Evaluation of SSVEP as passive feedback for improving the performance of Brain Machine Interfaces
Shaocheng Wang, Ehsan Tarkesh Esfahani, Sundararajan V. University of California Riverside
Research in brain-computer interfaces have focused primarily on motor imagery tasks such as those involving movement of a cursor or other objects on a computer screen. In such applications, it is important to detect when the user is interested in moving an object and when the user is not active in this task. This paper evaluates the steady state visual evoked potential (SSVEP) as a feedback mechanism to confirm the mental state of the user during motor imagery. These potentials are evoked when a subject looks at a flashing objects of interest. Four different experiments are conducted in this paper. Subjects are asked to imagine the movement of flashing object in a given direction. If the subject is involved in this task, the SSVEP signal will be detectable in the visual cortex and therefore the motor imagery task is confirmed. During the experiment, EEG signal is recorded at 4 locations near visual cortex. Using a weighting scheme, the best combination of the recorded signal is selected to evaluate the presence of flashing frequency. The experimental result shows that the SSVEP can be detected even in complex motor imagery of flickering objects. The detection rate of 85% is achieved while the refreshing time for SSVEP feedback is set to 0.5 seconds.