dc.creatorFushimi, Emilia
dc.creatorColmegna, Patricio Hernán
dc.creatorDe Battista, Hernán
dc.creatorGarelli, Fabricio
dc.creatorSánchez Peña, Ricardo Salvador
dc.date2019
dc.date2020-10-21T15:43:10Z
dc.date.accessioned2023-07-14T22:45:07Z
dc.date.available2023-07-14T22:45:07Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/107443
dc.identifierhttp://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6835180&blobtype=pdf
dc.identifierissn:1932-2968
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7448069
dc.descriptionBackground: Either under standard basal-bolus treatment or hybrid closed-loop control, subjects with type 1 diabetes are required to count carbohydrates (CHOs). However, CHO counting is not only burdensome but also prone to errors. Recently, an artificial pancreas algorithm that does not require premeal insulin boluses—the so-called automatic regulation of glucose (ARG)—was introduced. In its first pilot clinical study, although the exact CHO counting was not required, subjects still needed to announce the meal time and classify the meal size. Method: An automatic switching signal generator (SSG) is proposed in this work to remove the manual mealtime announcement from the control strategy. The SSG is based on a Kalman filter and works with continuous glucose monitoring readings only. Results: The ARG algorithm with unannounced meals (ARGum) was tested in silico under the effect of different types of mixed meals and intrapatient variability, and contrasted with the ARG algorithm with announced meals (ARGam). Simulations reveal that, for slow-absorbing meals, the time in the euglycemic range, [70-180] mg/dL, increases using the unannounced strategy (ARGam: 78.1 [68.6-80.2]% (median [IQR]) and ARGum: 87.8 [84.5-90.6]%), while similar results were found with fastabsorbing meals (ARGam: 87.4 [86.0-88.9]% and ARGum: 87.6 [86.1-88.8]%). On the other hand, when intrapatient variability is considered, time in euglycemia is also comparable (ARGam: 81.4 [75.4-83.5]% and ARGum: 80.9 [77.0-85.1]%). Conclusion: In silico results indicate that it is feasible to perform an in vivo evaluation of the ARG algorithm with unannounced meals.
dc.descriptionInstituto de Investigaciones en Electrónica, Control y Procesamiento de Señales
dc.descriptionConsejo Nacional de Investigaciones Científicas y Técnicas
dc.formatapplication/pdf
dc.format1035-1043
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectIngeniería Electrónica
dc.subjectartificial pancreas
dc.subjectcarbohydrate counting
dc.subjectsliding mode control
dc.subjectswitched control
dc.titleArtificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
dc.typeArticulo
dc.typeArticulo


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