Researchers from North Carolina State University, the University of North Carolina and Arizona State University have developed an intelligent system for “tuning” powered prosthetic knees. Among the researchers are BME Professor Helen Huang and PhD biomedical students Yue Wen and Andrea Brandt, who just published the paper “Online Reinforcement Learning Control for the Personalization of a Robotic Knee Prosthesis” in the journal IEEE Transactions on Cybernetics. This system is the first to rely solely on reinforcement learning to tune the robotic prosthesis. Normally, a human practitioner works for a few hours with the patient to modify the parameters so that they can walk comfortably on the powered prosthetic knee. In contrast, the computer program makes use of reinforcement learning to modify all 12 parameters in 10 minutes only. Read the full article here.
‘Tuning’ of Robotic Prosthetics with a computer program
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