Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints

Autores
Fushimi, Emilia; Serafini, María Cecilia; Sánchez Peña, Ricardo; De Battista, Hernan; Garelli, Fabricio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión enviada
Descripción
Arti cial 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, a new algorithm based on switched control and time-varying insulin-on-board (IOB) constraints is presented (ARGAE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses, and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population. Results show that the ARGAE presents improved performance compared to the ARG algorithm even in presence of misclassi ed meals. Thus, future in vivo testing will involve the AE con guration.
Materia
Ciencias de la Salud
Switched control
Sliding mode
Non-linear control systems
Biological and medical systems
Artificial Pancreas
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/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:11746/10805

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network_name_str CIC Digital (CICBA)
spelling Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraintsFushimi, EmiliaSerafini, María CeciliaSánchez Peña, RicardoDe Battista, HernanGarelli, FabricioCiencias de la SaludSwitched controlSliding modeNon-linear control systemsBiological and medical systemsArtificial PancreasArti cial 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, a new algorithm based on switched control and time-varying insulin-on-board (IOB) constraints is presented (ARGAE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses, and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population. Results show that the ARGAE presents improved performance compared to the ARG algorithm even in presence of misclassi ed meals. Thus, future in vivo testing will involve the AE con guration.2020-07-17info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/10805enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:48Zoai:digital.cic.gba.gob.ar:11746/10805Institucionalhttp://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 13:39:48.662CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
title Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
spellingShingle Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
Fushimi, Emilia
Ciencias de la Salud
Switched control
Sliding mode
Non-linear control systems
Biological and medical systems
Artificial Pancreas
title_short Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
title_full Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
title_fullStr Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
title_full_unstemmed Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
title_sort Pediatric glucose regulation without pre-meal insulin boluses: an approach based on switched control and time-varying IOB constraints
dc.creator.none.fl_str_mv Fushimi, Emilia
Serafini, María Cecilia
Sánchez Peña, Ricardo
De Battista, Hernan
Garelli, Fabricio
author Fushimi, Emilia
author_facet Fushimi, Emilia
Serafini, María Cecilia
Sánchez Peña, Ricardo
De Battista, Hernan
Garelli, Fabricio
author_role author
author2 Serafini, María Cecilia
Sánchez Peña, Ricardo
De Battista, Hernan
Garelli, Fabricio
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias de la Salud
Switched control
Sliding mode
Non-linear control systems
Biological and medical systems
Artificial Pancreas
topic Ciencias de la Salud
Switched control
Sliding mode
Non-linear control systems
Biological and medical systems
Artificial Pancreas
dc.description.none.fl_txt_mv Arti cial 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, a new algorithm based on switched control and time-varying insulin-on-board (IOB) constraints is presented (ARGAE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses, and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population. Results show that the ARGAE presents improved performance compared to the ARG algorithm even in presence of misclassi ed meals. Thus, future in vivo testing will involve the AE con guration.
description Arti cial 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, a new algorithm based on switched control and time-varying insulin-on-board (IOB) constraints is presented (ARGAE). This method is a combination of ideas from the previously introduced Automatic Regulation of Glucose (ARG) algorithm, which features no pre-meal insulin boluses, and the Amplitude Enable (AE) mode, which allows the controller to act more aggressively at the beginning of meal intake without risking postprandial hypoglycemia. The proposed control strategy is evaluated in silico and its performance contrasted with the ARG algorithm in the pediatric population. Results show that the ARGAE presents improved performance compared to the ARG algorithm even in presence of misclassi ed meals. Thus, future in vivo testing will involve the AE con guration.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-17
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info:eu-repo/semantics/submittedVersion
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dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/10805
url https://digital.cic.gba.gob.ar/handle/11746/10805
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
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instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
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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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