Improving individual identification in security check with an EEG based biometric solution

Authors:
Qinglin Zhao;Hong Peng;Bin Hu;Quanying Liu;Li Liu;YanBing Qi;Lanlan Li
Affiliations:
School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China
Venue:
BI'10 Proceedings of the 2010 international conference on Brain informatics
Year:
2010

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Abstract

Security issue is always challenging to the real world applications. Many biometric approaches, such as fingerprint, iris and retina, have been proposed to improve recognizing accuracy or practical facility in individual identification in security. However, there is little research on individual identification using EEG methodology mainly because of the complexity of EEG signal collection and analysis in practice. In this paper, we present an EEG based unobtrusive and non-replicable solution to achieve more practical and accurate in individual identification, and our experiment involving 10 subjects has been conducted to verify this method. The accuracy of 10 subjects can reach at 96.77%. The high-level accuracy result has validated the utility of our solution in the real world. Besides, subject combinations were randomly selected, and the recognizing performance from 3 subjects to 10 subjects can still keep equivalent, which has proven the extendibility of the solution.