Development of a Brain-Computer Interface to Control Finger Movements of a Robotic Hand

This study introduces the creation of a Brain-Computer Interface (BCI) based on superficial Electroencephalography (EEG) for the purpose of controlling individual finger movements of an off-the-shelf five degrees of freedom robotic hand to demonstrate the use of this information with the aims to obtain commands for improve human machine interfaces in the neurorehabilitation field. To facilitate the execution of finger movements, five distinct EEG patterns associated with the following actions were employed: motor imagery, eye blinks, eye gaze, eyebrow movements, and prolonged chewing. These specific actions were selected due to their high success rates among individuals with motor disabilities in generating them accurately. The initial findings indicate that a volunteer successfully performed finger movements according to his intention. These results hold significant promise for applications in post-stroke rehabilitation and neuroprosthesis training, as the ability to control finger movements through this technology has the potential to greatly benefit individuals in regaining motor function and improving their overall quality of life.