Glucose Prediction Display With Adaptive Hypoglycemia Time Windows
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Solution Overview
Problem
Existing glucose monitoring systems overwhelm users with excessive data, failing to appropriately draw attention to imminent hypoglycemic events by using static prediction time windows, which may lead to delayed user action.
Innovation Solution
A computer-implemented method and system that dynamically adjust the prediction time window based on hypoglycemic risk, displaying shorter windows when high risk is detected, using algorithms to predict and display glucose values for a shorter duration to focus user attention on immediate action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static prediction time windows are used to display glucose values, then the system provides comprehensive glucose data coverage, but users experience information overload and may miss critical hypoglycemic events
Solution Approach 1:
The patent applies dynamics by transitioning from static prediction time windows to dynamic adaptive time windows. The system automatically adjusts the prediction time window length based on real-time hypoglycemia risk assessment. When hypoglycemia risk is detected, the system shortens the prediction time window to focus user attention on imminent critical events, thereby preventing information overload while ensuring critical events are not missed.
2Reliability
If comprehensive glucose data is displayed to ensure complete monitoring, then all glucose information is available, but user attention is diluted and response time to critical events increases
Solution Approach 1:
The patent applies local quality by differentiating the display characteristics based on the specific glucose monitoring situation. Instead of uniform display for all data, the system applies enhanced visual emphasis (such as color coding, alerts, or prominent positioning) specifically to predicted glucose values that indicate hypoglycemia risk. This allows users to quickly identify critical events among comprehensive data without being overwhelmed by non-critical information.
3Adaptability or versatility
If static prediction time windows are used, then the system structure remains simple, but the system cannot adapt to varying hypoglycemia risks and may delay critical alerts
Solution Approach 1:
The patent applies feedback by implementing a closed-loop system where predicted glucose values continuously inform the adjustment of prediction time windows. The system calculates predicted glucose values using current and historical glucose data, assesses hypoglycemia risk based on these predictions, and feeds this risk assessment back to dynamically adjust the prediction time window length. This feedback mechanism enables automatic adaptation to varying hypoglycemia risks without requiring complex manual configuration.
Data Source
AI summary
A computer-implemented method and system for predicting and displaying glucose values, including receiving CGM data, determining, based on the data, a plurality of first predicted glucose values (33) for a first prediction time window (30), determining, based on the data, that a hypoglycemia event is predicted to occur during a second prediction time window (31) which has a contemporaneous beginning with the first prediction time window (30) but is shorter than the first window (30), and determining a plurality of second predicted glucose values (34) for the second prediction time window (31) and displaying the plurality of second predicted glucose values (34) for the second prediction time window (31) while not displaying predicted glucose values subsequent to the second prediction time window (31).