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Task sensitivity in EEG biometric recognition

Yang, Su, Deravi, Farzin, Hoque, Sanaul (2016) Task sensitivity in EEG biometric recognition. Pattern Analysis and Applications, 21 . pp. 105-117. ISSN 1433-7541. E-ISSN 1433-755X. (doi:10.1007/s10044-016-0569-4) (KAR id:56671)

Abstract

This work explores the sensitivity of electroencephalographic-based biometric recognition to the type of tasks required by subjects to perform while their brain activity is being recorded. A novel wavelet-based feature is used to extract identity information from a database of 109 subjects who performed four different motor movement/imagery tasks while their data was recorded. Training and test of the system was performed using a number of experimental protocols to establish if training with one type of task and tested with another would significantly affect the recognition performance. Also, experiments were conducted to evaluate the performance when a mixture of data from different tasks was used for training. The results suggest that performance is not significantly affected when there is a mismatch between training and test tasks. Furthermore, as the amount of data used for training is increased using a combination of data from several tasks, the performance can be improved. These results indicate that a more flexible approach may be incorporated in data collection for EEG-based biometric systems which could facilitate their deployment and improved performance.

Item Type: Article
DOI/Identification number: 10.1007/s10044-016-0569-4
Uncontrolled keywords: EEG, Biometrics, identification, verification
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Farzin Deravi
Date Deposited: 28 Jul 2016 09:42 UTC
Last Modified: 09 Dec 2022 02:38 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/56671 (The current URI for this page, for reference purposes)

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