Abstract: Exemplary embodiments may provide an on-body medicament delivery system that provides basal delivery of a medicament to a type 2 diabetes patient and that automatically performs medicament titration for the patient. The medicament delivery system performs medicament titration based on glucose level readings for the patient. These glucose levels may be provided wirelessly from a glucose sensor, such as a continuous glucose monitor, or may be entered manually by the patient into a management device, such as a smartphone running an application that provides a user interface for the patient to enter the glucose level readings. The medicament delivery system adjusts the basal medicament delivery rate/dose based on the glucose level readings for the patient. The adjustments may be performed by a programmatic mechanism, such as by computer programming instructions executing on a processor.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide an updated insulin-to-carbohydrate ratio and an updated total daily insulin. The described processes may be used for periodic updating of the insulin-to-carbohydrate ratio and the total daily insulin. The insulin-to-carbohydrate ratio and/or the total may be used in the calculation of new doses of insulin that a drug delivery device may be commanded to deliver to a user.

Abstract: Disclosed are techniques, devices and systems that provide adjustments to parameter settings of an insulin delivery algorithm based on inputs from a number of generic sensor devices. A majority of the generic sensor devices provide sensor readings that are unused as inputs to a drug deliver algorithm. The generic sensor devices may be operable to detect characteristics, such as changes in a state of a user. A processor may evaluate a sensor reading provided by a particular sensor with respect to a sensor baseline reading for the particular sensor. Using the result of the evaluation, the processor may calculate an adjustment to a parameter setting or settings of a medication delivery algorithm. A dosage of medication may be modified based on the adjustment of the parameter setting or settings.

Abstract: Disclosed are a device, a computer-readable medium, and techniques that provide an onboarding process and an adaptivity process for a drug delivery device. A processor executing an onboarding process determines whether a history of delivered insulin to a user meets certain sufficiency requirements. The onboarding process enables a processor to cause the drug delivery device to administer doses of insulin to a user according to an initial total daily insulin dose calculation that is determined based on the sufficiency of the insulin delivery history. The initial total daily insulin may be adapted according to the adaptivity process as new insulin delivery is collected. The insulin delivery history, when sufficient, may be used to set total daily insulin dosages that enable automated insulin delivery upon replacement of a drug delivery device. The adaptivity process may be implemented to modify an initial insulin delivery doses to provide adapted insulin delivery doses.

Abstract: Embodiments of this application provide a method and an apparatus for determining radio channel multipath information and a related device. A server obtains reference signal received powers of a plurality of downlink beams, and determines a path angle and path strength of a propagation path from an antenna in a power angular spectrum cell indicated by each power angular spectrum cell identity to a grid indicated by each grid identity, based on an association relationship between the reference signal received powers of the plurality of downlink beams and the following: a grid identity, a serving cell identity, and a power angular spectrum cell. The server can determine the radio channel multipath information based on the reference signal received powers of the plurality of downlink beams, instead of depending on map and engineering parameter information. This helps improve accuracy of the radio channel multipath information.

Abstract: Safety and accuracy measures may be provided in a medicament delivery device. The medicament delivery device may be able to identify the inadvertent delivery of duplicate medicament boluses by a user. The exemplary embodiments may set limits for maximum allowable medicament bolus doses and maximum cumulative bolus doses over an interval. The exemplary embodiments may provide automatic meal detection and may use detection of meals in determining whether a user-requested medicament bolus dose should be adjusted or rejected. The exemplary embodiments may facilitate delivery of partial boluses and the delivery of remainders of the boluses contingent on acceptable glucose level trends of the user. The exemplary embodiments may resolve potential conflicts among multiple medicament delivery devices via a broker or by providing a single actor, such as a medicament delivery controller, that has sole control of dosing and delivery of medicament boluses.

Abstract: Disclosed are techniques, devices and systems that modify an insulin delivery schedule based on how sensitive a diabetic user may to fluctuations in their total daily insulin or fluctuations in their blood glucose measurement values. As a control algorithm calculates how to adapt the calculation of the user's total daily insulin, a rate of adaptivity function may be used in the calculation. The rate of adaptivity may depend on a number of factors and the disclosed techniques, devices and systems enable calculation of the rate of adaptivity to provide effective implementation or modification of a diabetic treatment plan.

Abstract: Exemplary embodiments may apply a transform or filter to analyte level values of the users to make the analyte level values conform with a normal distribution that is symmetric relative to the mean. The transformed or filtered analyte level values may be used by the control system of a medicament delivery device in determining medicament delivery doses. In some embodiments, the medicament is insulin, and the analyte level is a glucose level of a user. In such instances, a logarithmic filter or transform may be applied to the glucose level readings of the user.

Abstract: Disclosed are techniques to establish initial settings for an automatic insulin delivery device. An adjusted total daily insulin (TDI) factor usable to calculate a TDI dosage may be determined. The adjusted TDI factor may be a TDI per unit of a physical characteristic of the user (e.g., weight) times a reduction factor. The adjusted TDI factor may be compared to a maximum algorithm delivery threshold. Based on the comparison result, the application or algorithm may set a TDI dosage and output a control signal. Blood glucose measurement values may be collected from a sensor over a period of time. A level of glycated hemoglobin of the blood may be determined based on the obtained blood glucose measurement values. In response to the level of glycated hemoglobin, the set TDI dosage may be modified. A subsequent control signal including the modified TDI dosage may be output to actuate delivery of insulin.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide techniques to implement functionality to receive blood glucose measurements over a period of time. An average of missing blood glucose measurement values may be maintained over a predetermined time period. A count of a number of missing blood glucose measurement values over a period of time may be established. A controller may calculate a divergence of the number of missing blood glucose measurement values over the period of time from the average of missing blood glucose measurements over the predetermined time period. Based on a value of the divergence, a determination that a safety constraint for delivery of insulin is to be reduced. The safety constraint may be reduced by a predetermined percentage. An instruction to deliver an insulin dosage may be generated according to the reduced safety constraint may be forwarded to a wearable drug delivery device.

Abstract: The exemplary embodiments provide medicament delivery devices that use cost functions in their control systems to determine medicament dosages. The cost function may have a medicament cost component and a performance cost component. The exemplary embodiments may use cost functions having medicament cost components that scale asymmetrically for different ranges of inputs (i.e., different candidate medicament dosages). The variance in scaling for different input ranges provides added flexibility to tailor the medicament cost component to the user and thus provide better management of medicament delivery to the user and better conformance to a performance target. The exemplary embodiments may use a cost function that has a medicament cost component (such as an insulin cost component) of zero for candidate dosages for a range of candidate dosages (e.g., below a reference dosage).

Abstract: Disclosed are a system, methods and computer-readable medium products that provide safety constraints for an insulin-delivery management program. Various examples provide safety constraints for a control algorithm-based drug delivery system that provides automatic delivery of a drug based on sensor input. Glucose measurement values may be received at regular time intervals from a sensor. A processor may predict future glucose values based on prior glucose measurement values. The safety constraints assist in safe operation of the drug delivery system during various operational scenarios. In some examples, predicted future glucose values may be used to implement safety constraints that mitigate under-delivery or over-delivery of the drug while not overly burdening the user of the drug delivery system and without sacrificing performance of the drug delivery system. Other safety constraints are also disclosed.

Abstract: Exemplary embodiments may determine anticipated basal insulin delivery action to a user from an insulin delivery device over a future time window. Indications of the anticipated basal insulin delivery action over the future time window may be output to the user. The exemplary embodiments may determine the anticipated basal insulin delivery action over the future time window based on a rate of change (ROC) of glucose level of the user by the insulin delivery device, a most recent (“current”) glucose level for the user and insulin on board (IOB) for the user. The exemplary embodiments may also determine whether the user is likely to experience a undesired high glucose level (e.g., hyperglycemia) and/or an undesired low glucose level (e.g., hypoglycemia) during the future time window. The exemplary embodiments may output recommendations based on the projected glucose levels of the user over the future time window.

Abstract: Disclosed are a system, methods and computer-readable medium products that provide bolus dosage calculations by a control algorithm-based drug delivery system that provides automatic delivery of a drug, such as insulin or the like, based on sensor input. Blood glucose measurement values may be received at regular time intervals from a sensor. Using the blood glucose measurements, the control algorithm may perform various calculations and determinations to provide an appropriate bolus dosage. The appropriate bolus dosage may be used to respond to a trend in a trajectory of blood glucose measurements. In addition, a bolus dosage may also be determined by the disclosed device, system, method and/or computer-readable medium product in response to an indication that a user consumed a meal.

Abstract: Exemplary embodiments may provide for the switching of glucose prediction models responsive to certain conditions. For example, glucose prediction models may be switched responsive to a detected crashing glucose level condition. Exemplary embodiments also may dynamically customize parameters, such as coefficient values, of the glucose prediction model to a user. The exemplary embodiments may customize the glucose prediction model based on the history of glucose levels of the user and the history of insulin deliveries to the user. The exemplary embodiments may determine a set of parameters that provides an improved fit of the parameters to the history of glucose levels and insulin deliveries of the user. The improved fit parameters may be used to adapt the parameter set to the most recent run.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide techniques to implement functionality to receive blood glucose measurements over a period of time. An average of missing blood glucose measurement values may be maintained over a predetermined time period. A count of a number of missing blood glucose measurement values over a period of time may be established. A controller may calculate a divergence of the number of missing blood glucose measurement values over the period of time from the average of missing blood glucose measurements over the predetermined time period. Based on a value of the divergence, a determination that a safety constraint for delivery of insulin is to be reduced. The safety constraint may be reduced by a predetermined percentage. An instruction to deliver an insulin dosage may be generated according to the reduced safety constraint may be forwarded to a wearable drug delivery device.

Abstract: Disclosed are techniques, devices and systems that obtain a glucose measurement history and a liquid drug delivery history. An expected drug delivery amount may be calculated based on the obtained glucose measurement history and the obtained liquid drug delivery history. A processor may calculate a plurality of respective drug delivery amounts implemented using different advisory mode algorithms. A respective advisory drug delivery amount of the plurality of respective advisory drug delivery amounts may be selected by the processor. A recommendation may be generated based on the selected respective advisory drug delivery amount.

Abstract: The exemplary embodiments may dynamically adjust an Insulin on Board (JOB) profile for a user of a medicament delivery system to customize the IOB profile to the user based on recent glucose level history and insulin deliveries rather than use the conventional static IOB profiles that are based on population averages. The exemplary embodiments may calculate a Duration of Insulin Action (DIA) for a user from the customized insulin decay curves. The exemplary embodiments may generate and send notifications to the user to help reduce the DIA of the user and/or to keep the DIA of the user from rising. The exemplary embodiments may aim to not overly constrain insulin delivery due to the contribution of insulin boluses to JOB.

Abstract: The exemplary embodiments may employ a glucose prediction model (GPM) that is tailored to a user to account for insulin sensitivity or insulin insensitivity. The exemplary embodiments may predict future glucose levels based on past glucose levels for the user. Specifically, the GPM in exemplary embodiments may predict the future glucose level of the user as a weighted sum of most recent glucose level readings from the user. The exemplary embodiments may employ linear regression analysis to determine the values of the weights. These weights customize the GPM of the user based on the user's most recent glucose level history. Due to the customization, the GPM may more accurately predict future glucose levels of the user. As a result, the AID may exhibit better glucose level control for the user. The GPM of the exemplary embodiments may be updated on an ongoing basis.

Abstract: Disclosed are techniques and devices that are operable to receive one or a number of generalized parameters of an automated insulin delivery algorithm. An input of at least one generalized parameter corresponding to a user may be used to set one or more of the number of specific parameters of the automated insulin delivery algorithm based on the inputted at least one generalized parameter. Physiological condition data related to the user may be collected. The automated insulin delivery algorithm may determine a dosage of insulin to be delivered based on the collected physiological condition. Signals may be output to cause a liquid drug to be delivered to the user based on an output of the automated insulin delivery algorithm related to the determined dosage of insulin.