Electroencephalographic profiles for differentiation of disorders of consciousness.

[en] BACKGROUND: Electroencephalography (EEG) is best suited for long-term monitoring of brain functions in patients with disorders of consciousness (DOC). Mathematical tools are needed to facilitate efficient interpretation of long-duration sleep-wake EEG recordings. METHODS: Starting with matching pursuit (MP) decomposition, we automatically detect and parametrize sleep spindles, slow wave activity, K-complexes and alpha, beta and theta waves present in EEG recordings, and automatically construct profiles of their time evolution, relevant to the assessment of residual brain function in patients with DOC. RESULTS: Above proposed EEG profiles were computed for 32 patients diagnosed as minimally conscious state (MCS, 20 patients), vegetative state/unresponsive wakefulness syndrome (VS/UWS, 11 patients) and Locked-in Syndrome (LiS, 1 patient). Their interpretation revealed significant correlations between patients' behavioral diagnosis and: (a) occurrence of sleep EEG patterns including sleep spindles, slow wave activity and light/deep sleep cycles, (b) appearance and variability across time of alpha, beta, and theta rhythms. Discrimination between MCS and VS/UWS based upon prominent features of these profiles classified correctly 87 % of cases. CONCLUSIONS: Proposed EEG profiles offer user-independent, repeatable, comprehensive and continuous representation of relevant EEG characteristics, intended as an aid in differentiation between VS/UWS and MCS states and diagnostic prognosis. To enable further development of this methodology into clinically usable tests, we share user-friendly software for MP decomposition of EEG (http://braintech.pl/svarog) and scripts used for creation of the presented profiles (attached to this article).

Research center :

GIGA CRC (Cyclotron Research Center) In vivo Imaging-Aging & Memory - ULiège

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Malinowska, U

Chatelle, Camille ; Université de Liège - ULiège > Centre de recherches du cyclotron

Bruno, Marie-Aurélie ; Université de Liège - ULiège > Centre de recherches du cyclotron

Noirhomme, Quentin ; Université de Liège - ULiège > Centre de recherches du cyclotron

Laureys, Steven ; Université de Liège - ULiège > Centre de recherches du cyclotron

Durka, Piotr

Language :

English

Title :

Electroencephalographic profiles for differentiation of disorders of consciousness.

Publication date :

October 2013

Journal title :

BioMedical Engineering OnLine

eISSN :

1475-925X

Publisher :

BioMed Central, London, United Kingdom

Volume :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://www.biomedical-engineering-online.com/content/12/1/109

Available on ORBi :

since 23 December 2013

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