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Sensors 2018, 18(2), 335;

An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals

China National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450001, China
Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610000, China
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 20 January 2018 / Accepted: 21 January 2018 / Published: 24 January 2018
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems. View Full-Text
Keywords: person authentication; EEG; eye blinking; multi-task; score fusion; open-set authentication; permanence capability person authentication; EEG; eye blinking; multi-task; score fusion; open-set authentication; permanence capability

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Wu, Q.; Zeng, Y.; Zhang, C.; Tong, L.; Yan, B. An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals. Sensors 2018, 18, 335.

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