A Proposed Feature Extraction Method for EEG-based Person Identification

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

34 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
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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",
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booktitle = "ICAI 2012 : Proceedings of the 2012 International Conference on Artificial Intelligence, WORLDCOMP'12 : Volume II",
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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

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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