Eeg-based biometrie authentication using self-referential visual stimuli

Biometrie recognition of persons are widely explored nowadays to develop robust and trustworthy security systems. On account of the unique neural signature of each person, the brain activity recorded by Electroencephalogram (EEG) has recently been identified as a potential biometric trait. In this paper, we propose an online EEG-based biometric system which utilizes the activations of brain towards a set of subject-specific self-referential visual stimuli. The stimuli set consist of a number of self-face images and that of subject's relatives, which are expected to elicit brain activity in a subject-specific manner. The subject-specific biometric marker used in the proposed authentication system is the relative spectral activity of left and right hemisphere EEG in various frequency bands. Experimental analysis reveals utility of alpha and beta bands for the proposed approach, offering an average biometric recognition accuracy of 87.50% over 4 subjects. Results of the proposed methodology give insights for further research to examine the permanence and generalization of the proposed system in a larger group of subjects.

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