stub Researchers Develop New Approach for Robotic Exosuit Assistance - Unite.AI
Connect with us

Robotics

Researchers Develop New Approach for Robotic Exosuit Assistance

Published

 on

Image: The Harvard Biodesign Lab/Harvard SEAS

Researchers at Harvard John A. Paulson School of Engineering and Applied Sciences have developed a new approach for robotic exosuit assistance. It helps overcome a major challenge in designing wearable robotics that can be used to assist walking in real-world conditions. 

Today's customizable wearable robotic assistance platforms require a lot of manual or automatic tuning to assist individuals, which can be difficult for patients. 

The new approach relies on robotic exosuit assistance being calibrated to an individual, and it adapts to various different real-world walking tasks in just seconds. The bio-inspired system uses ultrasound measurements of muscle dynamics, which enables it to be personalized and activity-specific for users.

Robert D. Howe is an Abbott and James Lawrence Professor of Engineering and co-author of the paper, which was published in Science Robotics

“Our muscle-based approach enables relatively rapid generation of individualized assistance profiles that provide real benefit to the person walking,” said Howe.

A personalized exosuit for real-world walking

Previous Bio-Inspired Systems vs. New Approach

Previous bio-inspired systems have focused on the dynamic movements of the limbs and the wearers, but the researchers looked outside this. 

Richard Nuckols is a Postdoctoral Research Associate at SEAS and co-first author of the paper. 

“We used ultrasound to look under the skin and directly measured what the user's muscles were doing during several walking tasks,” said Nuckols. “Our muscles and tendons have compliance which means there is not necessarily a direct mapping between the movement of the limbs and that of the underlying muscles driving their motion.”

The research team attached a portable ultrasound system to the calves of participants before imaging their muscles while they performed different walking tasks. 

Krithika Swaminathan is a graduate student at SEAS and the Graduate School of Arts and Sciences (GSAS) and co-first author of the study. 

“From these pre-recorded images, we estimated the assistive force to be applied in parallel with the calf muscles to offset the additional work they need to perform during the push off phase of the walking cycle,” said Swaminathan.

Capturing Muscle’s Profile

The system requires just a few seconds of walking to capture the muscle’s profile, and for each of the profiles, the researchers measured how much metabolic energy the person used during walking with and without the exosuit. 

The team found that the metabolic energy of walking across a range of speeds and inclines was reduced significantly with the muscle-based assistance. They also found that lower assistance force was required to achieve the same or improved metabolic energy benefit when compared to previous studies. 

Sangjun Lee is a graduate student at SEAS and GSAS and co-first author of the study. 

“By measuring the muscle directly, we can work more intuitively with the person using the exosuit,” said Lee. “With this approach, the exosuit isn't overpowering the wearer, it's working cooperatively with them.”

In real-world situations, the exosuit demonstrated an ability to quickly adapt to changes in walking speed and incline. The team will now look to test the system with real-time adjustments.

“This approach may help support the adoption of wearable robotics in real-world, dynamic situations by enabling comfortable, tailored, and adaptive assistance,” said Walsh.

Alex McFarland is a tech writer who covers the latest developments in artificial intelligence. He has worked with AI startups and publications across the globe.