High-accuracy user identification using EEG biometrics

Toshiaki Koike-Akino; Ruhi Mahajan; Tim K. Marks; Ye Wang; Shinji Watanabe; Oncel Tuzel; Philip Orlik

doi:10.1109/EMBC.2016.7590835

High-accuracy user identification using EEG biometrics

Toshiaki Koike-Akino, Ruhi Mahajan, Tim K. Marks, Ye Wang, Shinji Watanabe, Oncel Tuzel, Philip Orlik

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

45 Citations (Scopus)

Abstract

We analyze brain waves acquired through a consumer-grade EEG device to investigate its capabilities for user identification and authentication. First, we show the statistical significance of the P300 component in event-related potential (ERP) data from 14-channel EEGs across 25 subjects. We then apply a variety of machine learning techniques, comparing the user identification performance of various different combinations of a dimensionality reduction technique followed by a classification algorithm. Experimental results show that an identification accuracy of 72% can be achieved using only a single 800 ms ERP epoch. In addition, we demonstrate that the user identification accuracy can be significantly improved to more than 96.7% by joint classification of multiple epochs.

Original language	English
Title of host publication	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	854-858
Number of pages	5
Volume	2016-October
ISBN (Electronic)	9781457702204
DOIs	https://doi.org/10.1109/EMBC.2016.7590835
Publication status	Published - 2016 Oct 13
Externally published	Yes
Event	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States Duration: 2016 Aug 16 → 2016 Aug 20

Other

Other	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country/Territory	United States
City	Orlando
Period	16/8/16 → 16/8/20

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

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10.1109/EMBC.2016.7590835

Cite this

Koike-Akino, T., Mahajan, R., Marks, T. K., Wang, Y., Watanabe, S., Tuzel, O., & Orlik, P. (2016). High-accuracy user identification using EEG biometrics. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (Vol. 2016-October, pp. 854-858). Article 7590835 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7590835

High-accuracy user identification using EEG biometrics. / Koike-Akino, Toshiaki; Mahajan, Ruhi; Marks, Tim K. et al.
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October Institute of Electrical and Electronics Engineers Inc., 2016. p. 854-858 7590835.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Koike-Akino, T, Mahajan, R, Marks, TK, Wang, Y, Watanabe, S, Tuzel, O & Orlik, P 2016, High-accuracy user identification using EEG biometrics. in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. vol. 2016-October, 7590835, Institute of Electrical and Electronics Engineers Inc., pp. 854-858, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 16/8/16. https://doi.org/10.1109/EMBC.2016.7590835

Koike-Akino T, Mahajan R, Marks TK, Wang Y, Watanabe S, Tuzel O et al. High-accuracy user identification using EEG biometrics. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October. Institute of Electrical and Electronics Engineers Inc. 2016. p. 854-858. 7590835 doi: 10.1109/EMBC.2016.7590835

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High-accuracy user identification using EEG biometrics

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