As people age, walking becomes more difficult and the energy needed to walk also increases.
During a 10-minute walk, for example, a healthy young adult consumes less energy than the calorie content of a slice of bread. As the adult ages, however, that 10-minute walk becomes more strenuous as their body becomes less energy efficient.
Scientists who have studied the metabolic cost of different phases of the gait cycle have encountered difficulties in collecting data, in part because of the physical demands of the test subjects and because measurements are not collected quickly enough to be useful. great value.
A collaboration between researchers at the University of Nebraska–Lincoln’s College of Engineering and the University of Nebraska at Omaha College of Education, Health and Human Sciences is looking to use advanced digital technologies – such as artificial intelligence and machine learning – to improve current collection methods and develop algorithms who can investigate further.
The National Science Foundation’s Disability and Rehabilitation Engineering Program and the Program Established to Stimulate Competitive Research are funding this three-year project through a pair of grants totaling $473,720. The University of Nebraska-Lincoln grant is $235,290.
“We aim to estimate the metabolic cost of different gait phases in a more robust and model-free way than previous research that used musculoskeletal modeling,” said Kegan Moore, an assistant professor of mechanical and materials engineering at Nebraska. “What’s new is that we’re using smart technologies and harnessing data that can be measured – not models that rely on things that can’t be measured – to break down those barriers.”
Philippe Malcolm, professor of biomechanics at UNand his research team will conduct motion capture experiments in which they will influence different phases using a robotic-sized tether.
Engineers in Moore’s lab will use the data from these experiments to develop algorithms that will estimate fluctuations in a person’s metabolism during different phases of their gait cycle.
Malcolm’s research should create practical applications for gait rehabilitation.
“(This) would allow us to design improved assistive devices such as orthoses or exoskeletons that specifically target the most expensive phase of the gait cycle,” Malcolm said.
In addition to the research component, the NSF the funding will support the two principal investigators in teaching classes for older Nebraskas at the Osher Lifelong Learning Institute. Course content will include the health benefits of walking and introductions to machine learning, in the service of NSFaims to integrate research and education for all.