Analyte Monitoring Interfaces for Glucose Trends and Alerts
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Solution Overview
Problem
Individuals with diabetes often fail to monitor their glucose levels frequently due to convenience, testing discretion, pain, and cost, leading to reluctance in using analyte monitoring systems, which are complex and lack user-friendly interfaces and actionable information.
Innovation Solution
Improved graphical user interfaces (GUIs) and digital interfaces for analyte monitoring systems that are intuitive, user-friendly, and provide rapid access to physiological information, with features like sensor results, trend alerts, alarms, and insights, along with methods for sensor activation, pairing, and data backfilling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If analyte monitoring systems are implemented to improve glucose monitoring frequency and glycemic control, then health outcomes are improved, but device complexity and user interface complexity increase making the system harder to use
Solution Approach 1:
The system segments complex analyte monitoring data into distinct, manageable components including current analyte levels, trend information, alerts, and insights. Each segment is presented through dedicated interface elements that focus on specific aspects of glucose management, making the overall complex system more approachable and easier to navigate for users.
Solution Approach 2:
The patent introduces an intermediary processing layer between the sensor and the user that transforms raw analyte data into actionable insights. This intermediary includes algorithms that generate trend information, predict future analyte levels, and provide contextualized recommendations, effectively mediating between complex sensor data and user decision-making.
2Measurement precision
If comprehensive analyte data is collected and presented to users, then measurement precision and information completeness are improved, but the volume of data increases making it harder for users to process and understand
Solution Approach 1:
The system extracts and isolates the most critical and actionable information from comprehensive analyte data sets. Key features include extracting current glucose levels, identifying significant trends, and pulling out specific actionable insights while filtering out redundant or less relevant data, presenting only the essential information needed for effective glucose management.
Solution Approach 2:
The patent transforms raw analyte parameters into meaningful clinical parameters through processing algorithms. Raw glucose measurements are converted into trend directions, rate of change indicators, and predictive future levels, changing the parameter representation from simple numerical values to clinically actionable information that is easier to interpret and respond to.
3Measurement precision
If users are provided with detailed analyte monitoring information, then measurement precision is improved, but the time required to process and understand the data increases
Solution Approach 1:
The system performs preliminary processing and analysis of analyte data in the background before presentation to the user. Trends are pre-calculated, alerts are pre-generated based on threshold violations, and insights are pre-computed using predictive algorithms, so that when users access the information, it is already organized and ready for immediate interpretation without requiring additional processing time.
Solution Approach 2:
The patent implements feedback mechanisms that adapt to user behavior and preferences. The system learns from user interactions with the interface and adjusts the presentation of information accordingly, providing more or less detailed information based on individual user needs, thereby reducing the time required for each user to process relevant data while maintaining measurement precision.
Data Source
AI summary
Improved graphical user and digital interfaces for analyte monitoring systems are provided. For example, disclosed herein are various embodiments of GUIs including, sensor results, trend alerts, alarms, and insights interfaces. In addition, various embodiments of digital interfaces are described, including methods for sensor activation and pairing, wherein an analyte monitoring software application is configured to pair with a plurality of different types of sensors, and methods data backfilling in an analyte monitoring system, among other embodiments.