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Brain-Computer interfaces (BCI) are widely used in reading brain signals andconverting them into real-world motion. However, the signals produced from theBCI are noisy and hard to analyze. This paper looks specifically towardscombining the BCI's latest technology with ultrasonic sensors to provide ahands-free wheelchair that can efficiently navigate through crowdedenvironments. This combination provides safety and obstacle avoidance featuresnecessary for the BCI Navigation system to gain more confidence and operate thewheelchair at a relatively higher velocity. A population of six human subjectstested the BCI-controller and obstacle avoidance features. Subjects were ableto mentally control the destination of the wheelchair, by moving the targetfrom the starting position to a predefined position, in an average of 287.12seconds and a standard deviation of 48.63 seconds after 10 minutes of training.The wheelchair successfully avoided all obstacles placed by the subjects duringthe test.

BCI-Controlled Hands-Free Wheelchair Navigation with Obstacle Avoidance