公开(公告)号：WO2021242304A1

公开(公告)日：2021-12-02

申请号：PCT/US2020/063437

申请日：2020-12-04

Applicant: DEXCOM, INC.

Inventor： DERDZINSKI, Mark ,  PARKER, Andrew Scott

IPC: G01N33/48 ,  A61B5/00

Abstract: Glucose prediction using machine learning (ML) and time series glucose measurements is described. Given the number of people that wear glucose monitoring devices and because some wearable glucose monitoring devices can produce measurements continuously, a platform providing such devices may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process and covers a robust number of state spaces unlikely to be covered without the enormous amount of data. In implementations, a glucose monitoring platform includes an ML model trained using historical time series glucose measurements of a user population. The ML model predicts upcoming glucose measurements for a particular user by receiving a time series of glucose measurements up to a time and determining the upcoming glucose measurements of the particular user for an interval subsequent to the time based on patterns learned from the historical time series glucose measurements.

公开(公告)号：WO2021126583A1

公开(公告)日：2021-06-24

申请号：PCT/US2020/063655

申请日：2020-12-07

Applicant: DEXCOM, INC.

Inventor： PARKER, Andrew Scott ,  JIMENEZ, Annika Emilie Kristina ,  PATTERSON, Chad ,  PAI, Subrai Girish ,  KAMATH, Apurv Ullas

IPC: A61B5/00 ,  A61B5/0004 ,  A61B5/0022 ,  A61B5/14532 ,  A61B5/167 ,  A61B5/4833 ,  A61B5/4842 ,  A61B5/7264 ,  A61B5/7275 ,  A61B5/742 ,  A61B5/7475 ,  G06N3/08 ,  G06Q30/0201 ,  G16H10/60 ,  G16H40/67 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70

Abstract: Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.