Q&A: Surgery and AI give amputees better control of prosthetic hand

People with amputated limbs have few options to regain meaningful function in their arms or legs. In a new study, scientists describe a procedure that uses an implant and machine learning algorithm to capture and interpret electrical signals from severed nerves, enabling four patients to pick up small toy blocks and food cans with a prosthetic hand, as well as make a fist or pinch fingers together. I spoke with Cynthia Chestek, a biomedical engineer at the University of Michigan and an author of the new paper, to learn more. 

Why is it difficult to integrate prosthetic control interfaces with nerves?
During amputation, a nerve is cut and while that nerve continues to carry signals about intended movements, it’s really hard to get those signals out. It’s very hard to record these very small [nerve] signals, and it’s hard to put anything inside the nerve because it causes a lot of scarring.

Did patients have trouble using this system?
It works on the first try. We were able to just ask people to make a bunch of movements that we’re showing them on the screen and then they’re able to replicate that with the hand.

Read the rest of our conversation here.