Glucose Sensor Calibration via Time Lag Compensation
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Solution Overview
Problem
Conventional glucose sensors for diabetes management are plagued by inaccuracies and discomfort, with existing implantable and transdermal sensors providing short-term and less-than-accurate glucose monitoring, and conventional self-monitoring methods failing to provide timely and continuous real-time blood glucose information, leading to delayed detection of dangerous hyperglycemic or hypoglycemic conditions.
Innovation Solution
A method and system for calibrating glucose sensor data by matching reference glucose values with sensor glucose values, either immediately or after compensating for a time lag, to rapidly and accurately display estimated analyte values, utilizing a processor module to process data from continuous glucose sensors and adjust calibration states, and a system that includes a user interface for displaying calibration information and setting modes based on glucose thresholds and user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional self-monitoring blood glucose methods are used, then the diabetic can obtain glucose readings, but the measurements are delayed and do not provide real-time information
Solution Approach 1:
The system performs preliminary calibration by matching sensor data with reference data before continuous monitoring begins, establishing an accurate baseline relationship. This preliminary action ensures that when continuous monitoring starts, the system is already calibrated and ready to provide immediate real-time glucose information without delay.
Solution Approach 2:
The system continuously compares sensor-generated glucose values with reference meter values and uses this feedback to dynamically adjust and refine the calibration relationship. This feedback mechanism maintains measurement accuracy over time and ensures real-time detection of glycemic events by constantly validating sensor readings against reference standards.
2Duration of action of stationary object
If implantable or transdermal glucose sensors are used for continuous monitoring, then real-time glucose data can be obtained, but the sensors provide only short-term and less-than-accurate sensing
Solution Approach 1:
The system implements dynamic calibration that adapts over time by continuously matching sensor readings with reference measurements. The calibration relationship is not fixed but evolves dynamically, allowing the system to maintain high accuracy throughout the sensor's lifetime by adjusting to changes in sensor performance and biological conditions.
Solution Approach 2:
The system changes the calibration parameters by matching sensor data with reference data at different time points and conditions. This parameter adjustment allows the system to compensate for sensor drift and degradation over time, maintaining measurement accuracy throughout the extended monitoring period rather than relying on a single initial calibration.
3Measurement precision
If sensor data is matched with reference data to form calibration, then accurate glucose values can be obtained, but the calibration process may take time
Solution Approach 1:
The system performs preliminary calibration matching before continuous monitoring begins, establishing the initial sensor-to-reference relationship in advance. This preliminary action ensures that when monitoring starts, the calibration is already complete and the system can immediately provide accurate real-time glucose values without calibration delays.
Solution Approach 2:
The calibration process is made continuous rather than periodic, with the system constantly matching sensor data with reference data as new measurements become available. This continuous calibration approach maintains accuracy without requiring separate calibration sessions, as the useful action of calibration occurs continuously in the background alongside monitoring.
Data Source
AI summary
Systems and methods for processing sensor data are provided. In some embodiments, systems and methods are provided for calibration of a continuous analyte sensor. In some embodiments, systems and methods are provided for classification of a level of noise on a sensor signal. In some embodiments, systems and methods are provided for determining a rate of change for analyte concentration based on a continuous sensor signal. In some embodiments, systems and methods for alerting or alarming a patient based on prediction of glucose concentration are provided.