AR-assisted navigation of a mobile robot controlled by an SSVEP-based BCI

A Brain-Computer Interface (BCI) is a system that can be used to remotely control devices by using brain signals without moving any muscle. This control could benefit patients with motor neuron diseases such as Amyotrophic Lateral Sclerosis (ALS). This paper used a Steady-State Visual Evoked Potetinals (SSVEP) - based BCI to control a mobile robot. The system was successfully tested by ten healthy subjects who could complete a navigation task where they had to follow a route in a real office environment, achieving an average total time of 652 seconds. The system also used markers during the route to give Augmented Reality (AR) directions, which helped the subjects have a better orientation. The general feeling of the system was good since the subjects stated that they were excited while controlling the robot, proving that besides further improvements, this could be used to improve the quality of life of ALS patients.