Carnegie Mellon University researchers have achieved the first noninvasive system that enables real-time control of individual robotic fingers through brain signals alone, using electroencephalography (EEG) technology.

The breakthrough system uses deep neural networks to decode brain signals associated with movement execution and motor imagery of individual finger movements, translating them into corresponding robotic finger motions.

Carnegie Mellon University researchers have achieved the first noninvasive system that enables real-time control of individual robotic fingers through brain signals alone, using electroencephalography (EEG) technology.

The breakthrough system uses deep neural networks to decode brain signals associated with movement execution and motor imagery of individual finger movements, translating them into corresponding robotic finger motions.