2026-04-16 カリフォルニア大学アーバイン校（UCI）
＜関連情報＞
- https://news.uci.edu/2026/04/16/uc-irvine-led-study-achieves-brain-controlled-walking-with-artificial-sensory-feedback/
- https://www.brainstimjrnl.com/article/S1935-861X(26)00042-2/fulltext
両側感覚フィードバックを備えた歩行外骨格のリアルタイム脳コンピュータインターフェース制御 Real-time brain-computer interface control of walking exoskeleton with bilateral sensory feedback
Jeffrey Lim ∙ Po T. Wang ∙ Won Joon Sohn ∙ … ∙ Zoran Nenadic ∙ Charles Y. Liu ∙ An H. Do
Brain Stimulation Published:February 28, 2026
DOI:https://doi.org/10.1016/j.brs.2026.103065
Highlights
- First BDBCI for gait using leg motor cortex signals sensory cortex stimulation.
- Interhemispheric ECoG implantation for BDBCI gait application may be safe.
- A wholly embedded systems BDBCI enabled untethered mobile functionality.
Abstract
Purpose
Brain–computer interfaces (BCIs) offer a pathway to restore ambulation in individuals with spinal cord injury (SCI). However, existing BCI systems for gait are unidirectional and lack sensory feedback. This study aimed to demonstrate that a bidirectional brain–computer interface (BDBCI) can simultaneously enable real-time brain-controlled walking and artificial leg sensation via electrical stimulation of the sensory cortex.
Methods
Epilepsy patients undergoing bilateral interhemispheric subdural electrocorticography (ECoG) implantation were recruited for this proof-of-concept study. Motor mapping identified electrodes in the leg motor cortex for decoding stepping intent, while sensory stimulation mapping determined stimulation sites in the somatosensory cortex to elicit artificial leg percepts. A custom embedded BDBCI decoded motor intent in real time to actuate a robotic gait exoskeleton (RGE) from ECoG signals and delivered leg swing sensory feedback via direct cortical stimulation. Performance was assessed through correlations between cued and decoded states, sensory reliability tasks, and control experiments.
Results
One subject was recruited and achieved a high decoding performance (ρ = 0.92 ± 0.04, lag of 3.5 ± 0.5 s) across 10 runs of operating the BDBCI-controlled RGE. Bilateral leg percepts were validated through a blind step-counting task (92.8% accuracy, p < 10−6). Control experiments verified that decoding was not affected by stimulation artifacts. No adverse events were reported.
Discussion
This study establishes the feasibility of an embedded system BDBCI for restoring both motor control and artificial sensation of walking. Leveraging interhemispheric leg sensorimotor cortices is safe and yields superior decoding compared to prior lateral brain convexity approaches. These findings provide a foundation for translating BDBCI technology into fully implantable systems for SCI patients with paraplegia.
