Closed-Loop Insulin Pump Glycemic Control
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Solution Overview
Problem
Current closed-loop infusion pump systems for diabetes management have limited ability to tailor insulin delivery to individual patient characteristics, leading to inadequate glycemic control and increased risk of extreme blood glucose levels.
Innovation Solution
A system that determines a patient's meal and insulin profiles, estimates physiological parameters based on blood glucose observations, and adjusts insulin infusion rates to maintain target glucose levels, using a special purpose computing apparatus and continuous glucose monitoring, to model and control blood glucose concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If closed-loop infusion pump systems are used to automatically control insulin delivery based on blood glucose measurements, then glycemic control is improved, but the system complexity increases
Solution Approach 1:
The system employs continuous feedback from glucose sensors to automatically adjust insulin infusion rates. The controller receives real-time blood glucose measurements and modifies pump delivery accordingly, creating a closed-loop control system that adapts to patient needs and maintains glycemic control without manual intervention.
Solution Approach 2:
The infusion pump system performs self-regulation by automatically adjusting its own insulin delivery based on embedded sensor data. The system monitors its own performance through continuous glucose monitoring and autonomously corrects deviations from target glycemic levels, reducing the need for external manual control.
2Reliability
If insulin delivery is manually adjusted by patients, then ease of operation is maintained, but glycemic control reliability deteriorates
Solution Approach 1:
The system transfers the manual adjustment task to the automated pump controller, which continuously monitors blood glucose and self-adjusts insulin delivery. This eliminates the burden of manual calculation and decision-making from patients while maintaining reliable glycemic control through continuous automated optimization.
Solution Approach 2:
Real-time feedback from continuous glucose monitoring enables the system to automatically respond to glycemic deviations. The controller processes sensor data and adjusts insulin rates dynamically, providing reliable control without requiring patient intervention in the control loop.
3Reliability
If individualized insulin delivery is tailored to patient characteristics, then glycemic control improves, but device complexity increases
Solution Approach 1:
The system dynamically adapts insulin delivery parameters based on real-time patient responses and individual characteristics. The controller continuously learns from glucose patterns and adjusts infusion rates to match each patient's unique metabolic profile, achieving personalized control without requiring manual programming of complex algorithms.
Solution Approach 2:
The system uses feedback from continuous glucose monitoring to automatically personalize insulin delivery for each patient. By analyzing individual glycemic responses to meals, exercise, and stress, the controller optimizes infusion rates specific to that patient's physiology, achieving tailoring without manual complexity.
Data Source
AI summary
Subject matter disclosed herein relates to a method and/or system for tailoring insulin therapies to physiological characteristics of a patient. In particular, observations of a blood glucose concentration of a patient responsive to a meal profile and an insulin profile may be used for estimating one or more physiological parameters.