Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome.
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.
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.|2 School of Engineering and Institute for Brain Science, Brown University, Providence, RI, USA.|3 Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI, USA.
Damien
D
Lesenfants
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.
Dina
D
Habbal
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.|4 Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA.
Camille
C
Chatelle
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.|5 Brain and Mind Institute, Physics and Astronomy Department, University of Western Ontario, London, Ontario, Canada.
Andrea
A
Soddu
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.
Steven
S
Laureys
1 Coma Science Group, GIGA-Research, CHU University Hospital of Liege, Liege, Belgium.|6 Brain Innovation B.V., Maastricht, the Netherlands.|7 Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.
Quentin
Q
Noirhomme
D000328:Adult; D000368:Aged; D001288:Attention / Q000502:physiology*; D001921:Brain / Q000503:physiopathology*; D003244:Consciousness Disorders / Q000503:physiopathology; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018458:Persistent Vegetative State / Q000503:physiopathology; D011782:Quadriplegia / Q000175:diagnosis / Q000503:physiopathology*; D012146:Rest / Q000502:physiology; D014851:Wakefulness / Q000502:physiology*; D055815:Young Adult
diagnostic tool; entropy; focal attention; locked-in syndrome; response to command