A groundbreaking study conducted jointly by Uppsala University and Karolinska Institutet offers promising insights into the potential of prosthetic hands and robots to emulate the sense of touch akin to human hands. Published in the prestigious journal Science, the research opens avenues for enhancing tactile capabilities, with potential applications in restoring lost functionalities in stroke patients.
Zhibin Zhang, a docent at Uppsala University’s Department of Electrical Engineering, highlights the system’s remarkable capability to discern objects as swiftly as a blindfolded individual, merely by tactile sensation. Collaborating closely with researchers from Uppsala University’s Signals and Systems Division, adept in data processing and machine learning, and a team from Karolinska Institutet’s Department of Neurobiology, Care Sciences, and Society, Division of Neurogeriatrics, Zhang and colleague Libo Chen pioneered the study.
Drawing inspiration from neuroscience, the team devised an artificial tactile system mirroring the human nervous system’s response to touch. Employing electrical pulses, the system processes dynamic tactile information akin to the human nervous system.
“With this technology, a prosthetic hand would feel like an integral part of the wearer’s body,” Zhang elucidates.
Comprising three core components, the artificial system includes an electronic skin (e-skin) equipped with touch-sensitive sensors, artificial neurons translating analog touch signals into electrical pulses, and a processor discerning object characteristics. While theoretically capable of recognizing an array of objects, the researchers tested the system with 22 objects for grasping and 16 surfaces for tactile exploration.
Looking ahead, Assistant Professor Libo Chen, leading the study, underscores plans to extend the system’s capabilities to perceive pain, heat, and material properties like wood or metal. Enhanced tactile feedback promises safer and more natural interactions between humans and robots or prosthetic devices, facilitating dexterous object manipulation akin to human hands.
Chen envisions broader applications in the medical domain, such as monitoring movement dysfunctions in conditions like Parkinson’s and Alzheimer’s diseases, or aiding post-stroke rehabilitation. The technology’s potential to predict falls and trigger preventive interventions underscores its utility in enhancing patient safety and autonomy.
Excitingly, the prospect of developing artificial skin for entire robots, leveraging this technology’s capacity to emulate millions of receptors found in human skin, holds promise for future advancements in robotics and healthcare.
