Analyte Sensor Signal Attenuation Detection and Data Gap Backfilling
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Solution Overview
Problem
Existing analyte monitoring systems face challenges in accurately processing sensor data during adverse conditions, leading to gaps in data output and potential inaccuracies due to unsuitable calibration periods or system malfunctions.
Innovation Solution
The system includes a method to detect adverse conditions, disable data output during such periods, retrieve stored data, and process it using calibration parameters from a successful calibration event to backfill the gaps in the data display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system disables data output during adverse conditions to prevent inaccuracies, then data reliability is improved, but data continuity is worsened due to gaps in output
Solution Approach 1:
The system performs preliminary actions by storing sensor data in memory during adverse conditions before calibration is restored. This allows the data to be processed and output later, maintaining data continuity while ensuring reliability by not outputting potentially inaccurate data during the adverse condition period.
Solution Approach 2:
The system introduces an intermediary storage mechanism (memory) that holds sensor data during adverse conditions. This intermediary allows the system to maintain data continuity by retrieving and processing stored data after calibration is restored, while still ensuring reliability by preventing direct output of potentially inaccurate data during the adverse condition.
2Duration of action of stationary object
If the system processes sensor data continuously without calibration checks, then data continuity is maintained, but measurement precision deteriorates due to unsuitable calibration periods
Solution Approach 1:
The system implements feedback by continuously monitoring calibration status and system conditions. When adverse conditions are detected (such as unsuitable calibration periods), the system adjusts its data processing behavior by disabling output and storing data instead. This feedback loop ensures measurement precision is maintained by preventing output of data obtained during unsuitable calibration periods, while still maintaining data continuity through proper calibration management.
3Loss of information
If the system retrieves and processes stored data after calibration restoration, then data completeness is improved, but processing complexity increases
Solution Approach 1:
The system performs self-service by automatically retrieving, processing, and outputting stored sensor data after calibration is restored, without requiring external intervention. This self-service mechanism improves data completeness by ensuring all stored data is eventually processed and output, while managing processing complexity through automated routines that handle the retrieval and processing workflow.
Data Source
AI summary
Provided are methods and apparatus for receiving sensor data from an analyte sensor of a sensor monitoring system, processing the received sensor data with time corresponding calibration data, outputting the processed sensor data, detecting one or more adverse conditions associated with the sensor monitoring system, disabling the output of the sensor data during the adverse condition time period, determining that the one or more detected adverse conditions is no longer present in the sensor monitoring system, retrieving the sensor data during the adverse condition time period, processing the retrieved sensor data during the adverse condition time period, and outputting the processed retrieved sensor data.