Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (33): 169-171.DOI: 10.3778/j.issn.1002-8331.2010.33.047
• 图形、图像、模式识别 • Previous Articles Next Articles
XIAO Dan,HU Jian-feng
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肖 丹,胡剑锋
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Abstract: Subjects are identified by classifying motor imagery EEG signal.Second-Order Blind Identification(SOBI),a Blind Source Separation(BSS) algorithm is applied to preprocess EEG data for higher signal-to-noise ratio.Subsequently,Fisher distance is used to extract features.Finally,classification of extracted features is performed by back-propagation neural networks.Four types motor imagery EEG of three subjects is classified respectively.The results show that the average classification accuracy achieves over 80%,and the highest is 88.1% on tongue movement imagery EEG.
Key words: person identification, second-order blind identification, motor imagery, Electroencephalo gram(EEG)
摘要: 通过对运动想象脑电信号的分类,对受试者进行身份识别。采用一种盲源分离算法——二阶盲辨识对运动想象脑电信号进行处理,提高运动想象脑电信号的信噪比,进而采用Fisher距离对处理后的信号进行特征提取,最后采用BP神经网络对特征集进行分类,从而实现对受试者的身份识别。对3位受试者的4类运动想象脑电信号分别进行了分类识别,结果显示,4类运动想象脑电信号的识别率均达到80%左右,其中最高的是想象舌动脑电信号,其识别率达到88.1%,这在类似研究中属于较高的水平。
关键词: 身份识别, 二阶盲辨识, 运动想象, 脑电
CLC Number:
TP391
XIAO Dan,HU Jian-feng. Identification of motor imagery EEG signal[J]. Computer Engineering and Applications, 2010, 46(33): 169-171.
肖 丹,胡剑锋. 运动想象脑电信号识别研究[J]. 计算机工程与应用, 2010, 46(33): 169-171.
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URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2010.33.047
http://cea.ceaj.org/EN/Y2010/V46/I33/169