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

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          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. 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. 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 ( FMAUE), 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 FMAUE 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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          Brain-machine interface in chronic stroke rehabilitation: a controlled study.

          Chronic stroke patients with severe hand weakness respond poorly to rehabilitation efforts. Here, we evaluated efficacy of daily brain-machine interface (BMI) training to increase the hypothesized beneficial effects of physiotherapy alone in patients with severe paresis in a double-blind sham-controlled design proof of concept study. Thirty-two chronic stroke patients with severe hand weakness were randomly assigned to 2 matched groups and participated in 17.8 ± 1.4 days of training rewarding desynchronization of ipsilesional oscillatory sensorimotor rhythms with contingent online movements of hand and arm orthoses (experimental group, n = 16). In the control group (sham group, n = 16), movements of the orthoses occurred randomly. Both groups received identical behavioral physiotherapy immediately following BMI training or the control intervention. Upper limb motor function scores, electromyography from arm and hand muscles, placebo-expectancy effects, and functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent activity were assessed before and after intervention. A significant group × time interaction in upper limb (combined hand and modified arm) Fugl-Meyer assessment (cFMA) motor scores was found. cFMA scores improved more in the experimental than in the control group, presenting a significant improvement of cFMA scores (3.41 ± 0.563-point difference, p = 0.018) reflecting a clinically meaningful change from no activity to some in paretic muscles. cFMA improvements in the experimental group correlated with changes in fMRI laterality index and with paretic hand electromyography activity. Placebo-expectancy scores were comparable for both groups. The addition of BMI training to behaviorally oriented physiotherapy can be used to induce functional improvements in motor function in chronic stroke patients without residual finger movements and may open a new door in stroke neurorehabilitation. Copyright © 2013 American Neurological Association.
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            Closed-loop brain training: the science of neurofeedback

            Neurofeedback is a psychophysiological procedure in which online feedback of neural activation is provided to the participant for the purpose of self-regulation. Learning control over specific neural substrates has been shown to change specific behaviours. As a progenitor of brain–machine interfaces, neurofeedback has provided a
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              Clinically important differences for the upper-extremity Fugl-Meyer Scale in people with minimal to moderate impairment due to chronic stroke.

              The upper-extremity portion of the Fugl-Meyer Scale (UE-FM) is one of the most established and commonly used outcome measures in stroke rehabilitative trials. Empirical work is needed to determine the amount of change in UE-FM scores that can be regarded as important and clinically meaningful for health professionals, patients, and other stakeholders. This study used anchor-based methods to estimate the clinically important difference (CID) for the UE-FM in people with minimal to moderate impairment due to chronic stroke. One hundred forty-six individuals with stable, mild to moderate upper-extremity (UE) hemiparesis were administered the UE-FM before and after an intervention targeting their affected UEs. The treating therapists rated each participant's perceived amount of UE motor recovery on a global rating of change (GROC) scale evaluating several facets of UE movement (grasp, release, move the affected UE, perform 5 important functional tasks with the affected UE, overall UE function). Estimated CID of the UE-FM scores was calculated using receiver operating characteristic (ROC) curve with the GROC scores as the anchor. The ROC curve analysis revealed that change in UE-FM scores during the intervention period distinguished participants who experienced clinically important improvement from those that did not based on the therapists' GROC scores. The area under the curve ranged from 0.61 to 0.70 for the different facets of UE movement. The estimated CID of the UE-FM scores ranged from 4.25 to 7.25 points, depending on the different facets of UE movement.

                Author and article information

                Ann Clin Transl Neurol
                Ann Clin Transl Neurol
                Annals of Clinical and Translational Neurology
                John Wiley and Sons Inc. (Hoboken )
                25 March 2018
                May 2018
                : 5
                : 5 ( doiID: 10.1002/acn3.2018.5.issue-5 )
                : 651-663
                [ 1 ] Life Sciences and Technology École polytechnique fédérale de Lausanne (EPFL) Lausanne Switzerland
                [ 2 ] Applied Neurotechnology Laboratory Department of Psychiatry and Psychotherapy University Hospital of Tübingen Tübingen Germany
                [ 3 ] Department of Biosciences and Informatics Faculty of Science and Technology Keio University Yokohama Japan
                [ 4 ] Defitech Chair in Brain‐Machine Interface Center for Neuroprosthetics École polytechnique fédérale de Lausanne (EPFL) Lausanne Switzerland
                [ 5 ] Department of Rehabilitation Medicine Keio University School of Medicine Tokyo Japan
                [ 6 ] Institute for Medical Psychology and Behavioural Neurobiology University Tübingen Tübingen Germany
                [ 7 ] WYSS Center for Bio and Neuroengineering Geneva Switzerland
                [ 8 ] MindMaze SA Lausanne Switzerland
                Author notes
                [* ] Correspondence

                Gangadhar Garipelli, MindMaze SA, Lausanne, Switzerland. Tel: +41 21 552 0805; E‐mail: Gangadhar.Garipelli@ 123456MindMaze.ch

                © 2018 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                Page count
                Figures: 6, Tables: 3, Pages: 13, Words: 7584
                Funded by: European Commission
                Award ID: 645322
                Funded by: Baden‐Württemberg Stiftung
                Award ID: NEU007/1
                Funded by: European Research Council
                Award ID: 759370
                Funded by: Brain & Behavior Research Foundation
                Funded by: Japan Agency for Medical Research and Development
                Funded by: Deutsche Forschungsgemeinschaft
                Funded by: Bundesministerium für Bildung und Forschung
                Funded by: Wyss Center for Bio and Neuroengineering
                This work was funded by European Commission grant 645322; Baden‐Württemberg Stiftung grant NEU007/1; European Research Council grant 759370; Brain & Behavior Research Foundation grant ; Japan Agency for Medical Research and Development grant ; Deutsche Forschungsgemeinschaft grant ; Bundesministerium für Bildung und Forschung grant ; Wyss Center for Bio and Neuroengineering grant .
                Review Article
                Review Article
                Custom metadata
                May 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version= mode:remove_FC converted:11.05.2018


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