Cloud Big Data Insulin Pump Parameter Optimization
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Solution Overview
Problem
Current insulin pump systems struggle to provide accurate and timely individualized insulin infusion due to significant individual differences among patients and varying physiological parameters, leading to suboptimal blood glucose regulation and potential safety hazards.
Innovation Solution
A cloud big data-based system that integrates a real-time continuous glucose monitoring system, a smartphone application, and a cloud big data server to calculate and optimize insulin pump parameters such as basal infusion rate and high-dose injection volume based on historical data and real-time carbohydrate intake, using regression analysis and correction algorithms to adjust settings dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If insulin pump parameters are set according to specification or experience, then the device complexity is reduced and ease of operation is improved, but the manufacturing precision and reliability of individualized treatment are worsened due to significant individual differences among patients
Solution Approach 1:
The system automatically calculates and optimizes insulin pump parameters (basal infusion rate, high-dose injection volume, insulin-to-carb ratio, insulin sensitivity factor) using regression analysis on historical glucose monitoring data, eliminating the need for manual configuration by healthcare providers and enabling self-adjustment based on individual patient responses
Solution Approach 2:
The system continuously collects real-time glucose monitoring data and insulin pump operation records, uses regression analysis to identify patterns and individual characteristics, and dynamically adjusts parameters to optimize blood glucose control, creating a closed-loop feedback system that adapts to each patient's unique physiological responses
2Reliability
If insulin pump parameters are manually adjusted by healthcare providers, then the reliability of medical supervision is improved, but the productivity and timeliness of parameter optimization are worsened due to frequent medical consultations required
Solution Approach 1:
The system performs automatic parameter calculation and optimization using regression analysis on historical data, enabling continuous self-adjustment without requiring frequent medical consultations, thus maintaining reliability through algorithmic accuracy while dramatically improving timeliness of optimizations
Solution Approach 2:
The system pre-calculates optimal parameters by analyzing historical glucose monitoring data and insulin pump operation records before clinical needs arise, using regression analysis to predict individual responses and prepare optimized settings in advance, reducing the need for reactive adjustments
3Manufacturing precision
If cloud big data and regression analysis are used to optimize insulin pump parameters, then the precision of individualized treatment is improved, but the device complexity and loss of information are worsened due to data transmission and processing requirements
Solution Approach 1:
The system uses a cloud-based data processing platform as an intermediary to collect, store, and analyze glucose monitoring data and insulin pump records from multiple devices, performing regression analysis to identify individual patterns and generate optimized parameters, thereby managing complexity centrally while maintaining precision at the point of care
Data Source
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AI summary
A cloud big data-based system and method for insulin pump individualized configuration optimization are provided. The system includes an insulin pump, a real-time continuous glucose monitoring system, a smart phone, a glucose monitoring application software installed in the smart phone and a cloud big data server. By means of personal blood glucose measurement historical data of users stored in the cloud, the insulin pump individualized configuration optimization system provides effective calculation of an individualized optimal insulin injection volume and injection rate for each user, thus aiding physicians and patients to formulate diabetes treatment plans with increased effectiveness.