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dc.contributor.authorMiñano, Gorka
dc.contributor.authorLarrea Sukia, Mikel ORCID
dc.contributor.authorIrigoyen Gordo, Eloy
dc.date.accessioned2021-02-01T18:24:34Z
dc.date.available2021-02-01T18:24:34Z
dc.date.issued2019-06-30
dc.identifier.citationEUROSIM 2019: 10th EUROSIM Congress on Modelling and Simulation, Logroño, La Rioja, Spain, July 1-5, 2019es_ES
dc.identifier.urihttp://hdl.handle.net/10810/49982
dc.descriptionAbstract publicado en EUROSIM 2019 Abstract Volume. ARGESIM Report 58, ISBN: 978-3-901608-92-6 (ebook), DOI: 10.11128/arep.58es_ES
dc.description.abstractThis work gathers important developments carried out in a specific area of the Biomedical Engineering which applies advanced models based on Artificial Neural Networks to improve Cardiovascular Rehabilitation (CR) processes by using Cycloergometers. This work presents an updated revision of proposals, focusing on different problems involved in CR and considering features and requirements nowadays taken into account during their modelling processes. Furthermore, the signals analysed in these models are studied and presented below. Among them, a review of solutions applied to CR processes, focused on Computational Intelligence are cited.es_ES
dc.description.sponsorshipUPV/EHU, Grupo de Investigación de Inteligencia Computacionales_ES
dc.language.isoenges_ES
dc.publisherEUROSIMes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectcardiovascular rehabilitationes_ES
dc.subjectcomputational Intelligencees_ES
dc.subjectmodellinges_ES
dc.titleReview of neural modelling on cardiovascular rehabilitation active processes by using cycloergometerses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.holder(c) 2019 Los autoreses_ES
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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