AsianScientist (Jul. 15, 2019) – Researchers at Hiroshima University, Japan, have developed a 3D printed prosthetic hand that can respond to its users intentions. Their findings have been published in Science Robotics.
Losing a limb, either through illness or accident, can present emotional and physical challenges for an amputee, damaging their quality of life. Prosthetic limbs can be very useful but are often expensive and difficult to use. Unlike other prosthetics made of heavy and expensive metal, the 3D printed prosthetic developed by researchers at the Biological Systems Engineering Lab at Hiroshima University is cheap, light and reactive to motion intent.
Electrodes in the socket of the prosthetic equipment measure electrical signals from nerves through the skin, similar to how an ECG measures heart rate. The signals are sent to the computer, which only takes five milliseconds to make its decision about what movement it should be. The computer then sends the electrical signals to the motors in the hand.
A neural network, named Cybernetic Interface, was trained to recognize movements from each of the five fingers and then combine them into different patterns to turn Scissors into Rock, pick up a water bottle or to control the force used to shake someone’s hand.
“This is one of the distinctive features of this project. The machine can learn simple basic motions and then combine and then produce complicated motions,” said lead researcher Professor Toshio Tsuji.
“The patient just thinks about the motion of the hand and then the robot automatically moves. The robot is like a part of his body.”
Tsuji and his team tested the equipment with patients in the Robot Rehabilitation Center at the Hyogo Institute of Assistive Technology, Kobe. The researchers also collaborated with the company Kinki Gishi to develop the socket to accommodate the amputee patients’ arm.
Seven participants were recruited for this study, including one amputee who had worn a prosthesis for 17 years. Participants were asked to perform a variety of tasks with the hand that simulated daily life, such as picking up small items, or clenching their fist. The accuracy of prosthetic hand movements measured in the study for single simple motion was above 95 percent, and complicated, unlearned motions was 93 percent.
However, using the hand for a long time can be burdensome for the wearer as they must concentrate on the hand position in order to sustain it, which caused muscle fatigue. The team are planning on creating a training plan in order to make the best use of the hand and hope it will become an affordable alternative on the prosthetics market.
The article can be found at: Furui et al. (2019) A Myoelectric Prosthetic Hand With Muscle Synergy–based Motion Determination and Impedance Model–based Biomimetic Control.
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Source: Hiroshima University.
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