A Cloud-based Brain-controlled Wheelchair with Autonomous Indoor Navigation System

Abstract

Paralysis is the most inhibiting among all the severe motor disabilities. Indeed, people are inflicted with paralysis as the result of an accident or a medical condition that affects - completely or partially, the way muscles and nerves function. However, these patients are cognitively aware, and their mental abilities are unimpaired, and can still be autonomous and more useful in many other ways than many able-bodied people. Brain-computer interface (BCI) technology is now being incorporated into the treatment of physically impaired patients offering them an improved mobility and thus autonomy. In this paper, we propose to develop a smart brain-controlled wheelchair with autonomous navigation system for people with severely impaired motor functions. Our proposed solution allows its users to move around in indoor premises with great flexibility and minimum instructions. That is, high-level commands such as “Go to location X” is enough for the wheelchair to move to the desired location while finding its way around obstacles and obstructions. This system relies on two main components: a BCI interface to issue high level commands to the wheelchair, and a component for autonomous indoor navigation system which integrates all the elements of path planning obstacle detection and avoidance. In addition, the solution relies on the use of trained models that are deployed in cloud and provided as facility specific services.