US 11,722,229 B2
Method, system and computer program product for real-time detection of sensitivity decline in analyte sensors
Marc D. Breton, Charlottesville, VA (US); Boris P. Kovatchev, Charlottesville, VA (US); Erwin S. Budiman, Fremont, CA (US); and Kenneth J. Doniger, Menlo Park, CA (US)
Assigned to ABBOTT DIABETES CARE INC., Alameda, CA (US); and UNIVERSITY OF VIRGINIA PATENT FOUNDATION, Charlottesville, VA (US)
Filed by ABBOTT DIABETES CARE INC., Alameda, CA (US); and UNIVERSITY OF VIRGINIA PATENT FOUNDATION, Charlottesville, VA (US)
Filed on Jan. 22, 2021, as Appl. No. 17/156,169.
Application 17/156,169 is a continuation of application No. 15/866,384, filed on Jan. 9, 2018, granted, now 10,903,914.
Application 15/866,384 is a continuation of application No. 14/266,612, filed on Apr. 30, 2014, granted, now 9,882,660, issued on Jan. 30, 2018.
Application 14/266,612 is a continuation of application No. 13/418,305, filed on Mar. 12, 2012, granted, now 8,718,958, issued on May 6, 2014.
Application 13/418,305 is a continuation of application No. 11/925,689, filed on Oct. 26, 2007, granted, now 8,135,548, issued on Mar. 13, 2012.
Claims priority of provisional application 60/854,566, filed on Oct. 26, 2006.
Prior Publication US 2021/0218481 A1, Jul. 15, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. H04B 17/00 (2015.01); A61B 5/145 (2006.01); A61B 5/00 (2006.01); A61B 5/1473 (2006.01); G16H 40/60 (2018.01); G16H 40/67 (2018.01); G16H 10/40 (2018.01)
CPC H04B 17/00 (2013.01) [A61B 5/002 (2013.01); A61B 5/14503 (2013.01); A61B 5/14532 (2013.01); A61B 5/14546 (2013.01); A61B 5/1473 (2013.01); A61B 2560/0223 (2013.01); G16H 10/40 (2018.01); G16H 40/60 (2018.01); G16H 40/67 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A computer implemented method, comprising:
receiving a set of analyte sensor data taken over a first time period after initialization of a sensor;
performing a sliding window analysis on the set of analyte sensor data, wherein performing the sliding window analysis comprises extracting a first sensor data characteristic for a first window of the set of analyte sensor data, wherein the first window starts at a first start time, ends at a first end time, and has a first duration less than the first time period;
determining a probability of existence of signal attenuation associated with a decline in analyte sensor response based on the first sensor data characteristics; and
comparing the determined probability of existence of signal attenuation to a predetermined threshold value.