Abstract: Location-aided glycemic control is described. A glycemic control system obtains sensor data is from one or more sensors, and detects a location of a user based on the sensor data. The glycemic control system predicts an activity that the user will perform at the location based on the location of the user, and generates a recommendation to control a glycemic response of the user to the predicted activity. In one or more implementations the glycemic control system causes display of the recommendation to control the glycemic response of the user. In one or more implementations the recommendation corresponds to administering an amount of a medicament to the user to control the glycemic response to the predicted activity, and the glycemic control system communicates instructions to a medicament delivery system which causes the medicament delivery system to administer the amount of the medicament to the user.

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: Sleeves and cases for protecting medical devices against contamination, and methods for cleaning and disinfecting medical devices are provided. The various embodiments enable a single medical device to be used by more than one patient successively while reducing the risk of disease transmission from patient to patient.

Abstract: Devices are provided for measurement of an analyte concentration, e.g., glucose in a host. The device can include a sensor configured to generate a signal associated with a concentration of an analyte; and a sensing membrane located over the sensor. The sensing membrane comprises a diffusion resistance domain configured to control a flux of the analyte therethrough. The diffusion resistance domain comprises one or more zwitterionic compounds and a base polymer comprising both hydrophilic and hydrophobic regions.

Abstract: An analyte sensor system is provided. The system includes a base configured to attach to a skin of a host. The base includes an analyte sensor configured to generate a sensor signal indicative of an analyte concentration level of the host, a battery, and a first plurality of contacts. The system includes a sensor electronics module configured to releasably couple to the base. The sensor electronics module includes a second plurality of contacts, each configured to make electrical contact with a respective one of the first plurality of contacts, and a wireless transceiver configured to transmit a wireless signal based at least in part on the sensor signal. The system includes a first sealing member configured to provide a seal around the first and second plurality of contacts within a first cavity. Related analyte sensor systems, analyte sensor base assemblies and methods are also provided.

Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: Sensor devices including dissolvable tissue-piercing tips are provided. The sensor devices can be used in conjunction with dissolvable needles configured for inserting the sensor devices into a host. Hardening agents for strengthening membranes on sensor devices are also provided. Methods of using and fabricating sensor devices are also provided.

Abstract: A sensor cable support device is described. The sensor cable support device can be used to implemented in wearable monitoring device to support a proximal portion of a sensor cable and electrically connect the proximal portion with a sensing circuitry. A distal portion of the sensor cable is insertable into a person's skin. The sensor cable support device may include a rigid body defining a pair of openings, a set legs attached to the rigid body, and a pair of electrical traces extending between the pair of openings and distal ends of a pair of legs of the set of legs. The pair of openings may be sized and configured to receive a pair of pucks that mechanically retain a sensor cable to the body and electrically connect the sensor cable with the electrical traces.

Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.

Abstract: Certain aspects of the present disclosure relate to methods and systems for optimized delivery of communications including content to users of a software application. The method also includes obtaining, by a customer engagement platform (CEP), a set of cohort selection criteria for identifying a user cohort to deliver the content; identifying, by a data analytics platform (DAP), the user cohort to communicate with in accordance with the set of cohort selection criteria; identifying, by the DAP, one or more communication configurations for communicating with one or more sub-groups within the user cohort; and to each user of the user cohort, transmitting one or more communications based on the content and a corresponding communication configuration for a sub-group that may include the corresponding user; and measuring engagement outcomes associated with usage of the corresponding one or more communication configurations in communication with each of the sub-groups.

Abstract: Methods, devices and systems are disclosed for inter-app communications between software applications on a mobile communications device. In one aspect, a computer-readable medium on a mobile computing device comprising an inter-application communication data structure to facilitate transitioning and distributing data between software applications in a shared app group for an operating system of the mobile computing device includes a scheme field of the data structure providing a scheme id associated with a target software app to transition to from a source software app, wherein the scheme id is listed on a scheme list stored with the source software app; and a payload field of the data structure providing data and/or an identification where to access data in a shared file system accessible to the software applications in the shared app group, wherein the payload field is encrypted.

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: Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.

Abstract: Adaptive on board estimation of exogenous pharmacon responsive to transient (i.e., impermanent) physiological effects is provided. Dynamically estimating an equivalent amount of an exogenous pharmacon on board (XOB), such as insulin and/or carbohydrates, left in the subject, is based on predictions of glucose time-series data. These estimated values, such as insulin on board (IOB), are useful for diabetes management software, including decision support and/or artificial pancreas (AP) algorithms, for example.

Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.

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

Abstract: Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes receiving a sensor signal from an analyte sensor. A plurality of risk factors associated with end of life symptoms of analyte sensors is evaluated. The risk factors include a downward drift in sensor sensitivity over time, an amount of non-symmetrical, nonstationary noise and a duration of noise. An end of life status of the analyte sensor is determined based at least in part on the evaluating. An output related to the end of life status of the analyte sensor is provided.

Abstract: Systems and methods are provided for identifying therapeutic zones where there is glycemic dysfunction of a specific type that can be addressed by making strategic changes to behavior and/or therapy parameters. Systems and methods described herein evaluate large historical data sets to: identify a therapeutic zone or zones with glycemic dysfunction that are most readily addressable; quantify the glycemic impact of a plurality of different therapeutic adjustments in terms of either adjustments to historical doses or the parameters of a prospective dosing strategy to determine the highest possible improvement; and/or identify patient dosing strategies to provide therapy recommendations adapted for the patient's preferred behavioral dosing strategy.

Abstract: A mathematical model of type 1 diabetes (T1D) patient decision-making can be used to simulate, in silico, realistic glucose/insulin dynamics, for several days, in a variety of subjects who take therapeutic actions (e.g. insulin dosing) driven by either self-monitoring blood glucose (SMBG) or continuous glucose monitoring (CGM). The decision-making (DM) model can simulate real-life situations and everyday patient behaviors. Accurate submodels of SMBG and CGM measurement errors are incorporated in the comprehensive DM model. The DM model accounts for common errors the patients are used to doing in their diabetes management, such as miscalculations of meal carbohydrate content, early/delayed insulin administrations and missed insulin boluses. The DM model can be used to assess in silico if/when CGM can safely substitute SMBG in T1D management, to develop and test guidelines for CGM driven insulin dosing, to optimize and individualize off-line insulin therapies and to develop and test decision support systems.