Glucose Profile Visualization for Pattern Recognition
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Solution Overview
Problem
Current glucose monitoring systems, both discontinuous and continuous, lack effective methods for analyzing glucose level data to quickly identify patterns and risks of hypoglycemia, making it difficult for clinicians and patients to manage diabetes effectively.
Innovation Solution
A system and method for analyzing glucose monitoring data that includes an input device, data processing device, output device, and display device, which receives glucose monitoring data, determines minimum and maximum glucose values, and provides graphical representations to display these values, allowing for the creation of ambulatory glucose profiles that highlight median, percentile curves, and threshold values, facilitating quick identification of glycemic patterns and risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous glucose monitoring data is collected over multiple days, then more comprehensive glucose patterns can be identified, but the complexity of data analysis increases
Solution Approach 1:
The patent segments the continuous glucose monitoring data into discrete time blocks (e.g., 24-hour periods) and creates separate glucose profiles for each block. This segmentation allows clinicians to analyze multiple days of data without being overwhelmed by the continuous stream, making the complex data more manageable while preserving comprehensive pattern information.
Solution Approach 2:
The patent creates visual copies of glucose data in the form of graphical representations for each time block. These graphical copies allow clinicians to quickly compare patterns across multiple days without analyzing raw numerical data, reducing analysis complexity while maintaining reliability of pattern identification.
2Measurement precision
If detailed glucose monitoring data is analyzed, then more accurate glycemic patterns can be identified, but the time required for analysis increases
Solution Approach 1:
By dividing detailed glucose data into standardized time blocks and generating one graphical representation per block, the patent enables clinicians to quickly scan multiple days of data without being overwhelmed by details. This maintains measurement precision through systematic analysis while significantly reducing the time required compared to examining raw continuous data.
Solution Approach 2:
The patent employs color-coded graphical representations to visually encode glucose level information (e.g., color gradients indicating hyperglycemia or hypoglycemia). This allows clinicians to rapidly assess glycemic patterns across multiple days by detecting color variations rather than analyzing numerical data, reducing analysis time while preserving accuracy.
3Reliability
If glucose data from multiple days is aggregated, then more reliable hypoglycemia risks can be identified, but the difficulty of interpreting data increases
Solution Approach 1:
The patent segments multi-day glucose data into distinct time block profiles with individual graphical representations. This segmentation maintains reliability by preserving data from all days while reducing interpretation difficulty by presenting each block's information in a standardized, comparable visual format rather than requiring integration of raw multi-day data.
Solution Approach 2:
Instead of aggregating multiple days of glucose data into a single complex dataset that requires sophisticated interpretation, the patent inverts the approach by creating separate graphical profiles for each time block. This allows clinicians to easily compare patterns across days by reviewing individual profiles, making hypoglycemia risk identification more straightforward while maintaining reliability through comprehensive data inclusion.
Data Source
AI summary
A system for analyzing glucose monitoring data indicative of a glucose level in a bodily fluid. The system includes an input device, a data processing device, an output device, a display device, and machine readable instructions that are executed by the data processing device, wherein the machine readable instructions cause the data processing device to receive glucose monitoring data via the input device, the glucose monitoring data indicating a glucose level in a bodily fluid sampled for a person at a plurality of sample times over a measurement time period in a glucose level measurement, and comprising a plurality of glucose profiles, each of the glucose profiles comprising a plurality of glucose values assigned to one of the plurality of sample times. Furthermore, a method for analyzing glucose monitoring data indicative of a glucose level in a system is provided.