Ulster University Logo

Ulster Institutional Repository

Using motor imagery based brain-computer interface for post-stroke rehabilitation

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Prasad, G, Herman, P, Coyle, DH, McDonough, S M and Crosbie, J.H. (2009) Using motor imagery based brain-computer interface for post-stroke rehabilitation. In: 2009. NER '09. 4th International IEEE/EMBS Conference on Neural Engineering, Antalya, Turkey. IEEE. 5 pp. [Conference contribution]

Full text not available from this repository.

URL: http://ieeexplore.ieee.org/search/freesrchabstract.jsp?tp=&arnumber=5109282&queryText%3DUsing+motor+imagery-based+brain-computer+interface+for+post-stroke+rehabilitation%26openedRefinements%3D*%26searchField%3DSearch+All

DOI: 10.1109/NER.2009.5109282

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.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Life and Health Sciences
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
Institute of Nursing and Health Research > Centre for Health and Rehabilitation Technologies
ID Code:12218
Deposited By:Professor Girijesh Prasad
Deposited On:09 Mar 2010 12:37
Last Modified:28 Feb 2012 14:52

Repository Staff Only: item control page