Nerve signal-decoding technology could make prosthetic hands easier to use

The human hand is a fiendishly complicated mechanism whose control system is even more obscure. Engineers designing prosthetic hands have for centuries struggled to help the users move them in a natural way. The best technology until now has involved picking up electrical signals from muscles in an amputee's remaining stump and using those to control motors in the wrist, finger and thumb joints of the prosthetic. Although a major step forward from the primitive systems of unpowered hands, this is still not an ideal solution because users have to learn which muscle twitches to use, and the hand’s systems also have to be taught what the patterns of twitches are meant to mean.

Research from the joint biomedical engineering program at North Carolina State University and the University of North Carolina at Chapel Hill promises to make using a prosthetic hand a much more natural experience. Relying on computer models that mimic the behaviour of natural structures in the human forearm, the researchers, led by Prof He (Helen) Huang, a biomedical engineer, have developed a generic musculoskeletal model that takes the place of an amputee's missing muscles, joints and bones to generate control signals for the prosthetic.