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.

An integrated diabetes management (IDM) system includes a safety layer which, in one configuration has two components, one located between a glucose sensor and a controller and a second component located between a controller and a pump, to monitor various aspects of signals and modify those signals for compatibility and safety purposes. In one application, the safety layer receives output control signals from a controller and modifies those control signals as a function of an actual amount of insulin delivered to the user. The safety layer allows for an increased level of safety in the IDM system and permits development of separate hardware and software upgrades with the safety layer assuring that compatibility between components will continue.

Systems and methods for integrating a continuous glucose sensor 12, including a receiver 14, a medicament delivery device 16, a controller module, and optionally a single point glucose monitor 18 are provided. Integration may be manual, semi-automated and/or fully automated.

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.

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.

Safety features are applied to an integrated insulin delivery system to enhance safety by controlling medication delivery including the automatic resumption of basal rate after a particular event, such as termination of a bolus, expiration of a time period, delayed resumption after the bolus has terminated, IOB comparison, and others. Other safety features include overriding a delivery control that may result in hypoglycemia, and terminating an extended bolus or temporary basal rate in view of a glucose signal indicating imminent carbohydrate deficiency. In another feature, an automatic resumption of a basal delivery rate is programmed into the delivery device to avoid the possibility of complete loss of delivery of insulin in the event that communication with the delivery device is disrupted.

The present invention discloses a monitoring system and method for use in monitoring diabetes treatment of a patient. The system comprises a control unit comprising a first processor module for processing measured data indicative of blood glucose level and generating first processed data indicative thereof, a second processor module comprising at least one fuzzy logic module; the second processor module receives input parameters corresponding to the measured data, the first processed data and a reference data including individualized patient's profile related data, individualized patient's treatment history related data and processes the received data to produce at least one qualitative output parameter indicative of patient's treatment parameters, such that the second processor module determines whether any of the treatment parameters is to be modified.

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.

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.

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.