Improving Myoelectric Prosthetic and Orthotic Limb Control Using Predictive Regression Algorithms and High-count Surface Electrodes
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Hemiparesis
- Sponsor
- University of Utah
- Enrollment
- 45
- Locations
- 1
- Primary Endpoint
- Box and Blocks Test (BBT)
- Status
- Recruiting
- Last Updated
- 2 years ago
Overview
Brief 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.
Investigators
Jacob George
Assistant Professor
University of Utah
Eligibility Criteria
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
Outcomes
Primary Outcomes
Box and Blocks Test (BBT)
Time Frame: while using the device (up to 2 hours)
The Box and Blocks test is performed using the orthotic device under each condition. The individual puts on the device for a maximum of two hours. During that time wearing the device, they will use two different algorithms for controlling the device to complete the Box and Blocks Test.