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Cited by 572

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Open access
Cervera, María A., Soekadar, Surjo R., Ushiba, Junichi, Millán, José del R., Liu, Meigen, Birbaumer, Niels, Garipelli, Gangadhar·2018·Annals of Clinical and Translational Neurology

Abstract

Brain‐computer interfaces ( BCI s) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCI s might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta‐analysis evaluating the clinical effectiveness of BCI ‐based post‐stroke motor rehabilitation. Trials were identified using MEDLINE , CENTRAL , PED ro and by inspection of references in several review articles. We selected randomized controlled trials that used BCI s for post‐stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random‐effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post‐stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta‐analysis. Motor improvements, mostly quantified by the upper limb Fugl‐Meyer Assessment ( FMA ‐ UE ), exceeded the minimal clinically important difference ( MCID =5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI : 0.37 to 1.20) in FMA ‐ UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI ‐induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post‐stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.

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Metadata

Authors
Cervera, M. A., Soekadar, S. R., Ushiba, J., Millán, J. D. R., Liu, M., Birbaumer, N., & Garipelli, G.
Venue
Annals of Clinical and Translational Neurology
Publisher
Wiley
Published
2018-03-25
Volume
5
Issue
5
Pages
651-663
ISSN
2328-9503 (ISSN-L)
OpenAlex
W2780011893
Cited by
572
References
71
FWCI
32.25
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis. https://app.cochat.ai/papers/10.1002/acn3.544
The paper
Cervera, M. A., Soekadar, S. R., Ushiba, J., Millán, J. D. R., Liu, M., Birbaumer, N., & Garipelli, G. (2018). Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis. Annals of Clinical and Translational Neurology. https://doi.org/10.1002/acn3.544

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.