Insulin Pump Correction Advisor for Dynamic Parameter Adjustment
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Solution Overview
Problem
Conventional insulin pumps face inaccuracies in insulin sensitivity (IS) and carbohydrate-to-insulin ratio (CIR) values due to limited applicable rules, and initial insulin delivery programming often results in inadequate glycemic control, leading to excessive insulin doses or suspensions, causing hypo- or hyper-glycemia.
Innovation Solution
The system adjusts and modifies fluid delivery based on historical delivery data and user-specific parameters, using a 'correction advisor' to assess and modify basal delivery profiles and CIR values, ensuring accurate insulin dosing by analyzing past correction boluses, meal boluses, and delivery suspensions, and providing personalized recommendations for improved glycemic control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional insulin pumps use pre-programmed basal rates and standard bolus calculations, then device complexity is reduced and ease of operation is improved, but measurement precision of insulin sensitivity and carbohydrate-to-insulin ratio values deteriorates
Solution Approach 1:
The system continuously monitors actual glycemic responses to insulin deliveries and uses this feedback to automatically recalculate and adjust insulin sensitivity (IS) and carbohydrate-to-insulin ratio (CIR) values. The processor compares predicted glucose levels with actual measurements and modifies delivery parameters accordingly, replacing static pre-programmed values with dynamically updated precise values.
Solution Approach 2:
The insulin pump performs self-calibration by automatically analyzing its own delivery history and the user's glycemic responses. The system autonomously calculates optimal IS and CIR values based on recorded data without requiring manual input or external intervention, enabling continuous improvement of dosing precision while maintaining ease of operation.
2Device complexity
If initial insulin delivery programming is used without adjustment, then device complexity is minimized, but reliability of glycemic control deteriorates due to inadequate dosing accuracy
Solution Approach 1:
The system performs preliminary analysis of delivery history and glycemic patterns to predict future dosing requirements. By pre-calculating optimal IS and CIR values based on accumulated data before the next insulin delivery, the system ensures reliable glycemic control while maintaining simple operation for the user.
Solution Approach 2:
The insulin pump transitions from static pre-programmed parameters to dynamic adaptive parameters. The processor continuously updates IS and CIR values based on real-time glycemic feedback and historical delivery patterns, allowing the system to adapt to changing user needs and physiological conditions while maintaining operational simplicity.
3Measurement precision
If frequent manual adjustment of insulin parameters is required to achieve accurate dosing, then measurement precision of glycemic control is improved, but ease of operation deteriorates and loss of time increases
Solution Approach 1:
The system automatically performs parameter optimization by analyzing its own delivery history and glycemic responses. The processor independently calculates and updates IS and CIR values without requiring manual user intervention, achieving high measurement precision while maintaining ease of operation through fully automated self-adjustment.
Solution Approach 2:
The system implements continuous feedback loops where actual glycemic measurements are compared with predicted values, and the difference is used to automatically adjust insulin parameters. This closed-loop control achieves precise glycemic control while eliminating the need for frequent manual adjustments by the user.
4Device complexity
If conventional fixed basal rates are used, then device complexity is reduced, but adaptability to changing user needs and physiological conditions deteriorates
Solution Approach 1:
The system replaces fixed basal rates with dynamic adaptive parameters that automatically adjust to changing user needs and physiological conditions. The processor continuously updates insulin sensitivity and carbohydrate-to-insulin ratio values based on real-time glycemic feedback and historical delivery patterns, enabling the device to adapt to varying metabolic states, activity levels, and dietary patterns while maintaining operational simplicity.
Data Source
AI summary
Devices, systems and methods for adjusting fluid delivery based on past or historical fluid delivery data and/or personal parameters of a user are disclosed. Devices, and corresponding systems and methods, may comprise a dispensing unit configured to deliver a fluid from a reservoir into the body of a user and a processor having instructions operating thereon to retrieve data relating to one or more time windows from a memory, assess a correction delivery for the one or more time windows based on the data, determine a new CIR value for the one or more time windows if the correction delivery regularly follows a meal bolus and/or determine a new basal delivery profile for the one or more time windows if the correction delivery regularly precedes a meal bolus.