Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.

Abstract: Systems and methods for continuous measurement of an analyte in a host are provided. The system generally includes a continuous analyte sensor configured to continuously measure a concentration of analyte in a host and a sensor electronics module physically connected to the continuous analyte sensor during sensor use, wherein the sensor electronics module is further configured to directly wirelessly communicate displayable sensor information to a plurality of different types of display devices.

Abstract: Systems and methods for applying time-dependent algorithmic compensation functions to data output from a continuous analyte sensor. Some embodiments determine a time since sensor implantation and/or whether a newly initialized sensor has been used previously.

Abstract: The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.

Abstract: The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.

Abstract: The present disclosure relates to systems, devices and methods for receiving biosensor data acquired by a medical device, e.g., relating to glucose concentration values, and controlling the access and distribution of that data. In some embodiments, systems and methods are disclosed for monitoring glucose levels, displaying data relating to glucose values and metabolic health information, and controlling distribution of glucose data between applications executing on a computer, such as a smart phone. In some embodiments, systems and methods are disclosed for controlling access to medical data such as continuously monitored glucose levels, synchronizing health data relating to glucose levels between multiple applications executing on a computer, and/or encrypting data.

Abstract: The present invention relates generally to systems and methods for processing, transmitting, and displaying data received from continuous analyte sensor, such as a glucose sensor. In some embodiments, the continuous analyte sensor system comprises a sensor electronics module that includes power saving features. One feature includes a low power measurement circuit that can be switched between a measurement mode and a low power mode, in which charging circuitry continues to apply power to electrodes of a sensor during the low power mode. In addition, the sensor electronics module can be switched between in a low power storage mode higher power operational mode via a switch. The switch can include a reed switch or optical switch, for example. A validation routine can also be implemented to ensure an interrupt signal sent from the switch is valid.

Abstract: The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.

Abstract: Various examples are directed to systems and methods for generating a bolus dose for a host. A bolus application may display a first bolus configuration parameter question at a user interface and receive, through the user interface, a first answer to the first bolus configuration parameter question. The first answer may describe a previous bolus determination technique of the host. The bolus application may select a second bolus configuration parameter question using the first answer and provide the second bolus configuration parameter question at the user interface. The bolus application may determine a set of at least one bolus configuration parameter using the first answer and a second answer to the second bolus configuration parameter question.

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: Systems and methods for processing sensor analyte data are disclosed, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. The sensor can be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. Reference data resulting from benchtop testing an analyte sensor prior to its insertion can be used to provide initial calibration of the sensor data. Reference data from a short term continuous analyte sensor implanted in a user can be used to initially calibrate or update sensor data from a long term continuous analyte sensor.

Abstract: The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.

Abstract: 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.

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: 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: 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: The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.