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EMG contributes to improve cerebral state Index modeling in dogs anesthesia

dc.contributor.authorBrás, S.
dc.contributor.authorFerreira, D. A.
dc.contributor.authorAntunes, L.
dc.contributor.authorRibeiro, L.
dc.contributor.authorNunes, Catarina S.
dc.contributor.authorGouveia, S.
dc.date.accessioned2023-05-29T09:20:10Z
dc.date.available2023-05-29T09:20:10Z
dc.date.issued2011
dc.description.abstractCerebral State Index (CSI) is a measure of depth of anesthesia (DoA) developed for humans, which is traditionally modeled with the Hill equation and the propofol effect-site concentration (Ce). The CSI has been studied in dogs and showed several limitations related to the interpretation of EEG data. Nevertheless, the CSI has a lot of potential for DoA monitoring in dogs, it just needs to be adjusted for this species. In this work, an adapted CSI model is presented for dogs considering a) both Ce and EMG as inputs and b) a fuzzy logic structure with parameters optimized using the ANFIS method. The new model is compared with traditional Hill model using data from dogs in routine surgery. The results showed no significant impact in the model performance with the change of model structure (Fuzzy instead of Hill). The residuals of the Hill model were significantly correlated with the EMG, indicating that the latter should be considered in the model. In fact, the EMG introduction in CSI model significantly decreased the modeling error: 11.8 [8.6; 15.2] (fuzzy logic) versus 20.9 [16.4; 29.0] (Hill). This work shows that CSI modeling in dogs can be improved using the current human anesthesia set-up, once the EMG signal is acquired simultaneously with the CSI index. However, it does not invalidate the search of new DoA indices more adjusted to use in dog’s anesthesia.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationS. Brás, D. A. Ferreira, L. Antunes, L. Ribeiro, C. S. Nunes and S. Gouveia, "EMG contributes to improve Cerebral State Index modeling in dogs anesthesia," 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, USA, 2011, pp. 6593-6596pt_PT
dc.identifier.doi10.1109/IEMBS.2011.6091626pt_PT
dc.identifier.pmid22255850
dc.identifier.urihttp://hdl.handle.net/10400.2/13875
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relationAUTOMAÇÃO EM ANESTESIA VETERINÁRIA: MODELAÇÃO E CONTROLO / AUTOMATION IN VETERINARY ANAESTHESIA: MODELLING AND CONTROL
dc.titleEMG contributes to improve cerebral state Index modeling in dogs anesthesiapt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleAUTOMAÇÃO EM ANESTESIA VETERINÁRIA: MODELAÇÃO E CONTROLO / AUTOMATION IN VETERINARY ANAESTHESIA: MODELLING AND CONTROL
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/CMU-PT%2FCPS%2F0046%2F2008/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/FARH/SFRH%2FBD%2F29864%2F2006/PT
oaire.citation.conferencePlaceBoston, MA, USApt_PT
oaire.citation.endPage6596pt_PT
oaire.citation.startPage6593pt_PT
oaire.citation.title2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Societypt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStreamFARH
person.familyNameNunes
person.givenNameCatarina S.
person.identifier.ciencia-id691F-CDC2-E26A
person.identifier.orcid0000-0002-8357-0994
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationcc3069ec-f930-455f-9226-b77e5d2dc14b
relation.isAuthorOfPublication.latestForDiscoverycc3069ec-f930-455f-9226-b77e5d2dc14b
relation.isProjectOfPublicationf26edfa5-69da-49da-8918-c181f9255b6a
relation.isProjectOfPublicatione1358503-b7d2-4b9d-9639-4d63d2502ec4
relation.isProjectOfPublication.latestForDiscoveryf26edfa5-69da-49da-8918-c181f9255b6a

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