Biometric Authentication Using Brain Responses to Visual Stimuli

Abstract

Abstract:This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted with visual stimulation, leading to biological brain responses known as Visual Evoked Potentials. We evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features. To classify the features obtained from each individual, we used a one-class classifier per subject and we tested four types of classifiers: K-Nearest Neighbor, Support Vector Data Description and two other classifiers resulting from the combination of the two ones previously mentioned. After testing these four classifiers with features of 70 subjects, the results showed that visual evoked potentials are suitable for an accurate biometric authentication.

Signal Generation, Acquisition, and Processing in Brain Machine Interfaces: A Unified Review

“…Signal noise is also another issue that distorts the signal and needs to be eliminated or reduced to obtain clear neuronal spikes. It is noted that motion-induced artifacts such as blinking, eye movement, skull movement can add to the distortion of recorded signal and need be accounted for in the techniques used for signal filtering (Zúquete et al, 2010).…”