Autonomous Glucose Control System Backup Protocol Generation
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Solution Overview
Problem
Current blood glucose control systems lack the ability to effectively generate and implement backup therapy protocols and track carbohydrate therapy equivalence, leading to potential disruptions in patient care when the primary system is unavailable or when counter-regulatory agents are not available.
Innovation Solution
An automated blood glucose control system that generates backup therapy protocols based on autonomously determined insulin doses and tracks carbohydrate therapy equivalence by using a medicament pump to deliver insulin and counter-regulatory agents, allowing for continuous glucose monitoring and adjusting therapy parameters to maintain optimal blood glucose levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system autonomously determines and modifies control parameters to optimize glucose control, then glycemic control effectiveness is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by autonomously determining optimal control parameters (such as insulin sensitivity factors and carbohydrate ratios) before glucose control issues arise. The processor pre-calculates and stores these parameters based on historical data and physiological models, enabling rapid response to glucose variations without real-time computational complexity.
Solution Approach 2:
The system implements self-service through autonomous parameter modification capabilities. The processor automatically adjusts control parameters based on detected glucose patterns and physiological responses, eliminating the need for manual programming or complex user intervention. The system serves itself by learning from past performance and adapting its own control strategy.
2Reliability
If the system tracks carbohydrate therapy equivalence and generates backup protocols, then patient care continuity is improved, but data processing requirements increase
Solution Approach 1:
The system creates backup therapy protocols as copies of the primary control strategy. When the primary system becomes unavailable, these pre-generated backup protocols can be executed without requiring real-time data processing or communication with the main system. The backup protocols contain essential control instructions that replicate the primary system's decision-making logic.
Solution Approach 2:
The system performs preliminary tracking and analysis of carbohydrate therapy equivalence data to generate backup protocols in advance. By pre-processing this information and storing it in accessible memory, the system ensures that critical therapy data is available immediately if system failure occurs, eliminating the need for complex real-time data reconstruction.
Data Source
AI summary
A blood glucose control system is configured to modify therapy provided to a subject. The system can cause first therapy to be delivered by the blood glucose control system to a subject during a first therapy period. The first therapy can be delivered based at least in part on a first value of a control parameter used by a control algorithm to generate a dose control signal. The system can determine a first effect corresponding at least in part to the first therapy and autonomously generate a second value of the control parameter. The system can cause second therapy to be delivered by the blood glucose control system to the subject during a second therapy period, wherein the second therapy is delivered based at least in part on the second value of the control parameter.