Person authentication from neural activity of face-specific visual self-representation

In this paper, we propose a new biometric system based on the neurophysiological features of face-specific visual self representation in a human brain, which can be measured by ElectroEncephaloGraphy (EEG). First, we devise a novel stimulus presentation paradigm, using self-face and non-self-face images as stimuli for a person authentication system that can validate a person's identity by comparing the observed trait with those stored in the database (one-to-one matching). Unlike previous methods that considered the brain activities of the resting state, motor imagery, or visual evoked potentials, there are evidences that the proposed paradigm generates unique subject-specific brain-wave patterns in response to self- and non-self-face images from psychology and neurophysiology studies. Second, we devise a method for adaptive selection of EEG channels and time intervals for each subject in a discriminative manner. This makes the system immune to forgery since the selected EEG channels and time intervals for a client may not be consistent with those of imposters in terms of the latency and amplitude of the brain-waves. Based on our experimental results and analysis, it is believed that the proposed person authentication system can be considered as a new biometric authentication system.