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University of Suceava
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Print ISSN: 1582-7445
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On Board Neuro Fuzzy Inverse Optimal Control for Type 1 Diabetes Mellitus Treatment: In-Silico Testing

RIOS, Y. See more information about RIOS, Y. on SCOPUS See more information about RIOS, Y. on IEEExplore See more information about RIOS, Y. on Web of Science, GARCIA-RODRIGUEZ, J. See more information about  GARCIA-RODRIGUEZ, J. on SCOPUS See more information about  GARCIA-RODRIGUEZ, J. on SCOPUS See more information about GARCIA-RODRIGUEZ, J. on Web of Science, SANCHEZ, E. See more information about  SANCHEZ, E. on SCOPUS See more information about  SANCHEZ, E. on SCOPUS See more information about SANCHEZ, E. on Web of Science, ALANIS, A. See more information about  ALANIS, A. on SCOPUS See more information about  ALANIS, A. on SCOPUS See more information about ALANIS, A. on Web of Science, RUIZ-VELAZQUEZ, E. See more information about  RUIZ-VELAZQUEZ, E. on SCOPUS See more information about  RUIZ-VELAZQUEZ, E. on SCOPUS See more information about RUIZ-VELAZQUEZ, E. on Web of Science, PARDO-GARCIA, A. See more information about PARDO-GARCIA, A. on SCOPUS See more information about PARDO-GARCIA, A. on SCOPUS See more information about PARDO-GARCIA, A. on Web of Science
 
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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
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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.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 34,974 TCR
SCOPUS® Citations for all references: 49,649 TCR

Web of Science® Average Citations per reference: 744 ACR
SCOPUS® Average Citations per reference: 1,056 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-05-26 09:51 in 273 seconds.




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