Robust Control of Maintenance-Phase Anesthesia

Detalhes bibliográficos
Autor(a) principal: Lemos, JM
Data de Publicação: 2014
Outros Autores: Caiado, DV, Costa, BA, Paz, LA, Mendonca, T, Rabico, R, Esteves, S, Seabra, M
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/110111
Resumo: In biomedical systems, feedback control can be applied whenever adequate sensors, actuators, and sufficiently accurate mathematical models are available. The key issue is the capacity of the control algorithm to tackle the large levels of uncertainty, both structured and unstructured, associated with patient dynamics. In the particular case of intravenous anesthesia considered here, manipulated variables are drug infusion rates, administered by syringe pumps, and the measured signal outputs are the levels of hypnosis or depth of anesthesia (DoA) and of neuromuscular blockade (NMB). Figure 1 provides an example of a loop closed for the control of NMB.
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spelling Robust Control of Maintenance-Phase AnesthesiaCiências Tecnológicas, Ciências da engenharia e tecnologiasTechnological sciences, Engineering and technologyIn biomedical systems, feedback control can be applied whenever adequate sensors, actuators, and sufficiently accurate mathematical models are available. The key issue is the capacity of the control algorithm to tackle the large levels of uncertainty, both structured and unstructured, associated with patient dynamics. In the particular case of intravenous anesthesia considered here, manipulated variables are drug infusion rates, administered by syringe pumps, and the measured signal outputs are the levels of hypnosis or depth of anesthesia (DoA) and of neuromuscular blockade (NMB). Figure 1 provides an example of a loop closed for the control of NMB.20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/110111eng1066-033X10.1109/mcs.2014.2350564Lemos, JMCaiado, DVCosta, BAPaz, LAMendonca, TRabico, REsteves, SSeabra, Minfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:11:59Zoai:repositorio-aberto.up.pt:10216/110111Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:17:54.466217Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Robust Control of Maintenance-Phase Anesthesia
title Robust Control of Maintenance-Phase Anesthesia
spellingShingle Robust Control of Maintenance-Phase Anesthesia
Lemos, JM
Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
title_short Robust Control of Maintenance-Phase Anesthesia
title_full Robust Control of Maintenance-Phase Anesthesia
title_fullStr Robust Control of Maintenance-Phase Anesthesia
title_full_unstemmed Robust Control of Maintenance-Phase Anesthesia
title_sort Robust Control of Maintenance-Phase Anesthesia
author Lemos, JM
author_facet Lemos, JM
Caiado, DV
Costa, BA
Paz, LA
Mendonca, T
Rabico, R
Esteves, S
Seabra, M
author_role author
author2 Caiado, DV
Costa, BA
Paz, LA
Mendonca, T
Rabico, R
Esteves, S
Seabra, M
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Lemos, JM
Caiado, DV
Costa, BA
Paz, LA
Mendonca, T
Rabico, R
Esteves, S
Seabra, M
dc.subject.por.fl_str_mv Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
topic Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
description In biomedical systems, feedback control can be applied whenever adequate sensors, actuators, and sufficiently accurate mathematical models are available. The key issue is the capacity of the control algorithm to tackle the large levels of uncertainty, both structured and unstructured, associated with patient dynamics. In the particular case of intravenous anesthesia considered here, manipulated variables are drug infusion rates, administered by syringe pumps, and the measured signal outputs are the levels of hypnosis or depth of anesthesia (DoA) and of neuromuscular blockade (NMB). Figure 1 provides an example of a loop closed for the control of NMB.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/110111
url https://hdl.handle.net/10216/110111
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1066-033X
10.1109/mcs.2014.2350564
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