Prediction of meal and/or exercise events based on persistent residuals

    公开(公告)号:US12036389B2

    公开(公告)日:2024-07-16

    申请号:US17142425

    申请日:2021-01-06

    CPC classification number: A61M5/1723 A61M5/14244 A61M2205/52 A61M2230/201

    Abstract: Exemplary embodiments provide an approach to predicting meal and/or exercise events for an insulin delivery system that otherwise does not otherwise identify such events. The insulin delivery system may use a model of glucose insulin interactions that projects estimated future glucose values based on a history of glucose values and insulin deliveries for a user. The predictions of meal events and/or exercise events may be based on residuals between actual glucose values and predicted glucose values. The exemplary embodiments may calculate a rate of change of the residuals over a period of time and compare the rate of change to thresholds to determine whether there likely has been a meal event or an exercise event. The insulin delivery system may then take measures to account for the meal event or the exercise event by the user.

    Compensation for missing readings from a glucose monitor in an automated insulin delivery system

    公开(公告)号:US12226612B2

    公开(公告)日:2025-02-18

    申请号:US17715589

    申请日:2022-04-07

    Abstract: Exemplary embodiments may address the problem of missing blood glucose concentration readings from a glucose monitor that transmits blood glucose concentration readings over a wireless connection due to problems with the wireless connection. In the exemplary embodiments, an automated insulin delivery (AID) device uses an estimate in place of a missing blood glucose concentration reading in determining a predicted future blood glucose concentration reading for a user. Thus, the AID device is able to operate normally in generating insulin delivery settings despite not receiving a current blood glucose concentration reading for a current cycle. There is no need to suspend delivery of insulin to the user due to the missing blood glucose concentration reading.

    Activity mode for artificial pancreas system

    公开(公告)号:US11628251B2

    公开(公告)日:2023-04-18

    申请号:US16586440

    申请日:2019-09-27

    Abstract: A wearable drug delivery device, techniques, and computer-readable media that provide an application that implements a diabetes treatment plan for a user are described. The drug delivery device may include a controller operable to direct operation of the wearable drug delivery device. The controller may provide a selectable activity mode of operation for the user. Operation of the drug delivery device in the activity mode of operation may reduce a likelihood of hypoglycemia during times of increased insulin sensitivity for the user and may reduce a likelihood of hyperglycemia during times of increased insulin requirements for the user. The activity mode of operation may be manually activated by the user or may be activated automatically by the controller. The controller may automatically activate the activity mode of operation based on a detected activity level of the user and/or a detected location of the user.

    User parameter dependent cost function for personalized reduction of hypoglycemia and/or hyperglycemia in a closed loop artificial pancreas system

    公开(公告)号:US11547800B2

    公开(公告)日:2023-01-10

    申请号:US16789051

    申请日:2020-02-12

    Abstract: Exemplary embodiments described herein relate to a closed loop artificial pancreas system. The artificial pancreas system seeks to automatically and continuously control the blood glucose level of a user by emulating the endocrine functionality of a healthy pancreas. The artificial pancreas system uses a closed loop control system with a cost function. The penalty function helps to bound the infusion rate of insulin to attempt to avoid hypoglycemia and hyperglycemia. However, unlike conventional systems that use a generic or baseline parameter for a user's insulin needs in a cost function, the exemplary embodiments may use a customized parameter in the cost function that reflects the individualized insulin needs of the user. The use of the customized parameter causes the cost function to result in insulin dosages over time better suited to the individualized insulin needs of the user. This helps to better avoid hypoglycemia and hyperglycemia.

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