Glucose Monitoring Calibration Control During Sensor Signal Errors
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Solution Overview
Problem
Continuous Glucose Monitoring Systems (CGMS) often provide inaccurate blood glucose values due to sensor errors, such as excessive pressure or instability, causing user confusion.
Innovation Solution
An electronic apparatus that detects errors in sensor signals by monitoring the rate of change of analyte concentration, adjusts thresholds based on user sleep status, and deactivates calibration input elements during errors, while calibrating sensor data using user-provided information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system continuously displays sensor data to provide real-time monitoring, then user awareness of glucose levels is improved, but user confusion increases when sensor errors occur
Solution Approach 1:
The system implements feedback by monitoring the rate of change of sensor data and comparing it against physiological thresholds. When the rate of change exceeds expected ranges, the system detects potential sensor errors and responds by adjusting display behavior, thereby maintaining reliability while preventing user confusion from erroneous readings
Solution Approach 2:
The display behavior is made dynamic based on sensor data quality. The system transitions between different display states (normal display vs. error indication) based on real-time analysis of sensor signal validity, allowing the interface to adapt its information presentation according to current sensor reliability conditions
2Measurement precision
If the system accepts calibration input from users to improve accuracy, then measurement precision is improved, but the risk of accepting incorrect calibration during sensor errors increases
Solution Approach 1:
The system performs preliminary validation of sensor data by analyzing the rate of change before accepting calibration inputs. By pre-checking whether sensor readings are within physiologically plausible ranges, the system ensures that calibration requests are only accepted when the sensor is providing reliable data, thus maintaining measurement precision without compromising reliability
Solution Approach 2:
The system uses feedback from rate-of-change analysis to control the availability of calibration functions. When sensor errors are detected through rate-of-change monitoring, the system provides feedback by disabling or warning against calibration input, preventing users from entering incorrect calibration values during periods of sensor malfunction
3Reliability
If the system monitors rate of change to detect sensor errors, then reliability is improved, but device complexity increases
Solution Approach 1:
The system monitors changes in the parameter of glucose concentration over time and compares the rate of change against predefined thresholds. This parameter-based approach to error detection provides a simple yet effective method for improving reliability without requiring complex algorithms, as it relies on straightforward mathematical comparisons of consecutive readings
Data Source
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AI summary
Provided are an electronic apparatus and a method of controlling the same. The method includes receiving a sensor data related to a concentration of an analyte from an analyte monitoring device at least partially implantable beneath a skin of a user; displaying a UI element for receiving a calibration information from the user, wherein the concentration of the analyte is acquired based on the sensor data and the calibration information; and deactivating the UI element when an error related to the sensor data is detected.