Glucose Reader Personalized Metrics Segmentation
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Solution Overview
Problem
Existing analyte monitoring systems face challenges in user adherence due to complexity, data volume, learning curve associated with software and user interfaces, and a lack of actionable information.
Innovation Solution
A system for monitoring glucose that includes a sensor control device and a reader device, where the reader device calculates personalized glucose metrics using physiological parameters and analyte data, and displays a report with multiple interfaces tailored to different user types, providing timely and actionable responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive analyte monitoring data is collected and presented to users, then the information completeness is improved, but the user interface complexity and data volume increase
Solution Approach 1:
The patent segments the comprehensive analyte monitoring data into distinct functional categories including glucose metrics, glycated hemoglobin data, personalized glucose targets, and time-in-range statistics. Each category is presented in separate interface sections with dedicated visualizations, allowing users to access comprehensive information without being overwhelmed by a single complex display.
Solution Approach 2:
The patent introduces processed and personalized glucose metrics as intermediary representations between raw sensor data and user decision-making. These intermediaries include calculated values such as time-in-range percentages, glucose management score, and personalized target ranges, which translate complex continuous data into actionable insights without requiring users to interpret raw numerical streams.
2Loss of information
If detailed glucose monitoring data is provided, then the information completeness is improved, but the ease of operation decreases due to learning curve
Solution Approach 1:
The patent employs color-coded visual indicators to represent glucose level categories and trends, using universal color associations (e.g., green for normal ranges, yellow for caution, red for alerts). This visual encoding system allows users to quickly comprehend glucose status without requiring detailed knowledge of numerical thresholds or complex interpretations.
Solution Approach 2:
The patent transforms raw glucose concentration values into standardized percentage metrics such as time-in-range and glucose management score. These parameter transformations normalize diverse data into intuitive scales that are easier to interpret and compare over time, reducing the cognitive load required to understand monitoring results.
3Loss of information
If personalized glucose metrics are calculated and displayed, then the actionable information is improved, but the device complexity increases
Solution Approach 1:
The patent implements automated calculation of personalized glucose metrics where the system independently processes raw sensor data to generate time-in-range statistics, glucose management scores, and personalized target recommendations without requiring manual user computation. This self-service approach consolidates processing complexity within the device while presenting simplified results to users.
Solution Approach 2:
The patent establishes feedback loops where calculated personalized metrics are continuously updated based on new sensor readings and compared against target ranges. The system automatically adjusts and refines personalized glucose targets based on historical data patterns, reducing the need for manual configuration while maintaining personalized relevance.
Data Source
AI summary
A glucose monitoring system comprising a sensor control device comprising an analyte sensor coupled with sensor electronics, the sensor control device configured to transmit data indicative of an analyte level of a subject, and a reader device. The reader device comprises a wireless communication circuitry configured to receive the data indicative of the analyte level and a glycated hemoglobin level for the subject, a non-transitory memory, and at least one processor communicatively coupled to the non-transitory memory and the analyte sensor and configured: calculate a plurality of personalized glucose metrics for the subject using at least one physiological parameter and at least one of the received data indicative of the analyte level or the received glycated hemoglobin level, and a display, on a display of the reader device, a report comprising a plurality of interfaces including at least two or more of the received data indicative of the analyte level, the received glycated hemoglobin level, or the calculated plurality of personalized glucose metrics, wherein the plurality of interfaces comprising the report are based on a user type.