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Using motor imagery based brain-computer interface for post-stroke rehabilitation
University of Ulster. (School of Computing and Intelligent Systems)
University of Ulster. (School of Computing and Intelligent Systems)ORCID iD: 0000-0001-6553-823X
University of Ulster. (School of Computing and Intelligent Systems)
University of Ulster. (Health and Rehabilitation Sciences Research Institute)
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2009 (English)In: 2009 4TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING, 2009, 251-255 p.Conference paper (Refereed)
Abstract [en]

There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice (or mental practice (MP)) in conjunction with physical practice (PP) of goal-directed rehabilitation tasks leads to enhanced functional recovery of paralyzed limbs among stroke sufferers. It is however difficult to ensure patient engagement during MP in the absence of any on-line measure of the MP. Fortunately in an EEG-based brain-computer interface (BCI), an on-line measure of MI activity is used to devise neurofeedback for the BCI user to help him/her focus better on the task. This paper reports a pilot study in which an EEG-based BCI system is used to provide neurofeedback to stroke participants during the MP part of the rehabilitation protocol. This helps patients to undertake the MP with stronger focus. The participants included five chronic stroke sufferers. The trial was undertaken for 12 sessions over a period of 6 weeks. A set of rehabilitation outcome measures including action research arm test (ARAT) and motricity index was made use of in assessing functional recovery. Moderate improvements approaching a minimal clinically important difference (MCID) were observed for the ARAT. Small positive improvements were also observed in other outcome measures. Participants appeared highly enthusiastic about participating in the study and regularly attended all the sessions. Although without a randomized control trial, it is difficult to ascertain whether the enhanced rehabilitation gain is primarily because of BCI neurofeedack, the positive gains in outcome measures demonstrate the potential and feasibility of using BCI for post-stroke rehabilitation.

Place, publisher, year, edition, pages
2009. 251-255 p.
, International IEEE EMBS Conference on Neural Engineering, ISSN 1948-3546
Keyword [en]
brain-computer interface, electroencephalography, motor imagery, stroke, mental practice
National Category
Other Computer and Information Science
URN: urn:nbn:se:kth:diva-90084DOI: 10.1109/NER.2009.5109282ISI: 000274650800063ISBN: 978-142442073-5OAI: diva2:504135
4th International IEEE/EMBS Conference on Neural Engineering, NER '09, Antalya, TURKEY, APR 29-MAY 02, 2009
QC 20120224Available from: 2012-02-18 Created: 2012-02-18 Last updated: 2012-02-24Bibliographically approved

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Herman, Pawel Andrzej
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