Automatic Glucose Target Adaptation for Stable Insulin Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing glucose control systems struggle to maintain stable euglycemia, particularly when counter-regulatory agents are unavailable or their delivery is compromised, leading to potential hypoglycemic events.
Innovation Solution
A glucose control system that dynamically adjusts the glucose target based on trends in glucose levels and computed doses of counter-regulatory agents, within predefined bounds, to ensure safe and stable glucose control, even in the absence of actual counter-regulatory agent delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed glucose target is used in insulin delivery control, then the control system is simple to operate, but the system cannot adapt to changing glucose trends and counter-regulatory agent availability, leading to hypoglycemic events
Solution Approach 1:
The patent implements a dynamic glucose target that automatically adjusts based on glucose trends and counter-regulatory agent delivery status. The target transitions between different values (e.g., normal target vs. elevated target) based on real-time system state, allowing the control system to adapt to changing conditions without manual intervention while maintaining manageable complexity through automated decision rules.
Solution Approach 2:
The system continuously monitors glucose levels, determines trends (rising, falling, stable), and uses this feedback to automatically adjust the glucose target. The control algorithm receives feedback about counter-regulatory agent delivery status and glucose trend direction, then modifies the target accordingly, creating a closed-loop adaptive control system that improves versatility without proportionally increasing complexity.
2Reliability
If the glucose target is dynamically adjusted based on glucose trends and counter-regulatory agent doses, then the system improves glucose control stability and reduces hypoglycemia, but the control algorithm becomes more complex
Solution Approach 1:
The control algorithm dynamically adjusts the glucose target based on real-time glucose trends and counter-regulatory agent delivery status. By making the target variable rather than fixed, the system achieves more reliable glucose control that adapts to changing physiological conditions and delivery system status, improving stability without requiring overly complex algorithms through the use of structured decision rules.
Solution Approach 2:
The system changes the glucose target parameter based on detected glucose trends (rising, falling, stable) and counter-regulatory agent delivery status. This parameter adaptation allows the control algorithm to maintain reliable glucose control across different operating conditions by adjusting the target value within a predefined range, achieving improved reliability through controlled parameter variation rather than complex algorithmic changes.
3Object-affected harmful factors
If counter-regulatory agents are delivered to prevent low glucose levels, then hypoglycemic events are reduced, but the system complexity increases and delivery reliability may be compromised
Solution Approach 1:
The system takes preliminary action by delivering counter-regulatory agents before severe hypoglycemia occurs, based on detected glucose trends and predicted glucose levels. By proactively administering agents to prevent low glucose events rather than reacting after hypoglycemia begins, the system reduces harmful effects while maintaining delivery reliability through anticipatory control strategies.
Solution Approach 2:
The control algorithm performs preliminary calculations to determine the need for counter-regulatory agent delivery based on current glucose levels, trends, and predicted future glucose values. This preliminary assessment allows the system to prepare and execute timely agent delivery to prevent hypoglycemic events, improving protection against harmful effects while maintaining reliable delivery through advance planning and prediction.
Data Source
AI summary
A glucose control system employs adaptation of a glucose target (set-point) control variable in controlling delivery of insulin to a subject to maintain euglycemia. The glucose target adapts based on trends in actual glucose level (e.g., measured blood glucose in the subject), and/or computed doses of a counter-regulatory agent such as glucagon. An adaptation region with upper and lower bounds for the glucose target may be imposed. Generally the disclosed techniques can provide for robust and safe glucose level control. Adaptation may be based on computed doses of a counter-regulatory agent whether or not such agent is actually delivered to the subject, and may be used for example to adjust operation in a bihormonal system during periods in which the counter-regulatory agent is not available for delivery.