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04 January 2019
Article (Scientific journals)
Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome
Lesenfants, Damien  ; Habbal, Dina  ; Chatelle, Camille  et al.
2018 • In Clinical EEG and Neuroscience, 49 (2), p. 122-135
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Keywords :
Article; Coma Recovery Scale Revised
Abstract :
[en] Electroencephalography (EEG) has been proposed as a supplemental tool for reducing clinical misdiagnosis in severely brain-injured populations helping to distinguish conscious from unconscious patients. We studied the use of spectral entropy as a measure of focal attention in order to develop a motor-independent, portable, and objective diagnostic tool for patients with locked-in syndrome (LIS), answering the issues of accuracy and training requirement. Data from 20 healthy volunteers, 6 LIS patients, and 10 patients with a vegetative state/unresponsive wakefulness syndrome (VS/UWS) were included. Spectral entropy was computed during a gaze-independent 2-class (attention vs rest) paradigm, and compared with EEG rhythms (delta, theta, alpha, and beta) classification. Spectral entropy classification during the attention-rest paradigm showed 93% and 91% accuracy in healthy volunteers and LIS patients respectively. VS/UWS patients were at chance level. EEG rhythms classification reached a lower accuracy than spectral entropy. Resting-state EEG spectral entropy could not distinguish individual VS/UWS patients from LIS patients. The present study provides evidence that an EEG-based measure of attention could detect command-following in patients with severe motor disabilities. The entropy system could detect a response to command in all healthy subjects and LIS patients, while none of the VS/UWS patients showed a response to command using this system. © 2016, © EEG and Clinical Neuroscience Society (ECNS) 2016.
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Author, co-author :
Lesenfants, Damien ;  Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium, School of Engineering and Institute for Brain Science, Brown University, Providence, RI, United States, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI, United States
Habbal, Dina ;  Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium
Chatelle, Camille ;  Université de Liège - ULiège > GIGA : Coma Group
Soddu, Andrea ;  Université de Liège - ULiège > Centre de recherches du cyclotron
Laureys, Steven  ;  Université de Liège - ULiège > GIGA : Coma Group
Noirhomme, Quentin ;  Université de Liège - ULiège > Centre de recherches du cyclotron
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Title :
Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome
Publication date :
Journal title :
Clinical EEG and Neuroscience
Publisher :
SAGE Publications Inc.
Volume :
Issue :
Pages :
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
FP7 - 247919 - DECODER - Deployment of Brain-Computer Interfaces for the Detection of Consciousness in Non-Responsive Patients
FP7 - 602450 - IMAGEMEND - IMAging GEnetics for MENtal Disorders
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique
JSMF - James S McDonnell Foundation
FWB - Fédération Wallonie-Bruxelles
ULiège - Université de Liège
CE - Commission Européenne


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