Intent Recognition for Prosthesis Control

Study Overview
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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.

Official Title
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User-Independent Intent Recognition on a Powered Transfemoral Prosthesis

Conditions
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Amputation

Intervention / Treatment
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* Device: Robotic Knee/Ankle Prosthesis


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: A unilateral transfemoral 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) 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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 75 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Basic Science
Intervention Model: Single Group Assignment
Interventional Model Description: The model used is a repeated measures single arm study.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Smart Robotic Knee/Ankle Prothesis<br>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). | Device: Robotic Knee/Ankle Prosthesis<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Self-selected Walking Speed | This measures the individuals preferred overground walking speed which indicates their physical capability with a device. | 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Protheses, Amputation