Ultra-precise, mind-controlled prosthetic hand for amputees via RPNI neural interface

“It’s like you have a hand again”: A new study from the University of Michigan gives amputees natural, finger-level control of a robotic hand: In this major advance for mind-controlled prosthetics, U-M research led by Paul Cederna and Cindy Chestek demonstrates an ultra-precise prosthetic interface technology that taps faint latent signals from nerves in the arm and amplifies them to enable real-time, intuitive, finger-level control of a robotic hand. For in-depth coverage of the research: U-M’s approach to neuroprosthetics centers on the Regenerative Peripheral Nerve Interface (RPNI)—a small graft of muscle tissue surgically attached to the end of a severed nerve in an amputee’s arm. While other neural interfaces are harmful to nerves, the RPNI promotes healthy nerve growth and acts as a bioamplifier, converting faint neural signals sent from the brain into large, recordable muscle signals that remain stable for years. Combined with machine learning algorithms, these signals enable intuitive, real-time mind control of advanced robotic prosthetic hands. The research is published in the journal Science Translational Medicine and is titled, “A regenerative peripheral nerve interface allows real-time control of an artificial hand in upper limb amputees.“ See it covered in: Wired: MIT Technology Review: Stat News: Paul Cederna is the Robert Oneal Collegiate Professor of Plastic Surgery and a professor of biomedical engineering. Cindy Chestek is an associate professor of biomedical engineering and part of U-M’s Robotics Institute. ------ Watch more videos from Michigan Engineering and subscribe: The University of Michigan College of Engineering is one of the world’s top engineering schools. Michigan Engineering is home to 12 highly-ranked departments, and its research budget is among the largest of any public university. Follow Michigan Engineering: Twitter: Facebook: Instagram: Contact Michigan Engineering: