A Review of Closed-Loop Algorithms for Glycemic Control in the Treatment of Type 1 Diabetes
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paper_title: Closing the Loop: The Adicol Experience

paper_content:

The objective of the project Advanced Insulin Infusion using a Control Loop (ADICOL) was to develop a treatment system that continuously measures and controls the glucose concentration in subjects with type 1 diabetes. The modular concept of the ADICOL's extracorporeal artificial pancreas consisted of a minimally invasive subcutaneous glucose system, a handheld PocketPC computer, and an insulin pump (D-Tron, Disetronic, Burgdorf, Switzerland) delivering subcutaneously insulin lispro. The present paper describes a subset of ADICOL activities focusing on the development of a glucose controller for semi-closed-loop control, an in silico testing environment, clinical testing, and system integration. An incremental approach was adopted to evaluate experimentally a model predictive glucose controller. A feasibility study was followed by efficacy studies of increasing complexity. The ADICOL project demonstrated feasibility of a semi-closed-loop glucose control during fasting and fed conditions with a wearable, m...
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paper_title: The future of open- and closed-loop insulin delivery systems.

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We have analysed several aspects of insulin-dependent diabetes mellitus, including the glucose metabolic system, diabetes complications, and previous and ongoing research aimed at controlling glucose in diabetic patients. An expert review of various models and control algorithms developed for the glucose homeostasis system is presented, along with an analysis of research towards the development of a polymeric insulin infusion system. Recommendations for future directions in creating a true closed-loop glucose control system are presented, including the development of multivariable models and control systems to more accurately describe and control the multi-metabolite, multi-hormonal system, as well as in-vivo assessments of implicit closed-loop control systems.
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paper_title: Hypoglycaemia: The limiting factor in the glycaemic management of Type I and Type II Diabetes*

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Hypoglycaemia is the limiting factor in the glycaemic management of diabetes. Iatrogenic hypoglycaemia is typically the result of the interplay of insulin excess and compromised glucose counterregulation in Type I (insulin-dependent) diabetes mellitus. Insulin concentrations do not decrease and glucagon and epinephrine concentrations do not increase normally as glucose concentrations decrease. The concept of hypoglycaemia-associated autonomic failure (HAAF) in Type I diabetes posits that recent antecedent iatrogenic hypoglycaemia causes both defective glucose counterregulation (by reducing the epinephrine response in the setting of an absent glucagon response) and hypoglycaemia unawareness (by reducing the autonomic and the resulting neurogenic symptom responses). Perhaps the most compelling support for HAAF is the finding that as little as 2 to 3 weeks of scrupulous avoidance of hypoglycaemia reverses hypoglycaemia unawareness and improves the reduced epinephrine component of defective glucose counterregulation in most affected patients. The mediator and mechanism of HAAF are not known but are under active investigation. The glucagon response to hypoglycaemia is also reduced in patients approaching the insulin deficient end of the spectrum of Type II (non-insulin-dependent) diabetes mellitus, and glycaemic thresholds for autonomic (including epinephrine) and symptomatic responses to hypoglycaemia are shifted to lower plasma glucose concentrations after hypoglycaemia in Type II diabetes. Thus, patients with advanced Type II diabetes are also at risk for HAAF. While it is possible to minimise the risk of hypoglycaemia by reducing risks ‐ including a 2 to 3 week period of scrupulous avoidance of hypoglycaemia in patients with hypoglycaemia unawareness ‐ methods that provide glucose-regulated insulin replacement or secretion are needed to eliminate hypoglycaemia and maintain euglycaemia over a lifetime of diabetes. [Diabetologia (2002) 45:937‐948]
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paper_title: Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose.

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The quantitative contributions of pancreatic responsiveness and insulin sensitivity to glucose tolerance were measured using the "minimal modeling technique" in 18 lean and obese subjects (88-206% ideal body wt). The individual contributions of insulin secretion and action were measured by interpreting the dynamics of plasma glucose and insulin during the intravenous glucose tolerance test in terms of two mathematical models. One, the insulin kinetics model, yields parameters of first-phase (phi 1) and second-phase (phi 2) responsivity of the beta-cells to glucose. The other glucose kinetics model yields the insulin sensitivity parameters, SI. Lean and obese subjects were subdivided into good (KG greater than 1.5) and lower (KG less than 1.5) glucose tolerance groups. The etiology of lower glucose tolerance was entirely different in lean and obese subjects. Lean, lower tolerance was related to pancreatic insufficiency (phi 2 77% lower than in good tolerance controls [P less than 0.03]), but insulin sensitivity was normal (P greater than 0.5). In contrast, obese lower tolerance was entirely due to insulin resistance (SI diminished 60% [P less than 0.01]); pancreatic responsiveness was not different from lean, good tolerance controls (phi 1: P greater than 0.06; phi 2: P greater than 0.40). Subjects (regardless of weight) could be segregated into good and lower tolerance by the product of second-phase beta-cell responsivity and insulin sensitivity (phi 2 . SI). Thus, these two factors were primarily responsible for overall determination of glucose tolerance. The effect of phi 1 was to modulate the KG value within those groups whose overall tolerance was determined by phi 2 . SI. This phi 1 modulating influence was more pronounced among insulin sensitive (phi 1 vs. KG, r = 0.79) than insulin resistant (obese, low tolerance; phi 1 vs. KG, r = 0.91) subjects. This study demonstrates the feasibility of the minimal model technique to determine the etiology of impaired glucose tolerance.
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paper_title: Reduced beta-cell compensation to the insulin resistance associated with obesity in members of caucasian familial type 2 diabetic kindreds.

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OBJECTIVE: Both obesity and a family history of diabetes reduce insulin sensitivity, but the impact of obesity on insulin secretion among individuals predisposed to diabetes is uncertain. We used a pedigree-based approach to test the hypothesis that beta-cell compensation to the insulin resistance associated with obesity is defective among individuals predisposed to diabetes by virtue of a strong family history of type 2 diabetes before the development of diabetes or glucose intolerance. RESEARCH DESIGN AND METHODS: A total of 126 members of 26 families ascertained for at least a sib pair with type 2 diabetes with onset before age 65 years underwent a tolbutamide-modified frequently sampled intravenous glucose tolerance test (FSIGT). Family members included 26 individuals with impaired glucose tolerance and 100 individuals with normal glucose tolerance (NGT). The acute insulin response to glucose (AIRglucose) was determined and insulin sensitivity (S(I)) estimated by minimal model analysis of FSIGT data. The beta-cell compensation for insulin sensitivity was estimated from the disposition index (DI), calculated as the product of S(I) and AIRglucose. Obesity was measured by BMI. RESULTS: Among all individuals, BMI was a significant predictor of both S(I) and AIRglucose, as expected. However, BMI also significantly predicted DI (P = 0.002) after correcting for age, sex, family membership, and glucose tolerance status. The relationship of BMI and DI was confirmed in 85 individuals with NGT who were aged 30), S(I) decreased progressively and significantly with obesity whereas AIRglucose rose significantly from lean to most obese classes. In contrast to the expectation of complete beta-cell compensation with obesity D1 fell significantly (P = 0.004) among obese family members. This relationship was not observed in control subjects. CONCLUSIONS: Individuals with a genetic predisposition to diabetes show a reduced beta-cell compensatory response to the reduced insulin sensitivity associated with obesity. We propose that this impaired compensation may be one manifestation of the underlying genetic defect in susceptible individuals. This finding helps explain the multiplicative effects of family history and obesity on risk of type 2 diabetes.
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paper_title: Continuous Glucose Monitoring and Intensive Treatment of Type 1 Diabetes

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BACKGROUND ::: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. ::: ::: ::: METHODS ::: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. ::: ::: ::: RESULTS ::: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. ::: ::: ::: CONCLUSIONS ::: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)
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paper_title: An overview of pancreatic beta-cell defects in human type 2 diabetes: Implications for treatment

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Type 2 diabetes is the most common form of diabetes in humans. It results from a combination of factors that impair beta-cell function and tissue insulin sensitivity. However, growing evidence is showing that the beta-cell is central to the development and progression of this form of diabetes. Reduced islet and/or insulin-containing cell mass or volume in Type 2 diabetes has been reported by several authors. Furthermore, studies with isolated Type 2 diabetic islets have consistently shown both quantitative and qualitative defects of glucose-stimulated insulin secretion. The impact of genotype in affecting beta-cell function and survival is a very fast growing field or research, and several gene polymorphisms have been associated with this form of diabetes. Among acquired factors, glucotoxicity, lipotoxicity and altered IAPP processing are likely to play an important role. Interestingly, however, pharmacological intervention can improve several defects of Type 2 diabetes islet cells in vitro, suggesting that progression of the disease might not be relentless.
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paper_title: The hot IVGTT two-compartment minimal model: indexes of glucose effectiveness and insulin sensitivity

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A two-compartment minimal model (2CMM) has been proposed [A. Caumo and C. Cobelli. Am. J. Physiol. 264 ( Endocrinol. Metab. 27): E829–E841, 1993] to describe intravenous glucose tolerance test (IVGTT) labeled (hereafter hot) glucose kinetics. This model, at variance with the one-compartment minimal model (1CMM), allows the estimation of a plausible profile of glucose production. The aim of this study is to show that the 2CMM also allows the assessment of insulin sensitivity (![Formula][1] ), glucose effectiveness (![Formula][2] ), and plasma clearance rate (PCR). The 2CMM was identified on stable-isotope IVGTTs performed in normal subjects ( n = 14). Results were (means ± SE) ![Formula][3] = 0.85 ± 0.14 ml ⋅ kg−1 ⋅ min−1, PCR = 2.02 ± 0.14 ml ⋅ kg−1 ⋅ min−1, and ![Formula][4] = 13.83 ± 2.54 × 10−2ml ⋅ kg−1 ⋅ min−1 ⋅ μU−1 ⋅ ml. The 1CMM was also identified; glucose effectiveness and insulin sensitivity indexes were ![Formula][5] V = 1.36 ± 0.08 ml ⋅ kg−1 ⋅ min−1and ![Formula][6] V = 12.98 ± 2.21 × 10−2ml ⋅ kg−1 ⋅ min−1 ⋅ μU−1 ⋅ ml, respectively, where V is the 1CMM glucose distribution volume.![Formula][7] V was lower than PCR and higher than ![Formula][8] and did not correlate with either [ r = 0.45 (NS) and r = 0.50 (NS), respectively], whereas ![Formula][9] V was not different from and was correlated with![Formula][10] ( r = 0.95; P compares well ( r = 0.78; P < 0.001) with PCR normalized by the 2CMM total glucose distribution volume. In conclusion, the 2CMM is a powerful tool to assess glucose metabolism in vivo. ::: ::: [1]: /embed/mml-math-1.gif ::: [2]: /embed/mml-math-2.gif ::: [3]: /embed/mml-math-3.gif ::: [4]: /embed/mml-math-4.gif ::: [5]: /embed/mml-math-5.gif ::: [6]: /embed/mml-math-6.gif ::: [7]: /embed/mml-math-7.gif ::: [8]: /embed/mml-math-8.gif ::: [9]: /embed/mml-math-9.gif ::: [10]: /embed/mml-math-10.gif ::: [11]: /embed/mml-math-11.gif
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paper_title: Coefficients of normal blood glucose regulation.

paper_content:

A previously formulated glucose-insulin feed-back theory was simplified with appropriate assumptions for the purpose of determining which physiological sensitivity coefficients dominate the mathematical characteristics of the normal insulin and glucose tolerance curves. It was found from experimental data that these physiological coefficients approximate the well-known critical damping criteria of servomechanism theory. Correlations between theoretical and experimental results were made with some particular solutions of the necessary differential equations, obtained with the aid of an electronic analogue computer. Using a distribution volume of 17.5 liters for the 70-kg adult in three different methods of approach, it was found that the average coefficients of the insulin and glucose responses of the liver, pancreas, and peripheral tissues are approximately ⍺ = 0.780 unit/hr/unit, β = 0.208 unit/hr/g, γ = 4.34 g/hr/unit, and δ = 2.92 g/hr/g. ::: ::: Submitted on December 27, 1960
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paper_title: A Mathematical Model for the Glucose Induced Insulin Release in Man

paper_content:

Abstract. The dynamics of the insulin response to intravenously administered glucose were studied in man. It was shown that (a) insulin response to prolonged stimulation is biphasic; (b) if the glucose stimulus is repeated with short intervals, inhibition of the second response occurs; (c) if longer time-intervals are used, enhancement of the response is noted at the second stimulation. These findings suggest that when the pancreatic islets are exposed to hyperglycaemia, three, kinetically distinct phenomena are initiated. Glucose induces almost instantaneous initiation of insulin release. Shortly thereafter, the pancreas enters a refractory phase. Thirdly, and at a later stage, a state of potentiation is built up in the islets. The effect of glucose on insulin synthesis is not considered here.–Against this background, and based on an earlier model, a mathematical model for the analysis of the glucose-insulin interplay during glucose infusions was constructed. The model describes the eventual occurrence of glucosuria, changes in the concentration of glucose in its pool, and mimics the effects of regulatory hormones when hypoglycemia appears. Insulin secretion is assumed to be con trolled, in a multiplicative manner, by an immediate glucose function, a hypothetical potentiator that is slowly generated by glucose, and a negative factor with a shorter time-course which corresponds to the refractory phase of the pancreas. A three compartment model is used in the simulation of the metabolism and distribution of insulin after its release. Finally, glucose utilization is described as a multiplicative function, related to the prevailing concentrations of glucose in blood and insulin in the extracellular space.–This model is able to simulate all the experimental situations described in this report, both in normal man and in the diabetic syndrome, in which insulin secretion shows varying degrees of impairment. The results of the simulation of individual experiments are given either as a set of theoretical parameter values, or described as the insulin response of the model to a standard, hypothetical glucose stimulus. The latter alternative is an attractive method for objectively evaluating the insulin response to a standard glucose load in clinical materials.
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paper_title: PID controller tuning for the first-order-plus-dead-time process model via Hermite-Biehler theorem.

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This paper discusses PID stabilization of a first-order-plus-dead-time (FOPDT) process model using the stability framework of the Hermite-Biehler theorem. The FOPDT model approximates many processes in the chemical and petroleum industries. Using a PID controller and first-order Padé approximation for the transport delay, the Hermite-Biehler theorem allows one to analytically study the stability of the closed-loop system. We derive necessary and sufficient conditions for stability and develop an algorithm for selection of stabilizing feedback gains. The results are given in terms of stability bounds that are functions of plant parameters. Sensitivity and disturbance rejection characteristics of the proposed PID controller are studied. The results are compared with established tuning methods such as Ziegler-Nichols, Cohen-Coon, and internal model control.
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paper_title: Modelingβ-Cell Insulin Secretion - Implications for Closed-Loop Glucose Homeostasis

paper_content:

Glucose sensing and insulin delivery technology can potentially be linked to form a closed-loop insulin delivery system. Ideally, such a system would establish normal physiologic glucose profiles. To this end, a model of β-cell secretion can potentially provide insight into the preferred structure of the insulin delivery algorithm. Two secretion models were evaluated for their ability to describe plasma insulin dynamics during hyperglycemic clamps (humans; n = 7), and for their ability to establish and maintain fasting euglycemia under conditions simulated by the minimal model. The first β-cell model (SD) characterized insulin secretion as a static component that had a delayed response to glucose, and a dynamic component that responded to the rate of increase of glucose. The second model (PID) described the response in terms of a proportional component without delay, an integral component that adjusted basal delivery in proportion to hyper/hypoglycemia, and a derivative component that responded to the rat...
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paper_title: Cascade control strategy for external carbon dosage in predenitrifying process

paper_content:

We propose a cascade control strategy composed of two Proportional-Integral (PI) controllers to regulate the nitrate concentration in the predenitrifying process by manipulating the external carbon dosage. It controls the nitrate concentrations in the effluent as well as in the final anoxic reactor simultaneously to strictly satisfy the quality of the effluent as well as to remove the effects of disturbances more quickly. The design of two PI controllers in the cascade control loop can be completed with the Ziegler–Nichols (Z–N) tuning rule together with a simple relay feedback identification method. Results from the Benchmark simulation confirm that both good set point tracking and satisfactory disturbance rejection can be guaranteed due to the structural advantages of the proposed cascade control strategy. Also, compared with a previous work, the fluctuation of the nitrate concentration in the effluent has been decreased significantly.
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paper_title: Continuous Glucose Monitoring and Intensive Treatment of Type 1 Diabetes

paper_content:

BACKGROUND ::: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. ::: ::: ::: METHODS ::: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. ::: ::: ::: RESULTS ::: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. ::: ::: ::: CONCLUSIONS ::: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)
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paper_title: Process Control in Municipal Solid Waste Incinerators: Survey and Assessment

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As there is only rare and scattered published information about the process control in industrial incineration facilities for municipal solid waste (MSW), a survey of the literature has been supplemented by a number of waste incineration site visits in Belgium and the Netherlands, in order to make a realistic assessment of the current status of technology in the area. Owing to the commercial character, and therefore, the confidentiality restrictions imposed by plant builders and many of the operators, much of the information collected has either to be presented in a generalized manner, and in any case anonymously. The survey was focused on four major issues: process control strategy, process control systems, monitors used for process control and finally the correlation between the 850°C/2 s rule in the European waste incineration directive and integrated process control. The process control strategies range from reaching good and stable emissions at the stack to stabilizing and maximizing the energy outpu...
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paper_title: Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes

paper_content:

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L−1 per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.
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paper_title: Blood Glucose Control by a Model Predictive Control Algorithm with Variable Sampling Rate Versus a Routine Glucose Management Protocol in Cardiac Surgery Patients: A Randomized Controlled Trial

paper_content:

Context: Elevated blood glucose levels occur frequently in the critically ill. Tight glucose control by intensive insulin treatment markedly improves clinical outcome. Objective and Design: This is a randomized controlled trial comparing blood glucose control by a laptop-based model predictive control algorithm with a variable sampling rate [enhanced model predictive control (eMPC); version 1.04.03] against a routine glucose management protocol (RMP) during the peri- and postoperative periods. Setting: The study was performed at the Department of Cardiac Surgery, University Hospital. Patients: A total of 60 elective cardiac surgery patients were included in the study. Interventions: Elective cardiac surgery and treatment with continuous insulin infusion (eMPC) or continuous insulin infusion combined with iv insulin boluses (RMP) to maintain euglycemia (target range 4.4–6.1 mmol/liter) were performed. There were 30 patients randomized for eMPC and 30 for RMP treatment. Blood glucose was measured in 1- to 4...
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paper_title: Closing the Loop: The Adicol Experience

paper_content:

The objective of the project Advanced Insulin Infusion using a Control Loop (ADICOL) was to develop a treatment system that continuously measures and controls the glucose concentration in subjects with type 1 diabetes. The modular concept of the ADICOL's extracorporeal artificial pancreas consisted of a minimally invasive subcutaneous glucose system, a handheld PocketPC computer, and an insulin pump (D-Tron, Disetronic, Burgdorf, Switzerland) delivering subcutaneously insulin lispro. The present paper describes a subset of ADICOL activities focusing on the development of a glucose controller for semi-closed-loop control, an in silico testing environment, clinical testing, and system integration. An incremental approach was adopted to evaluate experimentally a model predictive glucose controller. A feasibility study was followed by efficacy studies of increasing complexity. The ADICOL project demonstrated feasibility of a semi-closed-loop glucose control during fasting and fed conditions with a wearable, m...
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paper_title: Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes

paper_content:

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L−1 per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.
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paper_title: Blood Glucose Control by a Model Predictive Control Algorithm with Variable Sampling Rate Versus a Routine Glucose Management Protocol in Cardiac Surgery Patients: A Randomized Controlled Trial

paper_content:

Context: Elevated blood glucose levels occur frequently in the critically ill. Tight glucose control by intensive insulin treatment markedly improves clinical outcome. Objective and Design: This is a randomized controlled trial comparing blood glucose control by a laptop-based model predictive control algorithm with a variable sampling rate [enhanced model predictive control (eMPC); version 1.04.03] against a routine glucose management protocol (RMP) during the peri- and postoperative periods. Setting: The study was performed at the Department of Cardiac Surgery, University Hospital. Patients: A total of 60 elective cardiac surgery patients were included in the study. Interventions: Elective cardiac surgery and treatment with continuous insulin infusion (eMPC) or continuous insulin infusion combined with iv insulin boluses (RMP) to maintain euglycemia (target range 4.4–6.1 mmol/liter) were performed. There were 30 patients randomized for eMPC and 30 for RMP treatment. Blood glucose was measured in 1- to 4...
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paper_title: Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients

paper_content:

OBJECTIVE ::: Tight glycaemic control (TGC) in critically ill patients improves clinical outcome, but is difficult to establish The primary objective of the present study was to compare glucose control in medical ICU patients applying a computer-based enhanced model predictive control algorithm (eMPC) extended to include time-variant sampling against an implemented glucose management protocol. ::: ::: ::: DESIGN ::: Open randomised controlled trial. ::: ::: ::: SETTING ::: Nine-bed medical intensive care unit (ICU) in a tertiary teaching hospital. ::: ::: ::: PATIENTS AND PARTICIPANTS ::: Fifty mechanically ventilated medical ICU patients. ::: ::: ::: INTERVENTIONS ::: Patients were included for a study period of up to 72 h. Patients were randomised to the control group (n = 25), treated by an implemented insulin algorithm, or to the eMPC group (n = 25), using the laptop-based algorithm. Target range for blood glucose (BG) was 4.4-6.1 mM. Efficacy was assessed by mean BG, hyperglycaemic index (HGI) and BG sampling interval. Safety was assessed by the number of hypoglycaemic-episodes < 2.2 mM. Each participating nurse filled-in a questionnaire regarding the usability of the algorithm. ::: ::: ::: MEASUREMENTS AND MAIN RESULTS ::: BG and HGI were significantly lower in the eMPC group [BG 5.9 mM (5.5-6.3), median (IQR); HGI 0.4 mM (0.2-0.9)] than in control patients [BG 7.4 mM (6.9-8.6), p < 0.001; HGI 1.6 mM (1.1-2.4), p < 0.001]. One hypoglycaemic episode was detected in the eMPC group; no such episodes in the control group. Sampling interval was significantly shorter in the eMPC group [eMPC 117[Symbol: see text]min (+/- 34), mean (+/- SD), vs 174 min (+/- 27); p < 0.001]. Thirty-four nurses filled-in the questionnaire. Thirty answered the question of whether the algorithm could be applied in daily routine in the affirmative. ::: ::: ::: CONCLUSIONS ::: The eMPC algorithm was effective in maintaining tight glycaemic control in severely ill medical ICU patients.
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paper_title: Blood Glucose Control by a Model Predictive Control Algorithm with Variable Sampling Rate Versus a Routine Glucose Management Protocol in Cardiac Surgery Patients: A Randomized Controlled Trial

paper_content:

Context: Elevated blood glucose levels occur frequently in the critically ill. Tight glucose control by intensive insulin treatment markedly improves clinical outcome. Objective and Design: This is a randomized controlled trial comparing blood glucose control by a laptop-based model predictive control algorithm with a variable sampling rate [enhanced model predictive control (eMPC); version 1.04.03] against a routine glucose management protocol (RMP) during the peri- and postoperative periods. Setting: The study was performed at the Department of Cardiac Surgery, University Hospital. Patients: A total of 60 elective cardiac surgery patients were included in the study. Interventions: Elective cardiac surgery and treatment with continuous insulin infusion (eMPC) or continuous insulin infusion combined with iv insulin boluses (RMP) to maintain euglycemia (target range 4.4–6.1 mmol/liter) were performed. There were 30 patients randomized for eMPC and 30 for RMP treatment. Blood glucose was measured in 1- to 4...
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paper_title: Model Predictive Control of Type 1 Diabetes: An in Silico Trial

paper_content:

BACKGROUND ::: The development of artificial pancreas has received a new impulse from recent technological advancements in subcutaneous continuous glucose monitoring and subcutaneous insulin pump delivery systems. However, the availability of innovative sensors and actuators, although essential, does not guarantee optimal glycemic regulation. Closed-loop control of blood glucose levels still poses technological challenges to the automatic control expert, most notable of which are the inevitable time delays between glucose sensing and insulin actuation. ::: ::: ::: METHODS ::: A new in silico model is exploited for both design and validation of a linear model predictive control (MPC) glucose control system. The starting point is a recently developed meal glucose-insulin model in health, which is modified to describe the metabolic dynamics of a person with type 1 diabetes mellitus. The population distribution of the model parameters originally obtained in healthy 204 patients is modified to describe diabetic patients. Individual models of virtual patients are extracted from this distribution. A discrete-time MPC is designed for all the virtual patients from a unique input-output-linearized approximation of the full model based on the average population values of the parameters. The in silico trial simulates 4 consecutive days, during which the patient receives breakfast, lunch, and dinner each day. ::: ::: ::: RESULTS ::: Provided that the regulator undergoes some individual tuning, satisfactory results are obtained even if the control design relies solely on the average patient model. Only the weight on the glucose concentration error needs to be tuned in a quite straightforward and intuitive way. The ability of the MPC to take advantage of meal announcement information is demonstrated. Imperfect knowledge of the amount of ingested glucose causes only marginal deterioration of performance. In general, MPC results in better regulation than proportional integral derivative, limiting significantly the oscillation of glucose levels. ::: ::: ::: CONCLUSIONS ::: The proposed in silico trial shows the potential of MPC for artificial pancreas design. The main features are a capability to consider meal announcement information, delay compensation, and simplicity of tuning and implementation.
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paper_title: An implantable subcutaneous glucose sensor array in ketosis-prone rats: closed loop glycemic control.

paper_content:

A closed loop system of diabetes control would minimize hyperglycemia and hypoglycemia. We therefore implanted and tested a subcutaneous amperometric glucose sensor array in alloxan-diabetic rats. Each array employed four sensing units, the outputs of which were processed in real time to yield a unified signal. We utilized a gain-scheduled insulin control algorithm which rapidly reduced insulin delivery as glucose concentration declined. Such a system was generally effective in controlling glycemia and the degree of lag between blood glucose and the sensor signal was usually 3-8 min. After prolonged implantation, this lag was sometimes longer, which led to impairment of sensor accuracy. Using a prospective two-point calibration method, sensor accuracy and closed loop control were good. A revised algorithm yielded better glycemic control than the initial algorithm did. Future research needs to further improve calibration methods and reduce foreign body fibrosis in order to avoid a time-related increase in lag duration.
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paper_title: The Benefit of Subcutaneous Glucagon During Closed-Loop Glycemic Control in Rats With Type 1 Diabetes

paper_content:

Because of its prolonged action, subcutaneously administered insulin has a potential for overcorrection hypoglycemia during closed-loop glucose control. For this reason, we hypothesized that subcutaneous glucagon, whose action is faster, could lessen the risk for hypoglycemia during closed-loop control. We therefore compared insulin alone versus insulin plus glucagon in diabetic rats in a controlled closed-loop study. Both hormones were delivered by algorithms based on proportional error, derivative error, and the glucose history. Based on this algorithm, glucagon was delivered when glucose was declining and approaching a hypoglycemic level. The delivery of glucagon was largely reciprocal with the delivery of insulin. With the addition of glucagon, there was less hypoglycemia at the glucose nadir, less hyperglycemia later in the study, and lower absolute error values during these periods. We also found that for 7 days after glucagon reconstitution, commercially available glucagon retained its original ability to quickly raise glucose level. We conclude that when subcutaneous insulin delivery is accompanied by subcutaneous glucagon, glycemic control during closed-loop treatment is improved. Since its action is faster than that of insulin, glucagon may prove useful during closed-loop diabetes control.
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paper_title: Pharmacodynamics And Stability of Subcutaneously Infused Glucagon in A Type 1 Diabetic Swine Model In Vivo

paper_content:

Background: The objective of this study was to determine the in vivo pharmacodynamics of glucagon and to test its glycemic effect over days by assessing its time course of activity and potency in a...
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paper_title: Diminished B cell secretory capacity in patients with noninsulin-dependent diabetes mellitus.

paper_content:

In order to assess whether patients with noninsulin-dependent diabetes mellitus (NIDDM) possess normal insulin secretory capacity, maximal B cell responsiveness to the potentiating effects of glucose was estimated in eight untreated patients with NIDDM and in eight nondiabetic controls. The acute insulin response to 5 g intravenous arginine was measured at five matched plasma glucose levels that ranged from approximately 100-615 mg/dl. The upper asymptote approached by acute insulin responses (AIRmax) and the plasma glucose concentration at half-maximal responsiveness (PG50) were estimated using nonlinear regression to fit a modification of the Michaelis-Menten equation. In addition, glucagon responses to arginine were measured at these same glucose levels to compare maximal A cell suppression by hyperglycemia in diabetics and controls. Insulin responses to arginine were lower in diabetics than in controls at all matched glucose levels (P less than 0.001 at all levels). In addition, estimated AIRmax was much lower in diabetics than in controls (83 +/- 21 vs. 450 +/- 93 microU/ml, P less than 0.01). In contrast, PG50 was similar in diabetics and controls (234 +/- 28 vs. 197 +/- 20 mg/dl, P equals NS) and insulin responses in both groups approached or attained maxima at a glucose level of approximately 460 mg/dl. Acute glucagon responses to arginine in patients with NIDDM were significantly higher than responses in controls at all glucose levels. In addition, although glucagon responses in control subjects reached a minimum at a glucose level of approximately 460 mg/dl, responses in diabetics declined continuously throughout the glucose range and did not reach a minimum. Thus, A cell sensitivity to changes in glucose level may be diminished in patients with NIDDM. In summary, patients with NIDDM possess markedly decreased maximal insulin responsiveness to the potentiating effects of glucose. Such a defect indicates the presence of a reduced B cell secretory capacity and suggests a marked generalized impairment of B cell function in patients with NIDDM.
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paper_title: Autonomic mechanism and defects in the glucagon response to insulin-induced hypoglycaemia.

paper_content:

In summary, this article briefly reviews the evidence that three separate autonomic inputs to the islet are capable of stimulating glucagon secretion and that each is activated during IIH. We have reviewed our evidence that these autonomic inputs mediate the glucagon response to IIH, both in non-diabetic animals and humans. Finally, we outline our new preliminary data suggesting an eSIN in an autoimmune animal model of T1DM. We conclude that the glucagon response to IIH is autonomically mediated in non-diabetic animals and humans. We further suggest that at least one of these autonomic inputs, the sympathetic innervation of the islet, is diminished in autoimmune T1DM. These data raise the novel possibility that an autonomic defect contributes to the loss of the glucagon response to IIH in T1DM.
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paper_title: A Novel Insulin Delivery Algorithm in Rats With Type 1 Diabetes: The Fading Memory Proportional-Derivative Method

paper_content:

An algorithm designed to automatically control insulin delivery was tested in rats with Type 1 diabetes. This nonlinear algorithm included a fading memory component of proportional and derivative errors in order to simulate normal insulin secretion. Error-weighting functions for the proportional and derivative terms were used with a performance index designed for error adaptation. In the first version of the algorithm, the proportional gain was adaptively varied. In the second version, a low rate of basal insulin delivery was adaptively varied. Six 6-h studies with each version were conducted using frequent blood sampling and intravenous insulin delivery. In Version 2 studies, blood glucose levels during the last two hours were well-controlled and significantly lower than in Version 1 (118 +/- 2.0 vs. 130 +/- 2.9 mg/dL). Neither version produced hypoglycemia. Future research using this algorithm needs to focus on automated glucose sensing in combination with insulin delivery.
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paper_title: Fuzzy-Based Controller for Glucose Regulation in Type-1 Diabetic Patients by Subcutaneous Route

paper_content:

This paper presents an advisory/control algorithm for a type-1 diabetes mellitus (TIDM) patient under an intensive insulin treatment based on a multiple daily injections regimen (MDIR). The advisory/control algorithm incorporates expert knowledge about the treatment of this disease by using Mamdani-type fuzzy logic controllers to regulate the blood glucose level (BGL). The overall control strategy is based on a two-loop feedback strategy to overcome the variability in the glucose-insulin dynamics from patient to patient. An inner-loop provides the amount of both rapid/short and intermediate/long acting insulin (RSAI and ILAI) formulations that are programmed in a three-shots daily basis before meals. The combined preparation is then injected by the patient through a subcutaneous route. Meanwhile, an outer-loop adjusts the maximum amounts of insulin provided to the patient in a time-scale of days. The outer-loop controller aims to work as a supervisor of the inner-loop controller. Extensive closed-loop simulations are illustrated, using a detailed compartmental model of the insulin-glucose dynamics in a TIDM patient with meal intake
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paper_title: Neural network modeling and control of type 1 diabetes mellitus.

paper_content:

This paper presents a developed and validated dynamic simulation model of type 1 diabetes, that simulates the progression of the disease and the two term controller that is responsible for the insulin released to stabilize the glucose level. The modeling and simulation of type 1 diabetes mellitus is based on an artificial neural network approach. The methodology builds upon an existing rich database on the progression of type 1 diabetes for a group of diabetic patients. The model was found to perform well at estimating the next glucose level over time without control. A neural controller that mimics the pancreas secretion of insulin into the body was also developed. This controller is of the two term type: one stage is responsible for short-term and the other for mid-term insulin delivery. It was found that the controller designed predicts an adequate amount of insulin that should be delivered into the body to obtain a normalization of the elevated glucose level. This helps to achieve the main objective of insulin therapy: to obtain an accurate estimate of the amount of insulin to be delivered in order to compensate for the increase in glucose concentration.
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paper_title: Fuzzy filter for state estimation of a glucoregulatory system.

paper_content:

A filter based on fuzzy logic for state estimation of a glucoregulatory system is presented. A published non-linear model for the dynamics of glucose and its hormonal control including a single glucose compartment, five insulin compartments and a glucagon compartment was used for simulation. The simulated data were corrupted by an additive white noise with zero mean and a coefficient of variation (CV) of between 2 and 20% and then submitted to the state estimation procedure using a fuzzy filter (FF). The performance of the FF was compared with an extended Kalman filter (EKF) for state estimation. Both the FF and the EKF were evaluated in the following cases: (a) five state variables are measurable; three plasma variables are measurable; only plasma glucose is measurable; (b) for different measurement noise levels (CV of 2-20%); and (c) a mismatch between the glucoregulatory system and the given mathematical model (uncertain or approximate model). In contrast to the FF, in the case of approximate model of the glucose system, the EKF failed to achieve useful state estimation. Moreover, the performance of the FF was independent of the noise level. In conclusion, the FF approach is a viable alternative for state estimation in a noisy environment and with an uncertain mathematical model of the glucoregulatory system.
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paper_title: A robust controller for insulin pumps based on H-infinity theory

paper_content:

The feedback control of insulin pumps for diabetic patients is discussed. Because the parameters in the mathematical model of the blood glucose dynamics present a considerable amount of uncertainty, the H- infinity framework is well suited for the design of controllers that take into account a nice compromise between robust closed-loop regulation of a constant set point and performance expressed in terms of peak values of the plasma glucose concentration. >
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Title: A Review of Closed-Loop Algorithms for Glycemic Control in the Treatment of Type 1 Diabetes

Section 1: Introduction
Description 1: Introduce the significance of insulin in diabetes management, challenges in treating Type 1 diabetes, and the concept of closed-loop glycemic control.

Section 2: History of Closed Loop Systems
Description 2: Detail the historical development of closed-loop systems, components involved, and significant advancements in glucose sensing and insulin delivery technology.

Section 3: Proportional-Integral-Derivative (PID) Algorithms
Description 3: Explain the fundamentals and application of PID algorithms in closed-loop glycemic control, including successful implementations and inherent challenges.

Section 4: Model Predictive Control Algorithms
Description 4: Describe the principles of Model Predictive Control (MPC) algorithms and their application in managing insulin delivery for tight glycemic control.

Section 5: Fading Memory Proportional Derivative Algorithm
Description 5: Introduce the Fading Memory Proportional Derivative (FMPD) algorithm, its components, and its advantages over traditional PID approaches in diabetes management.

Section 6: Other Algorithms
Description 6: Review additional closed-loop control algorithms such as H-infinity loops, fuzzy logic systems, and neural networks, with their respective advantages and application in glycemic control.