Closed Loop Insulin Control Fault Detection
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Solution Overview
Problem
Closed loop control systems for insulin delivery in diabetic patients face safety and accuracy issues due to potential failures in glucose sensors and infusion components, leading to unreliable insulin administration.
Innovation Solution
A method and device that monitor analyte sensor signals for fault conditions, dynamically adjust insulin infusion rates to predetermined ranges, and implement safety measures to prevent over-dosing, including reverting to pre-programmed rates and issuing notifications for user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If closed loop control systems automatically adjust insulin delivery based on glucose sensor signals, then insulin delivery accuracy is improved, but system reliability deteriorates due to potential sensor failures and infusion errors
Solution Approach 1:
The system performs preliminary actions by detecting potential fault conditions in the glucose sensor before they lead to dangerous insulin delivery errors. The control system proactively identifies sensor failures and switches to alternative control modes or pre-programmed insulin delivery schedules, preventing harmful outcomes before they occur.
Solution Approach 2:
The system implements beforehand cushioning by establishing safety mechanisms and alternative control strategies in advance. When sensor faults are detected, the system has pre-prepared fallback options such as switching to pre-programmed insulin delivery rates or alerting the user, thereby cushioning against the potential harmful effects of sensor failures.
2Reliability
If the system continuously monitors sensor signals for fault conditions, then safety is improved, but device complexity increases
Solution Approach 1:
The system employs feedback mechanisms by continuously monitoring glucose sensor signals and comparing them against expected physiological ranges and patterns. When deviations indicating potential faults are detected, the feedback loop triggers appropriate responses such as switching control modes or notifying the user, thereby maintaining safety through intelligent monitoring without requiring overly complex hardware modifications.
Data Source
AI summary
Method of monitoring a control operation of a medication delivery system, determining whether a signal level received from an analyte sensor is associated with a fault condition and a potential fault condition, and adjusting a medication delivery rate executed by the control operation when it is determined that the signal level from the analyte sensor is associated with one of the fault condition or the potential fault condition, where the medication delivery rate is adjusted to a first predetermined range when the signal level is associated with the fault condition, and adjusted to a second predetermined range when the signal level is associated with the potential fault condition is provided. Devices, systems and kits for implementing the afore-mentioned method are also provided.