Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement

Autores
Fushimi, Emilia; Colmegna, Patricio Hernán; De Battista, Hernán; Garelli, Fabricio; Sánchez Peña, Ricardo Salvador
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: 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.
Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales
Consejo Nacional de Investigaciones Científicas y Técnicas
Materia
Ingeniería Electrónica
artificial pancreas
carbohydrate counting
sliding mode control
switched control
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/107443

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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Artificial Pancreas: Evaluating the ARG Algorithm Without Meal AnnouncementFushimi, EmiliaColmegna, Patricio HernánDe Battista, HernánGarelli, FabricioSánchez Peña, Ricardo SalvadorIngeniería Electrónicaartificial pancreascarbohydrate countingsliding mode controlswitched controlBackground: 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.Instituto de Investigaciones en Electrónica, Control y Procesamiento de SeñalesConsejo Nacional de Investigaciones Científicas y Técnicas2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf1035-1043http://sedici.unlp.edu.ar/handle/10915/107443enginfo:eu-repo/semantics/altIdentifier/url/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6835180&blobtype=pdfinfo:eu-repo/semantics/altIdentifier/issn/1932-2968info:eu-repo/semantics/altIdentifier/pmid/31339059info:eu-repo/semantics/altIdentifier/doi/10.1177/1932296819864585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:23:52Zoai:sedici.unlp.edu.ar:10915/107443Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:23:52.903SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
title Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
spellingShingle Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
Fushimi, Emilia
Ingeniería Electrónica
artificial pancreas
carbohydrate counting
sliding mode control
switched control
title_short Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
title_full Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
title_fullStr Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
title_full_unstemmed Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
title_sort Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement
dc.creator.none.fl_str_mv Fushimi, Emilia
Colmegna, Patricio Hernán
De Battista, Hernán
Garelli, Fabricio
Sánchez Peña, Ricardo Salvador
author Fushimi, Emilia
author_facet Fushimi, Emilia
Colmegna, Patricio Hernán
De Battista, Hernán
Garelli, Fabricio
Sánchez Peña, Ricardo Salvador
author_role author
author2 Colmegna, Patricio Hernán
De Battista, Hernán
Garelli, Fabricio
Sánchez Peña, Ricardo Salvador
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ingeniería Electrónica
artificial pancreas
carbohydrate counting
sliding mode control
switched control
topic Ingeniería Electrónica
artificial pancreas
carbohydrate counting
sliding mode control
switched control
dc.description.none.fl_txt_mv Background: 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.
Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales
Consejo Nacional de Investigaciones Científicas y Técnicas
description Background: 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.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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info:eu-repo/semantics/altIdentifier/pmid/31339059
info:eu-repo/semantics/altIdentifier/doi/10.1177/1932296819864585
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