Nonlinear analysis of the electroencephalogram in depth of anesthesia
12 página
- Autores:
-
Mosquera Dusan, Oscar Leonardo
Botero Rosas, Daniel Alfonso
Cagy, Mauricio
Henao Idárraga, Rubén Darío
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad de la Sabana
- Repositorio:
- Repositorio Universidad de la Sabana
- Idioma:
- eng
- OAI Identifier:
- oai:intellectum.unisabana.edu.co:10818/43735
- Acceso en línea:
- https://revistas.udea.edu.co/index.php/ingenieria/article/view/17958
http://hdl.handle.net/10818/43735
- Palabra clave:
- Depth of anesthesia monitoring
EEG features extraction
Nonlinear complexity analyses
Digital signal processing
- Rights
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
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Mosquera Dusan, Oscar LeonardoBotero Rosas, Daniel AlfonsoCagy, MauricioHenao Idárraga, Rubén Darío10/20/2020 11:102020-10-20T16:10:29Z2015-02-090120-6230https://revistas.udea.edu.co/index.php/ingenieria/article/view/17958http://hdl.handle.net/10818/4373510.17533/udea.redin.n75a0612 páginaDigital signal processing of the electroencephalogram (EEG) became important in monitoring depth of anesthesia (DoA) being used to provide a better anesthetic technique. The objective of this work was to conduct a review about nonlinear mathematical methods applied recently to the analyses of nonlinear non-stationary EEG signal. A review was conducted showing time- and frequency-domain nonlinear mathematical methods recently applied to EEG analysis: Approximate Entropy, Sample Entropy, Spectral Entropy, Permutation Entropy, Wavelet Transform, Wavelet Entropy, Bispectrum, Bicoherence and Hilbert Huang Transform. Some algorithms were implemented and tested in one EEG signal record from a patient at The Sabana University Clinic. Recently published results from different methods are discussed. Nonlinear techniques such as entropy analysis in time domain and combination with wavelet transform, and Hilbert Huang transform in frequency domain have shown promising results in classifications of depth of anesthesia stages.application/pdfengRevista Facultad de Ingenieria Universidad de AntioquiaRev. Fac. Ing. Univ. Antioquia N. º 75 pp. 45-56, June, 2015Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2Universidad de La SabanaIntellectum Repositorio Universidad de La SabanaDepth of anesthesia monitoringEEG features extractionNonlinear complexity analysesDigital signal processingNonlinear analysis of the electroencephalogram in depth of anesthesiaAnálisis no lineal de la señal de electroencefalograma en profundidad anestésicaarticlepublishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://intellectum.unisabana.edu.co/bitstream/10818/43735/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8498https://intellectum.unisabana.edu.co/bitstream/10818/43735/3/license.txtf52a2cfd4df262e08e9b300d62c85cabMD5310818/43735oai:intellectum.unisabana.edu.co:10818/437352022-05-10 05:20:22.676Intellectum Universidad de la Sabanacontactointellectum@unisabana.edu.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 |
dc.title.es_CO.fl_str_mv |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
dc.title.alternative.es_CO.fl_str_mv |
Análisis no lineal de la señal de electroencefalograma en profundidad anestésica |
title |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
spellingShingle |
Nonlinear analysis of the electroencephalogram in depth of anesthesia Depth of anesthesia monitoring EEG features extraction Nonlinear complexity analyses Digital signal processing |
title_short |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
title_full |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
title_fullStr |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
title_full_unstemmed |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
title_sort |
Nonlinear analysis of the electroencephalogram in depth of anesthesia |
dc.creator.fl_str_mv |
Mosquera Dusan, Oscar Leonardo Botero Rosas, Daniel Alfonso Cagy, Mauricio Henao Idárraga, Rubén Darío |
dc.contributor.author.none.fl_str_mv |
Mosquera Dusan, Oscar Leonardo Botero Rosas, Daniel Alfonso Cagy, Mauricio Henao Idárraga, Rubén Darío |
dc.subject.es_CO.fl_str_mv |
Depth of anesthesia monitoring EEG features extraction Nonlinear complexity analyses Digital signal processing |
topic |
Depth of anesthesia monitoring EEG features extraction Nonlinear complexity analyses Digital signal processing |
description |
12 página |
publishDate |
2015 |
dc.date.accessioned.none.fl_str_mv |
10/20/2020 11:10 |
dc.date.issued.none.fl_str_mv |
2015-02-09 |
dc.date.available.none.fl_str_mv |
2020-10-20T16:10:29Z |
dc.type.en.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.hasVersion.es_CO.fl_str_mv |
publishedVersion |
dc.identifier.issn.none.fl_str_mv |
0120-6230 |
dc.identifier.other.none.fl_str_mv |
https://revistas.udea.edu.co/index.php/ingenieria/article/view/17958 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10818/43735 |
dc.identifier.doi.none.fl_str_mv |
10.17533/udea.redin.n75a06 |
identifier_str_mv |
0120-6230 10.17533/udea.redin.n75a06 |
url |
https://revistas.udea.edu.co/index.php/ingenieria/article/view/17958 http://hdl.handle.net/10818/43735 |
dc.language.iso.es_CO.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.none.fl_str_mv |
Rev. Fac. Ing. Univ. Antioquia N. º 75 pp. 45-56, June, 2015 |
dc.rights.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
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application/pdf |
dc.publisher.es_CO.fl_str_mv |
Revista Facultad de Ingenieria Universidad de Antioquia |
dc.source.es_CO.fl_str_mv |
Universidad de La Sabana Intellectum Repositorio Universidad de La Sabana |
institution |
Universidad de la Sabana |
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https://intellectum.unisabana.edu.co/bitstream/10818/43735/2/license_rdf https://intellectum.unisabana.edu.co/bitstream/10818/43735/3/license.txt |
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Intellectum Universidad de la Sabana |
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contactointellectum@unisabana.edu.co |
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