EEG Biometrics for User Recognition Using Visually Evoked Potentials

Electroencephalographic signals (EEG) have been long supposed to contain features characteristic of each individual, yet a substantial interest for exploiting them as a potential biometrics for people recognition has only recently grown. The biggest advantages of EEG-based biometrics lie in its universality, security and robustness, while its major concerns are related to the acquisition protocol that can be inconvenient and time consuming. This paper investigates the use of EEG signals, elicited using visual stimuli, for the purpose of biometric recognition, and evaluates the performance obtained considering various frequency bands, different number of visual stimuli, and various subsets of time intervals after the stimuli presentation. An exhaustive set of experimental tests has been performed by employing EEG data of 50 different subjects acquired in two different sessions, separated by one week time.