Revolutionary Robotic Hand Can Feel Just Like A Human

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This revolutionary “feeling” robot hand could pave the way for new tactile prosthetics and robotics. Researchers from Uppsala University and Karolinska Institutet in Sweden report that the robotic hand can sense touch and distinguish different objects as effectively as a blindfolded human, determining what type of object it encounters just by feeling it and deciding whether it is a tennis ball or an apple, according to Zhibin Zhang from the Department of Electrical Engineering at Uppsala University.

This new artificial tactile system was inspired by neuroscience to imitate how the human nervous system reacts to touch, using electrical pulses to process dynamic tactile information in the same way as the human nervous system.

According to Interesting Engineering, the “feeling prosthetic” is mainly made of electronic skin (also called e-skin) with sensors that can detect touch pressure and a set of artificial neurons. These sensors convert analog touch signals into electrical pulses, which are processed by a processor that identifies the object.

The researchers claim that it could theoretically learn to identify an unlimited number of objects, though so far they tested the arm using 22 different objects for grasping and 16 different surfaces for touching. A possible future addition to the technology is enabling it to feel pain and heat, as well as feel the material the hand is touching, according to Assistant Professor Libo Chen, who led the study.

The researchers report that providing tactile feedback can make interactions between humans and robots or prosthetic hands safer and more natural, as well as equip prostheses to handle objects with the same dexterity as a human hand.

Another medical use for the technology could be to monitor movement dysfunctions caused by diseases like Parkinson’s and Alzheimer’s, or to help patients recover lost functionality after a stroke. Zhang adds: “The technology can be further developed to tell if a patient is about to fall. This information can be then used to either stimulate a muscle externally to prevent the fall or prompt an assistive device to take over and prevent it.”