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® 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.

Disclosed herein are method for controlling an insulin injection pump, a related control unit, and an injection pump. The control unit comprises an expected plasma insulin concentration value acquiring module, a current subcutaneous and interstitial insulin concentration value acquiring module, a supposed injection value acquiring module, an injection instruction sending module, and a counting module. The injection pump comprises a pump body and the control unit. The control unit is disposed in the pump body.

Pre-connected analyte sensors are provided. A pre-connected analyte sensor includes a sensor carrier attached to an analyte sensor. The sensor carrier includes a substrate configured for mechanical coupling of the sensor to testing, calibration, or wearable equipment. The sensor carrier also includes conductive contacts for electrically coupling sensor electrodes to the testing, calibration, or wearable equipment.

Pre-connected analyte sensors are provided. A pre-connected analyte sensor includes a sensor carrier attached to an analyte sensor. The sensor carrier includes a substrate configured for mechanical coupling of the sensor to testing, calibration, or wearable equipment. The sensor carrier also includes conductive contacts for electrically coupling sensor electrodes to the testing, calibration, or wearable equipment.

Systems and methods of use for continuous analyte measurement of a host's vascular system are provided. In some embodiments, a continuous glucose measurement system includes a vascular access device, a sensor and sensor electronics, the system being configured for insertion into communication with a host's circulatory system.

A method of managing insulin includes receiving blood glucose measurements on a computing device from a glucometer. The blood glucose measurements are separated by a time interval. The method includes determining, by the computing device, an insulin dose rate based on the blood glucose measurements and determining a blood glucose drop rate based on the blood glucose measurements and the time interval. The method also includes determining a blood glucose percentage drop based on the blood glucose measurements. The method includes decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose drop rate is greater than a threshold drop rate, and decreasing the time interval between blood glucose measurements by the glucometer when the blood glucose percentage drop is greater than a threshold percentage drop.

Systems and methods for processing sensor data and self-calibration are provided. In some embodiments, systems and methods are provided which are capable of calibrating a continuous analyte sensor based on an initial sensitivity, and then continuously performing self-calibration without using, or with reduced use of, reference measurements. In certain embodiments, a sensitivity of the analyte sensor is determined by applying an estimative algorithm that is a function of certain parameters. Also described herein are systems and methods for determining a property of an analyte sensor using a stimulus signal. The sensor property can be used to compensate sensor data for sensitivity drift, or determine another property associated with the sensor, such as temperature, sensor membrane damage, moisture ingress in sensor electronics, and scaling factors.

Methods and systems for delaying alarms that include detecting an analyte level using an analyte sensor; and delaying the annunciation of an analyte alarm after the analyte level crosses an analyte threshold, wherein the delay is based on one or both of (1) a magnitude of difference between the analyte level and the analyte threshold and (2) a duration of time in which the analyte level has crossed the analyte threshold.

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® 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.

The invention relates to a control device for controlling the administration of propofol to a patient according to the preamble of claim 1 and to a method for controlling the administration of propofol to a patient according to the preamble of claim 4. With a method of this kind a bispectral index (BIS) target value is set which shall be, at least approximately, reached within a patient. A controller then computes a recommended infusion rate of propofol based on the target BIS value and further based on a measured propofol level of the patient for administering propofol to the patient. The controller herein comprises a model unit for computing the recommended infusion rate such that, using the model unit for determining the propofol sensitivity of a patient by means of a mathematical model taking into account the bispectral index (BIS) value and optionally the measured propofol level as input variables, the recommended infusion rate for administering propofol to the patient to achieve the BIS target value may be determined.