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    An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy


    Leamy, Darren J. and Kocijan, Jus and Domijan, Katarina and Duffin, Joseph and Roche, Richard A.P. and Commins, Sean and Collins, Ronan and Ward, Tomas E. (2014) An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy. Journal of NeuroEngineering and Rehabilitation, 11 (9). pp. 1-16. ISSN 1743-0003

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    Official URL: http://www.jneuroengrehab.com/content/11/1/9


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    Abstract

    Background: Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke. Methods: 32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data. Results: Stroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification accuracy of stroke-affected EEG is lower than the average for healthy EEG. Classification accuracy of the late session stroke EEG is improved by training the BCI on the corresponding early stroke EEG dataset. Conclusions: This exploratory study illustrates that stroke and the accompanying neuroplastic changes associated with the recovery process can cause significant inter-subject changes in the EEG features suitable for mapping as part of a neurofeedback therapy, even when individuals have scored largely similar with conventional behavioural measures. It appears such measures can mask this individual variability in cortical reorganization. Consequently we believe motor retraining BCI should initially be tailored to individual patients.

    Item Type: Article
    Additional Information: © 2014 Leamy et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Cite this article as: Leamy et al.: An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy. Journal of NeuroEngineering and Rehabilitation 2014 11:9. This work is supported by Science Foundation Ireland (SFI) Grant No. 09/RFP/ECE2376, the Slovenian Research Agency Grant No. P2-0001, the Irish Research Council for Humanities and Social Sciences (IRCHS) and the NUI Maynooth John and Pat Hume scholarship programs. We acknowledge the technical assistance of student Martin Stepančič with data classification.
    Keywords: BCI; Stroke rehabilitation; EEG; CSP;
    Academic Unit: Faculty of Science and Engineering > Psychology
    Item ID: 6074
    Identification Number: https://doi.org/10.1186/1743-0003-11-9
    Depositing User: Richard Roche
    Date Deposited: 23 Apr 2015 15:07
    Journal or Publication Title: Journal of NeuroEngineering and Rehabilitation
    Publisher: BioMed Central
    Refereed: Yes
    Funders: Science Foundation Ireland (SFI), Slovenian Research Agency, Irish Research Council for Humanities and Social Sciences (IRCHS), NUI Maynooth John and Pat Hume scholarship
    URI:

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