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Brain-computer interface in detection of awareness and neurological rehabilitation

Coyle, Damien (2012) Brain-computer interface in detection of awareness and neurological rehabilitation. In: British Society of Rehabilitation Medicine Autumn Meeting, Belfast. British Society of Rehabilitation Medicine. 1 pp. [Conference contribution]

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The Minimally Conscious State (MCS) is a condition of severely altered consciousness, where there is minimal evidence of awareness. Up to 43% of patients diagnosed as vegetative are reclassified as (at the least) minimally conscious after further assessment by clinical experts. The diagnosis is often given if there are no overt behavioural responses to external stimuli. There is now a lot of evidence gathered through neuroimaging suggesting that a subset of patients diagnosed as vegetative actually have some level of awareness. Findings raise doubts about several of the core principles that underpin diagnosis of the vegetative state and the extent to which clinicians can confirm that a patient is unaware of themselves and their environment. It is therefore critical that new methods are developed and tested to detect awareness in disorder of consciousness (DoC). The differences in treatment paths for those with a diagnosis of vegetative state and minimally conscious states are significant. Individuals assessed as minimally conscious may be entitled to a high level of multidisciplinary input aimed at optimising their rehabilitation potential and providing a more stimulating environment in which to live. However, for vegetative state diagnoses, the outcome is often permanent residence in a nursing home, which may only comprise basic personal care from health care assistants. This presentation describes two case studies which involved EEG based detection of awareness in DoC patients and a follow up study involving real-time neurofeedback using a brain-computer interface (BCI). Prospects of applying BCI technology in the detection of awareness and possibly as an alternative communication channel for this group of users are highlighted.

Item Type:Conference contribution (Lecture)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:24054
Deposited By: Prof Damien Coyle
Deposited On:16 Nov 2012 14:52
Last Modified:16 Nov 2012 14:52

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