Wheelchair navigation with an audio-cued, two-class motor imagery-based brain-computer interface system

Abstract

Driving a real wheelchair by means of a brain-computer 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.