Insulin Dosage Prediction Using Blood Glucose Models
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Solution Overview
Problem
Current methods for determining insulin injection amounts in diabetes management require continuous blood glucose monitoring, making it inconvenient for patients to accurately predict and administer insulin without real-time feedback.
Innovation Solution
A method using a computer-based system that predicts insulin injection amounts by combining characteristic user information, current blood glucose content, a blood glucose prediction model, and an insulin injection amount prediction model, allowing for insulin injection amount determination without continuous blood glucose monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous blood glucose monitoring is used to determine insulin injection amount, then the accuracy of insulin dosage is improved, but the convenience and simplicity of operation deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-collecting user characteristic information and establishing prediction models in advance. The insulin injection amount is predicted based on historical data and current blood glucose content, eliminating the need for continuous real-time monitoring during insulin administration, thus improving convenience while maintaining accuracy.
Solution Approach 2:
The patent creates a virtual copy of the continuous monitoring function through prediction models. Instead of requiring actual continuous blood glucose monitoring, the system uses a prediction model that copies the essential function of determining insulin dosage based on historical patterns and current measurements, reducing operational complexity.
2Reliability
If continuous blood glucose monitoring equipment is required, then the reliability of insulin dosage determination is improved, but the device complexity increases
Solution Approach 1:
The patent extracts the essential function of continuous monitoring from the physical monitoring equipment. By separating the core function (determining insulin dosage) from the means of achieving it (continuous monitoring devices), the system maintains reliability through prediction models while eliminating the need for complex continuous monitoring hardware.
Solution Approach 2:
The system uses the user's own historical blood glucose data and characteristic information to generate predictions, making the system self-sufficient. The prediction model learns from and adapts to individual user patterns, providing reliable insulin dosage determination without requiring external continuous monitoring infrastructure.
3Reliability
If timely blood glucose feedback is required for insulin pump control, then the effectiveness of glucose metabolism control is improved, but the ease of operation deteriorates
Solution Approach 1:
The system performs preliminary prediction of insulin injection amounts based on historical data and current blood glucose content. This preliminary action provides the necessary feedback for insulin pump control without requiring continuous real-time interaction, maintaining effectiveness while improving ease of operation.
Solution Approach 2:
The prediction model acts as an intermediary between blood glucose measurements and insulin pump control. It translates current blood glucose content and historical patterns into recommended insulin injection amounts, providing effective glucose metabolism control while simplifying the interaction between patient and insulin pump.
Data Source
AI summary
Method of determining insulin injection amount, computer storage medium, and devices, the method includes including: obtaining characteristic information and a blood glucose content at a current time of a target user; and determining an insulin injection amount at each time of the target user based on the characteristic information of the target user, the blood glucose content at the current time of the target user, a predetermined blood glucose prediction model, and a predetermined insulin injection amount prediction model. The method can facilitate the determination of the insulin injection amount at each time.


