New Biometric Approach Based on Motor Imagery EEG signals

被引：17
|
作者：
Hu, Jian-feng [1 ]
机构：
[1] Jiangxi Bluesky Univ, Inst Informat Technol, Nanchang 330098, Jiangxi, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON FUTURE BIOMEDICAL INFORMATION ENGINEERING (FBIE 2009) | 2009年
关键词：
Biometric; Electroencephalogram (EEG); Nonlinear analysis; ARMA model;
D O I：
10.1109/FBIE.2009.5405787
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
A research on biometry based on motor imagery EEG signals was described. In this study, I select EEG signals related to motor imagery, and a model was built. Estimated model parameters as feature vector were extracted, and then to classified by an artificial neural network. Two different classify cases, including authentication and identification, were investigated. Four types of motor imagery EEG signals and three subjects were compared. Experiment results show that EEG carrying individual-specific information can be successfully exploited for purpose of person authentication and identification.
引用
收藏
页码：94 / 97
页数：4
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