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dc.contributor.author | Moreno-Oyervides, Aldo | es_ES |
dc.contributor.author | Martín-Mateos, Pedro | es_ES |
dc.contributor.author | Aguilera-Morillo, M. Carmen | es_ES |
dc.contributor.author | Ulisse, Giacomo | es_ES |
dc.contributor.author | Arriba, María C. | es_ES |
dc.contributor.author | Durban, María | es_ES |
dc.contributor.author | Del Rio, Marcela | es_ES |
dc.contributor.author | Larcher, Fernando | es_ES |
dc.contributor.author | Krozer, Viktor | es_ES |
dc.contributor.author | Acedo, Pablo | es_ES |
dc.date.accessioned | 2024-02-22T19:02:03Z | |
dc.date.available | 2024-02-22T19:02:03Z | |
dc.date.issued | 2019-08-01 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/202747 | |
dc.description.abstract | [EN] Diabetes is a very complex condition affecting millions of people around the world. Its occurrence, always accompanied by sustained hyperglycemia, leads to many medical complications that can be greatly mitigated when the disease is treated in its earliest stage. In this paper, a novel sensing approach for the early non-invasive detection and monitoring of sustained hyperglycemia is presented. The sensing principle is based on millimeter-wave transmission spectroscopy through the skin and subsequent statistical analysis of the amplitude data. A classifier based on functional principal components for sustained hyperglycemia prediction was validated on a sample of twelve mice, correctly classifying the condition in diabetic mice. Using the same classifier, sixteen mice with drug-induced diabetes were studied for two weeks. The proposed sensing approach was capable of assessing the glycemic states at different stages of induced diabetes, providing a clear transition from normoglycemia to hyperglycemia typically associated with diabetes. This is believed to be the first presentation of such evolution studies using non-invasive sensing. The results obtained indicate that gradual glycemic changes associated with diabetes can be accurately detected by non-invasively sensing the metabolism using a millimeter-wave spectral sensor, with an observed temporal resolution of around four days. This unprecedented detection speed and its non-invasive character could open new opportunities for the continuous control and monitoring of diabetics and the evaluation of response to treatments (including new therapies), enabling a much more appropriate control of the condition. | es_ES |
dc.description.sponsorship | This research was supported in part by the Spanish Ministry of Economy and Competitiveness through the project TEC2017-86271-R and the Instituto de Salud Carlos III (Spain) through the grant DTS17/00135. Thanks to the Consejo Nacional de Ciencia y Tecnología de México (CONACYT) for financially supporting the doctoral education of Aldo M-O (PhD. Grant). Viktor Krozer is thankful for partial financial support in the frame of the Chairs of Excellence program of the Universidad Carlos III, Madrid, Spain. This research was partially supported by Project MTM2017-88708-P from Ministerio de Economía y Competitividad, FEDER funds, Project IJCI-2017-34038 from Agencia Estatal de Investigación, Ministerio de Ciencia, Innovación y Universidades and the Spanish Ministry of Economy and Competitiveness MTM2014-52184-P. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sensors | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Early diabetes detection | es_ES |
dc.subject | Functional principal component analysis | es_ES |
dc.subject | Millimeter-wave spectroscopy | es_ES |
dc.subject | Non-invasive diagnosis techniques | es_ES |
dc.subject | Sustained hyperglycemia | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.title | Early, Non-Invasive Sensing of Sustained Hyperglycemia in Mice Using Millimeter-Wave Spectroscopy | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s19153347 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-88708-P/ES/CONTRIBUCIONES METODOLOGICAS Y APLICADAS EN MODELIZACION ESTOCASTICA Y FUNCIONAL DE DATOS ESTADISTICOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2017-86271-R/ES/EVALUACION EN TIEMPO REAL DE PARAMETROS DE CALIDAD DE AGUAS UTILIZANDO NUEVAS ARQUITECTURAS Y COMPONENTES FOTONICOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 (ISCIII)/DTS17%2F00135/ES/DESARROLLO, VALIDACION Y EVALUACION DE UNA NUEVA HERRAMIENTA NO INVASIVA PARA MEDIR LA HIPERGLUCEMIA SOSTENIDA USANDO ESPECTROSCOPIA DE ONDAS MILIMETRICAS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//MTM2014-52184-P/ES/MODELOS ADITIVOS GENERALIZADOS PARA DATOS COMPLEJOS Y DE ALTA DIEMNSION/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MCIU//IJCI-2017-34038/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.description.bibliographicCitation | Moreno-Oyervides, A.; Martín-Mateos, P.; Aguilera-Morillo, MC.; Ulisse, G.; Arriba, MC.; Durban, M.; Del Rio, M.... (2019). Early, Non-Invasive Sensing of Sustained Hyperglycemia in Mice Using Millimeter-Wave Spectroscopy. Sensors. 19(15). https://doi.org/10.3390/s19153347 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s19153347 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 19 | es_ES |
dc.description.issue | 15 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 31366169 | es_ES |
dc.identifier.pmcid | PMC6695793 | es_ES |
dc.relation.pasarela | S\408611 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades | es_ES |
dc.contributor.funder | Instituto de salud Carlos III | es_ES |