Researchers create responsive ankle exoskeleton algorithm

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Jacqueline Hannan, a PhD student in industrial and operations engineering, demonstrates walking with an ankle exoskeleton in Stirling’s lab. Photo credit: Brenda Ahearn, University of Michigan Engineering

Researchers at the University of Michigan have created a responsive ankle exoskeleton algorithm that uses direct muscle measurement to handle changes in pace and gait. The algorithm could potentially support a user who switches between walking and running with ease. 

The researchers hope that the algorithm will bring us a step closer to ankle exoskeletons that help people extend their endurance. In particular, the algorithm could help researchers develop exoskeletons that automatically adapt to individual users and tasks, eliminating or greatly reducing the need for manual recalibration in between each task. 

“This particular type of ankle exoskeleton can be used to augment people who have limited mobility,” Leia Stirling, U-M associate professor of industrial and operations engineering and robotics and senior author of the study published in the journal PLOS ONE, said.

“That could be an older adult who wouldn’t normally be able to walk to the park with their grandkids. But wearing the system, they now have extra assistance that enables them to do more than they could before.”

Current exoskeletons typically have to be tailored to a single user performing a single task, like walking in a straight line. Changing tasks or users requires a lengthy set of manual readjustments. This new algorithm has demonstrated the ability to handle different walking speeds as well as changes in gait between walking and running. 

What sets this control algorithm apart from ones typically used in exoskeletons is that it directly measures how quickly muscle fibers are expanding and contracting. It uses these measurements to determine the amount of chemical energy the muscle is using while doing work and then compares that measurement with a biological model to determine the best way to assist movement. 

Current methods use broader measures of motion to determine how to assist movement, making them less accurate than this method, which measures muscle physiology directly. 

The University of Michigan researchers chose to focus on the ankle because of the key role it plays in mobility. The team found that assisting the muscles in the ankle could have a dramatic impact on our ability to walk further and faster. 

While the team was unable to test on humans because they were working during COVID-19 restrictions, they did use data on existing exoskeleton devices and muscle dynamics to simulate and test their algorithm. During testing, the team made adjustments to make their algorithm more responsive to changes in speed and gait. 

The team’s next step will be to perform tasks on humans. During testing, the team will use ultrasound to measure muscle fibers in real time.

The study was funded by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001.