An investigation of using SSVEP for EEG-based user authentication system

User authentication system to identify individual by using electroencephalograph (EEG) feature based on steady-state visual evoked potential (SSVEP) has been proposed. Recently, SSVEP has been used as a stimulator due to it plays an important role in the response to various visual stimuli, i.e., flickering rate (F), intensity (I), and duty cycle (D). Moreover, the SSVEPs are practical and useful in research because of its excellent signal-to-noise ratio and relative immunity to artifacts and succeeded in many disciplines. In this paper, therefore, we investigate individual SSVEP corresponding to the different visual stimulation in terms of frequency component analysis in the four principal frequency bands, i.e., delta (0.1-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), and beta (14.0-30.0 Hz). Subjects were instructed to fixate an LED light source then record associated SSVEP waveform. The variation in displaying of the presentation stimuli during a task was examined thereby demonstrating the high usability, adaptability and flexibility of the visual stimulator and determine the optimal parameters for the subject comfort. The experiment achieved the true acceptance rate of 60% to 100% approximately revealing the potential of proposed system for user classification/identification.