On Board Neuro Fuzzy Inverse Optimal Control for Type 1 Diabetes Mellitus Treatment: In-Silico Testing

dc.creatorRios, Yuliana
dc.creatorGarcia-Rodriguez, Julio
dc.creatorSanchez, Edgar
dc.creatorAlanis, Alma
dc.creatorRuizvelazquez, Eduardo
dc.creatorPardo-Garcia, Aldo
dc.date.accessioned2023-07-25T12:10:03Z
dc.date.accessioned2023-09-06T15:54:01Z
dc.date.available2023-07-25T12:10:03Z
dc.date.available2023-09-06T15:54:01Z
dc.date.created2023-07-25T12:10:03Z
dc.date.issued2022
dc.identifierRios, Y., Garcia-Rodriguez, J., Sanchez, E., Alanis, A., Ruiz-Velazquez, E., & Pardo-Garcia, A. (2022). On Board Neuro Fuzzy Inverse Optimal Control for Type 1 Diabetes Mellitus Treatment: In-Silico Testing. Advances in Electrical & Computer Engineering, 22(3).
dc.identifierhttps://hdl.handle.net/20.500.12585/12426
dc.identifier10.4316/AECE.2022.03001
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio Universidad Tecnológica de Bolívar
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8683552
dc.description.abstractType 1 Diabetes Mellitus (T1DM) is one of the most adverse diseases in the modern era; its treatment is mainly based on exogenous insulin injections. The scientific community has formulated strategies to improve insulin supply using state-of-the-art technology. Therefore, this article develops a multi-age glycemic control scheme, which can be implemented in an Artificial Pancreas (AP) device to enhance diabetics treatment. The procedure is based on the implementation of a neuro-fuzzy inverse optimal control (NFIOC) algorithm on the Texas Instrument LAUNCHXLF28069M development board; this controller communicates with the Uva/Padova simulator for diabetics' patients of different ages under predefined meal protocols running on a Personal Computer (PC). The novelty lies in the proposed NFIOC capability to regulate glucose within safe levels for virtual populations of 10 adults, 10 adolescents and, 10 children. © 2022 AECE
dc.languageeng
dc.publisherCartagena de Indias
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.sourceAdvances in Electrical and Computer Engineering
dc.titleOn Board Neuro Fuzzy Inverse Optimal Control for Type 1 Diabetes Mellitus Treatment: In-Silico Testing


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