Robust electroencephalogram channel set for person authentication

Salahiddin Altahat, Michael WAGNER, Elisa MARTINEZ MARROQUIN

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

13 Citations (Scopus)

Abstract

In electroencephalogram (EEG) based biometrics, the determination of the right channel set helps improve accuracy and usability, while reducing the required number of electrodes and hence the complexity and cost of the EEG system. In this work we find a reduced set of channels designed to enhance human authentication accuracy regardless of changes in the mental task. The study shows that the resulting eight EEG channels outperform previous state of the art studies. Also the experiments and quantitative comparison are conducted in a database significantly larger (106 subjects) than the ones used previously. The suggested set half total error rate (HTER) is 14.69%.
Original languageEnglish
Title of host publicationProceedings of 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages997-1001
Number of pages5
ISBN (Electronic)9781467369978
ISBN (Print)9781467369978
DOIs
Publication statusPublished - 19 Apr 2015
EventInternational Conference on Acoustics, Speech and Signal Processing (ICASSP) - Brisbane, Brisbane, Australia
Duration: 19 Apr 201524 Apr 2015

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August
ISSN (Print)1520-6149

Conference

ConferenceInternational Conference on Acoustics, Speech and Signal Processing (ICASSP)
CountryAustralia
CityBrisbane
Period19/04/1524/04/15

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  • Cite this

    Altahat, S., WAGNER, M., & MARTINEZ MARROQUIN, E. (2015). Robust electroencephalogram channel set for person authentication. In Proceedings of 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 997-1001). (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2015-August). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICASSP.2015.7178119