Abstract: The present disclosure relates to techniques for receiving glucose data from a continuous glucose sensor and controlling the use and redistribution of that data so it is used in an intended manner. In one aspect, a system includes a plurality of continuous glucose monitor (CGM) devices; a plurality of display devices to receive data from the CGM devices classified into a plurality of classifications based on data type; a cloud server architecture to receive the data from the display devices on an intermittent basis, in which the data routed to a particular server of the plurality of servers is determined by the data type, and in which the intermittent basis varies depending upon data type; a plurality of remote monitor display devices; and an analysis and report engine.

Abstract: Systems and methods for analyte monitoring, particularly systems and methods for monitoring and managing life of a battery in an analyte sensor system worn by a user, are provided.

Abstract: Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration level. The glucose concentration level may be provided to a stored model to determine a state. The guidance may be determined based at least in part on the determined state.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In this regard, in embodiments, a mobile includes a transceiver configured to transmit and receive wireless signals. The mobile device includes circuitry operatively coupled to the transceiver. The mobile device also includes a non-transitory computer-readable medium operatively coupled to the circuitry and storing instructions that, when executed, cause the mobile device to perform a number of operations. One such operation is to obtain a derivative of a first signal received via a first link. Another such operation is to obtain a derivative of a second signal received via a second link; and. Yet another such operation is to generate a selection for connection to an analyte sensor system, based on a comparison of the derivative of the first signal and the derivative of the second signal.

Abstract: The present disclosure relates to techniques for receiving glucose data from a continuous glucose sensor and controlling the use and redistribution of that data so it is used in an intended manner. In one aspect, a system includes a plurality of continuous glucose monitor (CGM) devices; a plurality of display devices to receive data from the CGM devices classified into a plurality of classifications based on data type; a cloud server architecture to receive the data from the display devices on an intermittent basis, in which the data routed to a particular server of the plurality of servers is determined by the data type, and in which the intermittent basis varies depending upon data type; a plurality of remote monitor display devices; and an analysis and report engine.

Abstract: 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.

Abstract: Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration data sensed by a glucose concentration sensor. A host state change associated with the host glucose concentration data may be determined. A guidance message based at least in part on the host state change may also be determined. The guidance message may be delivered through a user interface.

Abstract: Systems and methods for detecting and reporting patterns in analyte concentration data are provided. According to some implementations, an implantable device for continuous measurement of an analyte concentration is disclosed. The implantable device includes a sensor configured to generate a signal indicative of a concentration of an analyte in a host, a memory configured to store data corresponding at least one of the generated signal and user information, a processor configured to receive data from at least one of the memory and the sensor, wherein the processor is configured to generate pattern data based on the received information, and an output module configured to output the generated pattern data. The pattern data can be based on detecting frequency and severity of analyte data in clinically risky ranges.

Abstract: Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

Abstract: Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

Abstract: Systems and methods for providing sensitive and specific alarms indicative of glycemic condition are provided herein. In an embodiment, a method of processing sensor data by a continuous analyte sensor includes: evaluating sensor data using a first function to determine whether a real time glucose value meets a first threshold; evaluating sensor data using a second function to determine whether a predicted glucose value meets a second threshold; activating a hypoglycemic indicator if either the first threshold is met or if the second threshold is predicted to be met; and providing an output based on the activated hypoglycemic indicator.

Abstract: Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user’s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

Abstract: Systems and methods for analyte monitoring, particularly systems and methods for monitoring and managing life of a battery in an analyte sensor system worn by a user, are provided.

Abstract: Systems and methods for providing sensitive and specific alarms indicative of glycemic condition are provided herein. In an embodiment, a method of processing sensor data by a continuous analyte sensor includes: evaluating sensor data using a first function to determine whether a real time glucose value meets a first threshold; evaluating sensor data using a second function to determine whether a predicted glucose value meets a second threshold; activating a hypoglycemic indicator if either the first threshold is met or if the second threshold is predicted to be met; and providing an output based on the activated hypoglycemic indicator.

Abstract: Disclosed are systems and methods for secure and seamless set up and modification of bolus calculator parameters for a bolus calculator tool by a health care provider (HCP). In one aspect, a method for enabling HCP set up of a bolus calculator includes providing a server accessible by both an HCP and a patient; upon login by the HCP, displaying, or transmitting for display, a fillable form, the fillable form including one or more fields for entry of one or more bolus calculator parameters; receiving data from the fillable form, the data corresponding to one or more bolus calculator parameters; and upon login by the patient, transmitting data to a device associated with the patient, the transmitted data based on the received data, where the transmitted data corresponds to one or more of the bolus calculator parameters in a format suitable for entry to a bolus calculator.

Abstract: Methods and apparatus, including computer program products, are provided for processing analyte data. In some example implementations, a method may include generating glucose sensor data indicative of a host's glucose concentration using a glucose sensor; calculating a glycemic variability index (GVI) value based on the glucose sensor data; and providing output to a user responsive to the calculated glycemic variability index value. The GVI may be a ratio of a length of a line representative of the sensor data and an ideal length of the line. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: Systems and methods are described that provide a dynamic reporting functionality that can identify important information and dynamically present a report about the important information that highlights important findings to the user. The described systems and methods are generally described in the field of diabetes management, but are applicable to other medical reports as well. In one implementation, the dynamic reports are based on available data and devices. For example, useless sections of the report, such as those with no populated data, may be removed, minimized in importance, assigned a lower priority, or the like.

Abstract: Systems and methods for detecting and reporting patterns in analyte concentration data are provided. According to some implementations, an implantable device for continuous measurement of an analyte concentration is disclosed. The implantable device includes a sensor configured to generate a signal indicative of a concentration of an analyte in a host, a memory configured to store data corresponding at least one of the generated signal and user information, a processor configured to receive data from at least one of the memory and the sensor, wherein the processor is configured to generate pattern data based on the received information, and an output module configured to output the generated pattern data. The pattern data can be based on detecting frequency and severity of analyte data in clinically risky ranges.

Abstract: Systems and methods for dynamically and intelligently estimating analyte data from a continuous analyte sensor, including receiving a data stream, selecting one of a plurality of algorithms, and employing the selected algorithm to estimate analyte values. Additional data processing includes evaluating the selected estimative algorithms, analyzing a variation of the estimated analyte values based on statistical, clinical, or physiological parameters, comparing the estimated analyte values with corresponding measure analyte values, and providing output to a user. Estimation can be used to compensate for time lag, match sensor data with corresponding reference data, warn of upcoming clinical risk, replace erroneous sensor data signals, and provide more timely analyte information encourage proactive behavior and preempt clinical risk.

Abstract: Devices and methods are provided for continuous measurement of an analyte concentration. The device can include a sensor having a plurality of sensor elements, each having at least one characteristic that is different from other sensor(s) of the device. In some embodiments, the plurality of sensor elements are each tuned to measure a different range of analyte concentration, thereby providing the device with the capability of achieving a substantially consistent level of measurement accuracy across a physiologically relevant range. In other embodiments, the device includes a plurality of sensor elements each tuned to measure during different time periods after insertion or implantation, thereby providing the sensor with the capability to continuously and accurately measure analyte concentrations across a wide range of time periods.