Continuous Glucose Sensor Signal Processing
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Solution Overview
Problem
Conventional glucose sensors, both implantable and transdermal, face challenges in providing accurate and continuous blood glucose monitoring, often resulting in delayed detection of hyperglycemic or hypoglycemic events due to inaccuracies and short-term sensing, which can lead to dangerous health consequences for diabetic patients.
Innovation Solution
A system and method for processing data from a continuous glucose sensor that includes intelligent calibration, noise artifact detection, and signal filtering, utilizing a dual-electrode system to generate signals that isolate glucose-related data from non-glucose related noise, enabling real-time monitoring and prediction of glycemic episodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional glucose sensors are used for continuous monitoring, then real-time glucose detection is achieved, but measurement precision deteriorates due to noise and inaccuracies
Solution Approach 1:
The sensor signal is segmented into multiple frequency components using wavelet transform. By dividing the signal into different frequency bands, the method separates glucose-related information from noise artifacts, allowing real-time processing while maintaining measurement precision through selective frequency analysis.
Solution Approach 2:
The patent extracts glucose-related signal components by removing noise artifacts through wavelet thresholding. The harmful noise components are identified and extracted separately from the useful glucose signal, then eliminated to preserve only the meaningful physiological data for accurate real-time monitoring.
2Duration of action of stationary object
If implantable glucose sensors are used, then continuous sensing capability is improved, but reliability deteriorates due to short-term sensing and complications
Solution Approach 1:
The system performs preliminary calibration and noise characterization before actual glucose monitoring begins. By pre-processing the sensor signal to establish baseline behavior and filter characteristics, the method ensures reliable continuous sensing from the start of deployment, avoiding the short-term instability issue.
Solution Approach 2:
The patent implements continuous feedback processing where sensor output is constantly analyzed, calibrated, and corrected in real-time. The system monitors signal quality metrics and adjusts processing parameters dynamically, ensuring maintained reliability over extended continuous operation periods.
3Duration of action of stationary object
If transdermal sensors are used for extended period sensing, then duration of action is improved, but measurement precision worsens due to inaccurate glucose values
Solution Approach 1:
The patent employs dynamic adaptive filtering where filter parameters are continuously adjusted based on signal characteristics. As the sensor operates over extended periods, the system adapts to changing physiological conditions and sensor drift, maintaining measurement precision throughout the extended monitoring duration.
Solution Approach 2:
The method changes processing parameters dynamically based on signal quality and physiological state. By adjusting wavelet decomposition levels, threshold values, and filtering characteristics in response to changing conditions, the system maintains accurate glucose measurements over extended periods despite varying operational environments.
4Device complexity
If conventional SMBG methods are used, then device complexity is reduced, but loss of information increases due to missed glucose trends
Solution Approach 1:
The patent introduces an intermediary processing layer between the simple sensor and the user that automatically analyzes glucose trends. This intermediary system performs complex signal processing, calibration, and trend analysis, presenting simplified actionable information to the user while capturing complete glucose dynamics that would otherwise be lost.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate, real-time glucose monitoring, reducing the risk of dangerous glycemic events by filtering out noise and ensuring timely intervention, thereby improving the management of diabetes.
Implementation Method 1
a first working electrode configured to generate a first signal responsive to both an analyte and non-analyte electroactive compounds
Implementation Method 2
a second working electrode configured to generate a second signal responsive to non-analyte electroactive compounds
Implementation Method 3
a processor module configured to subtract the second signal from the first signal to generate a third signal responsive only to the analyte
Data Source
Figure 1A~1B
Figure 1C
Figure 2
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.