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    Dropout detection in continuous analyte monitoring data during data excursions
    33.
    发明授权
    Dropout detection in continuous analyte monitoring data during data excursions 有权

    公开(公告)号：US10942164B2

    公开(公告)日：2021-03-09

    申请号：US16850937

    申请日：2020-04-16

    申请人： Abbott Diabetes Care Inc.

    发明人： Junli Ou ,  Erwin Satrya Budiman

    IPC分类号： G01N33/49 ,  G06F16/901 ,  A61B5/145 ,  G16H10/60 ,  G16Z99/00 ,  G06K9/00

    摘要： Methods, devices, and systems are provided for identifying dropouts in analyte monitoring system sensor data including segmenting sensor data into a plurality of time series wherein each time series is associated with a different instance of a repeating event, selecting a first time series to analyze for dropouts from the plurality of time series; comparing the selected first time series to a second time series among the plurality of time series, determining whether the selected first time series includes a portion that is more than a predefined threshold lower than a corresponding portion of the second time series, and displaying, on a computer system display, an indication that the selected first time series includes a dropout if the selected first time series includes a portion that is more than the predefined threshold lower than the corresponding portion of the second time series.

    Method and Device for Providing Offset Model Based Calibration for Analyte Sensor
    35.
    发明申请
    Method and Device for Providing Offset Model Based Calibration for Analyte Sensor 审中-公开

    公开(公告)号：US20190035488A1

    公开(公告)日：2019-01-31

    申请号：US16147087

    申请日：2018-09-28

    申请人： Abbott Diabetes Care Inc.

    发明人： Erwin Satrya Budiman

    IPC分类号： G16H10/20 ,  A61B5/1486 ,  A61B5/1495 ,  A61B5/145

    摘要： Methods and devices to detect analyte in body fluid are provided. Embodiments include processing sampled data from analyte sensor, determining a single, fixed, normal sensitivity value associated with the analyte sensor, estimating a windowed offset value associated with the analyte sensor for each available sampled data cluster, computing a time varying offset based on the estimated windowed offset value, and applying the time varying offset and the determined normal sensitivity value to the processed sampled data to estimate an analyte level for the sensor.