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Driving a real wheelchair by means of a braincomputer interface (BCI) system must be a reliable option for locked-in patients. Such navigation should also be autonomous, i.e., not depending on a ground chart. In this work we test the feasibility of driving a customized robotic wheelchair with a BCI system that our group has used in previous studies with virtual and real mobile robots. The results obtained from a sample of three healthy naïve participants suggest that it is an effective option, which could ultimately provide locked-in patients with greater autonomy and quality of life.

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In this work, an electroencephalographic analysis-based, self-paced (asynchronous) brain-computer interface (BCI) is proposed to control a mobile robot using four different navigation commands: turn right, turn left, move forward and move back. In order to reduce the probability of misclassification, the BCI is to be controlled with only two mental tasks (relaxed state versus imagination of right hand movements), using an audio-cued interface. Four healthy subjects participated in the experiment. After two sessions controlling a simulated robot in a virtual environment (which allowed the user to become familiar with the interface), three subjects successfully moved the robot in a real environment. The obtained results show that the proposed interface enables control over the robot, even for subjects with low BCI performance.

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