Evaluation of Command Discrimination from EEG Signal for Controlling A Mind Drone

抄録

This research aims to discuss how to obtain the number of commands needed to control a mind drone from Electroencephalogram (EEG) signals. The brain-computer interface (BCI) analyzes brain waves to identify human emotions and brain perception and control locations. To use this technology, when a specific thought or stimulus is received, its brain waves can be used as a control command for the robot, but consumer BCIs can only handle fewer commands. On the other hand, to control a drone freely requires more than seven commands. This study investigates and compares what kind of stimulus-based command classification is necessary and what kind of machine learning algorithm can obtain more than seven commands.