Science Magazine | December 23, 2019
To understand, model and optimize the comfort of lower limb robotic exoskeletons, researchers in the Penn State Department of Mechanical Engineering have been awarded a $700,000 grant from the National Science Foundation.
Robotic exoskeletons are wearable devices that help enable movement in people with physical disabilities. They can also assist with strenuous tasks beyond normal human capabilities. For this project, the researchers are focused on lower limb exoskeletons — assistive walking devices worn on the leg — to help patients recovering from a stroke and spinal cord injuries or those with cerebral palsy.
“In the field of exoskeletons, everyone acknowledges that comfort is important, but no one measures it, partly because there is no good way to do so,” said Anne Martin, assistant professor of mechanical engineering.
This collaborative project will address those concerns by measuring the physiological signals a person naturally transmits and mapping those values with user-reported feelings of comfort. With that knowledge in hand, the researchers will then aim to develop machine learning techniques to teach the exoskeleton how to adjust its own controls to be more comfortable.
Ultimately, the researchers aim to create a deeper interaction between a person and the robotic device they are wearing. As the human begins walking and adapting their own gait to the machine, the machine learning embedded within the robotics will adjust itself for optimal user comfort.
“This will be co-learning — the mutual adaptation of the machine and the mind,” said Bo Cheng, assistant professor of mechanical engineering.
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