Intent Recognition for Prosthesis Control

Amputation Clinical Trial

Official title: User-Independent Intent Recognition on a Powered Transfemoral Prosthesis

Status Recruiting

Clinical Trial Summary

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.

Clinical Trial Description

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. ;

Related Conditions & MeSH terms

• Amputation

• NCT number: NCT05537792
• Study type: Interventional
• Source: Georgia Institute of Technology
• Contact: Aaron Young, Ph.D.
• Phone: 404-385-5306
• Email: aaron.young@me.gatech.edu
• Status: Recruiting
• Phase: N/A
• Start date: September 1, 2023
• Completion date: July 31, 2027