A Proposed Feature Extraction Method for EEG-based Person Identification

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    33 Citations (Scopus)

    Abstract

    We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction method that is currently used to extract speech features can be applied to extract brain wave features from EEG signal. Mel-frequency cepstral coefficients are features extracted and evaluated in EEG-based person identication. Experimental results show that the proposed method could provide very high recognition rate.
    Original languageEnglish
    Title of host publicationICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II
    EditorsHamid Reza Arabnia
    Place of PublicationUSA
    PublisherCSREA Press
    Pages826-831
    Number of pages6
    Volume2
    ISBN (Print)9781601322173
    Publication statusPublished - 2012
    Event2012 International Conference on Artificial Intelligence - Las Vegas, Las Vegas, United States
    Duration: 16 Jul 201219 Jul 2012

    Conference

    Conference2012 International Conference on Artificial Intelligence
    Abbreviated titleICAI 2012
    CountryUnited States
    CityLas Vegas
    Period16/07/1219/07/12

    Fingerprint

    Electroencephalography
    Feature extraction
    Brain

    Cite this

    Tran, D., Huang, X., & Sharma, D. (2012). A Proposed Feature Extraction Method for EEG-based Person Identification. In H. R. Arabnia (Ed.), ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II (Vol. 2, pp. 826-831). USA: CSREA Press.
    Tran, Dat ; Huang, Xu ; Sharma, Dharmendra. / A Proposed Feature Extraction Method for EEG-based Person Identification. ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II. editor / Hamid Reza Arabnia. Vol. 2 USA : CSREA Press, 2012. pp. 826-831
    @inproceedings{ca21229e1bd045d3b118dc90ddcc556b,
    title = "A Proposed Feature Extraction Method for EEG-based Person Identification",
    abstract = "We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction method that is currently used to extract speech features can be applied to extract brain wave features from EEG signal. Mel-frequency cepstral coefficients are features extracted and evaluated in EEG-based person identication. Experimental results show that the proposed method could provide very high recognition rate.",
    author = "Dat Tran and Xu Huang and Dharmendra Sharma",
    year = "2012",
    language = "English",
    isbn = "9781601322173",
    volume = "2",
    pages = "826--831",
    editor = "Arabnia, {Hamid Reza}",
    booktitle = "ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II",
    publisher = "CSREA Press",

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    Tran, D, Huang, X & Sharma, D 2012, A Proposed Feature Extraction Method for EEG-based Person Identification. in HR Arabnia (ed.), ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II. vol. 2, CSREA Press, USA, pp. 826-831, 2012 International Conference on Artificial Intelligence, Las Vegas, United States, 16/07/12.

    A Proposed Feature Extraction Method for EEG-based Person Identification. / Tran, Dat; Huang, Xu; Sharma, Dharmendra.

    ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II. ed. / Hamid Reza Arabnia. Vol. 2 USA : CSREA Press, 2012. p. 826-831.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    TY - GEN

    T1 - A Proposed Feature Extraction Method for EEG-based Person Identification

    AU - Tran, Dat

    AU - Huang, Xu

    AU - Sharma, Dharmendra

    PY - 2012

    Y1 - 2012

    N2 - We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction method that is currently used to extract speech features can be applied to extract brain wave features from EEG signal. Mel-frequency cepstral coefficients are features extracted and evaluated in EEG-based person identication. Experimental results show that the proposed method could provide very high recognition rate.

    AB - We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction method that is currently used to extract speech features can be applied to extract brain wave features from EEG signal. Mel-frequency cepstral coefficients are features extracted and evaluated in EEG-based person identication. Experimental results show that the proposed method could provide very high recognition rate.

    M3 - Conference contribution

    SN - 9781601322173

    VL - 2

    SP - 826

    EP - 831

    BT - ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II

    A2 - Arabnia, Hamid Reza

    PB - CSREA Press

    CY - USA

    ER -

    Tran D, Huang X, Sharma D. A Proposed Feature Extraction Method for EEG-based Person Identification. In Arabnia HR, editor, ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II. Vol. 2. USA: CSREA Press. 2012. p. 826-831