• DocumentCode
    662872
  • Title

    A study on the reproducibility of biometric authentication based on electroencephalogram (EEG)

  • Author

    Hong Ji Lee ; Hyun Seok Kim ; Kwang Suk Park

  • Author_Institution
    Interdiscipl. Program of Bioeng., Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2013
  • fDate
    6-8 Nov. 2013
  • Firstpage
    13
  • Lastpage
    16
  • Abstract
    This paper introduced a method for biometric authentication using EEG signals. Especially, we focused on the performance of reproducibility for personal authentication. Four healthy subjects participated in the experiment. EEG was measured from only one bipolar channel (O1A2) during resting state with closed eyes. EEG was also recorded with same protocol from same subjects on different days to verify reproducibility (the interval between 1st and 2nd recording: 10 days or 5 months). Three features were extracted: the spectral power, the maximum power, and the frequency of maximum power in alpha band. Linear discriminant analysis was used as a classifier. The authentication accuracy for reproducibility was 98.33% with 20s data length and 100% with 50s data length.
  • Keywords
    biometrics (access control); electroencephalography; feature extraction; medical signal processing; signal classification; EEG signals; alpha band; authentication accuracy; biometric authentication reproducibility; bipolar channel; classifier; closed eyes; data length; electroencephalogram; feature extraction; linear discriminant analysis; maximum power frequency; personal authentication; reproducibility performance; resting state; spectral power; time 20 s; time 50 s; Accuracy; Authentication; Electrodes; Electroencephalography; Face recognition; Feature extraction; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1948-3546
  • Type

    conf

  • DOI
    10.1109/NER.2013.6695859
  • Filename
    6695859