Analyte Sensor Data Verification for Sensitivity Variation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing analyte monitoring systems face challenges in tolerating a wide range of sensor sensitivities and require improved data processing and control methods to ensure accurate and reliable glucose monitoring.
Innovation Solution
A method and apparatus for initializing data condition identifiers, performing data verification routines, and storing values associated with these identifiers to manage conditions related to the operation of an analyte monitoring device, including temperature compensation, sensor insertion detection, and data quality verification, are implemented to enhance data processing and control in medical telemetry systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If a transcutaneous analyte sensor is used to detect analyte levels, then continuous monitoring capability is improved, but sensor sensitivity variation and data reliability deteriorate
Solution Approach 1:
The system performs preliminary actions by initializing data condition identifiers and executing verification routines before main monitoring operations begin. The transmitter unit prepares by setting up data condition identifiers (1120) and performing verification routines (1130) to establish baseline sensor functionality and detect potential issues early in the sensor lifecycle.
Solution Approach 2:
The system implements feedback mechanisms through data verification routines that continuously monitor sensor data quality and transmit condition information to the receiver unit. The receiver unit receives and processes data condition identifiers (1140) to provide feedback about sensor status, enabling continuous assessment of data reliability throughout the monitoring period.
2Ease of manufacture
If sensor sensitivity tolerance range is increased for manufacturing flexibility, then ease of manufacture is improved, but measurement precision deteriorates
Solution Approach 1:
The system addresses parameter variations by implementing verification routines that assess sensor response characteristics and set data condition identifiers based on measured sensitivity parameters. The transmitter unit compares sensor data against expected ranges and adjusts data condition flags (1120) to reflect actual sensor performance, allowing the system to accommodate manufacturing variations while maintaining measurement accuracy through parameter-based verification.
3Reliability
If data verification routines are implemented to ensure data quality, then reliability is improved, but device complexity increases
Solution Approach 1:
The verification system is segmented into distinct functional components: the transmitter unit executes verification routines and generates data condition identifiers (1120, 1130), while the receiver unit receives and processes these identifiers separately (1140). This segmentation distributes complexity across multiple units rather than concentrating all verification logic in one device, making the overall system more manageable while maintaining comprehensive data quality assurance.
Data Source
AI summary
Methods and apparatus for providing data processing and control for use in a medical communication system are provided.