Non-invasive neurodegenerative disease risk detection method
Detection of AGEs in the skin through autofluorescence multispectral imaging technology solves the problem of early diagnosis of neurodegenerative diseases, realizes non-invasive and economical risk assessment and treatment effect monitoring, and supports individualized medical care.
Patent Information
- Application Number
- CN202410004881.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-03
- Publication Date
- 2025-07-04
AI Technical Summary
The existing neurodegenerative disease detection methods have problems such as difficulty in early diagnosis, strong invasiveness and high cost. They lack effective means to monitor disease progression and treatment effects, and cannot understand the changes in the disease in a timely manner.
Using autofluorescence multispectral imaging technology, the fluorescence characteristics of advanced saccharified end products (AGEs) in the skin are detected, and fluorescent images are captured using a camera equipped with a specific optical bandpass filter, combining image analysis and machine learning algorithms to evaluate the risk of neurodegenerative diseases.
It has achieved non-invasive, early and economical risk monitoring of neurodegenerative diseases, which can identify risks before symptoms appear, help with early intervention, and monitor changes in AGEs levels during treatment, providing a basis for individualized medical care.
Smart Images
Figure CN120240956A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of biomedical imaging technology. Specifically, it relates to a non-invasive method for detecting advanced glycation end products (AGEs), which are oxidative stress markers in organisms and foods, and for monitoring the risk of neurodegenerative diseases in organisms. Background Art
[0002] Neurodegenerative diseases are a group of diseases that affect the central and peripheral nervous systems, and their main characteristic is the gradual loss of function and eventual death of nerve cells. These diseases are usually associated with aging and can lead to the loss of cognitive, motor, and sensory functions. Typical neurodegenerative diseases include Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis (ALS), and multiple sclerosis.
[0003] In the development of neurodegenerative diseases, advanced glycation end products (AGEs) play an important role, especially pentosidine, which has been used as a biomarker for the diagnosis of Alzheimer's disease in research. AGEs are glycated proteins or lipids formed after exposure to sugars, and their formation promotes protein deposition due to anti-protease cross-linking between peptides and proteins. For example, in Alzheimer's disease (AD), the accumulation of amyloid-β protein (Aβ) and tau protein is an important hallmark of the disease, and the accumulation of AGEs has been observed in different cortical regions of senile plaques, primitive plaques, the crown of classical plaques, and some glial cells in the AD brain. In addition, AGE-mediated protein cross-linking significantly accelerates the polymerization of β-amyloid protein. The expression of amyloid precursor protein (APP) is upregulated by AGEs both in vitro and in vivo, leading to an increase in β-amyloid protein levels. Neurofibrillary tangles (NFTs) are one of the main markers of AD and are formed by the aggregation of hyperphosphorylated microtubule-associated tau protein. It has been reported that AGEs induce hyperphosphorylation of tau protein through RAGE receptor activation and impair synapses and memory in rats. These data suggest that in addition to the role of AGEs in the formation and aggregation of β-amyloid protein, AGEs are also involved in the formation of NFTs.
[0004] The sources of advanced glycation end products (AGEs) can be divided into two major categories: endogenous and exogenous. Endogenous sources include the interaction between proteins and sugar molecules during the natural aging process, persistent hyperglycemic states, inflammatory responses, and oxidative stress, etc., all of which promote the formation and accumulation of AGEs in the body. Exogenous sources mainly involve dietary factors, such as AGEs formed during high-temperature cooking (roasting, frying, frying), as well as smoking and certain environmental pollutants. Controlling and monitoring the formation and accumulation of AGEs at any time is the key to preventing and managing health problems related to neurodegenerative diseases.
[0005] Currently, the detection methods for neurodegenerative diseases mainly include clinical assessment, neuroimaging scans, biomarker detection, etc. The problem is that many neurodegenerative diseases have no obvious symptoms in the early stage, making early diagnosis difficult. When the symptoms become obvious, the disease often has progressed to a relatively late stage. Currently, effective detection methods (such as cerebrospinal fluid analysis) are often somewhat invasive, bringing discomfort and risks to patients. Although imaging detection methods such as MRI and CT scans can provide useful information, they mainly evaluate the structural changes in the brain, and these changes are often significant only in the late stage of the disease. For some advanced detection methods, such as PET scans, the high cost limits their practicality in widespread clinical applications. Moreover, there is currently a lack of effective means to monitor the progression of the disease and the effectiveness of treatment, and it is impossible to timely understand and intervene in the changes in the patient's condition.
[0006] Therefore, although the current detection methods can diagnose and evaluate neurodegenerative diseases to a certain extent, there is an urgent need to improve the early detection, convenience, and economy, and to achieve the real-time monitoring of the risk of neurodegenerative diseases without causing discomfort to the subjects, which has important practical significance for improving people's health level and preventing and treating related diseases. Summary of the Invention
[0007] To achieve the above goals, the present invention has developed an innovative, non-invasive method for detecting the risk of neurodegenerative diseases, specifically involving using autofluorescence multispectral imaging to evaluate the accumulation of advanced glycation end products (AGEs) in the skin for predicting the risk of neurodegenerative diseases, providing a new tool for individual health monitoring, and also bringing an important technology to the medical and health field.
[0008] The method of the present invention is based on the autofluorescence characteristics of advanced glycation end products (AGEs), including Pentosidine. When these substances are irradiated by electromagnetic excitation of a specific wavelength, they can emit fluorescence of a specific wavelength. A camera equipped with a specific optical bandpass filter is used to capture the light of these wavelengths, recorded as an image. Through image analysis and calibration, an initial applicable region mask is selected, the level of skin autofluorescence glycation end products (AGEs) is calculated, and the risk of neurodegenerative diseases is predicted.
[0009] Multispectral imaging is an advanced imaging method that analyzes and captures the spectral characteristics of substances by using light of different wavelengths, especially in complex biological tissues, to identify and quantify the distribution of the fluorescence characteristics of AGEs in the skin or other tissues. The key to this method is that it can simultaneously obtain images of the same region in different spectral bands, thereby providing detailed spectral information about this region.
[0010] The invention relates to a device equipped with a monochromatic camera with spectral imaging, a lens, an optical band-pass filter, an adjustable excitation light source, and an image analysis and processing system. The device includes a fluorescence image acquisition module for fluorescence image acquisition and a data processing module for image analysis and predicting the risk of neurodegenerative diseases. By non-invasively irradiating living skin tissue or the surface of an object, spontaneous fluorescence measurements of the skin tissue or surface can be obtained, which can be used as a measure of the content of advanced glycation end products (AGEs) and detect the risk of neurodegenerative diseases. Among them, the living skin tissue is clinically healthy skin tissue, and local abnormal skin tissues such as moles, warts, scars, sunburn-affected skin tissues, tattoos, and very hairy skin tissues should be avoided as much as possible. When measuring, try to select skin areas that are not often exposed to sunlight, and curved areas such as the nose should be avoided. When detecting multiple times, try to fix the measurement at the same location. At the same time, try to avoid detecting areas where the skin is often treated with skin care products such as moisturizing creams, lotions, and sunscreens.
[0011] As Figure 1 shown, it is a non-invasive neurodegenerative disease risk detection system, including a fluorescence image acquisition module 12. Among them, it includes two ultraviolet excitation light sources 1, 2, and two monochromatic cameras 3, 4 are respectively equipped with medium-distance lenses and used together with optical band-pass filters 5, 6, and are installed in a support structure in the shape of a light-shielding housing 16. The housing 16 has a contact surface 14, and this contact surface is attached to the skin or sample surface 15. An opening on the contact surface 14 forms an irradiation window 17, and through this irradiation window, a part of the skin or object surface located behind the irradiation window and adjacent to the window opening can be irradiated. The irradiation window can be rectangular, circular, or other shapes. The images taken by the two monochromatic cameras 3, 4 are transmitted to the data processing module 13 through video data lines 11. 7 is an image processing and analysis unit, which performs neurodegenerative disease risk analysis at 9 and displays the detection results on the touch display screen at 10. If there is no risk of neurodegenerative diseases through the AGEs level analysis and evaluation, one can choose whether to conduct a cognitive assessment answering test. If there is a risk of neurodegenerative diseases, the system automatically enters the cognitive assessment answering test. 8 is a cognitive assessment test unit. If a test is required, it can be conducted on the touch display screen at 10.
[0012] Among them, the ultraviolet excitation light sources 1, 2 can be selected from ultraviolet ring lights, LED ultraviolet lights, fluorescent lights, etc., with a power of 8 watts or more, and the excitation light wavelength is in the range of 355 - 365 nanometers, which can excite the fluorescence characteristics of AGEs to emit fluorescence.
[0013] The monochromatic cameras 3, 4 and the lens selection can capture luminance information, featuring high sensitivity and higher spatial resolution. The focal length of the lens can be 8 - 10 mm, or adjusted as needed, such as selecting an 8 mm C-mount lens. The two monochromatic cameras are close to each other, with the distance between them in the range of 20 - 40 mm.
[0014] The optical band-pass filters 5, 6 are selected according to the need to capture different wavelength ranges and different types of light. In the invention, the two band-pass filters respectively select a filter for detecting autofluorescence and a filter for diffuse reflection ultraviolet light. The wavelength range of the fluorescence filter is 450 - 500 nm, and the wavelength range of the diffuse reflection ultraviolet light filter is 310 - 390 nm.
[0015] The image acquisition and transmission of the two monochromatic cameras are carried out using the video data line 11. The shooting is started and stopped simultaneously through a computer program using specific software, and the images are acquired. This control ensures that the two cameras capture images at the same moment, facilitating image processing and analysis. Each camera records a set of images. To reduce the impact caused by movement, the entire image acquisition process is completed quickly, usually within a few seconds.
[0016] The irradiation window 17 needs to maintain a certain distance from the contact surface 14 through the light-shielding housing for convenient measurement. The area of the contact surface 14 needs to be larger than the area of the irradiation window 17 to combine a large irradiated and measured skin or object surface with a compact measuring instrument.
[0017] Operating steps:
[0018] a. Use the images taken of the ultraviolet-exposed fluorescent object for calibration and calculate the calibration factor.
[0019] b. Select a representative skin area for imaging, which can be the inner arm, face or inner calf. Align the excitation source of the detection instrument with the skin surface of the subject or the surface of the sample to be measured, and the excitation source emits light of a specific wavelength for excitation.
[0020] c. Obtain images from the two cameras simultaneously. Each camera records a set of images, and they are taken respectively in the states when the ultraviolet excitation light source is on and off.
[0021] d. Process and analyze the captured images using specific software. First, perform image reconstruction processing, including geometric and spectral correction, to ensure that the captured images reflect the true skin condition. Next, conduct feature extraction, using a mask selection process to analyze the images of non-specular reflection regions, which involves identifying spectral features related to AGEs fluorescence and separating these features from the images. Then, enhance the signal, such as through filtering processing and contrast adjustment, to improve the clarity and detectability of the fluorescence signal. Finally, perform quantitative analysis using machine learning algorithms, such as MATLAB, Python combined with OpenCV, etc., and calculate the quantitative level of AGEs based on the fluorescence intensity and distribution.
[0022] e. Conduct statistical analysis and interpretation of the quantitative level of AGEs, predict the risk of neurodegenerative diseases, and output the detection results.
[0023] For the assessment of the risk of neurodegenerative diseases, cognitive assessment test questions are set. If the risk of neurodegenerative diseases is assessed as medium or low through the analysis of AGEs levels, the subject can choose whether to take the cognitive assessment test. If the risk of neurodegenerative diseases is high, the system will automatically enter the cognitive assessment test.
[0024] Interpretation of results:
[0025] High-risk assessment: If the analysis of AGEs levels indicates a high risk, or the results of the mental cognitive tests related to neurodegenerative diseases point to a high risk, then the subject's risk of neurodegenerative diseases is classified as high. In this case, further clinical assessment and possible intervention measures are recommended.
[0026] Very high-risk assessment: When both the analysis of AGEs levels and the results of the mental cognitive tests indicate a high risk, the subject is considered to be at a very high risk of neurodegenerative diseases. This assessment requires immediate medical intervention and may involve more in-depth neurological assessment and customized treatment plans.
[0027] Medium or low-risk assessment: If the results of the analysis of AGEs levels or the mental cognitive tests do not indicate a high risk, the subject's risk of neurodegenerative diseases is assessed as medium or low. In this case, regular monitoring and general preventive measures are recommended.
[0028] The analysis of AGEs levels and cognitive test results can be combined with other biomarkers and clinical assessments to provide a more comprehensive risk assessment and formulate corresponding management and treatment strategies based on the subject's overall health condition and other relevant medical information.
[0029] The neuro-degenerative disease risk detection instrument provided in the invention is compactly designed and convenient to use in various environments, including hospitals, laboratories, families, clinics, and outdoor working environments, etc. The detection instrument in the invention can be non-invasive contact type or can be designed as non-invasive non-contact type, and can be extended to the detection of other biomarkers with significant fluorescence characteristics, further improving its application value in the biomedical field. The instrument design takes into account the safety of users, ensuring that the excitation light source will not cause harm to the skin, and the light intensity used throughout the detection process is within the safe range.
[0030] The autofluorescence multispectral imaging technology of the present invention has significant application potential in evaluating the accumulation of advanced glycation end products (AGEs) in the skin, especially in the field of evaluating the risk of neuro-degenerative diseases. The main advantage of this technology lies in its non-invasiveness, which can detect without damaging skin tissue, providing a more comfortable and safe examination method for the subjects. It can achieve early risk monitoring, helping to identify the risk of neuro-degenerative diseases before the clinical symptoms appear, thus providing the possibility for early intervention. During the treatment process, this technology also helps to monitor the changes in AGEs levels, providing an important basis for evaluating the treatment effect and adjusting the treatment plan. In addition, the autofluorescence multispectral imaging technology is extremely important for the implementation of personalized medicine, and more precise treatment plans, intervention measures, and lifestyle adjustment suggestions can be formulated according to the AGEs accumulation levels of different populations. As a research tool, it also helps to deepen our understanding of the relationship between AGEs and neuro-degenerative diseases and explore the effects of different treatment means. Finally, its simple and non-invasive characteristics make it an ideal choice for identifying high-risk groups in public health screening, and it is expected to have a profound impact on the management and prevention of neuro-degenerative diseases in the future. Brief Description of the Drawings
[0031] Figure 1 Composition of the Instrument for Non-invasive Detection of Neuro-degenerative Disease Risk Detailed Implementation Modes
[0032] The following uses examples to illustrate Figure 1 using the measurement system to detect the risk of neuro-degenerative diseases and advanced glycation end products (AGEs) in food.
[0033] Example 1
[0034] The accumulation of advanced glycation end products (AGEs) can promote oxidative stress and inflammatory responses, which are key factors in the development of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. AGEs bind to receptors on the surface of nerve cells, activating inflammatory pathways, which may lead to cell damage, impairment of the blood-brain barrier, and decline in cognitive function. A study of the present invention aims to non-invasively measure the skin AGEs levels in different subject populations to explore their use in the risk of neurodegenerative diseases.
[0035] The study recruited 45 subjects of either gender, divided into two groups: 19 subjects with Alzheimer's disease (AD) and 26 age-matched healthy subjects. Using the Figure 1 measurement system shown in the present invention, the non-invasive skin autofluorescence AGEs levels of the two groups of subjects were detected under the same conditions.
[0036] Subject selection:
[0037] Control group: 26 healthy subjects without abnormalities in kidney, liver, or mental cognitive status, with an average age of 74 years. This group was used as a control for comparing the AGEs levels with those of the AD group subjects.
[0038] AD group: The selection criteria for 19 subjects were based on their cognitive impairment characteristics, representing typical AD clinical manifestations, with an average age of 80 years.
[0039] Testing method:
[0040] All detections were carried out in a dark room at room temperature. The faces of the subjects were selected for measurement. Before the test, the skin area was ensured to be clean and unobstructed (such as cosmetics or coverings) to avoid affecting the fluorescence signal.
[0041] Using the Figure 1 calibrated detection system shown, the skin was excited by irradiation at a wavelength of 365 nm, and the measured area was evenly irradiated to ensure that the light covered the entire detection area.
[0042] Images were acquired simultaneously from two cameras. One camera captured images in the fluorescence wavelength range of 450 - 500 nm, and the other camera captured diffuse reflectance ultraviolet light images in the wavelength range of 310 - 390 nm. Each camera recorded a set of 8 images, taken separately when the ultraviolet excitation light source was on and off.
[0043] The captured images were processed and analyzed using specific software. This included image reconstruction, feature extraction, signal enhancement, and quantitative analysis. According to the fluorescence intensity and distribution, appropriate algorithms and models were used to quantitatively analyze the AGEs levels in the skin.
[0044] Research results:
[0045] There was a significant difference in the AGEs levels of the two groups of subjects tested by the method of the present invention. The average AGEs level of healthy subjects was 1.98, and the average AGEs level of AD subjects was 2.81. The AGEs level of the Alzheimer's disease (AD) population was significantly higher than that of the healthy population. By using the receiver operating characteristic (ROC) curve for evaluation, when the threshold of the AGEs level detected by the method of the present invention was set to 2.45, its high risk prediction value for AD was 77%. This study proves that the method of the present invention can be used to comprehensively monitor biomarker levels and cognitive levels, thereby achieving continuous assessment of the risk of neurodegenerative diseases in non-laboratory environments. This discovery provides a new tool for early identification of signs of AD, which helps to carry out lifestyle intervention and disease management as early as possible, and is of great significance for improving the quality of life of AD patients and slowing down the progression of the disease.
[0046] Example 2 Detection of Advanced Glycation Endproducts (AGEs) in Food
[0047] In the human body, two main sources of advanced glycation end products (AGEs) have been found, namely exogenous and endogenous AGEs. Exogenous AGEs mainly come from food and drinks. During food processing and cooking, the formation of AGEs mainly occurs through the Maillard reaction. For example, when cooking at high temperatures (such as baking, frying, and roasting), the proteins and sugars in the food react to form AGEs. These AGEs are an important part of the flavor and appearance of food, but at the same time they have also caused concern in terms of human health because excessive intake of AGEs has been associated with certain health problems (such as Alzheimer's disease, cardiovascular disease, and inflammation).
[0048] Choose common food and beverages to use Figure 1 The measurement system shown in the figure is used for testing. Beverages and foods come from vending machines, convenience stores, supermarkets, fast food restaurants, and restaurants, including soy milk, milk, coffee, black tea, carbonated drinks, lactic acid bacteria drinks, tomato juice, carrot juice, yogurt, freeze-dried fruits, fresh fruits, steak, noodles, white rice, potatoes, ice cream, snacks (potato chips, etc.), and cakes / pastries. These foods can be eaten directly after processing.
[0049] When preparing food samples for measurement, first use a food processor or grinding rod to evenly crush solid food, use a homogenizer or stirring rod to homogenize, and use liquid samples directly. Prepare three samples of each food for testing, take the average value, and place the samples in a light-proof sample tank to avoid placing the samples in an environment exposed to sunlight.
[0050] The measurement system is calibrated before use. During measurement, the probe is placed on the sample cell, irradiated with excitation light of 355 - 365 nm, and at the same time, a set of fluorescence images and diffuse reflection ultraviolet light images in the wavelength range of 450 to 500 nm are collected. Specific software is used to process and analyze the captured images, including image reconstruction, feature extraction, signal enhancement, and quantitative analysis. According to the fluorescence intensity and distribution, appropriate algorithms and models are used to quantitatively analyze the level of AGEs in the skin.
[0051] The test results show that there is a consistent trend change between the AGEs levels measured by the method of the present invention and the results obtained by using a competitive enzyme - linked immunosorbent assay with immunospecific antibodies purified by immunoaflinity in the laboratory. The lactic acid bacteria beverage has a high AGEs content because it is produced by mixing high - fructose corn syrup (HFCS) and skim milk and reacting at high temperature. The AGEs content in beverages containing artificial sweeteners and carbonated beverages is relatively low, and the AGEs content in tea, black coffee, and black tea is also not high. Processed snacks have a high AGEs content because the production process of these foods involves heating, and raw materials containing a large amount of reducing sugars and soybean flour or flour need to be heated at high temperature for a long time during production.
[0052] Specifically, when the results of the present invention show a high AGEs level in a certain food, the enzyme - linked immunosorbent assay in the laboratory also reports a similar high - level result. Similarly, if the results of the present invention indicate a low AGEs content, the laboratory test results also tend to show a low AGEs level. The consistency of this trend indicates that, as a non - invasive and rapid detection method, there is an obvious positive correlation between the detection results of the method of the present invention and traditional laboratory methods. The reliability and effectiveness of this method in the rapid assessment of food AGEs levels also contribute to improving the effect of early lifestyle intervention.
[0053] It will be clearly recognized by those skilled in the art that within the framework of the present invention, many other embodiments and modes are possible, and the present invention is not limited to the examples described above.
Claims
1. A method for detecting the risk of non-invasive neurodegenerative diseases, comprising the following steps: a. Use the images taken from ultraviolet-exposed fluorescent objects for calibration and calculate the calibration factor; b. Select a representative skin area for imaging, which can be the inner arm or the inner calf. Align the excitation source of the detection instrument with the skin surface of the subject or the surface of the sample to be tested, and the excitation source emits light of a specific wavelength for excitation; c. Obtain images simultaneously from two cameras. One camera captures images with a fluorescence wavelength range of 450 - 500 nanometers, and the other camera captures images of diffuse-reflected ultraviolet light with a wavelength range of 310 - 390 nanometers. Each camera records a set of images, which are taken respectively when the ultraviolet excitation light source is on and off; d. Process and analyze the captured images with specific software. First, through image reconstruction processing, including geometric and spectral correction, to ensure that the captured images reflect the real skin state. Next, perform feature extraction. Use the mask selection process to analyze the images of the non-specular reflection area, which involves identifying the spectral features related to AGEs fluorescence and separating these features from the images. Then, through signal enhancement, such as filtering processing and contrast adjustment, improve the clarity and detectability of the fluorescence signal. Finally, use machine learning algorithms for quantitative analysis, such as MATLAB, Python combined with OpenCV, etc., and calculate the quantitative level of AGEs according to the fluorescence intensity and distribution; e. Conduct data statistical analysis and interpretation on the quantitative level of AGEs, predict the risk of neurodegenerative diseases, and output the detection results.
2. The detection method for the risk of non-invasive neurodegenerative diseases according to claim 1, characterized in that: The skin tissue mentioned is clinically healthy skin tissue, and local abnormal skin tissues should be avoided as much as possible, such as moles, warts, scars, skin tissues affected by sunburn, tattoos, and very hairy skin tissues. Try to select skin areas that are not often exposed to sunlight during measurement, and avoid curved areas such as the nose, etc. Try to fix the measurement at the same location during multiple detections. At the same time, try to avoid the skin areas where skin care products such as moisturizing creams, lotions, and sunscreen are often used.
3. The detection method for the risk of non-invasive neurodegenerative diseases according to claim 1, wherein: The irradiation window needs to maintain a certain distance from the contact surface through the light-shielding housing to facilitate measurement. The area of the contact surface needs to be larger than the area of the irradiation window to combine the large irradiated and measured skin or object surface with the compact measurement instrument.
4. A non-invasive detection instrument device for the risk of neurodegenerative diseases, comprising the following components: A fluorescence image acquisition module, including: Two ultraviolet excitation light sources. Two monochromatic cameras are respectively equipped with medium-distance lenses and used together with optical band-pass filters to non-invasively irradiate the surface part of the intact skin tissue behind the irradiation window with electromagnetic excitation on the surface of living skin and perform image acquisition; Video data lines for transmitting images are used to transmit the captured images to the data processing module; A data processing module, including: An image processing and analysis unit, a neurodegenerative disease risk analysis unit, a mental and cognitive state assessment test unit, and a touch display screen.
5. The detection instrument device for the risk of non-invasive neurodegenerative diseases according to claim 4, characterized in that: The ultraviolet excitation light source can be selected from an ultraviolet ring lamp, an LED ultraviolet lamp, a fluorescent lamp, etc., with a power of 8 watts or more, and the excitation light wavelength is in the range of 355 - 365 nanometers, which can excite the fluorescence characteristics of AGEs to emit fluorescence.
6. The detection instrument device for the risk of non-invasive neurodegenerative diseases according to claim 4, characterized in that: The selection of the monochromatic camera and lens can capture brightness information, with high sensitivity and higher spatial resolution performance. The focal length of the lens can be 8 - 10 millimeters, or adjusted according to needs. For example, an 8 - millimeter C - mount lens can be selected. The two monochromatic cameras are close to each other, and the distance between them is in the range of 20 - 40 millimeters.
7. The detection instrument device for the risk of non-invasive neurodegenerative diseases according to claim 4, characterized in that: The optical band - pass filter is selected according to the need to capture different wavelength ranges and different types of light. In the invention, the two band - pass filters respectively select a filter that can detect autofluorescence and a filter that can detect diffuse - reflected ultraviolet light. The wavelength range of the fluorescence filter is 450 - 500 nanometers, and the wavelength range of the diffuse - reflected ultraviolet light filter is 310 - 390 nanometers.
8. The detection instrument device for the risk of non-invasive neurodegenerative diseases according to claim 4, characterized in that: The image acquisition and transmission of the two monochromatic cameras are transmitted using a video data cable. A specific software is used to control the start and stop of shooting simultaneously through a computer program and collect images. This control ensures that the two cameras capture images at the same moment, facilitating image processing and analysis. Each camera records a set of images, and the number of images can be 5 - 10. To reduce the impact caused by movement, the entire image acquisition process is completed quickly, usually within 2 - 5 seconds.
9. The detection instrument device for non-invasive risk of neurodegenerative diseases according to claim 4, characterized in that: The detection instrument in the invention can be non - invasive contact - type, or can be designed as non - invasive non - contact - type.