| Artificial neural networks for closed loop control of in silico and ad hoc type 1 diabetes. | |
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MedLine Citation:
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PMID: 22178070 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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The closed loop control of blood glucose levels might help to reduce many short- and long-term complications of type 1 diabetes. Continuous glucose monitoring and insulin pump systems have facilitated the development of the artificial pancreas. In this paper, artificial neural networks are used for both the identification of patient dynamics and the glycaemic regulation. A subcutaneous glucose measuring system together with a Lispro insulin subcutaneous pump were used to gather clinical data for each patient undergoing treatment, and a corresponding in silico and ad hoc neural network model was derived for each patient to represent their particular glucose-insulin relationship. Based on this nonlinear neural network model, an ad hoc neural network controller was designed to close the feedback loop for glycaemic regulation of the in silico patient. Both the neural network model and the controller were tested for each patient under simulation, and the results obtained show a good performance during food intake and variable exercise conditions. |
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Authors:
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J Fernandez de Canete; S Gonzalez-Perez; J C Ramos-Diaz |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-12-16 |
Journal Detail:
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Title: Computer methods and programs in biomedicine Volume: - ISSN: 1872-7565 ISO Abbreviation: - Publication Date: 2011 Dec |
Date Detail:
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Created Date: 2011-12-19 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8506513 Medline TA: Comput Methods Programs Biomed Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2011 Elsevier Ireland Ltd. All rights reserved. |
Affiliation:
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Dpt. System Eng. and Automation, Engineering School C/Dr. Ortiz Ramos s/n, 29071 Malaga, Spain. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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