Abbott Diabetes Care Inc.

Cambridge Enterprise Limited

Malgorzata E Wilinska

Gary Alan Hayter

Erwin Satrya Budiman

Marc Barry Taub

Roman Hovorka

David B Dunger

A closed-loop system for insulin infusion overnight uses a model predictive control algorithm ('MPC'). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator&#xae; Continuous Glucose Monitor System ('FSN'). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

Integrated closed-loop medication delivery with error model and safety check

A system and method for reducing the number of hypoglycemic alarms presented to a user is presented. The system and methods include use of model based state estimation and variable-delayed threshold values to balance the risk of not presenting an alarm caused by an actual hypoglycemic state with the presentation of alarms caused by artifacts in the signals produced by a continuous glucose monitor.

Methods for reducing false hypoglycemia alarm occurrence

A closed-loop method for insulin infusion overnight uses a model predictive control algorithm ('MPC'). Used with the MPC is a glucose measurement error model which was derived from actual glucose sensor error data. That sensor error data included both a sensor artifacts component, including dropouts, and a persistent error component, including calibration error, all of which was obtained experimentally from living subjects. The MPC algorithm advised on insulin infusion every fifteen minutes. Sensor glucose input to the MPC was obtained by combining model-calculated, noise-free interstitial glucose with experimentally-derived transient and persistent sensor artifacts associated with the FreeStyle Navigator&#xae; Continuous Glucose Monitor System ('FSN'). The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simulated overnight closed-loop control with the MPC algorithm using the glucose measurement error model suggesting that the continuous glucose monitoring technologies facilitate safe closed-loop insulin delivery.

Method of overnight closed-loop insulin delivery with model predictive control and glucose measurement error model

Overnight closed-loop insulin delivery with model predictive control and glucose measurement error model

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Cambridge, United Kingdom

Malgorzata E Wilinska