A Proposed Feature Extraction Method for EEG-based Person Identification

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

39 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

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  • 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). CSREA Press. http://world-comp.org/p2012/ICA4683.pdf