中国组织工程研究 ›› 2010, Vol. 14 ›› Issue (43): 8081-8085.doi: 10.3969/j.issn.1673-8225.2010.43.026

• 数字化骨科 digital orthopedics • 上一篇    下一篇

基于脑电密码的新型生物识别方法

胡剑锋,包学才   

  1. 江西蓝天学院信息技术研究所,江西省南昌市 330098
  • 出版日期:2010-10-22 发布日期:2010-10-22
  • 作者简介:胡剑锋☆,男,1976年生,江西省景德镇市人,汉族,2002年中国科学院毕业,博士,教授,研究所所长,主要从事脑机接口、身份识别等方面的研究。 huguess@21cn.com

A novel biometric recognition approach based on electroencephalogram password

Hu Jian-feng, Bao Xue-cai   

  1. Institute of Information Technology, Jiangxi Bluesky University, Nanchang  330098, Jiangxi Province, China
  • Online:2010-10-22 Published:2010-10-22
  • About author:Hu Jian-feng☆, Ph.D., Professor, Institute of Information Technology, Jiangxi Bluesky University, Nanchang 330098, Jiangxi Province, China huguess@21cn.com

摘要:

背景:脑电信号不仅是一个非常有用的临床诊断工具,而且也是一种很好的用于身份认证的生物识别工具。
目的:通过分析脑电信号进行个人身份认证及识别的问题,介绍一种新型身份识别方法。
方法:采用以回归系数、能量谱密度、相同步、线性复杂度等多种信号处理结合方法对脑电信号进行处理,运用神经网络等分类方法对不同脑电信号进行分类。
结果与结论:平均识别率在80%以上。对自由状态下的人在刺激作用或下达指令时的脑电活动进行实时记录,通过信号分析算法和分类算法对脑电的时空变化进行归类,最终实现通过脑电信号进行个人身份识别的目的。可见,以脑电信号作为身份识别完全可行,预计不远的将来必将普及。

关键词: 脑电信号, 脑电密码, 生物识别, 运动想象, 视觉诱发电位, 事件诱发电位

Abstract:

BACKGROUND: Electroencephalogram (EEG) is a useful tool for clinical diagnosis as well as a good tool for biometric authentication.
OBJECTIVE: To introduce a new method for the identification of a person, by analyzing EEG signals. 
METHODS: Several signal processing methods were used for feature extraction, such as autoregressive model, phase synchronization, energy spectral density, linear complexity, and different methods, including BP neural network, were used for classification of person identification.
RESULTS AND CONCLUSION: The identification rate was more than 80%. The EEG signals of people after stimulation or order performance were recorded, and EEG space-time changes were classified using signal analysis and classification. EEG signals can be used for person identification and generally used in near future.

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