Improving Myoelectric Prosthetic and Orthotic Limb Control
Improving Myoelectric Prosthetic and Orthotic Limb Control Using Predictive Regression Algorithms and High-count Surface Electrodes
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Heidi Hansen, BS
- Phone Number: 801.585.2373
- Email: heidi.hansen@hsc.utah.edu
Study Contact Backup
- Name: Jacob Wilson, BS
- Phone Number: 801.581.8911
- Email: jacob.wilson@hsc.utah.edu
Study Locations
-
-
Utah
-
Salt Lake City, Utah, United States, 84132-2101
- Recruiting
- University of Utah
-
Contact:
- Heidi Hansen
- Phone Number: 801.585.2373
- Email: heidi.hansen@hsc.utah.edu
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
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
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: Randomized
- Interventional Model: Crossover Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Active Comparator: Clinically Available Control Algorithm (MyoPro)
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.
|
Control of the prosthesis/orthosis is based on clinical standard of care using commercially available control algorithms.
|
|
Experimental: High-Density EMG Control Algorithm
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.
|
Control of the orthosis is based on residual muscle activity mapped to intended movement using high density electromyography and artificial intelligence control algorithms.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
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.
|
while using the device (up to 2 hours)
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- IRB_00098851
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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