Baniqued, PDE orcid.org/0000-0001-7141-8330, Stanyer, EC, Awais, M et al. (5 more authors) (2021) Brain-Computer Interface Robotics for Hand Rehabilitation After Stroke: A Systematic Review. Journal of NeuroEngineering and Rehabilitation, 18. 15. ISSN 1743-0003
Abstract
Background Hand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use of electroencephalography-based brain-computer interfaces (BCI) can promote this process. Here, we report the first systematic examination of the literature on the use of BCI-robot systems for the rehabilitation of fine motor skills associated with hand movement and profile these systems from a technical and clinical perspective.
Methods A search for January 2010–October 2019 articles using Ovid MEDLINE, Embase, PEDro, PsycINFO, IEEE Xplore and Cochrane Library databases was performed. The selection criteria included BCI-hand robotic systems for rehabilitation at different stages of development involving tests on healthy participants or people who have had a stroke. Data fields include those related to study design, participant characteristics, technical specifications of the system, and clinical outcome measures.
Results 30 studies were identified as eligible for qualitative review and among these, 11 studies involved testing a BCI-hand robot on chronic and subacute stroke patients. Statistically significant improvements in motor assessment scores relative to controls were observed for three BCI-hand robot interventions. The degree of robot control for the majority of studies was limited to triggering the device to perform grasping or pinching movements using motor imagery. Most employed a combination of kinaesthetic and visual response via the robotic device and display screen, respectively, to match feedback to motor imagery.
Conclusion 19 out of 30 studies on BCI-robotic systems for hand rehabilitation report systems at prototype or pre-clinical stages of development. We identified large heterogeneity in reporting and emphasise the need to develop a standard protocol for assessing technical and clinical outcomes so that the necessary evidence base on efficiency and efficacy can be developed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
Keywords: | Brain–computer interface; EEG, Robotics; Rehabilitation; Motor imagery; Stroke |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Psychology (Leeds) |
Funding Information: | Funder Grant number British Council, UK Appln ref 331486777 EPSRC (Engineering and Physical Sciences Research Council) EP/R031193/1 NIHR National Inst Health Research Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Jan 2021 10:04 |
Last Modified: | 27 Nov 2023 12:18 |
Status: | Published |
Publisher: | BioMed Central |
Identification Number: | 10.1186/s12984-021-00820-8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157161 |