Infusion Device Rescue Detection to Limit Insulin Overcorrection
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Solution Overview
Problem
Infusion devices struggle to distinguish between actionable and nonactionable events, leading to potential overcorrection in blood glucose levels, especially when a user consumes fast-acting carbohydrates, which can result in unintended insulin delivery.
Innovation Solution
The infusion device autonomously detects nonactionable conditions, such as rescue conditions, by analyzing glucose measurement values, and temporarily limits fluid delivery to prevent overcorrection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the infusion device automatically responds to rising glucose trends by delivering insulin, then the response time is quick and blood glucose control is improved, but the device may unintentionally counteract fast-acting carbohydrates and cause overcorrection
Solution Approach 1:
The system performs preliminary analysis of glucose measurement patterns and trends before triggering insulin delivery. By evaluating multiple consecutive glucose readings and detecting characteristic patterns of fast-acting carbohydrate consumption (rapid glucose elevation followed by stabilization), the system determines whether a rising glucose trend requires intervention. This preliminary assessment prevents premature or inappropriate insulin delivery while maintaining quick response to genuine hypoglycemic risks.
2Reliability
If the infusion device delivers insulin based on current glucose values, then blood glucose regulation is achieved, but the device cannot undo previous deliveries and may cause hyperglycemic events
Solution Approach 1:
The system implements continuous feedback monitoring by analyzing glucose measurement trends and patterns over time. The control algorithm evaluates whether recent insulin deliveries are having the intended effect by monitoring glucose level changes and adjusts subsequent delivery decisions accordingly. This feedback mechanism enables the system to recognize when carbohydrates have been consumed and when additional insulin delivery would be inappropriate, preventing overcorrection and hyperglycemic events without requiring complex manual intervention.
3Force
If the infusion device uses predictive algorithms to estimate future blood glucose levels, then delivery adjustments are made in advance, but the device may respond too quickly to nonactionable events
Solution Approach 1:
The system dynamically adjusts its predictive control behavior based on the detected glucose pattern. When a fast-acting carbohydrate pattern is detected (characterized by rapid glucose elevation over consecutive measurements), the system temporarily modifies its predictive algorithm to reduce or suspend insulin delivery predictions. This dynamic adaptation allows the system to maintain aggressive predictive control for genuine hypoglycemic risks while automatically becoming more conservative when carbohydrate consumption is detected, resolving the contradiction between predictive capability and false positive responses.
Data Source
AI summary
Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device to deliver fluid to a body of a user involves obtaining measurement values for a physiological condition influenced by the fluid, autonomously operating the infusion device to deliver the fluid based at least in part on the measurement values, and detecting a nonactionable condition based on the measurement values. In response to detecting the nonactionable condition, delivery of the fluid is limited while maintaining autonomous operation of the infusion device. In one exemplary embodiment, the nonactionable condition is a rescue condition indicative of the user having consumed fast-acting carbohydrates, and thus insulin delivery may be automatically limited in response to detecting the rescue carbohydrate consumption.