EEG Brain-Machine Interface Control of an Upper-Limb Robotic Exoskeleton for Robot-Assisted Rehabilitation After Stroke
NCT ID: NCT05374486
Last Updated: 2022-05-16
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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UNKNOWN
NA
30 participants
INTERVENTIONAL
2022-04-25
2022-08-31
Brief Summary
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The proposed smart co-robot training system (NeuroExo) is based on a physical upper-limb robotic exoskeleton commanded by a non-invasive brain machine interface (BMI) based on scalp EEG to actively include the participant in the control loop .
The study will demonstrate that the Neuroexo smart co-robot arm training system is feasible and effective in improving arm motor functions in the stroke population for their use at home.The NeuroExo study holds the promise to be cost-effective patient-centered neurorehabilitation system for improving arm functions after stroke.
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Detailed Description
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Conditions
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Study Design
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NA
SINGLE_GROUP
TREATMENT
NONE
Study Groups
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NeuroExo
NeuroExo is a device which includes a robotic exoskeleton that you were in your affected arm to assist you with arm movements, a headset that you wear on your head to measure your brain activity and detect your intention to move, and a graphical user interface that allows you to initiate and stop neurotherapy, and track your motor performance.
NeuroExo co-robot neurorehabilitation system
In this longitudinal study, adult subjects with hemiparesis due to chronic stroke will receive robotic-assisted upper-arm training through an EEG-based BMI control of robotic exoskeleton to study the changes in upper extremity motor function, cortical plasticity (using the EEG). After one screening visit, two baseline visits for EEG signal screens, six onsite training sessions will be provided with the NeuroExo system, followed by 60 home therapy sessions (2 sessions per day, 5 days per week for 6 weeks). If the participant have completed at least 50 sessions of neurotherapy at home, the participant will complete a set of measurements to assess function of the affected upper arm and brain activity within 3 days after the last session for post-assessment visit, and one-month post follow-up session. The total amount of time for this study is 16-20 weeks.
Interventions
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NeuroExo co-robot neurorehabilitation system
In this longitudinal study, adult subjects with hemiparesis due to chronic stroke will receive robotic-assisted upper-arm training through an EEG-based BMI control of robotic exoskeleton to study the changes in upper extremity motor function, cortical plasticity (using the EEG). After one screening visit, two baseline visits for EEG signal screens, six onsite training sessions will be provided with the NeuroExo system, followed by 60 home therapy sessions (2 sessions per day, 5 days per week for 6 weeks). If the participant have completed at least 50 sessions of neurotherapy at home, the participant will complete a set of measurements to assess function of the affected upper arm and brain activity within 3 days after the last session for post-assessment visit, and one-month post follow-up session. The total amount of time for this study is 16-20 weeks.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* mild-to- moderate unilateral stroke confirmed by brain CT or MRI scan and manifested by a Glasgow Coma scale (GCS) score between 15 and 9 documented within 6 months,
* the ability to perform 20deg of active wrist/elbow for upper limb robotic movement on the affected side, no planned alteration in lower/upper- extremity therapy/medication for muscle tone during course of study,
* Anticipated length of needed acute interdisciplinary rehabilitation of 30 days or more.
* Patients are required to have a MMSE\>=24 to rule out those with cognitive impairments.
* Patients will have to have normal/near normal strength in one upper/lower extremity and appreciable weakness in the other upper/lower extremity.
Exclusion Criteria
20 Years
65 Years
ALL
No
Sponsors
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TIRR Memorial Hermann
OTHER
The University of Texas Health Science Center, Houston
OTHER
University of Houston
OTHER
Responsible Party
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Jose L.Contreras-Vidal, Ph.D.
Hugh Roy and Lillie Cranz Cullen Distinguished Professor
Principal Investigators
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Jose L Contreras-Vidal, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Houston
Gerard Francisco, MD
Role: PRINCIPAL_INVESTIGATOR
The University of Texas Health Science Center, Houston
Locations
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The Institute for Rehabilitation and Research (TIRR) at Memorial Hermann
Houston, Texas, United States
TIRR Memorial Hermann Hospital
Houston, Texas, United States
University of Houston
Houston, Texas, United States
Countries
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Central Contacts
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Facility Contacts
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References
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Bhagat NA, Yozbatiran N, Sullivan JL, Paranjape R, Losey C, Hernandez Z, Keser Z, Grossman R, Francisco GE, O'Malley MK, Contreras-Vidal JL. Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation. Neuroimage Clin. 2020;28:102502. doi: 10.1016/j.nicl.2020.102502. Epub 2020 Nov 19.
Sullivan JL, Bhagat NA, Yozbatiran N, Paranjape R, Losey CG, Grossman RG, Contreras-Vidal JL, Francisco GE, O'Malley MK. Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial. IEEE Int Conf Rehabil Robot. 2017 Jul;2017:122-127. doi: 10.1109/ICORR.2017.8009233.
Bhagat NA, Venkatakrishnan A, Abibullaev B, Artz EJ, Yozbatiran N, Blank AA, French J, Karmonik C, Grossman RG, O'Malley MK, Francisco GE, Contreras-Vidal JL. Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors. Front Neurosci. 2016 Mar 31;10:122. doi: 10.3389/fnins.2016.00122. eCollection 2016.
Bhagat NA, French J, Venkatakrishnan A, Yozbatiran N, Francisco GE, O'Malley MK, Contreras-Vidal JL. Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4127-4130. doi: 10.1109/EMBC.2014.6944532.
Venkatakrishnan A, Francisco GE, Contreras-Vidal JL. Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation. Curr Phys Med Rehabil Rep. 2014 Jun 1;2(2):93-105. doi: 10.1007/s40141-014-0051-4.
Other Identifiers
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HSC-MS-20-1287
Identifier Type: OTHER
Identifier Source: secondary_id
G0501521
Identifier Type: -
Identifier Source: org_study_id
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