Exposure Calibration for Fluorescence Analyte Imaging on Skin
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Solution Overview
Problem
Existing analyte testing technologies face challenges such as invasiveness, high cost, bulkiness, and inaccuracy due to variations in human skin colors and testing scenarios, particularly in non-invasive methods like Raman spectroscopy and electrochemical sensors.
Innovation Solution
A method and system for adjusting photographing parameters using infrared and ultraviolet light sources to capture grayscale images, establishing linear relationships between exposure time and grayscale values, and utilizing fluorescence spectroscopy for analyte testing, enabling real-time, non-invasive, and accurate analyte concentration measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If Raman spectroscopy is used for non-invasive testing, then user acceptance improves, but device portability and cost worsen
Solution Approach 1:
The patent changes the fundamental testing parameter from Raman spectroscopy to fluorescence spectroscopy. This parameter change enables the use of simpler, more portable excitation light sources and detectors, directly resolving the portability issue while maintaining non-invasive testing and real-time measurement capabilities
Solution Approach 2:
The patent employs cost-effective fluorescence spectroscopy components instead of expensive Raman spectroscopy systems. This includes using standard LED or laser light sources and conventional photodetectors, which are significantly cheaper than the specialized equipment required for Raman testing, thereby reducing device cost
2Adaptability or versatility
If different exposure times are used for imaging, then adaptability to different skin colors improves, but system complexity increases
Solution Approach 1:
The patent implements preliminary calibration by establishing linear function relationships between exposure time and average grayscale values for different light sources before actual testing. This pre-established calibration data allows the system to automatically adapt to different skin colors during testing without requiring complex real-time adjustments, thus improving adaptability while keeping the system relatively simple
Solution Approach 2:
The patent uses feedback mechanisms where the system measures the actual grayscale values obtained from images, compares them with expected values from calibration data, and adjusts exposure times accordingly. This feedback loop enables automatic adaptation to different skin colors and testing conditions without manual intervention
3Measurement precision
If linear function relationships are established for parameter adjustment, then testing accuracy improves, but calculation complexity increases
Solution Approach 1:
The patent transforms the complex problem of image parameter adjustment into a simple linear parameter relationship. By establishing linear function relationships between exposure time and grayscale values, the system can accurately adjust imaging parameters through simple linear calculations rather than complex iterative optimization, thereby improving testing accuracy while minimizing calculation complexity
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
The method reduces the influence of skin color and testing scenarios, achieves non-invasive testing, lowers costs, and enables miniaturization with real-time results, improving testing accuracy and convenience.
Implementation Method 1
utilizing fluorescence spectroscopy for analyte testing
Data Source
AI summary
The present invention provides a photographing parameter adjustment method and system in analyte testing, a medium, and a device. The method includes: in a plurality of different exposure time, exposing and imaging a first area by using a first light source, to obtain a first image, and exposing and imaging the first area by using a second light source, to obtain a second image; respectively calculating average grayscale values of pixels in reference areas based on the reference areas; respectively establishing linear function relationships between the exposure time and the average grayscale values; and inputting a grayscale value of the first image into the linear function relationship, to obtain an exposure time after first light source adjustment, and inputting a grayscale value of the second image into the linear function relationship, to obtain an exposure time after second light source adjustment.