US engineers create AI bionic hand that grips object like a human hand

Engineers at the University of Utah have developed an AI-enhanced bionic hand that mimics the natural grasping ability of a human hand by integrating pressure and proximity sensors with an artificial neural network trained on natural hand movements. This prosthetic hand can intuitively and securely grip objects, allowing users to perform everyday tasks such as picking up small items or drinking from a cup with greater precision and less mental effort, even without extensive practice. The sensors are sensitive enough to detect very light touches, and the AI independently adjusts each finger’s position to form an optimal grasp, resulting in a prosthetic that functions more naturally and reduces cognitive strain. A key innovation of this system is its bioinspired control scheme that balances user intent with AI assistance, allowing the prosthetic to adapt when the user wants to release an object or modify their grip. Tested on four amputee participants, the hand improved performance on standardized assessments and enabled fine motor tasks that were previously difficult, enhancing usability and user confidence. This breakthrough points