# Investigation of Transtibial Amputee Ability to Coordinate Residual Antagonistic Muscle Activations with Direct Electromyographic Control for the Enhancement of Postural Control

> **NIH NIH F31** · NORTH CAROLINA STATE UNIVERSITY RALEIGH · 2021 · $40,519

## Abstract

PROJECT SUMMARY
The ability to control standing posture is an essential aspect of daily living and this ability is altered for lower-limb
amputees. With the loss of active ankle joint control, amputees have decreased stability and adapt compensatory
strategies of control, favoring their intact limb. A small amount of work has been done to assist postural control
with a powered ankle prosthesis, though this control is ill-fitted for situations of expected perturbation due to the
ability to produce only reactive responses. Normative responses involve anticipatory changes in ankle-
mechanics before a perturbation occurs. Direct electromyographic (EMG) control provides promise as a means
of incorporating high-level human intent via descending neural commands for the restoration of postural control
mechanisms at the prosthetic ankle joint. Current work has only tested the potential for direct EMG control of a
powered prosthesis with only single-muscle input or with cyclic tasks (like walking). Postural control mechanisms
require coordinated control from antagonistic ankle muscles to generate patterns of reciprocal and coactivation
at the ankle-joint. It is unknown then whether amputees are able to coordinate residual muscle activations and
if direct EMG control with a powered ankle prosthesis can assist postural control under expected perturbation.
The objective of my proposed work is to develop a deeper understanding of residual antagonistic shank muscles
as a control source to help restore the ability to generate postural control mechanisms at the amputated ankle.
The proposed research will facilitate my long-term goal of developing technology that will improves prosthesis
functionality and amputee quality of life. Specifically, direct EMG control from residual antagonistic muscle can
take advantage of human intent via descending neural commands, allowing for anticipatory modulation of
prosthetic ankle-joint mechanics. Thus, I propose the following research aims: 1) To investigate residual
antagonistic muscle as an input for direct EMG control; and 2) To assess the extent to which transtibial amputees
use direct EMG control of a powered ankle prosthesis with antagonistic residual muscles to generate postural
control mechanisms under expected perturbations.
To execute my aims, I will test the ability of residual antagonist muscles in a virtual system and powered ankle
prosthesis separately. I will use two virtual systems to test the ability for amputees to 1) generate varying levels
of activation and coactivation and 2) control a highly dynamic system. I will quantify the ability to complete both
tasks and analyze the correlation in performance. I will then use an expected perturbation testing paradigm to
test the ability for amputees to use direct EMG control of a powered ankle prosthesis to enhance postural control.
I will quantify the contribution of the powered prosthetic ankle to overall stability. Overall the outcomes will provide
a deeper unde...

## Key facts

- **NIH application ID:** 10051314
- **Project number:** 5F31HD101285-02
- **Recipient organization:** NORTH CAROLINA STATE UNIVERSITY RALEIGH
- **Principal Investigator:** Aaron Fleming
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $40,519
- **Award type:** 5
- **Project period:** 2019-11-01 → 2022-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10051314

## Citation

> US National Institutes of Health, RePORTER application 10051314, Investigation of Transtibial Amputee Ability to Coordinate Residual Antagonistic Muscle Activations with Direct Electromyographic Control for the Enhancement of Postural Control (5F31HD101285-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10051314. Licensed CC0.

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