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


Autoria(s): Orozco López, Onofré; Castañeda Hernández, Carlos Eduardo; Rodríguez Herrero, Agustín; García Saéz, Gema; Hernando Pérez, María Elena
Data(s)

01/09/2014

Resumo

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.

Formato

application/pdf

Identificador

http://oa.upm.es/35099/

Idioma(s)

eng

Publicador

E.T.S.I y Sistemas de Telecomunicación (UPM)

Relação

http://oa.upm.es/35099/1/INVE_MEM_2014_189551.pdf

http://www.seekdl.org/journal_page_papers.php?jourid=84&issueid=93

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

International Journal of Artificial Intelligence and Neural Networks (IJAINN), ISSN 2250-3749, 2014-09, Vol. 4, No. 3

Palavras-Chave #Matemáticas #Medicina
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed