NCT05509101

Improving Myoelectric Prosthetic and Orthotic Limb Control

Improving Myoelectric Prosthetic and Orthotic Limb Control Using Predictive Regression Algorithms and High-count Surface Electrodes

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 45 (estimated)
• Sponsor: University of Utah · Academic / Other
• Sex: All
• Age: 18 Years – 70 Years
• Healthy volunteers: Accepted

Summary

The purpose of this study is to improve control of myoelectrically-controlled advanced orthotic devices (an exoskeleton device that use the body's muscle signals to drive movements of a robotic brace) by using advanced predictive decode algorithms, and the use of high count (\> 8) surface electromyographic (sEMG) electrodes.

Detailed description

This study looks to improve control of myoelectrically-controlled advanced powered orthoses (orthoses that use the body's muscle signals to drive movements of a robotic exoskeleton) by using advanced predictive decode algorithms, and the use of high count (\> 8) surface electromyographic (sEMG) electrodes.

Conditions

• Hemiparesis

Interventions

Type	Name	Description
OTHER	commercially available control algorithm	Control of the prosthesis/orthosis is based on clinical standard of care using commercially available control algorithms.
OTHER	experimental control algorithm	Control of the orthosis is based on residual muscle activity mapped to intended movement using high density electromyography and artificial intelligence control algorithms.

Timeline

• Start date: 2017-03-01
• Primary completion: 2025-08-31
• Completion: 2025-08-31
• First posted: 2022-08-19
• Last updated: 2023-09-25

Locations

1 site across 1 country: United States