Personalization of a compartmental physiological model for an artificial pancreas through integration of patient's state estimation
| Description | |
| Date | |
| Authors | Jallon P., Lachal S., Franco C., Charpentier G., Huneker E., Doron M. |
| Year | 2017-0442 |
| Source-Title | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
| Affiliations | Univ. Grenoble Alpes, France, CEA, LETI, MINATEC Campus, Grenoble, France, Centre Hospitalier Sud-Francilien, Department of Diabetes and Endocrinology, Corbeil-Essones, France, Centre d'Etudes et de Recherche Pour l'Intensification du Traitement du Diabète (CERITD), Corbeil-Essonnes, France, Diabeloop SAS, 155 Cours Berriat, France |
| Abstract | Artificial Pancreas (AP) are developed for patients with Type 1 diabetes. This medical device system consists in the association of a subcutaneous continuous glucose monitor (CGM) providing a proxy of the patient's glycaemia and a control algorithm offering the real-time modification of the insulin delivery with an automatic command of the subcutaneous insulin pump. The most complex algorithms are based on a compartmental model of the glucoregulatory system of the patient coupled to an approach of MPC (Model-Predictive-Control) for the command. The automatic and unsupervised control of insulin regulation constitutes a major challenge in AP projects. A given model with its parameterization on the shelf will not directly represent the patient's data behavior and the personalization of the model is a prerequisite before using it in a MPC. The present paper focuses on the personalization of a compartmental showing a method where taking into account the estimation of the patient's state in addition to the parameter estimation improves the results in terms of mean quadratic error. © 2017 IEEE. |
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| ISSN | 1557170X |
| Link | Link |