UV Fluorescence Analyte Testing With IR Skin Compensation
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Solution Overview
Problem
Existing non-invasive analyte testing methods, such as Raman spectroscopy and hyperspectral data analysis, face challenges in accurately measuring analytes like blood glucose due to interference from skin tissue components and varying skin conditions, leading to inaccurate results and high costs, and lack portability and real-time capabilities.
Innovation Solution
A method utilizing infrared and ultraviolet light to image and obtain spectral data, with compensation based on grayscale differences between testing and reference points, enabling accurate analyte measurement by excluding non-analyte influences and minimizing system size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Raman spectroscopy is used for non-invasive blood glucose measurement, then measurement accuracy is improved, but device size and cost increase significantly
Solution Approach 1:
The patent extracts and utilizes the natural fluorescence emission from glucose molecules in the skin, separating this useful signal from the complex background. By focusing on the intrinsic fluorescence property of glucose rather than using complex Raman scattering mechanisms, the system achieves accurate measurement with simpler, more compact equipment.
Solution Approach 2:
The patent changes the detection parameter from Raman scattering intensity to fluorescence emission intensity. This parameter change enables the use of simpler detectors and light sources, reducing device complexity while maintaining measurement accuracy for blood glucose concentration.
2Reliability
If absorption spectroscopy with hyperspectral data is used for non-invasive testing, then non-invasive measurement is achieved, but spectral signal separation becomes difficult due to mixing of blood glucose and skin tissue signals
Solution Approach 1:
The patent segments the spectral analysis by focusing on specific fluorescence emission wavelengths characteristic of glucose molecules. Instead of analyzing the entire hyperspectral range, the system isolates and analyzes only the glucose-specific fluorescence signals, effectively separating them from skin tissue background signals.
Solution Approach 2:
The patent uses fluorescence emission as an intermediary signal that naturally separates glucose information from skin tissue information. The fluorescence signal acts as a mediator that carries glucose concentration information while being inherently distinguishable from skin tissue absorption signals.
3Measurement precision
If multiple sensors and modules are used to collect biological signals from different body positions, then comprehensive data is obtained, but system complexity and cost increase, and portability is reduced
Solution Approach 1:
The patent makes the single imaging device universal by enabling it to perform both structural imaging (to locate blood vessels) and spectral analysis (to measure glucose concentration) functions. This multi-functionality eliminates the need for separate sensors at multiple body positions, reducing device complexity while maintaining comprehensive measurement capability.
4Quantity of substance
If spectral signals from different wavelengths are mixed together for analysis, then comprehensive spectral data is obtained, but fine separation and extraction of blood glucose signals becomes difficult
Solution Approach 1:
The patent extracts only the fluorescence emission spectral components related to glucose from the mixed spectral data. By selectively extracting the glucose-specific fluorescence wavelengths and excluding other wavelength components, the system achieves precise blood glucose signal separation while maintaining the essential spectral information needed for accurate measurement.
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 allows for non-invasive, real-time, and cost-effective analyte testing with improved accuracy by distinguishing analyte signals from skin variations, using fluorescence spectroscopy and machine learning models to compensate for depth and thickness effects.
Implementation Method 1
irradiating a first area by infrared light within a first wavelength range and imaging the first area, to obtain a first image of an imaging area, where the first image includes data that indicate grayscale distribution in the imaging area of a reflection signal generated by the analyte when irradiated by the infrared light
Implementation Method 2
irradiating the first area by ultraviolet light within a second wavelength range and imaging the first area, to obtain a second image of the imaging area, where the second image includes spectral data that indicate a fluorescence radiation signal in the imaging area excited by the analyte when irradiated by the ultraviolet light
Data Source
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AI summary
The present invention provides a method and a system for testing an analyte, a medium, and a device. The method includes: imaging: irradiating a first area by infrared light within a first wavelength range and imaging the first area; and irradiating the first area by ultraviolet light within a second wavelength range and imaging the first area; spectral obtaining: selecting a testing point and a reference point from the second image to obtain information about the analyte in the imaging area, where the information about the analyte includes information about the analyte correlated to the spectral data; and compensating: compensating the information about the analyte based on a grayscale difference between the testing point and the reference point in the first image. In this application, spectral data in different areas is analyzed, to provide a more accurate test result.