Spatial Signatures for EEG-based Biometric Person Recognition

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 fea...

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Vydáno v:9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019) s. 12 (68 - 73
Hlavní autoři: Al-Darkazali, M, Hoque, S, Deravi, F
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Stevenage, UK IET 2019
The Institution of Engineering & Technology
Témata:
Bioelectric signals
Biology and medical computing
Biometrics
Computer vision and image processing techniques
Digital signal processing
Electrical activity in neurophysiological processes
Electrodiagnostics and other electrical measurement techniques
Electroencephalography
Image recognition
Other topics in statistics
Recognition
Signal processing and detection
Speech processing techniques
Speech recognition and synthesis
Visual signals
electroencephalography
visual representation
DEAP database
co-activation feature
biometrics (access control)
visual signature
identity-bearing nature
spatial correlations
medical signal processing
spatial signatures
feature extraction
EEG signals
EEG-based biometric person recognition
ISBN:9781839531095, 1839531096
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
ObjectType-Feature-2
SourceType-Conference Papers & Proceedings-1
content type line 22
ISBN:9781839531095
1839531096
DOI:10.1049/cp.2019.1170