When training to regain movement after stroke or spinal cord injury (SCI), patients must once again learn how to keep their balance during walking movements. Current clinical methods support the weight of the patient during movement, while setting the body off balance. This means that when patients are ready to walk without mechanical assistance, it can be hard to re-train the body to balance against gravity. This is the issue addressed in a recent paper published in Science Translational Medicine by a team lead by Courtine-Lab, and featuring Ijspeert Lab, NCCR Robotics and EPFL.
Clinical trials of Russia’s first medical exoskeleton have begun in a Moscow hospital, marking the latest step in the Skolkovo-backed innovation’s battle to reach the market.
Associate Professor Toshiaki Tsuji’s Laboratory at Saitama University has developed R-cloud, a rehabilitation support robot that enables users to view how their own muscles move during rehabilitation and training.
“This rehabilitation support robot is used for strengthening the arms. Its moving parts use pneumatic muscles, and it provides support with gentle movements so it is very safe. Another distinguishing feature is haptic signal processing, a technique that estimates muscular force during training and makes this information visible. It also has a feature that quantifies and evaluates the effect of training.”
In this sixth part of the ShanghAI Lecture series, Rolf Pfeifer introduces the topic “Artificial Evolution” and gives examples of evolutionary processes in artificial intelligence. The first guest lecture, by Francesco Mondada (EPFL) is about the use of robots in daily life; in the second guest lecture, Robert Riener (ETH Zürich) talks about rehabilitation robots.
August 9, 2020
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