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Researchers at Johns Hopkins University have developed a cutting-edge prosthetic hand that mimics human grip with remarkable accuracy. Unlike traditional robotic hands that are either too rigid or too soft, this new hybrid design adjusts its grasp based on the shape and texture of objects, preventing damage while allowing for a natural feel. The breakthrough, published in Science Advances, could revolutionize prosthetics and robotic systems.
Led by Sriramana Sankar, the team designed the bionic hand with a multifinger system made of soft, rubber-like polymers and a rigid internal skeleton. Inspired by human skin, the hand features three layers of tactile sensors that enable it to distinguish between different textures and shapes, not just detect touch. Controlled by muscle signals from the forearm, it uses machine learning algorithms to process sensory data, creating a realistic sense of touch.
In laboratory tests, the hand successfully identified and manipulated 15 everyday objects, from delicate stuffed toys to rigid metal bottles. It achieved a 99.69% accuracy rate, even demonstrating the ability to pick up a fragile plastic cup filled with water without crushing it. Nitish Thakor, the senior researcher on the project, explains that this system replicates how human hands interact with the environment—sending signals to the brain to detect if an object is slipping or how much pressure is needed to hold it securely.
The research, funded by the Department of Defence and the National Science Foundation, represents a major step forward in prosthetic technology. While improvements are still needed—such as enhanced grip strength and more sensors—this innovation brings prosthetic hands closer than ever to replicating the dexterity and sensitivity of a real human hand.
