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

Autores
Fushimi, Emilia; Serafini, María Cecilia; De Battista, Hernán; Garelli, Fabricio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
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.
Materia
Ingeniería Eléctrica y Electrónica
Artificial pancreas
Switched control
Insulin on board
Constrained control
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/10826

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network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico studyFushimi, EmiliaSerafini, María CeciliaDe Battista, HernánGarelli, FabricioIngeniería Eléctrica y ElectrónicaArtificial pancreasSwitched controlInsulin on boardConstrained controlArtificial 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.2020-06-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/10826enginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s11517-020-02213-winfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:49Zoai:digital.cic.gba.gob.ar:11746/10826Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:39:50.074CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
title Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
spellingShingle Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study
Fushimi, Emilia
Ingeniería Eléctrica y Electrónica
Artificial pancreas
Switched control
Insulin on board
Constrained control
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
dc.creator.none.fl_str_mv Fushimi, Emilia
Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
author Fushimi, Emilia
author_facet Fushimi, Emilia
Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
author_role author
author2 Serafini, María Cecilia
De Battista, Hernán
Garelli, Fabricio
author2_role author
author
author
dc.subject.none.fl_str_mv Ingeniería Eléctrica y Electrónica
Artificial pancreas
Switched control
Insulin on board
Constrained control
topic Ingeniería Eléctrica y Electrónica
Artificial pancreas
Switched control
Insulin on board
Constrained control
dc.description.none.fl_txt_mv 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.
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.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-24
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/10826
url https://digital.cic.gba.gob.ar/handle/11746/10826
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s11517-020-02213-w
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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