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Updated: Oct 25, 2026

Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke
Published on: September 1, 2023
Restoration of volitional lower-limb movement after motor-complete spinal cord injury with brain-spine interface
Xinyu Jiang1, Mingfang Shi2, Jionghui Liu1
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Background:
Spinal cord injury (SCI) interrupts volitional control of lower limbs. Brain-spine interfaces (BSIs), which decode cortical motor intent to trigger epidural electrical stimulation (EES), can provide an artificial pathway linking the brain to spinal motor circuits. Reported benefit, however, has been confined to participants who already retain substantial motor function, leaving unresolved whether those with little or no motor function can benefit, how soon, and how consistently.
Methods:
Three individuals with motor-complete SCI were enrolled in a registered trial (ChiCTR2500095359). None could stand or step with braces, walking aids, or physical assistance. Each received one depth electrode per hemisphere in the lower-limb motor cortex and an epidural paddle spanning the L1-S2 nerve roots. The participants underwent 2-3 weeks of closed-loop BSI training.
Findings:
The interface restored brain-controlled volitional lower-limb movement on the first postoperative day in all three participants and assisted walking with body-weight support followed within 2 weeks. Over the training period, all three developed coordinated remodeling across cortical, spinal, and muscular levels, with thigh muscle volume increasing by 4.9% on average.
Conclusions:
These findings widen the conditions under which a BSI is known to work. It can take effect rapidly in participants with no volitional lower-limb movement to build on, at a low implant demand, and consistently across all three participants.
Funding:
This work was supported by the National Key R&D Program of China (Disruptive Technology Innovation; grant no. 2025YFF1501400) and the Shanghai Municipal Science and Technology Major Project (grant no. 25DP3200100).
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