Enhancing hand movement control for amputees using nerve signals
Official title: Improving hand kinematic predictions from implanted EMG in humans and monkeys
Funded at University of Michigan at Ann Arbor · NIH-10979725 · Data updated 2026-11-12
This study is working on a new way to help people with upper limb amputations control prosthetic hands more naturally by using signals from their nerves, making it easier for them to move their fingers and wrists just like they would with real hands.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | September 17, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $577,880 |
| NIH project number | 1R01NS134834-01A1 |
| Project ID | NIH-10979725 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with upper limb amputations who are seeking improved control over their prosthetic devices.
✕Less likely to help
Patients with lower limb amputations or those who do not use prosthetic devices may not benefit from this research.
What this research studies
This research focuses on improving the control of prosthetic hands for individuals with upper limb amputations by utilizing electrical signals from nerves. The team has developed a method called the Regenerative Peripheral Nerve Interface (RPNI), which allows for better signal acquisition from nerve fascicles. By employing advanced deep learning techniques, the project aims to enable continuous and simultaneous control of finger and wrist movements in both humans and monkeys. This innovative approach seeks to restore more natural hand functions for amputees, enhancing their ability to perform daily activities.
Why it matters
Potential benefit: If successful, this research could significantly improve the functionality and usability of prosthetic hands for amputees, leading to greater independence in daily life.
How similar studies have gone: Previous research has shown promise in using similar deep learning techniques for brain-machine interfaces, indicating potential success for this novel approach.
Where this research is happening
-
University of Michigan at Ann Arbor
Ann Arbor, United States Active
Researchers
- Principal investigator: Chestek, Cynthia Anne — University of Michigan at Ann Arbor
- Study coordinator: Chestek, Cynthia Anne
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.