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Hybrid EEG-NIRS based active command generation for quadcopter movement control

In this study, we have generated four active commands using hybrid electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) for quadcopter control in online environment. Mental arithmetic, left hand clench imagery, and left and right eye-movements are used to navigate the quadcopter. Mental arithmetic task (decoded by fNIRS from the prefrontal cortex) is used to move the quadcopter in forward direction. The left hand clench imagery (decoded by EEG) is used to increase/decrease the height of flight. Signals generated using eye movement in the left/right direction is used for the rotation of the quadcopter. The flight is monitored by the user using the feedback from the frontal camera. The system is unaware of the obstacles in the environment. A fail-safe switch is incorporated in the program using steady-state evoked visual potentials (SSVEP) activity generated at 6 Hz. The fail-safe mechanism stops the forward movement of the quadcopter and the user can adjust the direction of the quadcopter to avoid any collisions with obstacles. The fail-safe trigger can be disabled by focusing on the 6 Hz signal trigger to resume the movement. The experiments conducted on 3 subjects show the possibility of controlling the quadcopter with active commands with increased safety features. The results show the feasibility of increasing commands using hybrid EEG-NIRS for brain-computer interface with applications to quadcopter control.