DocumentCode :
2222768
Title :
Using motor imagery based brain-computer interface for post-stroke rehabilitation
Author :
Prasad, Girijesh ; Herman, Pawel ; Coyle, Damien ; McDonough, Suzanne ; Crosbie, Jacqueline
Author_Institution :
Intell. Syst. Res. Centre (ISRC), Univ. of Ulster, Derry, UK
fYear :
2009
fDate :
April 29 2009-May 2 2009
Firstpage :
258
Lastpage :
262
Abstract :
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.
Keywords :
bioelectric phenomena; brain-computer interfaces; diseases; electroencephalography; medical computing; neurophysiology; patient rehabilitation; ARAT; BCI systems; action research arm test; mental practice; motor imagery based brain-computer interface; neurofeedback; post-stroke rehabilitation; Brain computer interfaces; Electroencephalography; Focusing; Gain measurement; Intelligent systems; Neural engineering; Neurofeedback; Pattern analysis; Protocols; Testing; BCI; Event Related Desynchronisation; mental practice; motor imagery; physical practice;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
978-1-4244-2073-5
Type :
conf
DOI :
10.1109/NER.2009.5109282
Filename :
5109282
Link To Document :
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