Carroll, Aine

Coyle, DH

McElligott, Jacinta

Satti, A

Stow, Jacqueline

English

OPUS

        Citation for published version:Stow, J, Coyle, DH, Carroll, A, Satti, A & McElligott, J 2011, Achievable Brain Computer Communication throughShort Intensive Motor Imagery Training despite Long Term Spinal Cord Injury. in Unknown Host Publication.Ireland, Irish Institute of Clinical Neuroscience Registrar's Prize in Neuroscience 2011 , 11/11/11.Publication date:2011Document VersionPeer reviewed versionLink to publicationUniversity of BathAlternative formatsIf you require this document in an alternative format, please contact:openaccess@bath.ac.ukGeneral rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 16. Jul. 2024Achievable Brain Computer Communication through Short Intensive Motor Imagery Training despite Long Term Spinal Cord Injury  Jacqueline Stow#, Damien Coyle*, Aine Carroll#, Abdul Satti*, and Jacinta McElligott# #National Rehabilitation Hospital, Rochestown Avenue, Dun Laoghaire, Republic of Ireland. *Intelligent Systems Research Centre, University of Ulster, Derry, BT48 7JL, UK email jacqui.stow@nrh.ie  Keywords :  BCI, Spinal Cord Injury, motor imagery                         A. Background: Severely motor disabled individuals face challenges to move independently and control their environment. Various different assistive technologies exist, however the ideal solution would be to bypass any need for neuromuscular involvement and allow the individual to use goal directed thoughts to achieve their intentions through a computer interface. Brain-computer interface technology offers this potential [1]-[3]. BCIs utilize a number of self-directed neurophysiological processes such as the activation of sensorimotor cortex during motor imagery (MI). Concerns exist that prolonged inactivity of sensorimotor cortex will impact on the amount of training and accuracies achieved limiting the usefulness of this technology. Here we demonstrate that in two individuals with long term tetraplegia from spinal cord injury, good accuracy levels can be achieved through short intensive training periods.  B. Case Description: Case 1 : female, aged 60, with a C4 ASIA A traumatic spinal cord injury (SCI) sustained 35 years ago. Case 2: male, aged 42,with a C5 ASIA B traumatic SCI sustained 12 years ago. Both individuals initially took part in 10 training sessions over 3 months to familiarise with the technology and 4 months later  took part in an intensive 2-3 sessions over 1 week. A binary class BCI (left vs. right hand MI) with three bipolar channels over the sensorimotor cortex (CP3-FC3, CPz-FCz,CP4-FC4 and a reference at AFPz) was used [3][4]. Experiments were conducted in the participant’s home environments.  C. Results of Investigations:  Both subjects had achieved accuracy levels in the range of normality [2] (60%-70%) during an initial 10 training sessions. After a short intensive training period both participants showed clear performance gains, achieving accuracy in the range 70%-88%.  D. Discussion: Individuals who have sustained high level injuries to their spinal cord resulting in prolonged inactivation of sensorimotor regions can still achieve accuracies needed to control a BCI within a relatively short intensive training period.   E. References: [1] J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, T. M. Vaughan, "Brain-computer interfaces for communication and control", (invited review) Journal Clinical Neurophysiology Elsevier, vol. 113, pp. 767-791, 2002. [2] G. Pfurtscheller, C. Guger, G. Muller, G. Krausz, C. Neuper. “Brain oscillations control hand orthosis in a tetraplegic”, Neuroscience Letters, vol. 292, pp. 211–214, 2000, [3] D. Coyle, “Neural network based auto association and time-series prediction for biosignal processing in brain-computer interfaces”, IEEE Computational Intelligence Magazine (invited), pp.47-59, vol. 4, no. 4, 2009. [4] D. Coyle, J. Garcia, A. Satti, and T. M. McGinnity, "EEG-based Continuous Control of a Game using a 3 Channel Motor Imagery BCI", IEEE Symposium Series on Computational Intelligence, pp. 88-93, April, 2011.    

Achievable Brain Computer Communication through Short Intensive Motor Imagery Training despite Long Term Spinal Cord Injury

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Achievable Brain Computer Communication through Short Intensive Motor Imagery Training despite Long Term Spinal Cord Injury

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