Identification of Intended Arm Movement Using Electrocorticographic Signals
This research addresses the critical need for communication and mobility aids for individuals with locked-in syndrome, who have lost voluntary muscle control but remain cognitively intact, potentially improving their independence and quality of life.
The paper tackles the problem of identifying intended arm movements using electrocorticographic signals for Brain Computer Interfaces (BCIs), aiming to translate neurological signals into control commands for devices like wheelchairs to aid individuals with locked-in syndrome.
A Brain Computer Interface (BCI) is a communication system that receives neurological signals from the brain and translates them into control commands for electrical (e.g., computer mouse) and electromechanical (e.g., Wheelchair) devices. The development of such systems was intended originally to aid individuals with a condition called locked-in syndrome. Individuals with this condition have lost all their voluntary muscle control but remain cognitively intact (i.e., mentally aware of their surroundings- can feel emotions, recognize objects/people but are unable to move). This means that they are trapped in their own bodies. The use of BCI may one day improve the independence and quality of life of people with this disability.