WebZine
2020. 04
What's New
Joe Hamilton, a participant in the University of Michigan RPNI study, naturally uses his mind to control a DEKA prosthetic hand to pinch a small zipper on a hand development testing platform.
Image credit: Evan Dougherty, Michigan Engineering
ANN ARBOR—In a major advance in mind-controlled prosthetics for amputees, University of Michigan researchers have tapped faint, latent signals from arm nerves and amplified them to enable real-time, intuitive, finger-level control of a robotic hand.
To achieve this, the researchers developed a way to tame temperamental nerve endings, separate thick nerve bundles into smaller fibers that enable more precise control, and amplify the signals coming through those nerves. The approach involves tiny muscle grafts and machine learning algorithms borrowed from the brain-machine interface field.
“This is the biggest advance in motor control for people with amputations in many years,” said Paul Cederna, who is the Robert Oneal Collegiate Professor of Plastic Surgery at the U-M Medical School, as well as a professor of biomedical engineering.
“We have developed a technique to provide individual finger control of prosthetic devices using the nerves in a patient’s residual limb. With it, we have been able to provide some of the most advanced prosthetic control that the world has seen.”
Cederna co-leads the research with Cindy Chestek, associate professor of biomedical engineering at the U-M College of Engineering. In a paper published March 4 in Science Translational Medicine, they describe results with four study participants using the Mobius Bionics LUKE arm. View an in-depth multimedia presentation about the work.
Intuitive prosthetic control works on the first try
“You can make a prosthetic hand do a lot of things, but that doesn’t mean that the person is intuitively controlling it. The difference is when it works on the first try just by thinking about it, and that’s what our approach offers,” Chestek said. “This worked the very first time we tried it. There’s no learning for the participants. All of the learning happens in our algorithms. That’s different from other approaches.”
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AI-Powered Shoes Unlock the Secrets of Your Sole
Stevens Institute of Technology is turning running shoes into portable laboratories
The smart insole can deliver real-time data on the length, speed, and power of a wearer's stride with better accuracy than existing foot-worn technologies.
Source: Stevens Institute of Technology
Researchers at Stevens Institute of Technology have developed an AI-powered, smart insole that instantly turns any shoe into a portable gait-analysis laboratory.
The work, reported in IEEE Transactions on Neural Systems and Rehabilitation Engineering, could benefit clinical researchers by providing a new way to precisely measure walking function in patients with movement disorders or musculoskeletal injuries, in their living environments. The technology could also lead to significant advances for athletes, by helping them improve their running technique.
“From a practical standpoint, that’s invaluable,” said Damiano Zanotto, lead author and director of Stevens Wearable Robotic Systems Lab. “We’re now able to accurately analyze a person’s gait in real time, in real-world environments.”
Taking a single step might seem simple, but capturing reliable information about a person’s gait in real-life environments remains a major challenge for researchers. Gold-standard gait-analysis technologies, such as camera-based motion-capture systems and force plates, are expensive and can only be used inside laboratories, so they offer few insights into how people walk around in the real world. Emerging wearable technologies such as smart shoes, pods, and insoles can potentially overcome this limitation, but the existing products cannot provide accurate gait data.
In their work, Zanotto and his team show that their smart insole can deliver real-time data on the length, speed, and power of a wearer’s stride with better accuracy than existing foot-worn technologies – and at a fraction of the cost of traditional laboratory equipment. (Zanotto and his team are seeking two patents relating to the SportSole, and several companies and professional sporting franchises are closely following the team’s work.)