Challenges and Opportunities of Data-Driven Learning in Physical Robots for Neurorehabilitation

Explore the challenges and opportunities of data-driven learning in physical robots for neurorehabilitation in this 39-minute talk by Prof. Heike Vallery from RWTH Aachen. Delve into the complexities of embodying intelligent behavior in robots that physically interact with humans, including regulatory constraints, potential damage to robot components during exploration, and unexpected human interactions with animated physical objects. Discover applications in rehabilitation robotics, such as control systems for balance-assisting backpacks, fall detection algorithms for wearable airbags to prevent hip fractures, and intelligent robotic balls for neurorehabilitation. Gain insights from Prof. Vallery's extensive experience in robot-assisted rehabilitation and prosthetic legs, developed through collaborations with clinicians and industry partners. Learn about her academic journey, awards, and research interests in minimalistic robotics design and control, as part of the RWTH Artificial Intelligence Colloquium series.

AIC: Challenges and opportunities of data-driven learning in physical robots for neurorehabilitation