Dropout detection in continuous analyte monitoring data during data excursions
First Claim
1. A method, comprising:
- receiving sensor data from an analyte monitoring device;
segmenting the sensor data by time to obtain segmented data;
identifying a periodic event from the segmented data, the periodic event independently occurring at a first window of time and a second window of time;
defining a set of time dilation parameters;
applying the time dilation parameters to the second window of time to obtain a baseline-normalized ratio for a portion of the first window of time;
determining that the baseline-normalized ratio for the portion of the first window of time is below a predetermined threshold; and
displaying an indication that the portion of the first window of time includes a dropout.
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Abstract
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.
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Citations
20 Claims
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1. A method, comprising:
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receiving sensor data from an analyte monitoring device; segmenting the sensor data by time to obtain segmented data; identifying a periodic event from the segmented data, the periodic event independently occurring at a first window of time and a second window of time; defining a set of time dilation parameters; applying the time dilation parameters to the second window of time to obtain a baseline-normalized ratio for a portion of the first window of time; determining that the baseline-normalized ratio for the portion of the first window of time is below a predetermined threshold; and displaying an indication that the portion of the first window of time includes a dropout. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus for identifying a signal dropout in sensor data, comprising:
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a processor; and a memory coupled to the processor, the memory storing instructions which, when executed by the processor, cause the processor to; receive sensor data from an analyte monitoring device; segment the sensor data by time to obtain segmented data; identify a periodic event from the segmented data, the periodic event independently occurring at a first window of time and a second window of time; define a set of time dilation parameters; apply the time dilation parameters to the second window of time to obtain a baseline-normalized ratio for a portion of the first window of time; determine that the baseline-normalized ratio for the portion of the first window of time is below a predetermined threshold; and display an indication that the portion of the first window of time includes a dropout. - View Dependent Claims (15, 16, 17)
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18. A system, comprising:
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an analyte sensor positioned in fluid contact with bodily fluid under a skin layer and configured to generate signals corresponding to a monitored analyte level; sensor electronics operatively coupled to the analyte sensor and configured to generate analyte data based on the signals generated by the analyte sensor; and a receiving device comprising a display, one or more processors, and a memory storing instructions which, when executed by the one or more processors, cause the receiving device to; receive the analyte data from the sensor electronics; segment the analyte data by time to obtain segmented data; identify a periodic event from the segmented data, the periodic event independently occurring at a first window of time and a second window of time; define a set of time dilation parameters; apply the time dilation parameters to the second window of time to obtain a baseline-normalized ratio for a portion of the first window of time; determine that the baseline-normalized ratio for the portion of the first window of time is below a predetermined threshold; and provide an indication on the display that the portion of the first window of time includes a dropout. - View Dependent Claims (19, 20)
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Specification