Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients
Open accessAbstract
Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3–13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects. Following 12 months of training with this paradigm, all eight patients experienced neurological improvements in somatic sensation (pain localization, fine/crude touch and proprioceptive sensing) in multiple dermatomes. Patients also regained voluntary motor control in key muscles below the SCI level, as measured by EMGs, resulting in marked improvement in their walking index. As a result, 50% of these patients were upgraded to an incomplete paraplegia classification. Neurological recovery was paralleled by the reemergence of lower limb motor imagery at cortical level. We hypothesize that this unprecedented neurological recovery results from both cortical and spinal cord plasticity triggered by long-term BMI usage.
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Brain-controlled neuromuscular stimulation also mediated durable functional improvements of the engaged muscles after stroke and spinal cord injury.
“Brain-controlled neuromuscular stimulation also mediated durable functional improvements of the engaged muscles after stroke36 and spinal cord injury22,24,37.”
From Walking naturally after spinal cord injury using a brain–spine interface (2023) · cites this paper as [22]
The Results (page not provided) report that patients with spinal cord injury regained voluntary control of leg muscles after BMI-based training, with recovery stable or improved by 12 months. But the Methods describe brain control of virtual and robotic leg movements, not brain-controlled neuromuscular stimulation. The stroke finding is attached to a different citation in the citing sentence. (LLM, conf=0.88)
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Asynchronous Prediction of Human Gait Intention in a Pseudo Online Paradigm Using Wavelet Transform
Hasan, S. M. S., Siddiquee, M. R., & Bai, O. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2998778 · Cited by 22 · see citing works
- Authors
- Donati, A. R. C., Shokur, S., Morya, E., Campos, D. S. F., Moioli, R. C., Gitti, C. M., Augusto, P. B., Tripodi, S., Pires, C. G., Pereira, G. A., Brasil, F. L., Gallo, S., Lin, A. A., Takigami, A. K., Aratanha, M. A., Joshi, S., Bleuler, H., Cheng, G., Rudolph, A., & Nicolelis, M. A. L.
- Affiliations
- Associação de Assistência à Criança Deficiente (BR)
- École Polytechnique Fédérale de Lausanne (CH)
- Duke University (US)
- University of California, Davis (US)
- Technical University of Munich (DE)
- Corresponding author
- Nicolelis, Miguel A. L.
- ORCID
- Venue
- Scientific Reports
- Published
- 2016-08-11
- Volume
- 6
- Issue
- 1
- Pages
- 30383-30383
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC4980986
- OpenAlex
- W2508300267
- Cited by
- 428
- References
- 82
- Citations by year
- 2026: 20 · 2025: 31 · 2024: 26 · 2023: 34 · 2022: 41 · 2021: 69 · 2020: 48 · 2019: 44 · 2018: 52 · 2017: 55 · 2016: 8
- FWCI
- 48.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Ministério da Ciência, Tecnologia e Inovação
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Financiadora de Estudos e Projetos
- Fundação de Apoio à Pesquisa do Rio Grande do Norte
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Spinal Cord Injury Research
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- brain-computer interface, spinal cord injury, paraplegia, neurorehabilitation, gait training, lower limb exoskeleton, virtual reality, tactile feedback, proprioception, motor imagery, cortical plasticity, spinal cord plasticity, voluntary motor control, incomplete paraplegia
- MeSH terms
- Neurological Rehabilitation, Adolescent, Adult, Electroencephalography, Female, Gait, Humans, Locomotion, Male, Paraplegia, Robotics, Spinal Cord Injuries, Walking, Interdisciplinary Communication, Lower Extremity, Young Adult, Feedback, Sensory, Brain-Computer Interfaces
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