scholarly journals Closed-Loop Artificial Pancreas Using Subcutaneous Glucose Sensing and Insulin Delivery and a Model Predictive Control Algorithm: The Virginia Experience

2009 ◽  
Vol 3 (5) ◽  
pp. 1031-1038 ◽  
Author(s):  
William L. Clarke ◽  
Stacey Anderson ◽  
Marc Breton ◽  
Stephen Patek ◽  
Laurissa Kashmer ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Predictive Control ◽  
Insulin Infusion ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Open Loop ◽  
Closed Loop Control ◽  
Open Loop Control ◽  
Loop Control

Background: Recent progress in the development of clinically accurate continuous glucose monitors (CGMs), automated continuous insulin infusion pumps, and control algorithms for calculating insulin doses from CGM data have enabled the development of prototypes of subcutaneous closed-loop systems for controlling blood glucose (BG) levels in type 1 diabetes. The use of a new personalized model predictive control (MPC) algorithm to determine insulin doses to achieve and maintain BG levels between 70 and 140 mg/dl overnight and to control postprandial BG levels is presented. Methods: Eight adults with type 1 diabetes were studied twice, once using their personal open-loop systems to control BG overnight and for 4 h following a standardized meal and once using a closed-loop system that utilizes the MPC algorithm to control BG overnight and for 4 h following a standardized meal. Average BG levels, percentage of time within BG target of 70–140 mg/dl, number of hypoglycemia episodes, and postprandial BG excursions during both study periods were compared. Results: With closed-loop control, once BG levels achieved the target range (70–140 mg/dl), they remained within that range throughout the night in seven of the eight subjects. One subject developed a BG level of 65 mg/dl, which was signaled by the CGM trend analysis, and the MPC algorithm directed the discontinuance of the insulin infusion. The number of overnight hypoglycemic events was significantly reduced ( p = .011) with closed-loop control. Postprandial BG excursions were similar during closed-loop and open-loop control Conclusion: Model predictive closed-loop control of BG levels can be achieved overnight and following a standardized breakfast meal. This “artificial pancreas” controls BG levels as effectively as patient-directed open-loop control following a morning meal but is significantly superior to open-loop control in preventing overnight hypoglycemia.

scholarly journals Closed-loop control with unannounced exercise for adults with type 1 diabetes using the Ensemble Model Predictive Control

2019 ◽  
Vol 80 ◽  
pp. 202-210 ◽  
Author(s):  
Jose Garcia-Tirado ◽  
John P. Corbett ◽  
Dimitri Boiroux ◽  
John Bagterp Jørgensen ◽  
Marc D. Breton
Keyword(s):  
Type 1 Diabetes ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Ensemble Model ◽  
Loop Control

scholarly journals Closed-Loop Artificial Pancreas Using Subcutaneous Glucose Sensing and Insulin Delivery and a Model Predictive Control Algorithm: Preliminary Studies in Padova and Montpellier

2009 ◽  
Vol 3 (5) ◽  
pp. 1014-1021 ◽  
Author(s):  
Daniela Bruttomesso ◽  
Anne Farret ◽  
Silvana Costa ◽  
Maria Cristina Marescotti ◽  
Monica Vettore ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Insulin Delivery ◽  
Glucose Sensing ◽  
Open Loop ◽  
Closed Loop Control ◽  
Loop Control

New effort has been made to develop closed-loop glucose control, using subcutaneous (SC) glucose sensing and continuous subcutaneous insulin infusion (CSII) from a pump, and a control algorithm. An approach based on a model predictive control (MPC) algorithm has been utilized during closed-loop control in type 1 diabetes patients. Here we describe the preliminary clinical experience with this approach. In Padova, two out of three subjects showed better performance with the closed-loop system compared to open loop. Altogether, mean overnight plasma glucose (PG) levels were 134 versus 111 mg/dl during open loop versus closed loop, respectively. The percentage of time spent at PG > 140 mg/dl was 45% versus 12%, while postbreakfast mean PG was 165 versus 156 mg/dl during open loop versus closed loop, respectively. Also, in Montpellier, two patients out of three showed a better glucose control during closed-loop trials. Avoidance of nocturnal hypoglycemic excursions was a clear benefit during algorithm-guided insulin delivery in all cases. This preliminary set of studies demonstrates that closed-loop control based entirely on SC glucose sensing and insulin delivery is feasible and can be applied to improve glucose control in patients with type 1 diabetes, although the algorithm needs to be further improved to achieve better glycemic control. Six type 1 diabetes patients (three in each of two clinical investigation centers in Padova and Montpellier), using CSII, aged 36 ± 8 and 48 ± 6 years, duration of diabetes 12 ± 8 and 29 ± 4 years, hemoglobin A1c 7.4% ± 0.1% and 7.3% ± 0.3%, body mass index 23.2 ± 0.3 and 28.4 ± 2.2 kg/m2, respectively, were studied on two occasions during 22 h overnight hospital admissions 2–4 weeks apart. A Freestyle Navigator® continuous glucose monitor and an OmniPod® insulin pump were applied in each trial. Admission 1 used open-loop control, while admission 2 employed closed-loop control using our MPC algorithm.

scholarly journals Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

2019 ◽  
Vol 40 (6) ◽  
pp. 1521-1546 ◽  
Author(s):  
Rayhan A Lal ◽  
Laya Ekhlaspour ◽  
Korey Hood ◽  
Bruce Buckingham
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Control ◽  
Closed Loop ◽  
Diabetes Management ◽  
Artificial Pancreas ◽  
Loop System ◽  
Closed Loop Control ◽  
Closed Loop System ◽  
Loop Control

Abstract Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an “artificial pancreas” that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

scholarly journals Closed-Loop Control During Intense Prolonged Outdoor Exercise in Adolescents With Type 1 Diabetes: The Artificial Pancreas Ski Study

Diabetes Care ◽  
2017 ◽  
Vol 40 (12) ◽  
pp. 1644-1650 ◽  
Author(s):  
Marc D. Breton ◽  
Daniel R. Cherñavvsky ◽  
Gregory P. Forlenza ◽  
Mark D. DeBoer ◽  
Jessica Robic ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Closed Loop Control ◽  
Loop Control

Insulin Dosage Optimization Based on Model Predictive Control with the Model Parameters Estimation

2014 ◽  
Vol 971-973 ◽  
pp. 1222-1229
Author(s):  
Sha Sha Zhang ◽  
Ming Zhong ◽  
Ya Xin Liu
Keyword(s):  
Type 1 Diabetes ◽  
Predictive Control ◽  
Glucose Concentration ◽  
Closed Loop ◽  
Control Method ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Closed Loop Control ◽  
Loop Control

Diabetes is a disease characterized by the inability of the pancreas to regulate blood glucose concentration. The development of the closed-loop control method for the treatment of type 1 diabetes is a highly desired endeavor for patients, physicians and scientists. Focusing on the need for maintaining normal glycaemia, the paper proposes an integrated closed-loop control method, which is the model predictive control (MPC) method combined with model parameters estimation. Using the static glucose model to be the internal model can’t achieve the good performance in different objects because of the individual differences. By updating the internal controller model with current measurement information using the parameters estimation, mismatch between the actual controlled object and the internal controller model is significantly reduced. Therefore, the predictions of future glucose values using the updated model are more accurate than those of the static input–output model. Finally, the integrated control method was tested on the T1DM simulator which was accepted by the FDA. Four objects are selected randomly in T1DM simulator. The control results showed it can modulate the glucose concentration to 85~120 mg/dl without severe hypoglycemia in the effective time. In conclusion, it is promising for the control of glucose concentration in subjects with type 1 diabetes.

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