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AI helps prosthetic hand grasp more naturally — person wearing blue and black gloves

AI helps prosthetic hand grasp more naturallyCEFR B1

9 Dec 2025

Adapted from Evan Lerner-Pennsylvania, Futurity CC BY 4.0

Photo by Marcos Ramírez, Unsplash

Level B1 – Intermediate
4 min
193 words

Researchers at the University of Utah used artificial intelligence to make a commercial TASKA Prosthetics hand act more like a natural hand. They fitted custom fingertips that measured pressure and included optical proximity sensors sensitive enough to detect an effectively weightless cotton ball landing on a finger.

The team trained a neural network on the proximity data so each finger moved to the right distance for a stable grasp. Each finger has its own sensor and can "see" what is in front of it, so the digits work in parallel to form a secure hold on different objects. To avoid the user and machine fighting over control, the researchers developed a bioinspired shared-control system that balances human and AI input.

The study, led by Jacob A. George and Marshall Trout, appears in Nature Communications. The system was tested with four participants whose amputations were between the elbow and wrist. Participants completed fine motor tasks like picking up small objects and drinking from a plastic cup. The team plans to combine these sensors and intelligent control with implanted neural interfaces. Funding came from the National Institutes of Health and the National Science Foundation.

Difficult words

  • artificial intelligencecomputer systems that learn and make decisions
  • fingertipend part of a finger used to touch
    fingertips
  • sensordevice that detects and measures changes
    sensors
  • neural networkcomputer model that learns from data
  • shared-controlmethod dividing control between human and machine
  • amputationloss of a limb by surgical removal
    amputations
  • neural interfacedevice connecting nerves to electronic systems
    neural interfaces

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