongqing 630044, Peoples R China
来源：
IEEE-EMBS ASIA PACIFIC CONFERENCE ON BIOMEDICAL ENGINEERING - PROCEEDINGS, PTS 1 & 2 | 2000年
关键词：
EEG; complexity; approximate entropy;
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：
This paper analyzed the patients' and normal EEG in different physiological state, with the aid of two algorithms to calculate 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 EEG. Six subjects in 4 different experimental conditions are reported. The result suggests that these two algorithms could be regarded as valued methods in the study of EEG time sequence.
引用
收藏
页码：664 / 665
页数：2
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