Overview
- The team modified a commercial TASKA hand with pressure sensors and optical proximity sensors that detect objects just before touch.
- An artificial neural network trained on proximity data autonomously fine-tunes each digit’s position to form stable, precise grasps.
- A bioinspired shared-control scheme balances user intent with AI assistance so the prosthesis augments control rather than competing with it.
- Four transradial amputees showed better performance on standardized tasks and completed fine-motor activities with less mental effort, according to the Nature Communications paper.
- Researchers plan to integrate implanted neural interfaces for thought-based control and restored touch, with broader clinical testing and commercialization not yet announced.