For human mobility to change, the exoskeleton needs to interact seamlessly with its user, providing the right level of support at the right time for us to cooperate with our muscles.
To help achieve this, University of Michigan researchers gave users direct control to customize the behavior of the ankle exoskeleton.
Not only was the process faster than the traditional approach, in which an expert would decide the settings, but it could have included priorities that an expert would have missed. For example, user height and weight, which are commonly used to tune exoskeletons and robotic prostheses, had no effect on preferred settings.
“Instead of a one-size-fits-all level of strength, or using measurements of muscle activity to optimize the behavior of the exoskeleton, this method uses active user feedback to gauge the assistance an individual receives. does,” said Kim Ingraham, first author of the Science of Studies in Robotics, and recent mechanical engineering PhD graduate.
Specialists typically tune comprehensive settings of the operated exoskeleton taking into account various characteristics of the human body, gait biomechanics and user preferences. This can be done by crunching quantitative data, such as metabolic rate or muscle activity, to deduce the amount of energy expended by the user, or by asking the user repeatedly to compare between pairs of settings to find which one is the most. feels good.
However, one that minimizes energy expenditure may not be the most convenient or useful. And asking the user to choose between options for multiple settings can be very time-consuming and also obscures how those settings can interact with each other to affect the user experience.
By allowing the user to directly manipulate the settings, preferences that are difficult to detect or measure can be accounted for by the users themselves. Users can quickly and independently decide which features are most important—for example, to trade off comfort, power or stability—and then use settings to best match those preferences without the need for an expert. Choose.
“Being able to choose and have control over how it feels to be able to use these tools in the future helps drive user satisfaction and adoption,” Ingraham said. “No matter how much an exoskeleton helps, people won’t wear them if they aren’t enjoyable.”
To test the feasibility of such a system, the research team outfitted users with a DeFi-powered ankle exoskeleton and a touch screen interface that displayed a blank grid. Selecting any point on the grid will change the torque output of the exoskeleton on one axis while changing the timing of that torque on the alternate axis.
When they were asked to find their preferences while walking on a treadmill, a group of users who had no previous experience with exoskeletons were able to confirm their optimal settings in about a minute, 45 seconds, on average.
“We were surprised by how accurately people were able to identify their preferences, especially because they were completely blind to what was happening—we didn’t tell them what parameters they were tuning. So they were just choosing their preferences based on how they felt the device was helping them,” Ingraham said.
In addition, user preference changed during the experiment. As first-time users gained more experience with the exoskeleton, they preferred a higher level of support. And, those already experienced with exoskeletons prefer a much higher level of support than first-time users.
These findings may help determine how often retuning of the exoskeleton is needed as a user gains experience and support the idea of incorporating direct user input into preference for the best experience.
“This is fundamental work in exploring how to incorporate people’s choices into exoskeleton control,” said Elliot Rouse, the study’s senior author, assistant professor of mechanical engineering and a core faculty member at the Institute of Robotics. “This work is driven by our desire to develop exoskeletons that go beyond the laboratory and have a transformative impact on society.
“Next answering why people like what they like is how these preferences affect their energy, their muscle activity, and their physiology, and how we automatically exert preference-based control in the real world. How can they be implemented? It is important that assistive technologies deliver meaningful benefits to their users.”
Source: University of Michigan