# Controlling Locomotion over Continuously Varying Activities for Agile Powered Prosthetic Legs

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $86,861

## Abstract

PROJECT ABSTRACT
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.

## Key facts

- **NIH application ID:** 10531998
- **Project number:** 3R01HD094772-05S1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Robert D Gregg
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $86,861
- **Award type:** 3
- **Project period:** 2018-09-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10531998

## Citation

> US National Institutes of Health, RePORTER application 10531998, Controlling Locomotion over Continuously Varying Activities for Agile Powered Prosthetic Legs (3R01HD094772-05S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10531998. Licensed CC0.

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