Motor Learning in a Customized Body-Machine Interface
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1 other identifier
interventional
157
1 country
1
Brief Summary
People with tetraplegia often retain some level of mobility of the upper body. The proposed study will test the hypothesis that it is possible to develop personalized interfaces, which utilize the residual mobility to enable paralyzed persons to control computers, wheelchairs and other assistive devices. If successful the project will result into the establishment of a new family of human-machine interfaces based on wearable sensors that adapt their functions to their users' abilities.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Feb 2013
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 16, 2012
CompletedFirst Posted
Study publicly available on registry
May 31, 2012
CompletedStudy Start
First participant enrolled
February 1, 2013
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2022
CompletedNovember 15, 2019
November 1, 2019
9.6 years
April 16, 2012
November 14, 2019
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Change in Time to task completion from Baseline at 8 months
The subjects will perform computer games requiring different data entry tasks (characters, cursor control) and navigate either a virtual or a real obstacle course. This primary outcome measure is the time it takes subjects to complete each task.
Baseline and 8 months
Secondary Outcomes (3)
Change in Movement Smoothness from Baseline at 8 months
Baseline and 8 months
Change in Strength
Baseline and 8 months
Change in Mental State
Baseline and 8 months
Study Arms (2)
SCI Static
EXPERIMENTALSCI group that practices with a static body-machine map
SCI Machine Learning
EXPERIMENTALSpinal Cord Injury patients who practice with a body-machine map that is adapted using machine learning
Interventions
The intervention compares two ways of customizing the body-machine interface which will be used for subjects for 40 sessions (spread over 8 months). In one case (SCI static), the body-machine interface is static. In the other case (SCI Machine Learning), there is a machine learning algorithm that adapts to the movements made by the subject.
Eligibility Criteria
You may qualify if:
- Age 18-65
- Injuries at C3-C6 level, complete (ASIA A) or incomplete (ASIA B and C)
- Able to follow simple commands
- Able to speak or respond to questions
You may not qualify if:
- Presence of tremors, spasm and other significant involuntary movements
- Cognitive impairment
- Deficit of visuo-spatial orientation
- Concurrent pressure sores or urinary tract infection
- Any metal in head with the exception of dental work or any ferromagnetic metal elsewhere in the body. This applies to all metallic hardware such as cochlear implants, or an Internal Pulse Generator or medication pumps, implanted brain electrodes, and peacemaker.
- Personal history of epilepsy (untreated with one or a few past episodes), or treated patients
- Vascular, traumatic, tumoral, infectious, or metabolic lesion of the brain, even without history of seizure, and without anticonvulsant medication
- Administration of drugs that potentially lower seizure threshold \[62\], without concomitant administration of anticonvulsant drugs which potentially protect against seizures occurrence
- Change in dosage for neuro-active medications (Baclophen, Lyrica, Celebrex, Cymbalta, Gapapentin, Naposyn, Diclofenac, Diazapam, Tramadol, etc) within 2 weeks of any study visit.
- Skull fractures, skull deficits or concussion within the last 6 months
- unexplained recurring headaches
- Sleep deprivation, alcoholism
- Claustrophobia precluding MRI
- Pregnancy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Shirley Ryan AbilityLablead
- National Institutes of Health (NIH)collaborator
Study Sites (1)
Shirley Ryan AbilityLab
Chicago, Illinois, 60611, United States
Related Publications (2)
Abdollahi F, Farshchiansadegh A, Pierella C, Seanez-Gonzalez I, Thorp E, Lee MH, Ranganathan R, Pedersen J, Chen D, Roth E, Casadio M, Mussa-Ivaldi F. Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept. Neurorehabil Neural Repair. 2017 May;31(5):487-493. doi: 10.1177/1545968317693111. Epub 2017 Feb 1.
PMID: 28413945BACKGROUNDDe Santis D, Mussa-Ivaldi FA. Guiding functional reorganization of motor redundancy using a body-machine interface. J Neuroeng Rehabil. 2020 May 11;17(1):61. doi: 10.1186/s12984-020-00681-7.
PMID: 32393288DERIVED
Related Links
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Ferdinando A Mussa-Ivaldi, PhD
Northwestern University
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Senior Research Scientist
Study Record Dates
First Submitted
April 16, 2012
First Posted
May 31, 2012
Study Start
February 1, 2013
Primary Completion
September 1, 2022
Study Completion
September 1, 2022
Last Updated
November 15, 2019
Record last verified: 2019-11