Improving Myoelectric Prosthetic and Orthotic Limb Control

Utah System of Higher Education (USHE)

Status: Enrolling

Conditions: Hemiparesis

Treatments: Other: experimental control algorithm; Other: commercially available control algorithm

Study type: Interventional

Funder types: Other

Identifiers

NCT05509101

IRB_00098851

Details and patient eligibility

About

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.

Full 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.

Enrollment: 45 estimated patients

Sex: All

Ages: 18 to 70 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• First-ever ischemic or hemorrhagic stroke
• Chronic Stroke (at least 6 months since onset)
• Chronic hemiparesis
• Functional range of motion for contralateral arm

Exclusion criteria

• Individuals who are currently Incarcerated

Trial design

Primary purpose: Other

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: Single Blind

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45 participants in 2 patient groups

Clinically Available Control Algorithm (MyoPro)

Active Comparator group

Description:

Binary control of the orthosis is based on a clinically available control algorithm. This condition serves as a control. Participants will use a commercially available device, the MyoPro.

Treatment:

Other: commercially available control algorithm

High-Density EMG Control Algorithm

Experimental group

Description:

Control of the orthosis is based on residual muscle activity mapped to intended movement using advanced predicted algorithms. This condition is a novel algorithm and serves as the experimental condition.

Treatment:

Other: experimental control algorithm