Artificial Pancreas Event Detection Using Blood Glucose Change Rates
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Solution Overview
Problem
Current artificial pancreas systems require manual input of meal and exercise information, limiting them to semi-closed-loop control, and there is a need for a method to achieve closed-loop control through automatic detection of these events.
Innovation Solution
An automatic detection method based on the change rate of the difference between actual blood glucose values, using thresholds and additional judgment criteria to determine meal or exercise events, allowing the artificial pancreas to adjust infusion strategies accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual input of meal and exercise information is required, then the system operation is simple and reliable, but the automation level is low and detection precision is insufficient
Solution Approach 1:
The system automatically detects meal and exercise events by analyzing blood glucose data patterns without requiring user input. The detection algorithm processes BG values, calculates differences and change rates, and autonomously identifies events based on predefined thresholds, enabling the system to serve itself in terms of event detection.
Solution Approach 2:
The invention transforms static blood glucose values into dynamic parameters including difference (ΔBG) and change rate (Δ²BG). By monitoring how these parameters change over time and comparing them against thresholds, the system detects meal and exercise events automatically, converting simple glucose measurements into actionable event detection.
2Measurement precision
If the detection interval is shortened to improve accuracy, then the measurement precision increases, but the energy consumption and device complexity increase
Solution Approach 1:
The system dynamically adjusts the detection interval based on blood glucose variability. When ΔBG or Δ²BG exceeds thresholds indicating potential events, the system shortens the interval for more frequent monitoring. During stable periods, the interval extends to conserve energy, creating an adaptive detection strategy that balances accuracy and energy efficiency.
Solution Approach 2:
The invention uses parameter thresholds (ΔBG threshold, Δ²BG threshold) to trigger interval adjustments. By monitoring changes in blood glucose parameters and comparing them against predefined thresholds, the system intelligently modulates detection frequency, maintaining high accuracy during critical periods while reducing energy consumption during stable periods.
Data Source
AI summary
The invention discloses an automatic detection method based on the change rate of the difference between the actual blood glucose values, including: obtaining an actual blood glucose value of the user at the current time; obtaining a historical actual blood glucose value of the user at the previous time, and calculate a difference between the actual blood glucose values at the current time and at the previous time; calculating a change rate of the difference between the actual blood glucose values at the current time; and comparing the change rate of the difference between the actual blood glucose values at the current time with a preset threshold, and determining an event type based on the comparing result. Based on the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy to achieve closed-loop control of the artificial pancreas.