- -

Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Manrique-Córdoba, J. es_ES
dc.contributor.author Romero-Ante, J. D. es_ES
dc.contributor.author Vivas, A. es_ES
dc.contributor.author Vicente, J.M. es_ES
dc.contributor.author Sabater-Navarro, J. M. es_ES
dc.date.accessioned 2020-05-12T18:11:01Z
dc.date.available 2020-05-12T18:11:01Z
dc.date.issued 2020-04-07
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/142982
dc.description.abstract [EN] Diabetes mellitus type 1 is a condition in which the pancreas loses its ability to produce enough insulin, increasing the levels of blood glucose. This work presents the design of a mathematical model of the glucose - insulin dynamics of a type 1 diabetes patient, contemplating the contribution to the concentration of blood glucose by the intake of carbohydrates, fats and proteins. The model also includes the absorption dynamics of 5 insulin types, different administration methods of exogenous insulin, and the variation of insulin sensitivity during the day. The model was integrated into a closed-loop insulin regulation algorithm, in order to evaluate the performance of the model and the efficiency of closed-loop treatments, compared to open-loop therapies. The results show the response of the model to different situations of a real patient, and tests of the controller’s performance. es_ES
dc.description.abstract [ES] La diabetes tipo 1 es una afección en la cual el páncreas pierde su capacidad de producir suficiente insulina, incrementando significativamente la concentración de glucosa en la sangre. En el presente trabajo se presenta el diseño de un modelo matemático de las dinámicas glucosa-insulina de un paciente con diabetes tipo 1, el cual contempla el aporte a la concentración de glucosa en la sangre por parte de la ingesta de carbohidratos, grasas y proteínas. El modelo incluye las dinámicas de absorción de 5 tipos de insulina, diferentes métodos de administración de la misma, y la variación de la sensibilidad a la insulina durante el día. Se integró el modelo a un algoritmo de regulación de insulina en lazo cerrado, con el fin de evaluar el desempeño del modelo y la eficacia de los tratamientos en lazo cerrado, en comparación con las terapias en lazo abierto. Los resultados muestran la respuesta del modelo ante distintas situaciones de un paciente real, y pruebas de funcionamiento del controlador. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Type 1 Diabetes es_ES
dc.subject Mathematical Model Dynamic Glucose Insulin es_ES
dc.subject Insulin Regulation in Closed Loop es_ES
dc.subject Diabetes Tipo 1 es_ES
dc.subject Modelo Matemático Dinámica Glucosa - Insulina es_ES
dc.subject Regulación de Insulina en Lazo Cerrado es_ES
dc.title Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado es_ES
dc.title.alternative Mathematical modeling of food intake and insulin infusion in a patient with type 1 Ddabetes in closed loop es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2019.11161
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Manrique-Córdoba, J.; Romero-Ante, JD.; Vivas, A.; Vicente, J.; Sabater-Navarro, JM. (2020). Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado. Revista Iberoamericana de Automática e Informática industrial. 17(2):156-168. https://doi.org/10.4995/riai.2019.11161 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2019.11161 es_ES
dc.description.upvformatpinicio 156 es_ES
dc.description.upvformatpfin 168 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\11161 es_ES
dc.description.references Ackerman, E., Rosevear, J. W., McGuckin, W. F., 1964. A mathematical model of the glucose-tolerance test. Physics in medicine & Biology 9 (2), 203. https://doi.org/10.1088/0031-9155/9/2/307 es_ES
dc.description.references American Diabetes Association, 2017. [Online; accessed October 2018]. URL: http://www.diabetes.org/ es_ES
dc.description.references Apablaza, P., Soto, N., Codner, E., 2017. De la bomba de insulina y el monitoreo continuo de glucosa al páncreas artificial. Revista Médica de Chile,145 (5), 630-640. https://doi.org/10.4067/S0034-98872017000500011 es_ES
dc.description.references Barrio, R., Andia, V., Vazquez, F., Salgado, Y., Valverde, M., Jansa, M., Flores, M., 2012. Guía de educación terapéutica, al inicio de tratamiento con infusión subcutánea continua de insulina (ISCI). PardeDós. URL: https://diabetesmadrid.org/ es_ES
dc.description.references Beneyto, A., Bertachi, A., Bondia, J., Vehi, J., 2018. A new blood glucose control scheme for unannounced exercise in type 1 diabetic subjects. IEEE Transactions on Control Systems Technology, 1-8. es_ES
dc.description.references Bergenstal, R. M., Garg, S., Weinzimer, S. A., Buckingham, B. A., Bode, B. W., Tamborlane, W. V., Kaufman, F. R., 2016. Safety of a hybrid closed-loop insulin delivery system in patients with type 1 diabetes. Jama 316 (13), 1407- 1408. https://doi.org/10.1001/jama.2016.11708 es_ES
dc.description.references Berger, M., Rodbard, D., 1989. Computer simulation of plasma insulin and glucose dynamics after subcutaneous insulin injection. Diabetes Care 12 (10), 725-736. https://doi.org/10.2337/diacare.12.10.725 es_ES
dc.description.references Binder, C., 1969. Absorption of injected insulin: A clinical-pharmacological study. Acta Pharmacologica et Toxicologica 27 (S2), 1-83. https://doi.org/10.1111/j.1600-0773.1969.tb03069.x es_ES
dc.description.references Bolie, V. W., 1961. Coefficients of normal blood glucose regulation. Journal of Applied Physiology 16 (5), 783-788. https://doi.org/10.1152/jappl.1961.16.5.783 es_ES
dc.description.references Breda, E., Cavaghan, M. K., Toffolo, G., Polonsky, K. S., Cobelli, C., 2001. Oral glucose tolerance test minimal model indexes of β-cell function and insulin sensitivity. Diabetes 50 (1), 150-158. https://doi.org/10.2337/diabetes.50.1.150 es_ES
dc.description.references Breton, M., Farret, A., Bruttomesso, D., Anderson, S., Magni, L., Patek, S., Dalla Man, C., Place, J., Demartini, S., Del Favero, S., 2012. Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia. Diabetes 61, 2230-2237. https://doi.org/10.2337/db11-1445 es_ES
dc.description.references Bruttomesso, D., Farret, A., Costa, S., Marescotti, M. C., Vettore, M., Avogaro, A., Tiengo, A., Dalla Man, C., Place, J., Facchinetti, A., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. Journal of Diabetes Science and Technology 3, 1014-1021. https://doi.org/10.1177/193229680900300504 es_ES
dc.description.references Clarke, W. L., Anderson, S., Breton, M., Patek, S., Kashmer, L., Kovatchev, B., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience. Journal of Diabetes Science and Technology 3, 1031-1038. https://doi.org/10.1177/193229680900300506 es_ES
dc.description.references Clemens, A., Chang, P., Myers, R., 1977. The development of biostator, a glucose controlled insulin infusion system (GCIIS). Hormone and metabolic research 7, 23-33. es_ES
dc.description.references Cobelli, C., Nucci, G., Del Prato, S., 1999. A physiological simulation model of the glucose-insulin system. Vol. 2. es_ES
dc.description.references Colino, E., 2018. Fundación para la Diabetes. [Online; October 2018]. URL: http://www.fundaciondiabetes.org/ es_ES
dc.description.references Craig, T. P., 2010. Dietary Carnitine Supplementation as a potential modulator of insulin sensitivity. Master's Thesis, University of Stirling. URL: https://dspace.stir.ac.uk/ es_ES
dc.description.references Dalla Man, C., Breton, M. D., Cobelli, C., 2009. Physical activity into the meal glucose-insulin model of type 1 diabetes: in silico studies 3, 56-67. https://doi.org/10.1177/193229680900300107 es_ES
dc.description.references Dalla Man, C., Camilleri, M., Cobelli, C., 2006. A system model of oral glucose absorption: validation on gold standard data. IEEE Transactions on Biomedical Engineering 53 (12), 2472-2478. https://doi.org/10.1109/TBME.2006.883792 es_ES
dc.description.references Dalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., Cobelli, C., 2014. The uva/padova type 1 diabetes simulator: new features. Journal of Diabetes Science and Technology 8 (1), 26-34. https://doi.org/10.1177/1932296813514502 es_ES
dc.description.references Dalla Man, C., Raimondo, D. M., Rizza, R. A., Cobelli, C., 2007a. GIM, simulation software of meal glucose insulin model. Journal of Diabetes Science and Technology 1, 323-330. https://doi.org/10.1177/193229680700100303 es_ES
dc.description.references Dalla Man, C., Rizza, R. A., Cobelli, C., 2007b. Meal simulation model of the glucose-insulin system. IEEE Transactions on Biomedical Engineering 54 (10), 1740-1749. https://doi.org/10.1109/TBME.2007.893506 es_ES
dc.description.references Haidar, A., 2016. The artificial pancreas: How close-loop control is revolutionizing diabetes. IEEE Condtrol Systems 36 (5), 28-47. https://doi.org/10.1109/MCS.2016.2584318 es_ES
dc.description.references International Diabetes Federation, 2017. IDF diabetes atlas, 8th Edition. URL: http://www.diabetesatlas.org/ es_ES
dc.description.references IRICOM, 2018. Sociedad Española de Diabetes. [Online; October 2018]. URL: http://www.sediabetes.org/ es_ES
dc.description.references Kadish, A. H., 1963. Automation control of blood sugar a servomechanism for glucose monitoring and control. ASAIO Journal 9 (1), 363-367. es_ES
dc.description.references Manrique, J., Romero, J. D., Sabater, J. M., Vivas, O. A., Vicente, J. M., 2018. Simulador de paciente T1D en tiempo real. Actas de las XXXIX Jornadas de Automática, Badajoz, 64-71. ' es_ES
dc.description.references Mauseth, R., Hirsch, I. B., Bollyky, J., Kircher, R., Matheson, D., Sanda, S., Greenbaum, C., 2013. Use of a "fuzzy logic" controller in a closed-loop artificial pancreas. Diabetes Technology & Therapeutics 15 (8), 628-633. https://doi.org/10.1089/dia.2013.0036 es_ES
dc.description.references Murillo, M. D., Fernandez, F., Tuneu, L., 2004. Guía de seguimiento farmacoterapéutico sobre diabetes. Grupo de Investigación en Atención Farmacéutica (GIAF). URL: http://www.ugr.es/ es_ES
dc.description.references National Center for Biotechnology Information, 2018. Insulin aspart. Pub Chem Compound Database, [Online; October 2018]. URL: https://pubchem.ncbi.nlm.nih.gov/compound/16132418 es_ES
dc.description.references Nimri, R., Atlas, E., Ajzensztejn, M., Miller, S., Oron, T., Phillip, M., 2012. Feasibility study of automated overnight closed-loop glucose control under md-logic artificial pancreas in patients with type 1 diabetes: the dream project. Diabetes Technology & Therapeutics 14 (8), 728-735. https://doi.org/10.1089/dia.2012.0004 es_ES
dc.description.references Nucci, G., Cobelli, C., 2000. Models of subcutaneous insulin kinetics. a critical review. Computer Methods and Programs in Biomedicine 62 (3), 249-257. https://doi.org/10.1016/S0169-2607(00)00071-7 es_ES
dc.description.references OpenAPS Community, 2015. Openaps. OpenAPS.org, [Online; October 2018]. URL: https://openaps.org/ es_ES
dc.description.references Renard, E., Place, J., Cantwell, M., Chevassus, H., Palerm, C. C., 2010. Closedloop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas. Diabetes Care 33 (1), 121-127. https://doi.org/10.2337/dc09-1080 es_ES
dc.description.references Segre, G., Turco, G., Vercellone, G., 1973. Modeling blood glucose and insulin kinetics in normal, diabetic and obese subjects. Diabetes 22 (2), 94-103. https://doi.org/10.2337/diab.22.2.94 es_ES
dc.description.references Steil, G. M., Palerm, C. C., Kurtz, N., Voskanyan, G., Roy, A., Paz, S., Kandeel, F. R., 2011. The effect of insulin feedback on closed loop glucose control. The Journal of Clinical Endocrinology & Metabolism 96 (5), 1402-1408. https://doi.org/10.1210/jc.2010-2578 es_ES
dc.description.references Toffolo, G., Bergman, R. N., Finegood, D. T., Bowden, C. R., Cobelli, C., 1980. Quantitative estimation of beta cell sensitivity to glucose in the intact organism: a minimal model of insulin kinetics in the dog. Diabetes 29 (12), 979-990. https://doi.org/10.2337/diab.29.12.979 es_ES
dc.description.references Trajanoski, Z., Wach, P., Kotanko, P., Ott, A., Skraba, F., 1993. Pharmacokinetic model for the absorption of subcutaneously injected soluble insulin and monomeric insulin-analogues. Biomedizinische Technik Biomedical Engineering 38 (9), 224-231. https://doi.org/10.1515/bmte.1993.38.9.224 es_ES
dc.description.references Turksoy, K., Cinar, A., 2014. Adaptive control of artificial pancreas systems-a review. Journal of Healthcare Engineering 5 (1), 1-22. https://doi.org/10.1260/2040-2295.5.1.1 es_ES
dc.description.references Weinzimer, S. A., Sherr, J. L., Cengiz, E., Kim, G., Ruiz, J. L., Carria, L., Voskanyan, G., Roy, A., Tamborlane, W. V., 2012. Effect of pramlintide on prandial glycemic excursions during closed-loop control in adolescents and young adults with type 1 diabetes. Diabetes Care. URL: http://care.diabetesjournals.org https://doi.org/10.2337/dc12-0330 es_ES
dc.description.references Yoldi, C., Mayo 2018. Las grasas y las proteínas también cuentan. Guía Diabetes tipo 1, [Online; October 2018]. URL: https://www.diabetes-cidi.org/ es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem