A study on EEG quality in physical movements with Steady-State Visual Evoked Potentials.

In this paper, we investigated the quality of ElectroEncephaloGraphic (EEG) signals during performing physical movements. By using a portable EEG device, the Steady-State Visual Evoked Potential (SSVEP) was recorded on parietal and occipital locations. The SSVEP induced by flickering stimuli was successfully observed in the self-paced mimic walking conditions as well as in the sitting conditions. To see the dependence of temporal and spatial filters on the potential performance of Brain-Computer Interfaces (BCI) we applied the signal processing of Principal Component Analysis and Linear Discriminant Analysis. The pattern recognition performances in inferring the subject's eye gaze directions from the EEG signals could be perfect even in the self-paced mimic walking conditions. It was found that three electrodes on parieto-occipital and occipital locations were essential in order to have perfect performances. From these results, we conclude that the applications using SSVEP-based BCI can be realized even in the physically moving context.