Glucose-Insulin regulator for type 1 diabetes using high order neural networks

Orozco López, Onofré and Castañeda Hernández, Carlos Eduardo and Rodríguez Herrero, Agustín and García Saéz, Gema and Hernando Pérez, María Elena (2014). Glucose-Insulin regulator for type 1 diabetes using high order neural networks. "International Journal of Artificial Intelligence and Neural Networks (IJAINN)", v. 4 (n. 3); pp. 40-47. ISSN 2250-3749.

Description

Title: Glucose-Insulin regulator for type 1 diabetes using high order neural networks
Author/s:
  • Orozco López, Onofré
  • Castañeda Hernández, Carlos Eduardo
  • Rodríguez Herrero, Agustín
  • García Saéz, Gema
  • Hernando Pérez, María Elena
Item Type: Article
Event Title: Proc. of the International Conference on Advances In Computing, Communication and Information Technology
Event Dates: 01/06/2014 - 02/06/2014
Event Location: LONDRES, UK
Título de Revista/Publicación: International Journal of Artificial Intelligence and Neural Networks (IJAINN)
Date: September 2014
ISSN: 2250-3749
Volume: 4
Subjects:
Freetext Keywords: Identification, Recurrent Neural Networks, Extended Kalman, Diabetes, Artificial Pancreas, insulin, glucose
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Ingeniería Telemática y Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

More information

Item ID: 35099
DC Identifier: http://oa.upm.es/35099/
OAI Identifier: oai:oa.upm.es:35099
Official URL: http://www.seekdl.org/journal_page_papers.php?jourid=84&issueid=93
Deposited by: Memoria Investigacion
Deposited on: 18 Mar 2016 20:20
Last Modified: 18 Mar 2016 20:20
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