Yang, Su ORCID: https://orcid.org/0000-0002-6618-7483 and Deravi, Farzin (2017) On the usability of electroencephalographic signals for biometric recognition: a survey. IEEE Transactions on Human-Machine Systems, 47 (6). pp. 958-969. ISSN 2168-2291

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Abstract

Research on using electroencephalographic signals for biometric recognition has made considerable progress and is attracting growing attention in recent years. However, the usability aspects of the proposed biometric systems in the literatures have not received significant attention. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of electroencephalography (EEG)-based biometric recognition. We first compare the characteristics of different stimuli that have been used for evoking biometric information bearing EEG signals. This is followed by a survey of the reported features and classifiers employed for EEG biometric recognition. To highlight the usability challenges of using EEG for biometric recognition in real-life scenarios, we propose a novel usability assessment framework which combines a number of user-related factors to evaluate the reported systems. The evaluation scores indicate a pattern of increasing usability, particularly in recent years, of EEG-based biometric systems as efforts have been made to improve the performance of such systems in realistic application scenarios. We also propose how this framework may be extended to take into account Aging effects as more performance data becomes available.

Item Type:	Article
Identifier:	10.1109/THMS.2017.2682115
Keywords:	Biometrics, electroencephalography (EEG), feature classification, feature extraction, usability
Subjects:	Computing
Related URLs:	Publisher
Depositing User:	Su Yang
Date Deposited:	03 Jun 2021 15:38
Last Modified:	04 Nov 2024 11:45
URI:	https://repository.uwl.ac.uk/id/eprint/7927

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