Micro models and layered prediction models for estimating sensor glucose values and reducing sensor glucose signal blanking
US12138047B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 22, 2021 |
| Grant date | Nov 12, 2024 |
| Priority date | — |
| Expiry date | Aug 29, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldMedical technology
- WIPO sectorInstruments
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.