Intent Recognition for Prosthesis Control

NCT ID: NCT05537792

Last Updated: 2024-10-02

Study Results

Results available

Outcome measurements, participant flow, baseline characteristics, and adverse events have been published for this study.

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Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

10 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-09-01

Study Completion Date

2024-05-23

Brief Summary

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This work will focus on new algorithms for powered prostheses and testing these in human subject tests. Individuals with above knee amputation will walk with a robotic prosthesis and ambulate over terrain that simulates community ambulation. The investigators will compare the performance of the advanced algorithm with the robotic system that does not use an advanced algorithm.

Detailed Description

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The focus of this work is a proposed novel AI system to self-adapt an intent recognition system in powered prostheses to aid deployment of intent recognition systems that personalize to individual patient gait. The investigators hypothesize that the prosthesis using our self-adaptive intent recognition system will improve walking speed. Independent community ambulation is known to be more challenging for individuals with TFA, and so the investigators will measure self-selected walking speed (SSWS) which is a correlate with overall health and is a predictor of functional dependence, mobility disability and falls; furthermore, slow SSWS are correlated to lower quality of life (QOL), decreased participation and symptoms of depression. Self-adapting intent recognition has great potential to restore gait in community settings and improve embodiment, which has been associated with improved QOL and increased device usage in patients who use advanced upper limb prostheses. In this experiment, patients with TFA will be fit with our robotic knee/ankle prosthesis and proceed to walk over a treadmill and overground at varying speeds, while the investigators capture 3D biomechanics in both the self-adaptive and static user-independent system (control condition). The investigators expect the self-adaptive system to learn the best prediction of the patient's unique gait, leading to advantages in functional and patient reported outcomes over the control and baseline conditions.

Conditions

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Amputation

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

The model used is a repeated measures single arm study.
Primary Study Purpose

BASIC_SCIENCE

Blinding Strategy

NONE

Study Groups

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Smart Robotic Knee/Ankle Prothesis

This study will be conducted on a sample population of individuals with transfemoral amputation (single arm). Each participant will test with each condition of the study (repeated measures).

Group Type EXPERIMENTAL

Robotic Knee/Ankle Prosthesis

Intervention Type DEVICE

The intervention is an experimental robotic knee/ankle prosthesis that has been previously developed by the team. It is used to improve walking gait performance.

Interventions

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Robotic Knee/Ankle Prosthesis

The intervention is an experimental robotic knee/ankle prosthesis that has been previously developed by the team. It is used to improve walking gait performance.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* A unilateral amputation of the lower limb
* Aged between 18 to 75 years, inclusive
* K3 or K4 level ambulators who can perform all locomotor tasks of interest (based on assessment of the physiatrist and/or prosthetist)
* If a prosthesis is used, the participant must use a prosthetic knee and foot in their clinically prescribed prosthesis.

Exclusion Criteria

* Individuals with history of neurological injury, gait pathology, or cardiovascular condition that would limit ability to ambulate for multiple hours
* Individuals who are currently pregnant (based on patient self-report) due to slight risk of falling during experiments
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

NIH

Sponsor Role collaborator

Georgia Institute of Technology

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Aaron Young, Ph.D.

Role: PRINCIPAL_INVESTIGATOR

Georgia Institute of Technology

Locations

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Exoskeleton and Prosthetic Intelligent Controls Lab

Atlanta, Georgia, United States

Site Status

Countries

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United States

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

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DP2HD111709

Identifier Type: NIH

Identifier Source: secondary_id

View Link

H21117

Identifier Type: -

Identifier Source: org_study_id

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