In this paper, a personal authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. To achieve performance stability, a sequence of self-face photographs including first-occurrence position and non-first-occurrence position are taken into account in the serial occurrence of visual stimuli. Additionally, a Fisher linear classification method and event-related potential technique for feature analysis is adapted to yield remarkably better outcomes than those obtained by most existing methods. Results show that EEG-based authentication of individuals via brain-computer interface can be considered suitable as an approach to biometric authentication.
Cite this article
Application of a brain-computer interface for person authentication using EEG responses to photo stimuli
1 Center of Collaboration and Innovation, Jiangxi University of Technology, Nanchang, Jiangxi Province, 330098, P.R. China
*Correspondence: firstname.lastname@example.org (Jianfeng Hu)
J. Integr. Neurosci. 2018, 17(1), 53–60; https://doi.org/10.31083/JIN-170042
Submitted: 8 August 2017 | Accepted: 25 July 2017 | Published: 15 January 2018