Image credit:  Lizhi Pan, Dustin L. Crouch, and He Huang, North Carolina State University and University of North Carolina

 

US researchers claim to have cracked nerve code to make prosthetic hands more intuitive to control

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.

Unlike existing myoelectric control systems, this technology does not rely on machine learning to generate control algorithms.

Every time you change your posture, your neuromuscular signals for generating the same hand/wrist motion change. So relying solely on machine learning means teaching the device to do the same thing multiple times; once for each different posture, once for when you are sweaty versus when you are not, and so on. Our approach bypasses most of that.
Prof He (Helen) Huang

In early testing, both able-bodied and amputee volunteers were able to use the model-controlled interface to perform all of the hand and wrist motions the team decided to test, despite having very little training. Before beginning full clinical trials, the team is looking for trans-radial amputee volunteers (who have lost an arm between the elbow and the wrist) to test how well the technology copes with activities of daily living.

To be clear, we are still years away from having this become commercially available for clinical use. And it is difficult to predict potential cost, since our work is focused on the software, and the bulk of cost for amputees would be in the hardware that actually runs the program. However, the model is compatible with available prosthetic devices.
Prof He (Helen) Huang

The use of the device is not limited to prosthetics. Huang also suggests that it might be useful in developing computer interfaces for able-bodied people, which might be used for computer gaming or manipulating objects in CAD programs.

 

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See also https://news.ncsu.edu/2018/05/generic-model-prosthetic-2018/

 
 
 
 
 

The Engineer