Design and Implementation of Steady State Visual Evoked Potential Based Brain Computer Interface Video Game

Abstract

Brain Computer Interface (BCI) is a system that enables device control by processing EEG signals acquired from scalp. This system can be used as a communication channel for severely disabled patients as well as other applications for healthy people. In this study, a BCI game was implemented based on classifying steady state visual evoked potentials (SSVEP) that occur in occipital lobe when a subject is exposed to a visual stimulus flickering at a certain frequency using canonical correlation analysis (CCA). In the experiment, the subjects were expected to move a square to specific locations using four visual stimuli with different frequencies. This task could be completed at 1.4 seconds in the best case scenario. The subjects completed this task at 1.4 seconds in the best run, 36.22 seconds in the worst run, and 8.57 seconds in average. The ratio of moves towards target to all moves were calculated as 66.72%.