Mostrar el registro sencillo del ítem
dc.contributor.author | Nunes, D. | es_ES |
dc.contributor.author | Rocha, T. | es_ES |
dc.contributor.author | Traver Salcedo, Vicente | es_ES |
dc.contributor.author | Teixeira, C. | es_ES |
dc.contributor.author | Ruano, M. | es_ES |
dc.contributor.author | Paredes, S. | es_ES |
dc.contributor.author | Carvalho, P. | es_ES |
dc.contributor.author | Henriques, J. | es_ES |
dc.date.accessioned | 2022-02-25T07:42:59Z | |
dc.date.available | 2022-02-25T07:42:59Z | |
dc.date.issued | 2019-07-27 | es_ES |
dc.identifier.isbn | 978-1-5386-1311-5 | es_ES |
dc.identifier.issn | 1558-4615 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/181064 | |
dc.description.abstract | [EN] Cardiac function deterioration of heart failure patients is frequently manifested by the occurrence of decompensation events. One relevant step to adequately prevent cardiovascular status degradation is to predict decompensation episodes in order to allow preventive medical interventions.In this paper we introduce a methodology with the goal of finding onsets of worsening progressions from multiple physiological parameters which may have predictive value in decompensation events. The best performance was obtained for the model composed by only two features using a telemonitoring dataset (myHeart) with 41 patients. Results were achieved by applying leave-one-subject-out validation and correspond to a geometric mean of 83.67%. The obtained performance suggests that the methodology has the potential to be used in decision support solutions and assist in the prevention of this public health burden. | es_ES |
dc.description.sponsorship | The authors acknowledge the financial support of the international project Link (H2020-692023). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | IEEE | es_ES |
dc.relation.ispartof | 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject.classification | TECNOLOGIA ELECTRONICA | es_ES |
dc.title | Latent states extraction through Kalman Filter for the prediction of heart failure decompensation events | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.type | Artículo | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.identifier.doi | 10.1109/EMBC.2019.8857591 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/692023/EU/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica | es_ES |
dc.description.bibliographicCitation | Nunes, D.; Rocha, T.; Traver Salcedo, V.; Teixeira, C.; Ruano, M.; Paredes, S.; Carvalho, P.... (2019). Latent states extraction through Kalman Filter for the prediction of heart failure decompensation events. IEEE. 3947-3950. https://doi.org/10.1109/EMBC.2019.8857591 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.conferencename | 41st International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019) | es_ES |
dc.relation.conferencedate | Julio 23-27,2019 | es_ES |
dc.relation.conferenceplace | Berlin, Germany | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/EMBC.2019.8857591 | es_ES |
dc.description.upvformatpinicio | 3947 | es_ES |
dc.description.upvformatpfin | 3950 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.identifier.pmid | 31946736 | es_ES |
dc.relation.pasarela | S\411282 | es_ES |