Unobtrusive biometric system based on electroencephalogram analysis

Abstract

Features extracted from electroencephalogram (EEG) recordings have proved to be unique enough between subjectsfor biometric applications. We show here that biometry based on these recordings offers a novel way to robustly authenticateor identify subjects. In this paper, we present a rapid and unobtrusive authentication method that only uses 2 frontal electrodesreferenced to another one placed at the ear lobe. Moreover, the system makes use of a multistage fusion architecture, whichdemonstrates to improve the system performance. The performance analysis of the system presented in this paper stemsfrom an experiment with 51 subjects and 36 intruders, where an equal error rate (EER) of 3.4 is obtained, that is, trueacceptance rate (TAR) of 96.6 and a false acceptance rate (FAR) of 3.4. The obtained performance measures improvethe results of similar systems presented in earlier work.