Fuzzy logic model to describe anesthetic effect and muscular influence on EEG Cerebral State Index

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorBrás, S.-
Autor(es): dc.creatorGouveia, S.-
Autor(es): dc.creatorRibeiro, L.-
Autor(es): dc.creatorFerreira, David A.-
Autor(es): dc.creatorAntunes, L.-
Autor(es): dc.creatorNunes, Catarina S.-
Data de aceite: dc.date.accessioned2025-08-22T11:50:09Z-
Data de disponibilização: dc.date.available2025-08-22T11:50:09Z-
Data de envio: dc.date.issued2023-05-25-
Data de envio: dc.date.issued2023-05-25-
Data de envio: dc.date.issued2013-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/10400.2/13855-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/10400.2/13855-
Descrição: dc.descriptionThe well-known Cerebral State Index (CSI) quantifies depth of anesthesia and is traditionally modeled with Hill equation and propofol effect-site concentration (Ce). This work brings out two novelties: introduction of electromyogram (EMG) and use of fuzzy logic models with ANFIS optimized parameters. The data were collected from dogs (n = 27) during routine surgery considering two propofol administration protocols: constant infusion (G1, n = 14) and bolus (G2, n = 13). The median modeling error of the fuzzy logic model with Ce and EMG was lower or similar than that of the Hill with Ce (p = 0.012-G1, p = 0.522-G2). Furthermore, there was no significant performance impact due to model structure alteration (p = 0.288-G1, p = 0.330-G2) and EMG introduction increased or maintained the performance (p = 0.036-G1, p = 0.798-G2). Therefore, the new model can achieve higher performance than Hill model, mostly due to EMG information and not due to changes in the model structure. In conclusion, the fuzzy models adequately describe CSI data with advantages over traditional Hill models.-
Descrição: dc.descriptioninfo:eu-repo/semantics/publishedVersion-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherElsevier-
Relação: dc.relationStrategic Project - UI 127 - 2011-2012-
Relação: dc.relationStrategic Project - UI 144 - 2011-2012-
Relação: dc.relationAUTOMAÇÃO EM ANESTESIA VETERINÁRIA: MODELAÇÃO E CONTROLO / AUTOMATION IN VETERINARY ANAESTHESIA: MODELLING AND CONTROL-
Palavras-chave: dc.subjectDepth of anesthesia-
Palavras-chave: dc.subjectCSI-
Palavras-chave: dc.subjectEMG-
Palavras-chave: dc.subjectDog-
Palavras-chave: dc.subjectFuzzy logic model-
Palavras-chave: dc.subjectHill equation-
Título: dc.titleFuzzy logic model to describe anesthetic effect and muscular influence on EEG Cerebral State Index-
Aparece nas coleções:Repositório Aberto - Universidade Aberta (Portugal)

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