Invention Grant
- Patent Title: Micro models and layered prediction models for estimating sensor glucose values and reducing sensor glucose signal blanking
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Application No.: US17156490Application Date: 2021-01-22
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Publication No.: US12138047B2Publication Date: 2024-11-12
- Inventor: Peter Ajemba , Keith Nogueira
- Applicant: MEDTRONIC MINIMED, INC.
- Applicant Address: US CA Northridge
- Assignee: MEDTRONIC MINIMED, INC.
- Current Assignee: MEDTRONIC MINIMED, INC.
- Current Assignee Address: US CA Northridge
- Agency: Weaver Austin Villeneuve & Sampson LLP
- Main IPC: A61B5/145
- IPC: A61B5/145 ; A61B5/00 ; G06N20/00 ; G06N20/20 ; G16H40/63 ; G16H50/20 ; G16H50/30

Abstract:
Methods, systems, and devices for improving continuous glucose monitoring (“CGM”) are described herein. More particularly, the methods, systems, and devices describe applying layered machine learning models to generate predicted sensor glucose values. The system may use the predicted sensor glucose values to display a sensor glucose value to a user. The layered models may generate more reliable sensor glucose predictions across many scenarios, leading to a reduction of sensor glucose signal blanking. The methods, systems, and devices described herein further comprise applying a plurality of micro model to estimate sensor glucose values under outlier conditions. The system may prioritize the models that are trained for certain outlier conditions when the system detects those outlier condition based on the sensor data.
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