Insulin Dosage Adjustment via Blood Glucose Variability Analysis
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Solution Overview
Problem
Current insulin therapy methods for diabetes management often fail to provide optimal glycemic control due to improper dosing of insulin, which can result in unpredictable blood glucose variability, leading to serious complications.
Innovation Solution
A method and device for adjusting insulin therapy settings by analyzing blood glucose data over multiple days, determining variability metrics such as dispersion and area-under-the-curve values, and modifying insulin dosage suggestions for long-acting and rapid-acting insulins based on these analyses to maintain optimal blood glucose levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed insulin dosage is administered daily, then therapy simplicity is maintained, but glycemic control precision deteriorates due to unpredictable blood glucose variability
Solution Approach 1:
The system implements feedback by continuously monitoring blood glucose levels and using this information to automatically adjust insulin dosage recommendations. The processor receives blood glucose data, analyzes variability metrics, and modifies dosage suggestions based on the analyzed patterns, creating a closed-loop control system that improves glycemic precision without requiring complex manual intervention from the patient.
Solution Approach 2:
The insulin therapy system performs self-adjustment by automatically analyzing blood glucose variability and generating modified dosage suggestions without requiring external medical intervention for each adjustment. The electronic device autonomously processes glucose data, determines variability metrics, and updates dosage recommendations, enabling the therapy to self-optimize based on observed patterns.
2Reliability
If insulin dosage is adjusted frequently based on blood glucose data, then glycemic control improves, but patient burden and operational complexity increase
Solution Approach 1:
The system automates the entire dosage adjustment process, eliminating the need for patients to manually calculate or adjust insulin doses. The electronic device autonomously receives blood glucose data, analyzes variability, and generates dosage suggestions, transforming a complex manual task into a simple automated process that patients can easily follow.
Solution Approach 2:
The patent replaces manual calculation and decision-making mechanisms with an electronic processing system. Instead of patients manually analyzing blood glucose patterns and calculating dosage adjustments, the system uses a processor to automatically analyze variability metrics and generate dosage recommendations, substituting mechanical human cognition with electronic computation.
3Measurement precision
If blood glucose monitoring is performed continuously, then data accuracy for dosage adjustment improves, but energy consumption and device complexity increase
Solution Approach 1:
The system employs periodic monitoring rather than continuous monitoring, collecting blood glucose data at regular intervals sufficient to capture variability patterns. This periodic approach provides accurate data for dosage adjustment while significantly reducing energy consumption compared to continuous monitoring, as the sensor and processing components are activated only at scheduled intervals.
Data Source
AI summary
A method of adjusting insulin therapy settings for a person with diabetes that treats the diabetes by administering first and second types of insulin includes: storing, in a non-transitory storage medium of an electronic device, a first-type insulin dosage suggestion for a person with diabetes regarding a first type of insulin having an active time that is longer than an active time for a second type of insulin; receiving blood glucose data for the person with diabetes, the blood glucose data including blood glucose values for a plurality of days; determining a first variability of the blood glucose values for a selected first period of time during the plurality of days; and modifying the first-type insulin dosage suggestion in the non-transitory storage medium based on the determined first variability.