Asynchronous control of unmanned aerial vehicles using a steady-state visual evoked potential-based brain computer interface

AbstractThe goal of this study is to design an asynchronous steady-state visual evoked potential (SSVEP) BCI system to enable control of an unmanned aerial vehicle (UAV) with multiple commands. An SSVEP-based BCI system with six different flickering frequencies was constructed to realize six actuation commands for UAV control. In addition, asynchronous control was achieved by including a detection of the ‘idle’ brain state using a novel likelihood ratio test and the hover command was implemented for the idle state. Offline recording was conducted to evaluate the detection accuracies and a game-like online experiment was also conducted to assess the online performance of the proposed system. Forty-two subjects participated in offline recordings to evaluate the detection accuracy of commands as well as detection of the ‘idle’ state. An average error rate of 15% was obtained for detecting the six commands, whereas an average error rate of 23.06% was obtained for differentiating commands from idle brain state...