Al-Darkazali, Mohammed, Hoque, Sanaul, Deravi, Farzin (2020) Spatial Signatures for EEG-based Biometric Person Recognition. In: Int. Conf. on Imaging for Crime Detection and Prevention (ICDP-19). . pp. 68-73. ISBN 978-1-83953-109-5. (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:77736)
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Abstract
Biometric person recognition using EEG signals has received considerable attention in recent years. This paper proposes a new feature based on the co-activation of EEG sensors. A visual representation of this co-activation feature is used to illustrate the identity-bearing nature of the proposed feature. The DEAP database was used to evaluate the proposed feature which was presented in the form of a visual signature indicating the spatial correlations around the scalp of EEG signals for an individual. The results show a high identification accuracy irrespective of the emotional state of the data subjects.
| Item Type: | Conference or workshop item (Paper) |
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| Uncontrolled keywords: | Biometrics, person recognition, feature extraction, EEG |
| Subjects: |
T Technology > TA Engineering (General). Civil engineering (General) > TA1653 Human face recognition T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
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| Depositing User: | Sanaul Hoque |
| Date Deposited: | 23 Oct 2019 08:35 UTC |
| Last Modified: | 20 May 2025 10:44 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/77736 (The current URI for this page, for reference purposes) |
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https://orcid.org/0000-0001-8627-3429
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