Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness
Patients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming...
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doaj-7992025452d54ac089fd26d5c29bc9b42020-11-25T01:19:16ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2019-08-011310.3389/fnins.2019.00807454899Computational Methods for Resting-State EEG of Patients With Disorders of ConsciousnessSilvia Corchs0Giovanni Chioma1Riccardo Dondi2Francesca Gasparini3Sara Manzoni4Urszula Markowska-Kaczmar5Giancarlo Mauri6Italo Zoppis7Angela Morreale8Department of Computer Science, University Milano-Bicocca, Milan, ItalyBehavioral Neurology, Montecatone Rehabilitation Institute, Imola, ItalyDepartment of Letter and Communication, University of Bergamo, Bergamo, ItalyDepartment of Computer Science, University Milano-Bicocca, Milan, ItalyDepartment of Computer Science, University Milano-Bicocca, Milan, ItalyDepartment of Computational Intelligence, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wroclaw, PolandDepartment of Computer Science, University Milano-Bicocca, Milan, ItalyDepartment of Computer Science, University Milano-Bicocca, Milan, ItalyBehavioral Neurology, Montecatone Rehabilitation Institute, Imola, ItalyPatients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming to correct any differentiation between VS and MCS are essential for the characterization of an adequate treatment and an effective prognosis. In recent decades, there has been a growing interest in the new EEG computational techniques. We have reviewed how resting-state EEG is computationally analyzed to support differential diagnosis between VS and MCS in view of applicability of these methods in clinical practice. The studies available so far have used different techniques and analyses; it is therefore hard to draw general conclusions. Studies using a discriminant analysis with a combination of various factors and reporting a cut-off are among the most interesting ones for a future clinical application.https://www.frontiersin.org/article/10.3389/fnins.2019.00807/fullcomputational methodsEEGDOCVSMCSmachine learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Silvia Corchs Giovanni Chioma Riccardo Dondi Francesca Gasparini Sara Manzoni Urszula Markowska-Kaczmar Giancarlo Mauri Italo Zoppis Angela Morreale |
spellingShingle |
Silvia Corchs Giovanni Chioma Riccardo Dondi Francesca Gasparini Sara Manzoni Urszula Markowska-Kaczmar Giancarlo Mauri Italo Zoppis Angela Morreale Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness Frontiers in Neuroscience computational methods EEG DOC VS MCS machine learning |
author_facet |
Silvia Corchs Giovanni Chioma Riccardo Dondi Francesca Gasparini Sara Manzoni Urszula Markowska-Kaczmar Giancarlo Mauri Italo Zoppis Angela Morreale |
author_sort |
Silvia Corchs |
title |
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness |
title_short |
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness |
title_full |
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness |
title_fullStr |
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness |
title_full_unstemmed |
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness |
title_sort |
computational methods for resting-state eeg of patients with disorders of consciousness |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroscience |
issn |
1662-453X |
publishDate |
2019-08-01 |
description |
Patients who survive brain injuries may develop Disorders of Consciousness (DOC) such as Coma, Vegetative State (VS) or Minimally Conscious State (MCS). Unfortunately, the rate of misdiagnosis between VS and MCS due to clinical judgment is high. Therefore, diagnostic decision support systems aiming to correct any differentiation between VS and MCS are essential for the characterization of an adequate treatment and an effective prognosis. In recent decades, there has been a growing interest in the new EEG computational techniques. We have reviewed how resting-state EEG is computationally analyzed to support differential diagnosis between VS and MCS in view of applicability of these methods in clinical practice. The studies available so far have used different techniques and analyses; it is therefore hard to draw general conclusions. Studies using a discriminant analysis with a combination of various factors and reporting a cut-off are among the most interesting ones for a future clinical application. |
topic |
computational methods EEG DOC VS MCS machine learning |
url |
https://www.frontiersin.org/article/10.3389/fnins.2019.00807/full |
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