Analyte Monitoring Device With Interaction-Frequency Feedback
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Solution Overview
Problem
Existing analyte monitoring systems do not effectively encourage users to interact with the device at a frequency that maximizes their benefits, leading to increased risks of hyperglycemic or hypoglycemic episodes.
Innovation Solution
A system that monitors user interaction frequency, compares it to predetermined target levels, and alerts users when interaction falls below these levels, with adjustable settings based on user history, activity, and analyte levels, and includes rewards and alarms to encourage consistent engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If continuous glucose monitoring is provided with frequent analyte level availability, then users can obtain accurate analyte levels at short intervals, but users may not interact with the system frequently enough to derive full benefit
Solution Approach 1:
The system monitors user interaction frequency and provides feedback by comparing actual interaction to target interaction levels. When interaction falls below the target, the system generates alerts to encourage users to engage with the device more frequently, creating a closed-loop feedback mechanism that addresses the contradiction between high-frequency data availability and actual user engagement.
Solution Approach 2:
The target interaction level is not fixed but can be adjusted based on user needs, activity level, and analyte levels. This dynamic adjustment allows the system to adapt the expected interaction frequency to match current physiological conditions and user behavior patterns, making the monitoring requirement more flexible and responsive to actual needs.
2Measurement precision
If manual periodic glucose testing is used, then users can monitor glucose levels, but consistency of testing varies widely among individuals
Solution Approach 1:
The system automatically monitors user interaction with the device and self-adjusts by generating alerts when interaction falls below target levels. This self-monitoring and self-correcting mechanism eliminates the need for users to manually track their own testing consistency, providing stable and consistent monitoring engagement without requiring user discipline or remembrance.
3Measurement precision
If in vivo glucose sensors provide continuous monitoring, then accurate analyte levels are available at frequent intervals, but patients derive little or no benefit if they do not frequently interact with the system
Solution Approach 1:
The system establishes a feedback loop that monitors whether users are actually utilizing the continuous monitoring capability. By comparing actual interaction frequency against target levels and providing alerts when interaction is insufficient, the system ensures that the accurate analyte level data is actually viewed and acted upon by the user, making the continuous monitoring reliable and beneficial.
Solution Approach 2:
The system pre-establishes target interaction levels based on user needs and clinical guidelines before monitoring begins. These predetermined targets serve as a framework to guide user interaction, ensuring that users know in advance what level of engagement is expected and needed to derive benefit from the continuous monitoring capability.
Data Source
AI summary
Methods and Devices to monitor the level of at least one analyte are provided.