Additive manufacturing Bionic hand grips like a human

Source: University John Hopkins | Translated by AI 4 min Reading Time

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Engineers at Johns Hopkins University have developed a prosthetic hand that can grasp stuffed animals, water bottles and other everyday objects like a human by adjusting its grip so that it does not damage or mishandle the objects. To enable a more precise and natural grasp, the engineers used technologies such as 3D printing.

The aim of the researchers at John Hopkins University was to develop a more natural prosthesis that functions and feels like a lost limb.(Image: University Johns Hopkins)
The aim of the researchers at John Hopkins University was to develop a more natural prosthesis that functions and feels like a lost limb.
(Image: University Johns Hopkins)

Reaching for a bottle, a ball or even a stuffed animal may seem harmless, but for people with amputations, these everyday actions present a challenge. The prosthesis developed at John Hopkins University could change this by automatically adapting its grip to the object being held. "The goal from the beginning was to develop a prosthetic hand that we model based on the physical and sensory capabilities of the human hand - a more natural prosthesis that functions and feels like a lost limb," said Sriramana Sankar, a Johns Hopkins doctoral student in biomedical engineering who led the work. "We want to give people who have lost their upper limbs the ability to interact safely and freely with their environment, to feel and hold their loved ones without fear of hurting them.

Tactile sensors inspired by the layers of human skin

The prosthesis consists of a multi-finger system with rubber-like polymers and a rigid 3D-printed inner skeleton. Its three layers of tactile sensors, inspired by the layers of human skin, allow it to sense and distinguish objects of different shapes and textures, rather than just recognizing touch. Each of its soft, air-filled finger joints can be controlled with the muscles of the forearm, according to Sankar, and machine learning algorithms focus the signals from the artificial tactile receptors to create a realistic sense of touch. "The sensory information from his fingers is translated into the language of nerves to provide lifelike sensory feedback through electrical nerve stimulation," says Sankar.

We combine the strengths of both rigid and soft robotics to imitate the human hand.

Sriramana Sankar


Prosthesis adjusts handle as required

In the laboratory, the hand identified and manipulated 15 everyday objects, including delicate stuffed animals, dishwashing sponges and cardboard boxes, as well as pineapples, metal water bottles and other more robust objects. In the experiments, the prosthetic hand achieved the best performance compared to the alternatives: it handled the objects with 99.69% accuracy and adjusted its grip when necessary to avoid mishaps. The best example was when it picked up a thin, fragile plastic cup filled with water with just three fingers without damaging it.

"We combine the strengths of both rigid and soft robotics to mimic the human hand," says Sankar. "The human hand is neither completely rigid nor purely soft - it is a hybrid system in which bones, soft joints and tissue work together. This is exactly what we want to achieve with our hand prosthesis. This is new territory for robotics and prosthetics, which have not yet made full use of this hybrid technology. It's about giving a firm handshake or picking up a soft object without fear of crushing it."

Our system is neurally inspired - it models the hand's touch receptors to generate nerve-like messages so that the 'brain' of the prosthesis, i.e. the computer, understands whether something is hot or cold, soft or hard, or slipping out of the grip.

Nitish Thakor


Hand prosthesis uses muscle signals from the forearm

The bio-inspired technology enables the hand to function in this way by using muscle signals from the forearm, like most prosthetic hands. These signals bypass the brain and nerves and allow the hand to flex, release or respond based on its sense of touch. The result, according to Nitish Thakor, professor of biomedical engineering at Johns Hopkins University, is a robotic hand that intuitively "knows" what it is touching, much like the nervous system does.

"When you hold a cup of coffee in your hand, how do you know you're about to drop it? Your palm and fingertips send signals to your brain that the cup is about to slip," says Thakor. "Our system is neurally inspired - it models the hand's touch receptors to generate nerve-like messages so that the 'brain' of the prosthesis, i.e. the computer, understands whether something is hot or cold, soft or hard, or slipping out of grip."

Breakthrough for hybrid robot technology

The research represents an early breakthrough for hybrid robot technology that could transform both prosthetics and robotics, but further work is needed to refine the system, Thakor said. Future improvements could include stronger gripping forces, additional sensors and industrial-grade materials. "This hybrid dexterity is not just important for the next generation of prosthetics," Thakor said. "It's what the robotic hands of the future will need, because they won't just be handling large, heavy objects. They will also have to work with delicate materials such as glass, fabric or soft toys. That's why a hybrid robot designed like the human hand is so valuable - it combines soft and rigid structures, just like our skin, tissue and bones."

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