Evaluation of Using a Recurrent Neural Network (RNN) and a Fuzzy Logic Controller (FLC) In Closed Loop System to Regulate Blood Glucose for Type-1 Diabetic Patients (original) (raw)

Blood glucose prediction for diabetes therapy using a recurrent artificial neural network

9th European Signal Processing Conference (EUSIPCO 1998), 1998

Expert short-term management of diabetes through good glycaemic control, is necessary to delay or even prevent serious degenerative complications developing in the long term, due to consistently high blood glucose levels (BGLs). Good glycaemic control may be achieved by predicting a future BGL based on past BGLs and past and anticipated diet, exercise schedule and insulin regime (the latter for insulin dependent diabetics). This predicted BGL may then be used in a computerised management system to achieve short-term normoglycaemia. This paper investigates the use of a recurrent artificial neural network for predicting BGL, and presents preliminary results for two insulin dependent diabetic females.

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

2014

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 ...

Modeling of Patient of Type 1 Diabetes for Blood Glucose Control

The recent development in the insulin delivery system is the automatic one .The blood glucose levels are controlled by the feedback loop. The initial success with the simple models in normalizing blood glucose level led to the improvement of the devices including variety of control system. The insulin delivery system to diabetic is a tedious job and doesn't ensure proper performance and leads to various complications if the delivery of insulin is not proper. The system which is a portable one used to control the blood glucose concentration. In this paper theoretical analysis has been performed to regulate blood glucose insulin concentration on the basis of some mathematical models. The closed-loop insulin delivery system is composed of three essential components: a stable glucose sensor for measuring the glucose concentration, a control system regulating external insulin infusion based on the glucose-insulin system and a safe and stable insulin pump. The goal is to control and analyze two controllers which were designed to control the plant which is diabetic patient for this paper and the controllers analyzed are proportional integral derivative (PID), and fuzzy logic controllers (FLC). Mathematical modeling of a patient is shown in this paper. Simulation would be performed in MATLAB software.