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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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Autores principales: Corchs, Silvia, Chioma, Giovanni, Dondi, Riccardo, Gasparini, Francesca, Manzoni, Sara, Markowska-Kaczmar, Urszula, Mauri, Giancarlo, Zoppis, Italo, Morreale, Angela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691089/
https://www.ncbi.nlm.nih.gov/pubmed/31447631
http://dx.doi.org/10.3389/fnins.2019.00807
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author Corchs, Silvia
Chioma, Giovanni
Dondi, Riccardo
Gasparini, Francesca
Manzoni, Sara
Markowska-Kaczmar, Urszula
Mauri, Giancarlo
Zoppis, Italo
Morreale, Angela
author_facet Corchs, Silvia
Chioma, Giovanni
Dondi, Riccardo
Gasparini, Francesca
Manzoni, Sara
Markowska-Kaczmar, Urszula
Mauri, Giancarlo
Zoppis, Italo
Morreale, Angela
author_sort Corchs, Silvia
collection PubMed
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.
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spelling pubmed-66910892019-08-23 Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness Corchs, Silvia Chioma, Giovanni Dondi, Riccardo Gasparini, Francesca Manzoni, Sara Markowska-Kaczmar, Urszula Mauri, Giancarlo Zoppis, Italo Morreale, Angela Front Neurosci Neuroscience 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. Frontiers Media S.A. 2019-08-06 /pmc/articles/PMC6691089/ /pubmed/31447631 http://dx.doi.org/10.3389/fnins.2019.00807 Text en Copyright © 2019 Corchs, Chioma, Dondi, Gasparini, Manzoni, Markowska-Kaczmar, Mauri, Zoppis and Morreale. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Corchs, Silvia
Chioma, Giovanni
Dondi, Riccardo
Gasparini, Francesca
Manzoni, Sara
Markowska-Kaczmar, Urszula
Mauri, Giancarlo
Zoppis, Italo
Morreale, Angela
Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness
title 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_short 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
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691089/
https://www.ncbi.nlm.nih.gov/pubmed/31447631
http://dx.doi.org/10.3389/fnins.2019.00807
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