Blood Glucose Excursion Attribution to Meals
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Solution Overview
Problem
Individuals with diabetes face challenges in consistently managing their blood glucose levels due to the difficulty in understanding how meals impact their glycemic health state, as existing methods lack effective attribution of blood glucose excursions to meal consumption.
Innovation Solution
A diabetes management platform that acquires and analyzes physiological data and meal data to identify excursions in blood glucose levels, match them to specific meals, and provide personalized recommendations for improving glycemic health by classifying meals as positive, negative, or neutral based on their impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional blood glucose monitoring methods are used, then blood glucose levels can be measured, but the ability to attribute excursions to specific meals is insufficient
Solution Approach 1:
The patent segments the blood glucose monitoring system into distinct functional modules: a physiological data acquisition module for collecting glucose levels, a meal data acquisition module for tracking meal consumption, and a matching module for attributing excursions to specific meals. This segmentation allows the system to maintain comprehensive functionality while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary matching module that acts as a bridge between physiological data and meal data. This intermediary component analyzes temporal relationships and patterns to attribute blood glucose excursions to specific meals, thereby recovering lost attribution information without requiring direct integration of all system components.
2Measurement precision
If comprehensive meal and physiological data analysis is implemented, then meal attribution accuracy improves, but computational requirements and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing both physiological data and meal data into structured formats before matching. The system prepares temporal markers and excitation patterns in advance, enabling faster and more accurate attribution when actual matching occurs, thus reducing real-time processing requirements.
Solution Approach 2:
The patent implements partial action by focusing analysis on relevant time windows around meal consumption rather than analyzing entire datasets. The matching module concentrates computational resources on identifying excursions within specific temporal ranges associated with meals, achieving high attribution accuracy without the need to process all possible data combinations.
Data Source
AI summary
To better understand the impact that meals have on the blood glucose level, some individuals with diabetes have begun recording meals consumed over time. However, the relationship between meals consumed by an individual and the glycemic health state of the individual has been difficult to understand. Introduced here are computer programs and associated computer-implemented techniques for utilizing information regarding the meals consumed by an individual to manage the blood glucose level of the individual in a personalized manner. By consistently and properly attributing physiological responses represented as excursions in blood glucose measurements to meals, the relationship between these meals and the glycemic health state can be better understood. For example, by examining this relationship, a diabetes management platform may be able to identify appropriate recommendations for monitoring, managing, and/or improving the glycemic health state of an individual.