EEG Classification Using Neural Networks and Independent Component Analysis

被引：0
|
作者：
Ashtiyani, M. [1 ]
Asadi, S. [2 ]
Birgani, P. M. [1 ]
Khordechi, E. A. [3 ]
机构：
[1] Islamic Azad Univ, YRC, Sci & Res Branch, Tehran, Iran
[2] Shahid Abbaspour Univ, Dept Elect, Tehran, Iran
[3] Islamic Azad Univ, Dept Biomed Engn, Sci & Res Branch, Tehran, Iran
来源：
4TH KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2008, VOLS 1 AND 2 | 2008年 / 21卷 / 1-2期
关键词：
Electroencephalography signal Classification; Independent Component Analysis; Neural Networks; Hidden Markov Modeling;
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：
In this paper we used Independent component analysis model of electroencephalography (EEG) signals for preprocessing and then Hidden Markov Modeling (HMM) analysis for feature extraction from electroencephalography signal which this features are useful in Brain Computer Interface (BCI) application. Then we used Neural Networks for recognition of some diseases like epileptic seizure, Cerebral Palsy, etc.
引用
收藏
页码：179 / +
页数：2
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