Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study

Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm...

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Detalles Bibliográficos
Autores principales: Fushimi, Emilia, Serafini, María Cecilia, De Battista, Hernán, Garelli, Fabricio
Formato: Articulo Preprint
Lenguaje:Inglés
Publicado: 2020
Materias:
Ingeniería
Artificial pancreas
Switched control
Insulin on board
Constrained control
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/119945
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-119945
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ingeniería
Artificial pancreas
Switched control
Insulin on board
Constrained control
spellingShingle Ingeniería
Artificial pancreas
Switched control
Insulin on board
Constrained control
Fushimi, Emilia
Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
topic_facet Ingeniería
Artificial pancreas
Switched control
Insulin on board
Constrained control
description Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm based on switched control and timevarying insulin-on-board (IOB) constraints is presented. The proposed control strategy is evaluated in silico using the FDA-approved UVA/Padova simulator and its performance contrasted with the previously introduced Automatic Regulation of Glucose (ARG) algorithm in the pediatric population.The effect of unannounced meals is also explored. Results indicate that the proposed strategy achieves lower hypo- and hyperglycemia than the ARG for both announced and unannounced meals.
format Articulo
Preprint
author Fushimi, Emilia
Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
author_facet Fushimi, Emilia
Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
author_sort Fushimi, Emilia
title Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title_short Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title_full Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title_fullStr Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title_full_unstemmed Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title_sort automatic glycemic regulation for the pediatric population based on switched control and time-varying iob constraints: an in silico study
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/119945
work_keys_str_mv AT fushimiemilia automaticglycemicregulationforthepediatricpopulationbasedonswitchedcontrolandtimevaryingiobconstraintsaninsilicostudy
AT serafinimariacecilia automaticglycemicregulationforthepediatricpopulationbasedonswitchedcontrolandtimevaryingiobconstraintsaninsilicostudy
AT debattistahernan automaticglycemicregulationforthepediatricpopulationbasedonswitchedcontrolandtimevaryingiobconstraintsaninsilicostudy
AT garellifabricio automaticglycemicregulationforthepediatricpopulationbasedonswitchedcontrolandtimevaryingiobconstraintsaninsilicostudy
bdutipo_str Repositorios
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