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Spinal Cord Stimulation Combined With Motor Imagery Brain-Computer Interface for Chronic Post-Stroke Upper Limb Motor Dysfunction
Sponsor: Zhejiang Provincial People's Hospital
Summary
This clinical study aims to evaluate the efficacy and safety of spinal cord stimulation combined with non-invasive motor imagery brain-computer interface rehabilitation training in patients with upper limb motor dysfunction after chronic stroke. The study includes an experimental group receiving spinal cord stimulation combined with motor imagery brain-computer interface rehabilitation training and a control group receiving motor imagery brain-computer interface rehabilitation training alone. The primary outcome is upper limb motor function assessed by the Fugl-Meyer Assessment for Upper Extremity. Secondary outcomes include muscle tone, upper limb functional activity, activities of daily living, adverse events, serious adverse events, and exploratory neurophysiological and neuroimaging indicators.
Official title: A Prospective, Single-Center, Non-Randomized, Parallel-Controlled Study to Evaluate the Efficacy and Safety of Spinal Cord Stimulation Combined With Non-Invasive Motor Imagery Brain-Computer Interface Rehabilitation Training for Upper Limb Motor Dysfunction in Patients With Chronic Stroke
Key Details
Gender
All
Age Range
18 Years - 75 Years
Study Type
INTERVENTIONAL
Enrollment
66
Start Date
2026-09
Completion Date
2028-05
Last Updated
2026-07-07
Healthy Volunteers
No
Conditions
Interventions
Spinal Cord Stimulation
Spinal cord stimulation will be delivered through epidural electrodes implanted at cervical spinal cord levels, typically C3-C7 for upper limb dysfunction. Stimulation parameters will be individually optimized within clinically safe and device-permitted ranges, including frequency, pulse width, amplitude, electrode configuration, and stimulation mode.
Motor Imagery Brain-Computer Interface Rehabilitation Training
Motor imagery brain-computer interface training will use a 64-channel medical-grade electroencephalography cap to acquire scalp EEG signals. Participants will perform motor imagery tasks involving the affected upper limb, such as grasping, elbow extension, or wrist lifting. Sensorimotor rhythm features, especially mu rhythm and beta rhythm event-related desynchronization, will be extracted in real time. When significant event-related desynchronization is detected, the system will trigger external feedback, such as a soft robotic glove or functional electrical stimulation, to assist the affected limb in completing the target movement.
Locations (1)
Zhejiang Provincial People's Hospital
Hangzhou, Zhejiang, China