Nav: Home

Personalizing wearable devices

February 28, 2018

When it comes to soft, assistive devices -- like the exosuit being designed by the Harvard Biodesign Lab -- the wearer and the robot need to be in sync. But every human moves a bit differently and tailoring the robot's parameters for an individual user is a time-consuming and inefficient process.

Now, researchers from the Harvard John A. Paulson School of Engineering and Applied and Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering have developed an efficient machine learning algorithm that can quickly tailor personalized control strategies for soft, wearable exosuits.

The research is described in Science Robotics.

"This new method is an effective and fast way to optimize control parameter settings for assistive wearable devices," said Ye Ding, a postdoctoral fellow at SEAS and co-first author of the research. "Using this method, we achieved a huge improvement in metabolic performance for the wearers of a hip extension assistive device."

When humans walk, we constantly tweak how we move to save energy (also known as metabolic cost).

"Before, if you had three different users walking with assistive devices, you would need three different assistance strategies," said Myunghee Kim, a postdoctoral research fellow at SEAS and co-first author of the paper. "Finding the right control parameters for each wearer used to be a difficult, step-by-step process because not only do all humans walk a little differently but the experiments required to manually tune parameters are complicated and time-consuming"

The researchers, led by Conor Walsh, the John L. Loeb Associate Professor of Engineering and Applied Sciences, and Scott Kuindersma, Assistant Professor of Engineering and Computer Science at SEAS, developed an algorithm that can cut through that variability and rapidly identify the best control parameters that work best for minimizing the of walking.

The researchers used so-called human-in-the-loop optimization, which uses real-time measurements of human physiological signals, such as breathing rate, to adjust the control parameters of the device. As the algorithm honed in on the best parameters, it directed the exosuit on when and where to deliver its assistive force to improve hip extension. The Bayesian Optimization approach used by the team was first reported in a paper last year in PLOSone.

The combination of the algorithm and suit reduced metabolic cost by 17.4 percent compared to walking without the device. This was a more than 60 percent improvement compared to the team's previous work.

"Optimization and learning algorithms will have a big impact on future wearable robotic devices designed to assist a range of behaviors," said Kuindersma. "These results show that optimizing even very simple controllers can provide a significant, individualized benefit to users while walking. Extending these ideas to consider more expressive control strategies and people with diverse needs and abilities will be an exciting next step."

"With wearable robots like soft exosuits, it is critical that the right assistance is delivered at the right time so that they can work synergistically with the wearer," said Walsh. "With these online optimization algorithms, systems can learn how do achieve this automatically in about twenty minutes, thus maximizing benefit to the wearer."

Next, the team aims to apply the optimization to a more complex device that assists multiple joints, such as hip and ankle, at the same time.

"In this paper, we demonstrated a high reduction in metabolic cost by just optimizing hip extension," said Ding. "This goes to show what you can do with a great brain and great hardware."
-end-
This research was supported by the Defense Advanced Research Projects Agency, Warrior Web Program, the Wyss Institute and the Harvard John A. Paulson School of Engineering and Applied Science.

Harvard John A. Paulson School of Engineering and Applied Sciences

Related Engineering Articles:

Engineering the meniscus
Damage to the meniscus is common, but there remains an unmet need for improved restorative therapies that can overcome poor healing in the avascular regions.
Artificially engineering the intestine
Short bowel syndrome is a debilitating condition with few treatment options, and these treatments have limited efficacy.
Reverse engineering the fireworks of life
An interdisciplinary team of Princeton researchers has successfully reverse engineered the components and sequence of events that lead to microtubule branching.
New method for engineering metabolic pathways
Two approaches provide a faster way to create enzymes and analyze their reactions, leading to the design of more complex molecules.
Engineering for high-speed devices
A research team from the University of Delaware has developed cutting-edge technology for photonics devices that could enable faster communications between phones and computers.
Breakthrough in blood vessel engineering
Growing functional blood vessel networks is no easy task. Previously, other groups have made networks that span millimeters in size.
Next-gen batteries possible with new engineering approach
Dramatically longer-lasting, faster-charging and safer lithium metal batteries may be possible, according to Penn State research, recently published in Nature Energy.
What can snakes teach us about engineering friction?
If you want to know how to make a sneaker with better traction, just ask a snake.
Engineering a plastic-eating enzyme
Scientists have engineered an enzyme which can digest some of our most commonly polluting plastics, providing a potential solution to one of the world's biggest environmental problems.
A new way to do metabolic engineering
University of Illinois researchers have created a novel metabolic engineering method that combines transcriptional activation, transcriptional interference, and gene deletion, and executes them simultaneously, making the process faster and easier.
More Engineering News and Engineering Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Uncharted
There's so much we've yet to explore–from outer space to the deep ocean to our own brains. This hour, Manoush goes on a journey through those uncharted places, led by TED Science Curator David Biello.
Now Playing: Science for the People

#556 The Power of Friendship
It's 2020 and times are tough. Maybe some of us are learning about social distancing the hard way. Maybe we just are all a little anxious. No matter what, we could probably use a friend. But what is a friend, exactly? And why do we need them so much? This week host Bethany Brookshire speaks with Lydia Denworth, author of the new book "Friendship: The Evolution, Biology, and Extraordinary Power of Life's Fundamental Bond". This episode is hosted by Bethany Brookshire, science writer from Science News.
Now Playing: Radiolab

Dispatch 2: Every Day is Ignaz Semmelweis Day
It began with a tweet: "EVERY DAY IS IGNAZ SEMMELWEIS DAY." Carl Zimmer – tweet author, acclaimed science writer and friend of the show – tells the story of a mysterious, deadly illness that struck 19th century Vienna, and the ill-fated hero who uncovered its cure ... and gave us our best weapon (so far) against the current global pandemic. This episode was reported and produced with help from Bethel Habte and Latif Nasser. Support Radiolab today at Radiolab.org/donate.