	US 12,011,262 B2
	Systems and methods for analyzing, interpreting, and acting on continuous glucose monitoring data
Shiping Liu, Columbia, MD (US); Mansur Shomali, Columbia, MD (US); Abhimanyu Kumbara, Columbia, MD (US); Anand Iyer, Columbia, MD (US); Malinda Peeples, Columbia, MD (US); Michelle Dugas, Columbia, MD (US); Kenyon Crowley, Columbia, MD (US); and Guodong Gao, Columbia, MD (US)
Assigned to WELLDOC, INC., Columbia, MD (US)
Filed by Welldoc, Inc., Columbia, MD (US)
Filed on Dec. 14, 2022, as Appl. No. 18/066,051.
Application 18/066,051 is a continuation of application No. 17/742,124, filed on May 11, 2022, granted, now 11,564,600.
Application 17/742,124 is a continuation of application No. 17/474,807, filed on Sep. 14, 2021, granted, now 11,357,427, issued on Jun. 14, 2022.
Application 17/474,807 is a continuation of application No. 17/206,858, filed on Mar. 19, 2021, granted, now 11,147,480, issued on Oct. 19, 2021.
Claims priority of provisional application 63/135,818, filed on Jan. 11, 2021.
Claims priority of provisional application 62/992,385, filed on Mar. 20, 2020.
Claims priority of provisional application 62/992,409, filed on Mar. 20, 2020.
Prior Publication US 2023/0110814 A1, Apr. 13, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 5/145 (2006.01); A61B 5/00 (2006.01); A61B 5/11 (2006.01); G06N 20/00 (2019.01); G16H 10/40 (2018.01); G16H 20/00 (2018.01); G16H 50/30 (2018.01)

CPC A61B 5/14532 (2013.01) [A61B 5/1118 (2013.01); A61B 5/48 (2013.01); A61B 5/7264 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); A61B 5/7282 (2013.01); A61B 5/7475 (2013.01); G06N 20/00 (2019.01); G16H 10/40 (2018.01); G16H 20/00 (2018.01); G16H 50/30 (2018.01); A61B 5/0022 (2013.01)]

20 Claims

1. A computer-implemented method for managing glucose states of a user, the method comprising:

receiving a plurality of optimization profiles for reaching an ideal state from a non-ideal state, the ideal state corresponding to a first time in range (TIR) state and a first glucose variability (GV) state and the non-ideal state comprising at least one of a second TIR state or a second GV state, wherein the first TIR state is above a threshold TIR value and the second TIR state is below the threshold TIR value;

determining a current TIR state based on a TIR value of the user's glucose level, wherein the TIR value is based on an amount of time the user's glucose level is within a threshold band;

determining a current GV state based on a GV value associated with the user's glucose level, wherein the GV value indicates a standard deviation (SD) of glucose levels or a coefficient of variance (CV), wherein the CV corresponds to a variability of the user's glucose level;

receiving one or more user vectors for the user;

identifying one of the plurality of optimization profiles based on the one or more user vectors;

identifying an optimized pathway based on the identified optimization profile, the current TIR state, and the current GV state, the optimized pathway comprising one or more adjustments to the one or more user vectors, wherein the one or more adjustments comprise a medication adjustment, a food consumption adjustment, or an exercise value, wherein:

the optimized pathway comprises a user vector change, the user vector change being based on the current TIR state, the current GV state, and user attributes, wherein the user attributes comprise a medical attribute, a user preference, a metabolic attribute, or a user demographic;

the optimized pathway is based on a habit index score of the user determined based on a cohort of users; and

providing the optimized pathway to the user.