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Author keywords
biomedical electronics, biomedical monitoring, fuzzy neural networks, neurocontrollers, virtual prototyping
References keywords
control(39), diabetes(29), systems(16), optimal(15), sanchez(13), neural(13), inverse(12), type(10), fuzzy(9), networks(7)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2022-08-31
Volume 22, Issue 3, Year 2022, On page(s): 3 - 14
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2022.03001
Web of Science Accession Number: 000861021000001
SCOPUS ID: 85137729315
Abstract
Type 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 (NF-IOC) algorithm on the Texas Instrument LAUNCHXL-F28069M 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 NF-IOC capability to regulate glucose within safe levels for virtual populations of 10 adults, 10 adolescents and, 10 children. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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