Researchers at Johns Hopkins University have created a better prosthetic hand with a hybrid design that can delicately grasp a variety of objects with just the right amount of pressure. The robot's appendages combine rigid and flexible components to mimic the natural structure of the human hand, as well as an array of sensors and systems that provide feedback to the user's nerves.
In experiments, it successfully picked up and manipulated 15 different objects, including delicate stuffed animals, cardboard boxes, pineapples, metal water bottles, and even a flimsy plastic cup filled with water -- without denting or damaging them.
"We want to allow people with missing upper limbs to safely and freely interact with their surroundings and feel and hug their loved ones without fear of harming them," explains Sriramana Sankar, a biomedical engineering doctoral student who led the research project. Sankar presented the findings in his first-author paper, published this week in Science Advances.
The prosthetic device closely resembles a human hand, with its five-jointed fingers made from a soft, rubbery polymer and a 3D-printed skeleton. Three layers of bio-inspired tactile sensors enable it to correctly grasp and differentiate various objects. The joints of the fingers are filled with air and controlled by the muscles of the forearm.
"Sensory information from the fingers is translated into neural language, providing natural sensory feedback through electrical nerve stimulation," Sankar said. "This is thanks to a machine learning algorithm that concentrates the signals from the sensors and then transmits them back to the nerves in the user's body - similar to other prosthetics."
These signals bridge the gap between the brain and nerves, allowing the hand to respond to what it touches. This system makes the robot more intuitive to use and more like a real robot hand than similar products we've seen before.
Currently, robotic hands can be controlled using myoelectric signals, and people with upper limb loss usually use myoelectric signals to control myoelectric prosthetic hands. A $150 gesture-controlled device called the MyoArmband collects and classifies myoelectric signals, then sends hand position to an Arduino microcontroller, which pneumatically actuates the robotic hand.
"If you're holding a cup of coffee, how do you know you're going to drop it?" said study leader Nitish Thakor. "Your palms and fingertips send signals to your brain that the cup is slipping." Our system is neurally inspired - it's modeled on the hand's touch receptors, which generate neural-like information so that the prosthetic's 'brain', or its computer, can understand whether something is hot or cold, soft or hard, or if it slips from the grip. "
This is a step forward from previous efforts we've seen in prosthetic development. Last year, Italian scientists demonstrated a way to detect the temperature of objects a prosthetic hand touches. And as early as 2021, a joint project between MIT and Shanghai Jiao Tong University demonstrated a prosthetic hand that can precisely inflate individual fingers made of soft elastomer to grasp objects and provide tactile feedback.
The new technology could provide amputees with more precise, natural-feeling prosthetics, and allow humanoid robots to more dexterously handle delicate items in the home and build more robots on assembly lines.
The team will continue to develop the device, exploring adding stronger grip, more sensors and higher-quality materials.