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Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data
Appropriate monitoring of the depth of anaesthesia is crucial to prevent deleterious effects of insufficient anaesthesia on surgical patients. Since cardiovascular parameters and motor response testing may fail to display awareness during surgery, attempts are made to utilise alterations in brain ac...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811188/ https://www.ncbi.nlm.nih.gov/pubmed/20126649 http://dx.doi.org/10.1371/journal.pone.0008876 |
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author | Becker, Klaus Schneider, Gerhard Eder, Matthias Ranft, Andreas Kochs, Eberhard F. Zieglgänsberger, Walter Dodt, Hans-Ulrich |
author_facet | Becker, Klaus Schneider, Gerhard Eder, Matthias Ranft, Andreas Kochs, Eberhard F. Zieglgänsberger, Walter Dodt, Hans-Ulrich |
author_sort | Becker, Klaus |
collection | PubMed |
description | Appropriate monitoring of the depth of anaesthesia is crucial to prevent deleterious effects of insufficient anaesthesia on surgical patients. Since cardiovascular parameters and motor response testing may fail to display awareness during surgery, attempts are made to utilise alterations in brain activity as reliable markers of the anaesthetic state. Here we present a novel, promising approach for anaesthesia monitoring, basing on recurrence quantification analysis (RQA) of EEG recordings. This nonlinear time series analysis technique separates consciousness from unconsciousness during both remifentanil/sevoflurane and remifentanil/propofol anaesthesia with an overall prediction probability of more than 85%, when applied to spontaneous one-channel EEG activity in surgical patients. |
format | Text |
id | pubmed-2811188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28111882010-02-02 Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data Becker, Klaus Schneider, Gerhard Eder, Matthias Ranft, Andreas Kochs, Eberhard F. Zieglgänsberger, Walter Dodt, Hans-Ulrich PLoS One Research Article Appropriate monitoring of the depth of anaesthesia is crucial to prevent deleterious effects of insufficient anaesthesia on surgical patients. Since cardiovascular parameters and motor response testing may fail to display awareness during surgery, attempts are made to utilise alterations in brain activity as reliable markers of the anaesthetic state. Here we present a novel, promising approach for anaesthesia monitoring, basing on recurrence quantification analysis (RQA) of EEG recordings. This nonlinear time series analysis technique separates consciousness from unconsciousness during both remifentanil/sevoflurane and remifentanil/propofol anaesthesia with an overall prediction probability of more than 85%, when applied to spontaneous one-channel EEG activity in surgical patients. Public Library of Science 2010-01-26 /pmc/articles/PMC2811188/ /pubmed/20126649 http://dx.doi.org/10.1371/journal.pone.0008876 Text en Becker et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Becker, Klaus Schneider, Gerhard Eder, Matthias Ranft, Andreas Kochs, Eberhard F. Zieglgänsberger, Walter Dodt, Hans-Ulrich Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title | Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title_full | Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title_fullStr | Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title_full_unstemmed | Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title_short | Anaesthesia Monitoring by Recurrence Quantification Analysis of EEG Data |
title_sort | anaesthesia monitoring by recurrence quantification analysis of eeg data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2811188/ https://www.ncbi.nlm.nih.gov/pubmed/20126649 http://dx.doi.org/10.1371/journal.pone.0008876 |
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