The overall goal of this project is to model human joint biomechanics over continuously-varying locomotion to enable adaptive control of powered above-knee prostheses. The central hypothesis of this project is that variable joint impedance can be parameterized by a continuous model based on measurable quantities called phase and task variables. This project will use machine learning to identify variable impedance functions from able-bodied data including joint perturbation responses across the phase/task space to bias the solution toward biological values.
Amputation
The overall goal of this project is to model human joint biomechanics over continuously-varying locomotion to enable adaptive control of powered above-knee prostheses. The central hypothesis of this project is that variable joint impedance can be parameterized by a continuous model based on measurable quantities called phase and task variables. This project will use machine learning to identify variable impedance functions from able-bodied data including joint perturbation responses across the phase/task space to bias the solution toward biological values.
Controlling Locomotion Over Continuously Varying Activities for Agile Powered Prosthetic Legs
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Rehab Lab, University of Michigan, Ann Arbor, Michigan, United States, 48109
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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18 Years to 65 Years
ALL
Yes
University of Michigan,
Robert D Gregg, PhD, PRINCIPAL_INVESTIGATOR, University of Michigan
2028-01-30