Analyte Sensor Data Processing for Continuous Glucose Monitoring
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Solution Overview
Problem
Conventional self-monitoring blood glucose (SMBG) methods for diabetes management are uncomfortable, inconvenient, and often result in delayed detection of hyperglycemic or hypoglycemic conditions due to infrequent measurements, leading to potential dangerous side effects.
Innovation Solution
A method and system for analyzing data from analyte sensors that calculates the rate of change of sensor data, smoothing techniques such as moving averages or filters are applied, and determines acceptability by comparing sensor data to reference data using boundary tests, enabling more frequent and accurate glucose level monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional self-monitoring blood glucose (SMBG) methods are used, then the measurement process is simple and requires minimal equipment, but the monitoring frequency is low (2-4 times per day) and timing is delayed, leading to late detection of glycemic conditions
Solution Approach 1:
The patent replaces the mechanical finger-pricking SMBG method with an electrochemical continuous glucose monitoring system. The analyte sensor continuously measures glucose levels in interstitial fluid, eliminating the need for repeated manual blood sampling and enabling real-time monitoring without mechanical intervention at each measurement point.
Solution Approach 2:
The system transitions from discrete intermittent measurements to continuous monitoring. The analyte sensor continuously generates glucose level data, and the processor continuously analyzes this data to detect glycemic conditions, ensuring uninterrupted monitoring and immediate detection of hyperglycemic or hypoglycemic events.
2Measurement precision
If noise detection and data smoothing algorithms are implemented, then the accuracy of rate of change calculation is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary data processing by detecting noise and applying smoothing algorithms to sensor data before calculating the rate of change. This preprocessing step ensures that the rate of change calculation is based on cleaned, reliable data, improving accuracy while managing computational complexity through structured processing stages.
Solution Approach 2:
The data processing is divided into distinct segments: noise detection, data smoothing, and rate of change calculation. This segmentation allows each processing stage to be optimized independently, with the smoothing step preparing data for the subsequent calculation step, making the overall complex process more manageable and efficient.
Data Source
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AI summary
The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for processing sensor data, including calculating a rate of change of sensor data and/or determining an acceptability of sensor or reference data. A system for measuring an analyte in a host is provided that includes a continuous analyte sensor 10, a receiver 158, and an external device 180.