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dc.contributor.author | Barceló Rico, Fátima![]() |
es_ES |
dc.contributor.author | Bondía Company, Jorge![]() |
es_ES |
dc.contributor.author | Diez Ruano, José Luís![]() |
es_ES |
dc.contributor.author | Rossetti ., Paolo![]() |
es_ES |
dc.date.accessioned | 2013-06-10T11:43:55Z | |
dc.date.available | 2013-06-10T11:43:55Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1520-9156 | |
dc.identifier.uri | http://hdl.handle.net/10251/29569 | |
dc.description | This is a copy of an article published in the Diabetes Technology & Therapeutics © 2012 copyright Mary Ann Liebert, Inc.; Diabetes Technology & Therapeutics is available online at: http://online.liebertpub.com/toc/dia/14/1 | es_ES |
dc.description.abstract | [EN] Background: Continuous glucose monitoring (CGM) devices estimate plasma glucose (PG) from measurements in compartments alternative to blood. The accuracy of currently available CGM is yet unsatisfactory and may depend on the implemented calibration algorithms, which do not compensate adequately for the differences of glucose dynamics between the compartments. Here we propose and validate an innovative calibration algorithm for the improvement of CGM performance. Methods: CGM data from GlucoDay (R) (A. Menarini, Florence, Italy) and paired reference PG have been obtained from eight subjects without diabetes during eu-, hypo-, and hyperglycemic hyperinsulinemic clamps. A calibration algorithm based on a dynamic global model (GM) of the relationship between PG and CGM in the interstitial space has been obtained. The GM is composed by independent local models (LMs) weighted and added. LMs are defined by a combination of inputs from the CGM and by a validity function, so that each LM represents to a variable extent a different metabolic condition and/or sensor-subject interaction. The inputs best suited for glucose estimation were the sensor current I and glucose estimations (G) over cap, at different time instants [I-k, Ik-1, (G) over cap (k-1)] (IIG). In addition to IIG, other inputs have been used to obtain the GM, achieving different configurations of the calibration algorithm. Results: Even in its simplest configuration considering only IIG, the new calibration algorithm improved the accuracy of the estimations compared with the manufacturer's estimate: mean absolute relative difference (MARD) = 10.8 +/- 1.5% versus 14.7 +/- 5.4%, respectively (P = 0.012, by analysis of variance). When additional exogenous signals were considered, the MARD improved further (7.8 +/- 2.6%, P<0.05). Conclusions: The LM technique allows for the identification of intercompartmental glucose dynamics. Inclusion of these dynamics into the calibration algorithm improves the accuracy of PG estimations. | es_ES |
dc.description.sponsorship | The authors acknowledge the partial funding of this work by the Spanish Ministry of Science and Innovation projects DPI2007-66728-C02-01 and DPI2010-20764-C02-01 and by the European Union through FEDER funds and grant FP7-PEOPLE-2009-IEF, Reference 252085. F.B.R. is the recipient of a fellowship (FPU AP2008-02967) from the Spanish Ministry of Education. | |
dc.language | Inglés | es_ES |
dc.publisher | Mary Ann Liebert | es_ES |
dc.relation.ispartof | Diabetes Technology & Therapeutics | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Plasma-Glucose | es_ES |
dc.subject | Interstitial glucose | es_ES |
dc.subject | Clinical accuracy | es_ES |
dc.subject | Blood-Glucose | es_ES |
dc.subject | Sensor | es_ES |
dc.subject | Microdialysis | es_ES |
dc.subject | Hypoglycemia | es_ES |
dc.subject | Insulin | es_ES |
dc.subject | Humans | es_ES |
dc.subject | Tissue | es_ES |
dc.subject.classification | INGENIERIA DE SISTEMAS Y AUTOMATICA | es_ES |
dc.title | A multiple local models approach to accuracy improvement in continuous glucose monitoring | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1089/dia.2011.0138. | |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/252085/EU/Seeking solutions for the artificial pancreas: new methods for improving continuous glucose monitoring and closed-loop postprandial glycaemic control./ | en_EN |
dc.relation.projectID | info:eu-repo/grantAgreement/MEC//DPI2007-66728-C02-01/ES/CONTROL DE GLUCEMIA EN LAZO CERRADO EN PACIENTES CON DIABETES MELLITUS 1 Y PACIENTES CRITICOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//DPI2010-20764-C02-01/ES/NUEVAS ESTRATEGIAS DE CONTROL GLUCEMICO POSTPRANDIAL MEDIANTE TERAPIA CON BOMBA DE INSULINA EN DIABETES TIPO 1/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//AP2008-02967/ES/AP2008-02967/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Automática e Informática Industrial - Institut Universitari d'Automàtica i Informàtica Industrial | es_ES |
dc.description.bibliographicCitation | Barceló Rico, F.; Bondía Company, J.; Diez Ruano, JL.; Rossetti ., P. (2012). A multiple local models approach to accuracy improvement in continuous glucose monitoring. Diabetes Technology & Therapeutics. 14(1):74-82. https://doi.org/10.1089/dia.2011.0138 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://online.liebertpub.com/doi/pdfplus/10.1089/dia.2011.0138 | es_ES |
dc.description.upvformatpinicio | 74 | es_ES |
dc.description.upvformatpfin | 82 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 14 | es_ES |
dc.description.issue | 1 | es_ES |
dc.relation.senia | 208962 | |
dc.contributor.funder | European Commission | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | |
dc.contributor.funder | Ministerio de Educación y Ciencia | es_ES |