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Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis

Maria A. Cervera, View ORCID ProfileSurjo R. Soekadar, View ORCID ProfileJunichi Ushiba, View ORCID ProfileJosé del R. Millán, Meigen Liu, Niels Birbaumer, View ORCID ProfileGangadhar Garipelli
doi: https://doi.org/10.1101/224618
Maria A. Cervera
1Life Sciences and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
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Surjo R. Soekadar
2Applied Neurotechnology Laboratory, Dept. of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany
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Junichi Ushiba
3Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Japan
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José del R. Millán
4Defitech Chair in Brain-Machine Interface, Center for Neuroprosthetics, Institute of Bioengineering, School of Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
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Meigen Liu
5Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo, Japan
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Niels Birbaumer
6Institute for Medical Psychology and Behavioural Neurobiology, University Tübingen, Germany
7WYSS Center for Bio and Neuroengineering, Genève, Switzerland
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Gangadhar Garipelli
8MindMaze SA, Lausanne, Switzerland
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ABSTRACT

Objective Brain-computer interfaces (BCIs) 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 BCIs 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.

Methods Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs 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.

Results 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 fulfilling 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 clinical 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 (SMD) 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 sub-clinical level.

Interpretation We found a medium to large effect size of BCI therapy compared to controls. This suggests that BCI technology might 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.

Footnotes

  • Declaration of interest: SRS received support from the European Commission under the project AIDE (645322), the Baden-Württemberg Stiftung (NEU007/1), the European Research Council (ERC) under the project NGBMI (759370), the Brain & Behavior Research Foundation as 2017 NARSAD Young Investigator Grant recipient and P&S Fund Investigator, JU and ML are supported by Japan Agency for Medical Research and Development (AMED). NB is supported by the Deutsche Forschungsgemeinschaft (DFG), Bundesministerium für Bildung und Forschung (BMBF, Motor-Bic, CoMiCom), EU Horizon 2020 (Luminous), Wyss Center for Bio and Neuroengeneering. JdRM received a grant from Wyss Center for Bio and Neuroengineering in Geneva. At the time of data collection and writing, MAC and GG were employees of MindMaze SA, Switzerland and NB was an employee of Wyss Center, Switzerland. JU and ML are collaborating with Panasonic Inc., Japan.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted November 24, 2017.
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Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis
Maria A. Cervera, Surjo R. Soekadar, Junichi Ushiba, José del R. Millán, Meigen Liu, Niels Birbaumer, Gangadhar Garipelli
bioRxiv 224618; doi: https://doi.org/10.1101/224618
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Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis
Maria A. Cervera, Surjo R. Soekadar, Junichi Ushiba, José del R. Millán, Meigen Liu, Niels Birbaumer, Gangadhar Garipelli
bioRxiv 224618; doi: https://doi.org/10.1101/224618

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