Identification of Intended Arm Movement Using Electrocorticographic Signals

TL;DR

This paper discusses the development of a Brain Computer Interface that translates electrocorticographic signals into commands to assist individuals with locked-in syndrome, aiming to improve their independence.

Contribution

The paper introduces a method for identifying intended arm movements using electrocorticographic signals for BCI applications.

Findings

Successful identification of arm movement intentions from ECoG signals

Potential to enhance BCI control accuracy for disabled individuals

Foundation for future real-time movement decoding systems

Abstract

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.