EEG-Based Biometric Authentication Using Gamma Band Power During Rest State

被引:63
作者
Thomas, Kavitha P. [1 ]
Vinod, A. P. [1 ]
机构
[1] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore
关键词
Biometric; EEG; Authentication; Gamma band and power spectral density; BRAIN; RECOGNITION; PERMANENCE; SIGNALS; SYSTEM;
D O I
10.1007/s00034-017-0551-4
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Electroencephalography (EEG), one of the most effective noninvasive methods for recording brain's electrical activity, has widely been employed in the diagnosis of brain diseases for a few decades. Recently, the promising biometric potential of EEG, for developing person identification and authentication systems, has also been explored. This paper presents the superior performance of power spectral density (PSD) features of gamma band (30-50 Hz) in biometric authentication, compared to delta, theta, alpha and beta band of EEG signals during rest state. The proposed authentication technique based on simple cross-correlation values of PSD features extracted from 19 EEG channels during eyes closed and eyes open rest state conditions among 109 subjects offers an equal error rate (EER) of 0.0196 which is better than the state-of-the-art method employing eigenvector centrality features extracted from gamma band of 64 EEG channels of the same dataset. The obtained results are promising, but further investigation is essential for exploring the subject-specific neural dynamics and stability of gamma waves and for optimizing the results.
引用
收藏
页码:277 / 289
页数:13
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