GLUCOSE ALERT PREDICTION HORIZON MODIFICATION

    公开(公告)号:US20220061774A1

    公开(公告)日:2022-03-03

    申请号:US17464452

    申请日:2021-09-01

    Applicant: DexCom, Inc.

    Abstract: Data describing glucose measurements is received from a continuous glucose monitoring (CGM) system worn by a user and predicted glucose values during a future time period are generated for the user based on the data. A determination is made that at least one of the predicted glucose values satisfies a threshold value for an alert, which is associated with a prediction horizon that defines an amount of time prior to satisfaction of the threshold value for communicating the alert to the user. Output of the alert is caused responsive to determining that the at least one predicted glucose value satisfies the threshold value for the alert within the prediction horizon, relative to a current time. The prediction horizon is modified based on a user response to the alert. Output of a subsequent instance of the alert is caused based on the modified prediction horizon.

    Glycemic Impact Prediction For Improving Diabetes Management

    公开(公告)号:US20230136188A1

    公开(公告)日:2023-05-04

    申请号:US17974296

    申请日:2022-10-26

    Applicant: Dexcom, Inc.

    Abstract: Glucose level measurements and additional data regarding a user are obtained over time, such as from a wearable glucose monitoring device being worn by the user. This additional data identifies events or conditions that may affect glucose of the user, such as physical activity engaged in by the user. A glucose prediction system analyzes, for example, activity data of the user and determines when a bout of physical activity occurs. The glucose prediction system predicts what the glucose measurements of the user would have been had the physical activity not occurred, and takes various actions based on the predicted glucose measurements (e.g., provides feedback to the user indicating what their glucose would have been had they not engaged in the physical activity).

    Behavior Modification Feedback For Improving Diabetes Management

    公开(公告)号:US20230140143A1

    公开(公告)日:2023-05-04

    申请号:US17974290

    申请日:2022-10-26

    Applicant: Dexcom, Inc.

    Abstract: Glucose measurements are received and features for corresponding time periods over a time window are generated, the features being values indicating whether the user has been engaging in beneficial diabetes management behaviors. Using the aggregated features patterns indicating that beneficial diabetes management behaviors are not being engaged in are identified. Potential behavior modification feedback is generated by including in the potential behavior modification feedback at least one behavior modification feedback, for each of the identified patterns, that a user could take to engage in beneficial diabetes management behavior. At least one of the potential behavior modification feedback is selected and displayed or otherwise presented to the user.

    Detection of anomalous computing environment behavior using glucose

    公开(公告)号:US12002591B2

    公开(公告)日:2024-06-04

    申请号:US17455277

    申请日:2021-11-17

    Applicant: DexCom, Inc.

    Abstract: Detection of anomalous computing environment behavior using glucose is described. An anomaly detection system receives glucose measurements and event records during a first time period. Missing events that are missing from the event records during the first time period are identified by processing the glucose measurements using an event engine simulator. An anomaly detection model is generated based on the missing events during the first time period. Subsequently, the anomaly detection system receives additional glucose measurements and additional event records during a second time period. Missing events that are missing from the additional event records during the second time period are identified by processing the additional glucose measurements using the event engine simulator. Anomalous behavior is detected if the identified missing events that are missing from the event records during the second time period are outside a predicted range of missing events of the anomaly detection model.

    Glucose alert prediction horizon modification

    公开(公告)号:US11969267B2

    公开(公告)日:2024-04-30

    申请号:US17464447

    申请日:2021-09-01

    Applicant: DexCom, Inc.

    Abstract: Data describing glucose measurements is received from a continuous glucose monitoring (CGM) system worn by a user and predicted glucose values during a future time period are generated for the user based on the data. A determination is made that at least one of the predicted glucose values satisfies a threshold value for an alert, which is associated with a prediction horizon that defines an amount of time prior to satisfaction of the threshold value for communicating the alert to the user. Output of the alert is caused responsive to determining that the at least one predicted glucose value satisfies the threshold value for the alert within the prediction horizon, relative to a current time. The prediction horizon is modified based on a user response to the alert. Output of a subsequent instance of the alert is caused based on the modified prediction horizon.

    DETECTION OF ANOMALOUS COMPUTING ENVIRONMENT BEHAVIOR USING GLUCOSE

    公开(公告)号:US20220165432A1

    公开(公告)日:2022-05-26

    申请号:US17455277

    申请日:2021-11-17

    Applicant: DexCom, Inc.

    Abstract: Detection of anomalous computing environment behavior using glucose is described. An anomaly detection system receives glucose measurements and event records during a first time period. Missing events that are missing from the event records during the first time period are identified by processing the glucose measurements using an event engine simulator. An anomaly detection model is generated based on the missing events during the first time period. Subsequently, the anomaly detection system receives additional glucose measurements and additional event records during a second time period. Missing events that are missing from the additional event records during the second time period are identified by processing the additional glucose measurements using the event engine simulator. Anomalous behavior is detected if the identified missing events that are missing from the event records during the second time period are outside a predicted range of missing events of the anomaly detection model.

    Ranking Feedback For Improving Diabetes Management

    公开(公告)号:US20230138673A1

    公开(公告)日:2023-05-04

    申请号:US17974299

    申请日:2022-10-26

    Applicant: DexCom, Inc.

    Abstract: Feedback regarding diabetes management by a user is generated, such as feedback identifying improvements in glucose measurements for a given time period over previous days, feedback identifying sustained positive patterns, feedback identifying deviations in glucose measurements between time periods, feedback identifying potential behavior modification that a user could take to engage in beneficial diabetes management behavior, feedback identifying what a user's glucose would have been had the particular events or conditions not occurred or not been present, and so forth. A feedback presentation system analyzes the identified feedback and selects feedback based on various rankings, rules and conditions for display to the user. The selected feedback is provided to the user at various times, such as regular reports (e.g., daily or weekly reports), in real time (e.g., notifying the user what his glucose level would have been had he not just taken a walk), and so forth.

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