Person identification using electroencephalographic signals evoked by visual stimuli

  • Authors:

  • Jia-Ping Lin;Yong-Sheng Chen;Li-Fen Chen

  • Affiliations:

  • Inst. of Biomedical Engineering, National Chiao Tung University, Hsinchu, Taiwan;Inst. of Biomedical Engineering, National Chiao Tung University, Hsinchu, Taiwan;Inst. of Brain Science, National Yang-Ming University, Taipei, Taiwan

  • Venue:
  • ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
  • Year:
  • 2011

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Abstract

In this work we utilize the inter-subject differences in the electroencephalographic (EEG) signals evoked by visual stimuli for person identification. The identification procedure is divided into classification and verification phases. During the classification phase, we extract the representative information from the EEG signals of each subject and construct a many-to-one classifier. The best-matching candidate is further confirmed in the verification phase by using a binary classifier specialized to the targeted candidate. According to our experiments in which 18 subjects were recruited, the proposed method can achieve 96.4% accuracy of person identification.