Above-knee amputees often struggle to perform the varying activities of daily life with conventional prostheses. Emerging powered knee-ankle prostheses have motors that can restore normative biomechanics, but these devices are limited to a small set of pre-defined activities that must be tuned to the user by technical experts over several hours. The overall goal of this project is to model and control human locomotion over continuously varying tasks for the design of agile, powered prostheses that require little to no tuning. The universal use of different task-specific controllers in current powered legs is a direct consequence of the prevailing paradigm for viewing human locomotion as a discrete set of activities. There is a fundamental gap in knowledge about how to analyze, model, and control continuously varying locomotion, which greatly limits the adaptability and agility of powered prostheses. The central hypothesis of this project is that continuously varying activities can be represented by a single mathematical model based on measureable physical quantities called task variables. The proposed project will be scientifically significant to understanding how humans continuously adapt to varying activities and environments, technologically significant to the design of agile, user-synchronized powered prosthetic legs, and clinically significant to the adoption of powered knee-ankle prostheses for improved community ambulation. The proposed model of human locomotion will enable new prosthetic strategies for controlling and adapting to the environment, which aligns with the missions of the NICHD/NCMRR Devices and Technology Development program area and the NIBIB Mathematical Modeling, Simulation, and Analysis program. The innovation of this work is encompassed in 1) a continuous paradigm for variable locomotor activities that challenges the existing discrete paradigm, 2) a unified task control methodology that drastically improves the agility of powered prosthetic legs, and 3) a partially automated tuning process that significantly reduces the time and technical expertise required to configure powered knee- ankle prostheses. This continuous task paradigm will provide new methods and models for studying human locomotion across tasks and task transitions. This innovation will address a key roadblock in control technology that currently restricts powered legs to a small set of activities that do not generalize well across users. The adaptability of the proposed control paradigm across users and activities will transform the prosthetics field with a new generation of ?plug-and-play? powered legs for community ambulation.

Public Health Relevance

The proposed research is relevant to public health because the clinical application of variable-activity powered prosthetic legs can significantly improve community mobility and therefore quality of life for nearly a million American amputees. Recently developed powered knee-ankle prostheses are limited to a small set of pre- defined activities that require several hours of expert tuning for each user. This project will model and control human locomotion over continuously varying tasks for the design of agile, powered prostheses that require little to no tuning, which aligns with the missions of the Devices and Technology Development program area of the NICHD National Center for Medical Rehabilitation Research and the Mathematical Modeling, Simulation, and Analysis program of the NIBIB.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
7R01HD094772-03
Application #
10055806
Study Section
Musculoskeletal Rehabilitation Sciences Study Section (MRS)
Program Officer
Quatrano, Louis A
Project Start
2018-09-01
Project End
2023-05-31
Budget Start
2019-12-01
Budget End
2020-05-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Embry, Kyle R; Villarreal, Dario J; Macaluso, Rebecca L et al. (2018) Modeling the Kinematics of Human Locomotion Over Continuously Varying Speeds and Inclines. IEEE Trans Neural Syst Rehabil Eng 26:2342-2350