Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
12 participants
INTERVENTIONAL
2025-10-15
2029-04-30
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
CROSSOVER
TREATMENT
NONE
Study Groups
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Glide then Pattern Recognition
Participants use a Glide-controlled upper limb prosthesis first, followed by a Pattern Recognition-based upper limb prosthesis.
Glide Control System
Glide is a commercially developed directional myoelectric control strategy from Infinite Biomedical Technologies (IBT) that sits between classic Direct Control (DC) and modern Pattern Recognition (PR). Instead of requiring an isolated on/off muscle signal for each function (e.g., DC) or training a complex classifier on many gestures (e.g., PR), Glide uses the relative activity across 2-8 EMG electrodes to move a virtual cursor on a 2-D "Glide map." The map is divided into adjustable sectors ("slices"), and each slice is assigned a prosthetic movement (e.g., hand open/close, wrist rotation, elbow flexion). Moving the cursor into a slice actuates that movement.
Pattern Recognition System
Pattern recognition (PR)-based myoelectric control is a data-driven approach that allows a user to control multiple prosthetic functions using natural muscle activation patterns rather than discrete, isolated signals. Instead of mapping one muscle to one motion (as in conventional Direct Control), PR systems record the spatial and temporal pattern of EMG activity from multiple sites on the residual limb and use machine learning algorithms to classify which intended movement the user is trying to make.
Pattern Recognition then Glide
Participants use a Pattern Recognition-based upper limb prosthesis first, followed by a Glide-controlled upper limb prosthesis.
Glide Control System
Glide is a commercially developed directional myoelectric control strategy from Infinite Biomedical Technologies (IBT) that sits between classic Direct Control (DC) and modern Pattern Recognition (PR). Instead of requiring an isolated on/off muscle signal for each function (e.g., DC) or training a complex classifier on many gestures (e.g., PR), Glide uses the relative activity across 2-8 EMG electrodes to move a virtual cursor on a 2-D "Glide map." The map is divided into adjustable sectors ("slices"), and each slice is assigned a prosthetic movement (e.g., hand open/close, wrist rotation, elbow flexion). Moving the cursor into a slice actuates that movement.
Pattern Recognition System
Pattern recognition (PR)-based myoelectric control is a data-driven approach that allows a user to control multiple prosthetic functions using natural muscle activation patterns rather than discrete, isolated signals. Instead of mapping one muscle to one motion (as in conventional Direct Control), PR systems record the spatial and temporal pattern of EMG activity from multiple sites on the residual limb and use machine learning algorithms to classify which intended movement the user is trying to make.
Interventions
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Glide Control System
Glide is a commercially developed directional myoelectric control strategy from Infinite Biomedical Technologies (IBT) that sits between classic Direct Control (DC) and modern Pattern Recognition (PR). Instead of requiring an isolated on/off muscle signal for each function (e.g., DC) or training a complex classifier on many gestures (e.g., PR), Glide uses the relative activity across 2-8 EMG electrodes to move a virtual cursor on a 2-D "Glide map." The map is divided into adjustable sectors ("slices"), and each slice is assigned a prosthetic movement (e.g., hand open/close, wrist rotation, elbow flexion). Moving the cursor into a slice actuates that movement.
Pattern Recognition System
Pattern recognition (PR)-based myoelectric control is a data-driven approach that allows a user to control multiple prosthetic functions using natural muscle activation patterns rather than discrete, isolated signals. Instead of mapping one muscle to one motion (as in conventional Direct Control), PR systems record the spatial and temporal pattern of EMG activity from multiple sites on the residual limb and use machine learning algorithms to classify which intended movement the user is trying to make.
Eligibility Criteria
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Inclusion Criteria
* Candidate for 2+ degree-of-freedom (DOF) myoelectric prosthesis as determined by the study prosthetist
* Age of 18 years or greater
Exclusion Criteria
* Individuals with a residual limb that is unhealed from the amputation surgery
* Individuals with easily damaged or sensitive skin who would not tolerate EMG electrodes
* Significant cognitive deficits as determined upon clinical evaluation
* Significant neurological deficits as determined upon clinical evaluation
* Significant physical deficits of the residual limb impacting full participation in the study as determined upon clinical evaluation
* Uncontrolled pain or phantom pain impacting full participation in the study as determined upon clinical evaluation
* Serious uncontrolled medical problems
18 Years
ALL
No
Sponsors
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Medical Center Orthotics and Prosthetics
UNKNOWN
Infinite Biomedical Technologies
INDUSTRY
Responsible Party
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Locations
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Medical Center Orthotics and Prosthetics - Annapolis
Annapolis, Maryland, United States
Medical Center Orthotics and Prosthetics - Baltimore
Baltimore, Maryland, United States
Medical Center Orthotics and Prosthetics - Silver Spring
Silver Spring, Maryland, United States
Medical Center Orthotics and Prosthetics - Allston
Allston, Massachusetts, United States
Medical Center Orthotics and Prosthetics - Milton
Milton, Massachusetts, United States
Medical Center Orthotics and Prosthetics - Charlotte
Charlotte, North Carolina, United States
Medical Center Orthotics and Prosthetics - Anderson
Anderson, South Carolina, United States
Medical Center Orthotics and Prosthetics - Greenville
Greenville, South Carolina, United States
Medical Center Orthotics and Prosthetics - Fairfax
Fairfax, Virginia, United States
Medical Center Orthotics and Prosthetics - Leesburg
Leesburg, Virginia, United States
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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OR240247
Identifier Type: -
Identifier Source: org_study_id
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