Brain-computer interfaces figure in much of the research and development in new prosthetics technology. We’ve written about work mind-controlled prosthetics often, including the BrainGate consortium’s work with a mind-controlled mouse for people with paralysis. Neurable unveiled a brain-controlled virtual reality platform with which developers create content for virtual reality applications using only their brains. Neuroscientists at École Polytechnique Fédérale de Lausanne (EPFL) used implants in the brain and spine to enable paralyzed primates to walk again.
More recently, University of Michigan researchers developed technology that separates thick nerve bundles into smaller fibers wrapped with tiny muscle grafts. Machine learning algorithms then enable precise control with hand prosthetics. Connecting to nerves in a patient’s residual limb, the Michigan technology amplifies the nerve signals to provide individual finger control in robot hands.
Wrapping muscle grafts around the residual limb nerve endings gave the nerves new tissue to which to attach and served as “megaphones” for the nerve signals. The result is a newfound ability to use individual fingers and individual, multi-degree thumb movements. This level of control is a breakthrough for prosthetic wearers.
According to Cindy Chestek, associate professor of biomedical engineering at the U-M College of Engineering, the prosthetic technology worked 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.”
Study participants used their minds to control the prosthetic hands to pick up objects with a pincer grasp, move their thumbs in continuous motion, and lift spherical objects. The subjects could even play a version of Rock, Paper, Scissors.
Next steps for the UMich team include clinical testing and finding new ways to completely restore the full range of natural hand movements.