Toward an attention-based diagnostic tool for patients with locked-in syndrome
| Autor: | Camille Chatelle, Steven Laureys, Andrea Soddu, Dina Habbal, Damien Lesenfants, Quentin Noirhomme |
|---|---|
| Přispěvatelé: | Vision, RS: FPN CN 1 |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Male
Electroencephalography/methods APPROXIMATE ENTROPY COMMUNICATION Electroencephalography Audiology ELECTROENCEPHALOGRAM Wakefulness/physiology 0302 clinical medicine response to command Attention Entropy (energy dispersal) BCI medicine.diagnostic_test 05 social sciences Brain General Medicine Middle Aged BISPECTRAL INDEX BRAIN-COMPUTER-INTERFACE Neurology Bispectral index VEGETATIVE STATE Consciousness Disorders Wakefulness Female Locked-in syndrome Quadriplegia/diagnosis Psychology diagnostic tool Adult medicine.medical_specialty Persistent Vegetative State/physiopathology DISORDERS Rest Quadriplegia Approximate entropy 050105 experimental psychology 03 medical and health sciences locked-in syndrome Young Adult medicine Humans 0501 psychology and cognitive sciences Attention/physiology Brain–computer interface Aged Communication CONSCIOUSNESS Brain/physiopathology business.industry Consciousness Disorders/physiopathology Persistent Vegetative State focal attention Rest/physiology medicine.disease Eeg rhythms COMA Neurology (clinical) business entropy 030217 neurology & neurosurgery |
| Zdroj: | Clinical Eeg and Neuroscience, 49(2), 122-135. EEG and Clinical Neuroscience Society (ECNS) Brain and Mind Institute Researchers' Publications |
| ISSN: | 1550-0594 |
| DOI: | 10.1177/1550059416674842 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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