EXERCISE SAFETY PREDICTION BASED ON PHYSIOLOGICAL CONDITIONS

    公开(公告)号:US20220392603A1

    公开(公告)日:2022-12-08

    申请号:US17834332

    申请日:2022-06-07

    Abstract: Described are techniques, processes, devices, computer-readable media that enable provision of an indication of whether it is safe for a person with diabetes to participate in exercise while using a wearable drug delivery system. A processor may receive or obtain physiological data related to a condition of a wearer of the wearable drug delivery system and by evaluating an exercise model that uses inputs related to the physiological data to make the determination of whether it is safe to exercise and output an exercise safety signal. Modifications to the wearer's medication treatment plan and other actions may be based on an outputted exercise safety signal.

    TECHNIQUES FOR IMPROVED AUTOMATIC DRUG DELIVERY PERFORMANCE USING DELIVERY TENDENCIES FROM PAST DELIVERY HISTORY AND USE PATTERNS

    公开(公告)号:US20210187197A1

    公开(公告)日:2021-06-24

    申请号:US17123378

    申请日:2020-12-16

    Abstract: Disclosed are devices, a system, methods and computer-readable medium products that provide techniques to implement functionality to determine when to softened upper bounds of drug delivery and how much to soften the upper bound. Future blood glucose measurement values may be predicted by calculating deviations between predicted blood glucose measurement values and additional blood glucose measurement values. A gain parameter may be determined for use with a model of predicting a user's blood glucose measurement values and determining future drug dosages. Safety constraints may be determined based on an evaluation of missing blood glucose measurement values. In addition, safety constraints may be determined based on an evaluation of a user's increased interaction with an automatic drug delivery device. A bolus uncertainty metric to determine an amount of insulin to be provided in a bolus dosage in response to a bolus request may be calculated.

    AUTOMATED MEDICAMENT DELIVERY SYSTEM MANAGEMENT WITHOUT ANALYTE MEASUREMENTS

    公开(公告)号:US20250132007A1

    公开(公告)日:2025-04-24

    申请号:US18909496

    申请日:2024-10-08

    Abstract: A medicament delivery system, process and techniques are provided. The medicament delivery system may include a wearable medicament delivery device, a memory storing programming instructions, and a processor. The processor may be operable to execute the programming instructions, which cause the processor to receive an available medicament delivery history of a user, and determine whether the available medicament delivery history spans an extent of time greater than a first glucose history duration. The processor, in response to a determination that the extent of time spanned by the available medicament delivery history is greater than the first glucose history duration, determines an average daily medicament delivered. The processor calculates a trust value of the available medicament delivery history, and utilizes the trust value to determine a total daily medicament value of the user.

    INFORMING A USER OF ANTICIPATED INSULIN DELIVERY ACTIONS AND PROVIDING RECOMMENDED USER ACTIONS

    公开(公告)号:US20240009392A1

    公开(公告)日:2024-01-11

    申请号:US18350223

    申请日:2023-07-11

    CPC classification number: A61M5/1723 A61M5/14244 A61M2202/0486

    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.

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