Management of diabetes using adaptive control

Abstract

The review focuses on adaptive systems for insulin treatment in type 1 diabetes. The review consists of two parts. First, adaptive approaches are described, which exploit infrequent glucose measurements (four to seven measurements per day). Second, adaptive approaches are described, which exploit frequent or continuous glucose measurements (every hour or more often). Each part is further divided into two subparts separating off-line and on-line adaptive techniques. The latter represents treatment strategies, which rely on continuous re-assessment of the glucoregulatory system. The former refers to treatment strategies, which are fixed for a day or longer and are revisited from time to time. It is concluded that the role of adaptive approaches will increase as new continuous glucose-sensing monitors reach the market.

A feedforward–feedback glucose control strategy for type 1 diabetes mellitus

“…Although this model has been effectively used in several studies [6], [24], it can result in non-physiological responses for some conditions. For example, large (but reasonable) basal infusion rates can produce an extended postprandial phase and meaningless negative G values [36].…”

“…Figure 1 shows the glucose responses for step changes in the manipulated variable and the disturbance variable. The disturbance response suggests that an appropriate disturbance model is a first-order transfer function: (6) where Because the step responses in Fig. 1a exhibit both nonlinear dynamic and steady-state behavior, specifying a form for the process transfer function, G p (s), is somewhat problematic.…”

“…During the past 30 years, a variety of glucose control strategies based on continuous and intermittent glucose sensing has been reported. Since this literature has been reviewed in recent survey articles [6][7][8][9][10][11][12], we will not present a detailed review here. Most of the relevant literature has been concerned with variations of proportional-integral-derivative (PID) control algorithms that are used in conjunction with an insulin injection (or bolus) at meal time.…”

“…A PID control strategy is attractive for glucose control because it mimics the first and second phase responses that the pancreas beta cells use to secrete insulin in response for non-diabetic individuals to the continuously sensed glucose [9]. In recent years, model-based control strategies such as model predictive control (MPC), adaptive control [6,[13][14][15][16][17][18], optimal control [19], neural networks [20,21], and H-infinity control [22,23], have been proposed and evaluated in simulation studies. A few experimental applications of MPC have also been reported [16,17,24].…”

Hypoglycemia Prevention in Closed-Loop Artificial Pancreas for Patients with Type 1 Diabetes

“…The complexity of glucose control mechanism highlights the need for an adaptive control algorithm to compensate for variations in patient dynamics (e.g. time-varying insulin sensitivity, stress and physical exercise) or disturbances by adapting the controller and model parameters to the changing patient conditions (Eren-Oruklu et al (2009a);Hovorka (2005)). Adaptive control includes several configurations that allow not only outputs of the controller to be changed over time, but also the method by which those outputs are generated; the controller continuously monitors its own adaptation through a defined metric, and is capable of altering its own control scheme to better meet the adaptation criterion.…”