Infrared Vessel Image Processing for Noninvasive Glucose Testing
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Solution Overview
Problem
Existing analyte testing technologies face challenges such as invasiveness, high cost, bulkiness, and inaccurate measurements due to mixed spectral signals and interference from skin components, making it difficult to achieve precise and portable glucose monitoring.
Innovation Solution
An image processing method that utilizes infrared and ultraviolet light to distinguish between blood vessel and non-blood vessel areas on the skin, selects candidate points based on grayscale gradients, and employs fluorescence spectroscopy for accurate analyte concentration measurement, using a portable device with a light source and imaging spectrum detection apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Raman spectroscopy is used for non-invasive in vivo measurement, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and eliminates the harmful spectral signals from skin tissue components while retaining the useful spectral signals from blood glucose. By using image processing to identify and select only the spectral signals from blood vessel areas, the method removes the interfering signals from surrounding skin tissue, achieving accurate glucose measurement without requiring complex laboratory-level Raman spectroscopy systems.
Solution Approach 2:
The patent introduces image processing technology as an intermediary step between light irradiation and spectral signal analysis. The image processing module processes infrared grayscale images to identify blood vessel locations, which then guides the selection of spectral signal acquisition positions. This intermediary approach enables portable device implementation while maintaining measurement precision.
2Ease of operation
If spectral signals from mixed areas are collected, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent segments the skin surface into different functional areas by processing infrared grayscale images to distinguish blood vessel areas from non-blood vessel areas. This segmentation is achieved through image processing that identifies grayscale gradient characteristics, allowing the system to selectively acquire spectral signals only from the relevant blood vessel areas, thereby improving measurement precision while maintaining operational simplicity.
Solution Approach 2:
The patent applies local quality by treating different regions of the skin surface differently. Instead of uniformly collecting spectral signals from the entire measurement area, the system identifies specific local regions (blood vessel areas) with distinct grayscale characteristics and acquires spectral signals only from these localized areas. This approach enhances measurement accuracy by focusing on the most relevant regions.
3Productivity
If outlier points are included in analysis, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent performs preliminary action by conducting image processing and outlier point detection before spectral signal analysis. The system processes infrared grayscale images to identify and eliminate outlier points that do not correspond to blood vessel areas. This preliminary filtering ensures that only valid spectral signals from blood vessel regions are included in subsequent glucose concentration calculations, maintaining both efficiency and precision.
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
Enables accurate, non-invasive, and cost-effective analyte testing by distinguishing between vessel and non-vessel areas, reducing outlier influence, and correlating spectral data directly with analyte concentration, facilitating real-time and miniaturized glucose monitoring.
Implementation Method 1
uses a light source and an imaging spectrum detection apparatus
Implementation Method 2
employs fluorescence spectroscopy for accurate analyte concentration measurement
Data Source
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AI summary
The present invention provides an image processing method and system in analyte testing, a medium, and a device. The method includes: image obtaining step: obtaining an infrared grayscale image by imaging a first area; dividing: based on a pixel gradient, distinguishing a dark spot from a bright spot, and dividing the infrared grayscale image into a dark spot area and a bright spot area; point selecting step: calculating and selecting first target candidate points; and selecting step: performing outlier point detection and selection on the first target candidate points, and obtaining a position of a first target.