System for illuminating analyte and system for testing analyte

Abstract

The invention provides an analyte illumination system and a detection system, and belongs to the field of optical analysis, the analyte illumination system comprises a shell and a light source, the light source can provide light in a preset wavelength range; the shell can be attached to a detection part of a detector, an imaging area is formed at the attached position, and the light source irradiates the imaging area. The wavelength range of the light provided by the light source covers the wavelength range capable of obtaining the analyte distribution condition data and the wavelength range capable of obtaining the analyte spectrum data, and the light source is arranged to be the annular light source, so that on one hand, stable and uniform illumination can be provided for an imaging area; the electrochemical reaction with the analyte is not needed during detection, the detection mode is more convenient, and the purpose of non-invasive detection can be achieved especially when the analyte in a living body is detected.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202410951464.4 (22) Application Date 2024.07.16 (71) Applicant Guangzhou Ruixin Microelectronics Co., Ltd. Address 510535, Room 1703, No. 188, Kaitai Avenue, Huangpu District, Guangzhou, Guangdong Province (72) Inventor Zheng Hongzhi (74) Patent Agency Shanghai Duan & Duan Law Firm 31334 Patent Attorney Huang Lei (51) Int.Cl. A61B 5 / 1455 (2006.01) A61B 5 / 145 (2006.01) (54) Invention Title: Analyte Illumination System and Detection System (57) Abstract: This invention provides an analyte illumination system and detection system, belonging to the field of optical analysis. It includes a housing and a light source, the light source providing light within a preset wavelength range. The housing is able to adhere to the detection area of ​​the user and form an imaging area at the adhesion point, the light source illuminating the imaging area. This application utilizes a light source whose wavelength range simultaneously covers the wavelength range capable of acquiring analyte distribution data and the wavelength range capable of acquiring analyte spectral data. Furthermore, by setting the light source as a ring light source, it provides stable and uniform illumination to the imaging area. During detection, no electrochemical reaction with the analyte is required, making the detection method more convenient. Especially when detecting analytes in living organisms, it can achieve non-invasive detection. Claims 1 page, Description 11 pages, Drawings 7 pages, CN 121337337 A 2026.01.16 CN 1 21 33 73 37 A 1. An analyte illumination system, characterized in that it comprises a housing and a light source (201), the light source (201) being capable of providing light within a preset wavelength range; the housing being capable of adhering to the detection site of the tester and forming an imaging area (100) at the adhering point, the light source (201) illuminating the imaging area (100). 2. The analyte illumination system according to claim 1, characterized in that the light source (201) comprises a single type of light source (201), the wavelength range of the light provided by the single type of light source (201) simultaneously covering the wavelength range capable of acquiring analyte distribution data and the wavelength range capable of acquiring analyte spectral data. 3. The analyte illumination system according to claim 2, characterized in that the light source (201) comprises multiple light-emitting modules, the multiple light-emitting modules being uniformly distributed on the same circumference. 4. The analyte illumination system as claimed in claim 1, characterized in that the light source (201) comprises two light sources (201), wherein one light source (201) provides light with a wavelength range covering the wavelength range capable of acquiring analyte distribution data.5. The analyte illumination system of claim 4, wherein each of the two light sources (201) comprises a plurality of light-emitting modules, the plurality of light-emitting modules of the two light sources (201) are arranged alternately on the same circumference, and the light-emitting modules are uniformly distributed on the same circumference. 6. The analyte illumination system of claim 4, wherein one of the light sources (201) provides infrared light with a wavelength range of 800 nm to 1000 nm; and the other light source (201) provides ultraviolet light with a wavelength range of 300 nm to 390 nm. 7. The analyte illumination system of claim 1, wherein a first bandpass filter (204) is further provided inside the housing, the first bandpass filter (204) being located between the light source (201) and the imaging region (100); the first bandpass filter (204) allows light within a preset wavelength range to pass through, while light outside the preset wavelength range is blocked. 8. The analyte illumination system as claimed in claim 1, characterized in that the shape and material of the housing allow the housing to conform to the skin around the detection site of the tester. 9. An analyte detection system, characterized in that it employs the analyte illumination system as claimed in any one of claims 1-8. 10. An analyte detection system, characterized in that it further includes a portable device, wherein the analyte illumination system is integrated into the portable device. Claims 1 / 1 page 2 CN 121337337 A Analyte Illumination System and Detection System Technical Field

[0001] This invention relates to the field of optical analysis, specifically to an analyte illumination system and a detection system. Background Art

[0002] Non-invasive measurement usually refers to non-invasive measurement, which, in contrast to invasive measurement, usually guides or senses the physiological and biochemical parameters of a living organism indirectly by means of contact between the measuring instrument and the skin of the test subject, hence it is also called indirect measurement. Currently, commonly used non-invasive measurement techniques include electrochemical methods and optical methods.

[0003] Taking the detection of glucose in the human body as an example: Existing patent document CN118078277A discloses a non-invasive blood glucose detection method based on hyperspectral data analysis. A light source provides ambient light to the hyperspectral analyzer. In a dark room, after illuminating the vascular area on the back of the hand with the aforementioned light source, the hyperspectral analyzer can take multiple images of the human skin vascular area of ​​the target, obtaining hyperspectral images of different concentrations. These multiple hyperspectral images are then sent to a detection device, which summarizes them to obtain a hyperspectral image dataset composed of two-dimensional spatial data and one-dimensional spectral data. This method has high requirements for the environmental conditions; light interference in the environment can affect the accuracy of the detection, making it unsuitable for miniaturized scenarios.

[0004] In addition, US6424849B1 discloses an independent method for determining blood glucose levels using an IR beam reflected from the skin surface. This device has receptacles for holding a body part against an ATR plate. During measurement, a selected skin surface is brought into contact with the ATR plate. The human skin surface is irradiated with an IR beam, and the reference and measurement wavelength components in the reflected IR beam are detected and quantified. During the measurement process, ambient light enters the receptacle through openings, and the measurement results are easily interfered with by ambient light, affecting the accuracy of the detection.

[0005] To address the deficiencies in the prior art, the object of this invention is to provide an analyte illumination system and a detection system.

[0006] According to the analyte illumination system provided by this invention, a housing and a light source are included. The light source is capable of providing light within a preset wavelength range. The housing is capable of fitting with the detection site of the subject and forming an imaging area at the fitting point. The light source irradiates the imaging area.

[0007] Further, the light source includes a single type of light source, and the wavelength range of the light provided by the single type of light source simultaneously covers the wavelength range capable of acquiring analyte distribution data and the wavelength range capable of acquiring analyte spectral data.

[0008] Further, the light source includes multiple light-emitting modules, which are uniformly distributed on the same circumference.

[0009] Further, the light source includes two types of light sources, wherein the wavelength range of light provided by one type of light source covers the wavelength range capable of acquiring analyte distribution data, and the wavelength range of light provided by the other type of light source covers the wavelength range capable of acquiring analyte spectral data.

[0010] Further, each of the two types of light sources includes multiple light-emitting modules, which are arranged alternately on the same circumference and are uniformly distributed on the same circumference.

[0011] Further, one type of light source provides infrared light with a wavelength range of 800 nm to 1000 nm; the other type of light source provides ultraviolet light with a wavelength range of 300 nm to 390 nm.

[0012] Further, a first bandpass filter is also provided inside the housing, the first bandpass filter being located between the light source specification page 1 / 11 3 CN 121337337 A and the imaging area; the first bandpass filter allows light within a preset wavelength range to pass through, while light outside the preset wavelength range is blocked.

[0013] Further, the shape and material of the housing allow the housing to fit snugly against the skin around the detection site of the user.

[0014] According to the detection system provided by the present invention, an analyte illumination system is employed.

[0015] Further, a portable device is included, and the analyte illumination system is integrated into the portable device.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. This application utilizes a light source whose wavelength range simultaneously covers both the wavelength range capable of acquiring analyte distribution data and the wavelength range capable of acquiring analyte spectral data. Furthermore, by setting the light source as a ring light source, it provides stable and uniform illumination to the imaging area. During detection, no electrochemical reaction with the analyte is required, making the detection method more convenient. This is particularly beneficial when detecting analytes in living organisms, achieving non-invasive detection.

[0018] 2. This application leverages the non-uniform distribution of analytes in the imaging area to obtain spectral data from different regions. Since the distribution of components other than the analyte in the imaging area is relatively uniform, the differences in spectral data from different regions directly reflect the correlation between the analyte and spectral data after essentially excluding the influence of non-analytes, such as analyte concentration.

[0019] 3. This application uses fluorescence spectroscopy for detection, avoiding the traditional method of measuring analytes using Raman spectroscopy. This enables the detection system to be low-cost and miniaturized, achieving real-time detection.

[0020] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0021] FIG1 is a schematic structural diagram of an analyte detection device provided in Embodiment 1;

[0022] FIG2 is a schematic structural diagram of a watch provided in Embodiment 1;

[0023] FIG3 is an exploded view of the internal structure of a watch provided in Embodiment 1;

[0024] FIG4 is a schematic structural diagram of a watch worn in Embodiment 1;

[0025] FIG5 is a schematic structural diagram of the back of a watch provided in Embodiment 1;

[0026] FIG6 is a flowchart of Embodiment 2;

[0027] FIG7 is a schematic diagram of the first image acquired in Embodiment 3;

[0028] FIG8 is a schematic diagram of the second image acquired in Embodiment 3;

[0029] FIG9 is a schematic diagram of the detection model of Embodiment 3;

[0030] FIG10 is a schematic diagram of the detection point-reference point spectral data obtained in Embodiment 3;

[0031] FIG11 is the experimental results of the accuracy of the analysis results of the analysis model;

[0032] Figure 12 is a schematic diagram of the electronic device provided in Embodiment 6.

[0033] In the figure:

[0034] 100: Imaging area; 200: Detection device;

[0035] 201: Light source; 202: Imaging spectral detection device;

[0036] 203: Controller; 204: First bandpass filter;

[0037] 205: Lens; 206: Second bandpass filter;

[0038] 207: Circuit board 207; 501: Processor;

[0039] 502: Memory. Specification 2 / 11 pages 4 CN 121337337 A Detailed Embodiments

[0040] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0041] Embodiment 1

[0042] Figure 1 is a structural diagram of this embodiment. This embodiment provides an analyte illumination system, including a housing and a light source 201. The light source 201 can provide light within a preset wavelength range. The housing can be attached to the detection area of ​​the tester and form an imaging area 100 at the attachment point. The light source 201 illuminates the imaging area 100.

[0043] The light source 201 includes a single type of light source 201. The wavelength range of the light provided by the single type of light source 201 simultaneously covers the wavelength range that can acquire data on the distribution of analytes and the wavelength range that can acquire spectral data of analytes. The light source 201 includes multiple light-emitting modules, which are uniformly distributed on the same circumference.

[0044] The light source 201 includes two light sources 201, one of which provides light with a wavelength range covering the wavelength range capable of acquiring analyte distribution data, and the other of which provides light with a wavelength range covering the wavelength range capable of acquiring analyte spectral data. Both light sources 201 include multiple light-emitting modules, which are arranged alternately on the same circumference and are uniformly distributed on the same circumference. One light source 201 provides infrared light with a wavelength range of 800 nm to 1000 nm. The other light source 201 provides ultraviolet light with a wavelength range of 300 nm to 390 nm.

[0045] The shape and material of the housing allow it to fit snugly against the skin around the detection site. A first bandpass filter 204 is also provided inside the housing, located between the light source 201 and the imaging area 100; the first bandpass filter 204 allows light within a preset wavelength range to pass through, while blocking light outside the preset wavelength range.

[0046] Specifically, the light source 201 is part of the detection device 200, which also includes an imaging spectral detection device, a controller 203, a first bandpass filter 204, a second bandpass filter 206, and a lens 205. The controller 203 establishes an electrical or communication connection with the light source 201 and the imaging spectral detection device, respectively.

[0047] The light source 201 is capable of providing light within a preset wavelength range. Since different wavelength ranges of light are required to obtain the distribution data and spectral data of the analyte, there are two possible implementation methods: one light source 201 capable of providing light with a larger wavelength range; or two light sources 201 that each provide light with a smaller wavelength range.When there is one type of light source 201, the wavelength range of the light provided by the light source 201 needs to cover both the wavelength range that can acquire data on the distribution of analytes and the wavelength range that can acquire spectral data of analytes, such as a halogen lamp. When there are two types of light sources 201, the two light sources 201 provide different light, one light whose wavelength covers the wavelength range that can acquire data on the distribution of analytes, and the other light whose wavelength covers the wavelength range that can acquire spectral data of analytes, such as an infrared lamp combined with an ultraviolet lamp, or a visible light lamp combined with an ultraviolet lamp.

[0048] In order to make the illumination of the imaging area 100 uniform, a ring light source 201 can be used. The light source 201 has multiple light-emitting modules, which are evenly distributed on the same circumference. When there are two types of light sources 201, the light-emitting modules of the two types of light sources 201 are arranged alternately.

[0049] The imaging spectral detection device can image the imaging area 100 according to the instructions to obtain the corresponding image, and can obtain the corresponding spectral data according to the instructions. The imaging spectral detection device includes a sensor and a periodic pixel-level filter structure set on the sensor surface. A periodic pixel-level filter structure is used to spectrally modulate the incoming light signal, so that the sensor can generate an image containing the spectral information to be measured. Specification 3 / 11 page 5 CN 121337337 A

[0050] This periodic pixel-level filter structure includes multiple filter pixel channels with different shapes. The multiple filter pixel channels have the same size and are uniformly arranged, with their length and width being integer multiples of the pixel size within the image sensor. Filter pixel channels with different shapes correspond to different spectral filtering coefficients, and pixel-level filter structures with different spectral filtering coefficients are periodically arranged after being combined in a fixed order. The sensor modulates the received first detection light through the periodic pixel-level filter structure set on its surface to form a mosaic image containing spectral information, and then uses an algorithm to reconstruct a grayscale image containing the spectral information to be measured.

[0051] The controller 203 is configured to control the light source 201 to provide light within a preset wavelength range to illuminate the first region, and to control the imaging spectral detection device to image the first region to obtain an image of the imaging region 100. The controller also controls the imaging spectral detection device to acquire spectral data from the image reflecting the uneven distribution of reflection or excitation signals generated by the analyte under light illumination within the imaging region 100. Information about the analyte in the imaging region 100 is obtained based on the acquired spectral data. This information includes information related to the analyte and the spectral data. When there is only one type of light source 201, one image is captured; when there are two types of light sources 201, two images are captured. When the first type of light source 201 is on, the second type of light source 201 is off; similarly, when the second type of light source 201 is on, the first type of light source 201 is off, and the two do not interfere with each other.

[0052] The first bandpass filter 204 is located between the light source 201 and the imaging area 100. Its function is to allow light within a preset wavelength range to pass through, while blocking light outside the preset wavelength range, thereby reducing the influence of other external light on the detection results. In this embodiment, a ring-shaped first bandpass filter 204 is preferably used. The ring shape of the first bandpass filter 204 matches the ring-shaped light source 201, thereby satisfying the requirement that the light emitted by the light source 201 passes through the first bandpass filter 204 and enters the imaging area 100.

[0053] The second bandpass filter 206 is located between the imaging spectral detection device 202 and the lens 205. Its function is to allow light within the wavelength range of the reflected signal or excitation signal generated by the analyte when it is irradiated to pass through, while blocking light in other wavelength ranges, thereby reducing the influence of the reflected signal or excitation signal of non-analyte on the detection results.

[0054] The lens 205 can be used for fixed focusing in order to obtain a clear image. In other embodiments, the second bandpass filter 206 may also be located on the side of the lens 205 away from the imaging spectral detection device 202, and the present invention does not limit this.

[0055] The illumination system of this embodiment can be integrated into the detection system and the detection device 200. The detection device 200 is a portable non-invasive detection device 200 for the human body. It can be a separate detection device 200 or integrated into a watch or mobile phone, thereby realizing convenient and quick detection of analytes inside the body surface.

[0056] As shown in Figures 2, 3, 4 and 5, the detection device 200 in this embodiment takes a watch as an example. The detection system is integrated into the watch. The lens 205, the second bandpass filter 206, the light source 201 and the first bandpass filter 204 are arranged sequentially from the inside to the outside. The controller 203 is integrated on the circuit board 207 of the watch. An opening area that fits against the skin of the user's wrist is formed on the back of the watch. During detection, the area where the opening area on the back of the watch fits against the skin of the user's wrist is the imaging area 100. The reflected signal or excitation signal of the human body enters the light-transmitting window, passes through the light source 201 and the hollow part in the middle of the first bandpass filter 204, passes through the lens 205 and enters the second bandpass filter 206, and enters the imaging spectrum detection device 202 after being filtered by the second bandpass filter 206.

[0057] Example 2

[0058] This example is based on Example 1 and provides a method for detecting an analyte. Figure 6 is a flowchart of this example, including:

[0059] Imaging step: The first area is irradiated by light within a preset wavelength range provided by the light source, and the first area is imaged by the imaging spectrum detection device to obtain an image of the imaging area. By irradiating the first area with light within a preset wavelength range, the image can reflect the reflected signal or excitation signal generated by the analyte under the irradiation of light in the imaging area.Distribution data and spectral data. The first region can be a certain area on the surface of human skin. To avoid the influence of external light such as ambient light on the detection, the lens of the imaging spectral detection device needs to be tightly attached to the surface of human skin in the first region. The imaging region refers to the area within the lens range of the imaging spectral detection device. In general, the imaging region can be a part of the first region or the same region as the first region.

[0060] Since different wavelength ranges of light are needed to irradiate the analyte to obtain distribution data and spectral data, there are two ways to achieve this: the light is a light with a large wavelength range provided by one light source or light with a small wavelength range provided by two light sources. When there is one light source, the wavelength range of the light provided by the light source needs to cover both the wavelength range that can be used to obtain distribution data and the wavelength range that can be used to obtain spectral data. When there are two light sources, the two light sources provide different light, one light whose wavelength covers the wavelength range that can be used to obtain distribution data and the other light whose wavelength covers the wavelength range that can be used to obtain spectral data. Meanwhile, when there is only one light source, the image is one; when there are two light sources, the image is two. For ease of processing, the imaging areas of the two images must be the same, that is, the lens of the imaging spectral detection device must not move on the surface of the human skin.

[0061] In this application, the analyte can be glucose, ketones, alcohols, lactate, oxygen, hemoglobin A1C, acetylcholine, amylase, bilirubin, cholesterol, human chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glutamine, growth hormone, hormones, peroxides, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone, or troponin, or it can be a drug such as antibiotics (e.g., gentamicin, vancomycin, etc.), digitalis, digoxin, abused drugs, theophylline, or warfarin. In embodiments that detect two or more analytes, the analytes can be monitored at the same or different times. In other embodiments, the analyte can also be other substances in the body surface, and non-invasive detection can be achieved through this invention.

[0062] Spectral acquisition step: Spectral data reflecting the uneven distribution of reflection or excitation signals generated by the analyte under light illumination in the imaging region is acquired from the image using an imaging spectral detection device. Specifically, the imaging region can be divided into zones based on different distribution patterns to facilitate the selection of locations from which spectral data is acquired.

[0063] Analysis step: Information about the analyte in the imaging region is obtained based on the acquired spectral data. This information includes the correlation between the analyte and the spectral data. Since the distribution of the analyte differs in different zones, the analyte...The reflected or excitation signals generated by light exposure will also differ. Taking human skin as an example, it is divided into three parts: epidermis, dermis, and subcutaneous tissue. Veins and other blood vessels are located in the subcutaneous tissue. Ultraviolet light can be used to irradiate skin areas with and without blood vessels to obtain corresponding spectral data, or skin areas with thicker blood vessels and skin areas with thinner blood vessels to obtain corresponding spectral data. The difference between the two spectral data can reflect the information related to the analyte in the blood vessels and the spectral data, such as the degree of influence of the analyte on the spectral data, etc., for further analysis, or directly obtain information such as the concentration of the analyte through the analysis model.

[0064] Example 3

[0065] This example is based on Example 2, taking the detection of glucose in human blood vessels as an example, and provides a non-invasive glucose detection method, including:

[0066] Imaging step: Irradiate the skin at the location of the vein, such as the wrist or back of the hand, with infrared light in the first wavelength range of 800-1000 nanometers, and acquire the first image of the imaging area. The first wavelength range is preferably the near-infrared band. And by irradiating the same location with ultraviolet light in the second wavelength range of 300-390 nanometers, a second image of the imaging area is acquired.

[0067] As shown in Figure 7, the horizontal axis is the horizontal coordinate of the first image, the vertical axis is the vertical coordinate of the first image, the white box represents the selected detection point pixel block on the vein, and the black box represents the selected reference point pixel block on the surrounding skin. In the first image, part of the infrared light will penetrate the human skin and part will be absorbed by the human skin. At the same time, it will also be absorbed in large quantities by the vein in the vein area. Therefore, the pixel gray value in the vein area is small and the pixel gray value in the non-vein area is large. In this way, the imaging area can be easily divided into the vein area and the non-vein area.

[0068] As shown in Figure 8, the horizontal axis is the horizontal coordinate of the second image, the vertical axis is the vertical coordinate of the second image, the white box represents the selected detection point pixel block on the vein, and the black box represents the selected reference point pixel block on the surrounding skin. In the second image, it is difficult to distinguish between areas containing veins and areas not containing veins; therefore, the first image is needed for differentiation. Using excitation light in the second wavelength range of 300-390 nm is to obtain high-quality effective fluorescence spectral signals. This is because the main response band of the imaging spectral detection device is located in the 400-800 nm range. When the wavelength of the excitation light used is less than 300 nm, the main peak of the excited fluorescence radiation signal is located in the <400 nm band, making it difficult for the imaging spectral detection device to obtain high-quality effective fluorescence spectral signals. When the wavelength of the excitation light used is >At 390nm, the excitation light itself is also visible light. The spectral signal of the excitation light is superimposed with the fluorescence spectral signal, making it difficult to eliminate the interference of the spectral signal of the excitation light and extract the effective fluorescence spectral signal. After absorbing ultraviolet light in the wavelength range of 300-390 nm, glucose in veins can emit fluorescence radiation signals in the visible light band of 400-800 nm. This band is within the effective response range of the imaging spectral detection device. The characteristic spectral intensity of this fluorescence radiation signal is positively correlated with the concentration of glucose and has high fluorescence excitation efficiency.

[0069] Spectral acquisition steps: According to the gray distribution of pixels in the first image, the imaging area is divided into the area where veins are located and the area where non-vein vessels are located. Detection points are selected from the positions in the second image corresponding to the areas where veins are located, and reference points are selected from the positions in the second image corresponding to the areas where non-vein vessels are located. The spectral data of the detection points and the spectral data of the reference points in the second image are obtained respectively. Specifically, based on the grayscale values ​​of pixels in the second image, a pixel with a grayscale value meeting a preset requirement is selected from the region where the vein is located as a detection point, or a combination of that pixel and its neighboring pixels is selected as a detection point. A pixel with a grayscale value within a preset deviation range from the selected detection point is selected from the region where the vein is not located as a reference point, or a combination of that pixel and multiple neighboring pixels is selected as a reference point. The fluorescence spectral data of the detection point and the fluorescence spectral data of the reference point are calculated in the second image. The spectral data is taken from a single pixel of the detection point or reference point, or an average of multiple pixels, which can be appropriately selected based on the width of the blood vessel. Averaging multiple pixels can improve the signal-to-noise ratio, but is limited by the width of the blood vessel, avoiding the capture of areas outside the blood vessel. Selecting a single pixel provides high spatial resolution and is suitable for thinner blood vessels, but the signal-to-noise ratio is lower. The preset requirement for grayscale value can be to select the point with the smallest grayscale value as the detection point, but this application does not impose this limitation. The calculation results are shown in Figure 10, where the horizontal axis represents wavelength (in nm) and the vertical axis represents relative radiance (in W / nm). The solid line represents the spectral data of the detection point, and the dashed line represents the spectral data of the reference point. The reason why the gray values ​​of the reference point and the selected detection point are within a preset deviation range is that the skin in the imaging area may have influencing factors such as skin color, blemishes, and cosmetics, which can directly affect the spectral data of the reference point. The first image cannot distinguish areas with these influencing factors. By setting a preset deviation range for the gray values, these influencing factors can be effectively eliminated. Furthermore, having the gray values ​​of the selected detection point within the preset deviation range ensures that the reference point is close to the detection point. For example, selecting it at the edge of a vein ensures that, apart from blood vessels, the color, thickness, and other parameters of the epidermis, dermis, and subcutaneous tissue are as close as possible, thus minimizing the influence of non-analytes on the deviation between the spectral data of the detection point and the spectral data of the reference point.

[0070] Besides the spectral reconstruction algorithm, spectral data can also be obtained by forming radiometric calibration coefficients through prior radiometric calibration, and then calculating the spectral line by multiplying the gray value by the radiometric calibration coefficients.

[0071] When selecting a combination of multiple pixels as the detection point, the fluorescence spectral data of the detection point can be the average of the fluorescence spectral data of these pixels as per the specification page 6 / 11, 8 CN 121337337 A. Simultaneously, the number of detection points and reference points can be one or more. When there are multiple detection points and reference points, the average of the fluorescence spectral data of all detection points and the average of the fluorescence spectral data of all reference points can be calculated separately.

[0072] Analysis steps: After preprocessing, the obtained spectral data of the detection points and reference points are input into the trained detection model, which outputs the glucose concentration or intermediate results relating glucose to the spectral data. During training, the detection model needs to simultaneously acquire the spectral data of the tested object and accurate test results, such as blood test results. The spectral data is used as the input to the detection model, and the blood test results are used as the output to train the detection model.

[0073] The detection model can adopt a convolutional neural network model, which sequentially includes an input layer, at least two convolutional layers, at least two activation function layers, a flatten layer, a fully connected layer, and an output layer. The convolutional layers and the activation function layers are distributed alternately. The activation function used in the activation function layer is the ReLU function.

[0074] In the convolutional neural network model, the kernel size of each convolutional layer is 1. The number of kernels in the first convolutional layer is 32, and the number of kernels in the second convolutional layer is 64. Both are used to extract blood glucose features, and the output of the convolutional layer is nonlinearly transformed by the activation function. The flatten layer flattens the output of the convolutional layer into a one-dimensional vector, which is convenient for connecting to the subsequent fully connected layers. The final output dimension is 1. During the model training process, the Adam optimizer is used for model training, and the mean squared error is used as the loss function. At the same time, the mean absolute error is calculated as the performance index for model evaluation.

[0075] When the output result of the detection model is glucose concentration, if the error between the output result and the measured standard glucose concentration value meets the preset condition, the training is stopped and the detection model is obtained. When the output of the detection model is an intermediate result related to glucose and spectral data, such as the result of an intermediate neuron, if the error between the output result and the result of the intermediate neuron meets a preset condition, training is stopped to obtain the detection model. Further model correction is performed on the result of the intermediate neuron to obtain the glucose concentration.

[0076] As shown in Figure 9, the Input layer is the spectral data input layer, obtained after preprocessing the original spectral data. The Hidden layer is an intermediate hidden layer, which performs deep learning through convolution operations, combines features, and outputs the final predicted blood glucose concentration value.layer. Alternatively, deep learning can be performed through convolution operations. After feature combination, a neuron Output1 is output as an intermediate result value. The intermediate result value Output1 and two infrared (IR) feature brightness values ​​are used to train the model again to further correct the blood glucose prediction error and output the final predicted blood glucose concentration value Output2. The training degree of the detection model needs to be set with different parameters as needed. The extracted glucose feature values ​​will continuously learn according to the different parameter settings until the error between the output result and the standard glucose value of the above label value meets the requirements. Then, the training stops and the detection model is obtained.

[0077] Through multiple iterations of training, the neurons learn the corresponding change rules between different glucose concentrations and glucose spectral features of different samplers, thereby improving the universality of the detection model and enabling the prediction of glucose concentrations of different users.

[0078] The entire glucose detection process does not require puncturing the skin to collect blood or puncturing the skin for implantation. It obtains the spectral information of the subject based on fluorescence spectroscopy and obtains the glucose detection result of the subject based on the spectral information, avoiding pain and discomfort and improving the comfort and convenience of the detection. This method can precisely distinguish spectral signals from vascular and skin sites, providing the possibility for accurate extraction of glucose signals in the future. It also strongly correlates spectral signals with glucose concentration, achieving accurate measurement of glucose concentration, resulting in more accurate detection results and easier processing.

[0079] Figure 11 shows a schematic diagram of the experimental effect of the trained detection model. The horizontal axis represents the reference blood glucose concentration (in mmol / L) collected by the blood glucose meter, and the vertical axis represents the blood glucose concentration (in mmol / L) predicted using the method of this patent. The total sample size was 2037, including 1537 training samples and 500 prediction samples. The figure shows the distribution of detection results of the detection model (page 7 / 11, CN 121337337 A) in the specification. The MARD value of the predicted samples was 11.32%, with the vast majority of samples falling into areas A and B. Specifically, 87.03% of the samples fell into area A, and 12.77% fell into area B, indicating that the detection model has high accuracy.

[0080] Example 4

[0081] This example is based on Example 3, replacing infrared light with visible light to provide another non-invasive glucose detection method, including:

[0082] Imaging steps: Irradiating the skin at the location of the vein, such as the wrist or back of the hand, with visible light to acquire a first image of the imaging area. Irradiating the same location with ultraviolet light in the second wavelength range of 300-390 nanometers to acquire a second image of the imaging area.

[0083] In the first image, because the color of the area where the vein is located differs from the color of the area where the non-vein is located...The difference allows for easy division of the imaging area into regions containing veins and regions not containing veins.

[0084] In the second image, since it is difficult to distinguish between regions containing veins and regions not containing veins, the first image is needed for differentiation. The excitation light in the second wavelength range of 300-390 nm is used to obtain high-quality effective fluorescence spectral signals. This is because the main response band of the imaging spectral detection device is located in the 400-800 nm range. When the wavelength of the excitation light used is less than 300 nm, the main peak of the fluorescence spectrum of the excited fluorescence radiation signal is located in the <400 nm band, making it difficult for the imaging spectral detection device to obtain high-quality effective fluorescence spectral signals. When the wavelength of the excitation light used is > 390 nm, the excitation light itself is also visible light, and the spectral signal of the excitation light is superimposed on the fluorescence spectral signal, making it difficult to eliminate the interference of the spectral signal of the excitation light and extract the effective fluorescence spectral signal. After absorbing ultraviolet light in the wavelength range of 300-390 nm, glucose in veins can emit fluorescence radiation signals in the visible light band of 400-800 nm. This band is within the effective response range of the imaging spectral detection device. The characteristic spectral intensity of this fluorescence radiation signal is positively correlated with the concentration of glucose and has high fluorescence excitation efficiency.

[0085] Spectral acquisition steps: According to the gray-scale distribution of pixels in the first image, the imaging area is divided into the vein area and the non-vein area. Detection points are selected from the second image corresponding to the vein area, and reference points are selected from the second image corresponding to the non-vein area. The spectral data of the detection points and the spectral data of the reference points are acquired respectively. Specifically, according to the gray-scale value of pixels in the second image, a pixel with a gray-scale value that meets the preset requirements or a combination of the pixel and its adjacent pixels is selected from the vein area as a detection point. A pixel with a gray-scale value within the preset deviation range of the selected detection point or a combination of the pixel and multiple adjacent pixels is selected from the non-vein area as a reference point. The fluorescence spectral data of the detection point and the fluorescence spectral data of the reference point are calculated. The reason why the gray values ​​of the reference point and the selected detection point are within a preset deviation range is that the skin in the imaging area may have influencing factors such as skin color, spots, and cosmetics, which will directly affect the spectral data of the reference point. The first image cannot simultaneously distinguish the areas of all influencing factors. By setting a preset deviation range for the gray values, these influencing factors can be effectively eliminated.

[0086] When a combination of multiple pixels is selected as the detection point, the fluorescence spectral data of the detection point can be the average value of the fluorescence spectral data of these pixels. At the same time, the number of detection points and reference points can be one or more. When the number of detection points and reference points is multiple, the average value of the fluorescence spectral data of all detection points and all reference points can be calculated separately.The average value of the fluorescence spectrum data of the test points.

[0087] Analysis steps: After preprocessing, the obtained spectral data of the test points and reference points are input into the trained detection model, and the glucose concentration is output. When the detection model is trained, it is necessary to simultaneously obtain the spectral data of the test object and the accurate test results, such as blood test results. The spectral data is used as the input of the detection model, and the blood test results are used as the output of the detection model.

[0088] The detection model can adopt a convolutional neural network model, which sequentially includes an input layer, at least two convolutional layers, at least two activation function layers, a Flatten layer, a fully connected layer and an output layer. The convolutional layers and the activation function layers are distributed alternately. The activation function used by the activation function layer is the ReLU function.

[0089] In the convolutional neural network model, the kernel size of each layer is 1. The first convolutional layer has 32 kernels, and the second convolutional layer has 64 kernels. Both are used to extract blood glucose features, and the output of the convolutional layer is non-linearly transformed through the activation function. The Flatten layer flattens the output of the convolutional layer into a one-dimensional vector, which is convenient for connecting to the subsequent fully connected layers. The final output dimension is 1. During the model training process, the Adam optimizer is used for model training, and the mean squared error is used as the loss function. At the same time, the mean absolute error is calculated as the performance index for model evaluation.

[0090] If the error between the output result of the detection model and the standard glucose value meets the preset condition, the training is stopped and the detection model is obtained.

[0091] The training degree of the detection model needs to be set with different parameters as needed. The extracted glucose feature values ​​will continuously learn according to the different parameter settings until the error between the output result and the standard glucose value of the above label value meets the requirements. Then the training is stopped and the detection model is obtained.

[0092] Through multiple iterative training, neurons learn the corresponding change patterns between different glucose concentrations and glucose spectral characteristics of different samplers, thereby improving the universality of the detection model and enabling the prediction of glucose concentrations for different users.

[0093] The entire glucose detection process does not require blood collection or skin puncture. It obtains the spectral information of the test subject based on fluorescence spectroscopy and obtains the glucose detection result of the test subject based on the spectral information, avoiding pain and discomfort and improving the comfort and convenience of the detection. This method can finely distinguish the spectral signals of blood vessels and skin, providing the possibility for accurate extraction of glucose signals in the future. At the same time, it also makes the spectral signal strongly correlated with the glucose concentration, realizing accurate measurement of glucose concentration, making the detection results more accurate and the processing more convenient.

[0094] Example 5

[0095] This example provides an analyte detection system based on Example 1.The system can be implemented by executing the steps of the method for detecting the analyte, that is, those skilled in the art can understand the method for detecting the analyte as a preferred embodiment of the system for detecting the analyte. The system for detecting the analyte includes:

[0096] An imaging module: a light source provides light within a preset wavelength range to illuminate a first region, and an imaging spectral detection device images the first region to obtain an image of the imaging region. By illuminating the first region with light within a preset wavelength range, the image can reflect the distribution data and spectral data of the reflected signal or excitation signal generated by the analyte under light irradiation in the imaging region. Since different wavelength ranges are required to obtain the distribution data and spectral data of the analyte, the light can be two corresponding wavelength ranges, or it can be a light with a larger wavelength range that covers both required wavelength ranges. When there are two types of light, two images are obtained. For ease of processing, it is usually required that the imaging areas of the two images are the same.

[0097] In this application, the analyte may be glucose, ketones, alcohols, lactate, oxygen, hemoglobin A1C, acetylcholine, amylase, bilirubin, cholesterol, human chorionic gonadotropin, creatine kinase (e.g., CK-MB), creatine, creatinine, DNA, fructosamine, glutamine, growth hormone, hormones, peroxides, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone, troponin, or drugs such as antibiotics (e.g., gentamicin, vancomycin, etc.), digitalis, digoxin, abused drugs, theophylline, and warfarin. In embodiments that detect more than one analyte, the analytes may be monitored at the same or different times. In other embodiments, the analyte may also be other substances in a liquid.

[0098] Spectral acquisition module: Acquires spectral data from an image using an imaging spectral detection device, reflecting the uneven distribution of the reflected or excitation signals generated by the analyte under light irradiation in the imaging area. Specifically, the imaging area can be partitioned according to different distribution data to facilitate the selection of locations for acquiring spectral data from different partitions.

[0099] Analysis module: Based on the acquired spectral data, information about the analytes in the imaging area is obtained. The information about the analytes includes information related to the analytes and the spectral data. Since the distribution of analytes in different partitions is different, the reflection signals or excitation signals generated by the analytes when irradiated by light will also be different. Utilizing this characteristic, the difference in spectral data between the two can be obtained, thereby accurately reflecting the information related to the analytes and the spectral data, such as the concentration of the analytes.

[0100] Those skilled in the art will know that, in addition to implementing the system provided by the present invention in a purely computer-readable program code manner...Besides its various devices, modules, and units, the system and its various devices, modules, and units provided by the present invention can achieve the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; the devices, modules, and units for implementing various functions can also be considered as both software modules for implementing the method and structures within the hardware component.

[0101] Embodiment 6

[0102] This embodiment provides a schematic diagram of the structure of an electronic device based on Embodiment 1, as shown in FIG12, including at least one processor 501; and a memory 502 communicatively connected to at least one processor 501; wherein, the memory 502 stores instructions that can be executed by at least one processor 501, and the instructions are executed by at least one processor 501 to enable at least one processor 501 to execute the above-mentioned method for detecting the analyte.

[0103] The memory 502 and the processor 501 are connected via a bus. The bus may include any number of interconnected buses and bridges, connecting various circuits of one or more processors 501 and memory 502 together. The bus may also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be further described here. The bus interface provides an interface between the bus and the transceiver. The transceiver may be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor 501 is transmitted over a wireless medium via an antenna, which further receives data and transmits it to the processor 501.

[0104] The processor 501 is responsible for managing the bus and general processing, and may also provide various functions, including timing, peripheral interface,

[0105] voltage regulation, power management, and other control functions. The memory 502 may be used to store data used by the processor 501 during operation.

[0106] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for detecting the analyte.

[0107] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or a processor to execute the methods described in the various embodiments of this application. (Pages 10 / 11 of the specification)12 CN 121337337 A All or part of the steps of the method. The aforementioned storage medium includes: USB flash drive, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code.

[0108] Those skilled in the art will understand that the above embodiments are specific embodiments of the present invention, and in actual applications, various changes can be made to them in form and detail without departing from the spirit and scope of the present invention.

[0109] In the description of this application, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0110] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in these embodiments can be arbitrarily combined with each other. Instruction manual 11 / 11 page 13 CN 121337337 A Figure 1 Instruction manual Figure 1 / 7 page 14 CN 121337337 A Figure 2 Figure 3 Instruction manual Figure 2 / 7 page 15 CN 121337337 A Figure 4 Figure 5 Instruction manual Figure 3 / 7 page 16 CN 121337337 A Figure 6 Figure 7 Instruction manual Figure 4 / 7 page 17 CN 121337337 A Figure 8 Figure 9 Instruction manual Figure 5 / 7 page 18 CN 121337337 A Figure 10 Figure 11 Instruction manual Figure 6 / 7 page 19 CN 121337337 A Figure 12 Instruction manual Figure 7 / 7 page 20 CN 121337337 A Abstract Abdominal ultrasound examination method, system and device Abstract The present invention provides an analytical illumination system and an analytical detection system,belonging to the field of optical analysis. The analyte illumination system comprises a shell and a light source, wherein the light source is capable of providing light within a preset wavelength range; the shell is capable of fitting a detection site of a subject to be tested and forming an imaging area at a fitting position; and the light source illuminates the imaging area. According to the present application, the wavelength range of the light provided by the light source simultaneously covers a wavelength range for obtaining analyte distribution data and a wavelength range for obtaining analyte spectral data. In addition, the light source is configured as a ring-shaped light source. On the one hand, stable and uniform illumination can be provided for the imaging area; during detection, no electrochemical reaction with the analyte is required, so the detection method is more convenient. In particular, when detecting an analyte in a living body, the purpose of non-invasive detectioncan be achieved.

Claims

1. An analyte illumination system characterized by, The shell and a light source (201) capable of providing light in a preset wavelength range; The shell is capable of being attached to the detection site of the subject and forming an imaging area (100) at the attachment site, and the light source (201) irradiates the imaging area (100).

2. The analyte illumination system of claim 1, wherein, The light source (201) includes a single light source (201) that provides light in a wavelength range that simultaneously covers a wavelength range capable of obtaining analyte distribution data and a wavelength range capable of obtaining analyte spectral data.

3. The analyte illumination system of claim 2, wherein, The light source (201) includes a plurality of light-emitting modules that are uniformly distributed on the same circumference.

4. The analyte illumination system of claim 1, wherein, The light source (201) includes two light sources (201), one of which provides light in a wavelength range that covers a wavelength range capable of obtaining analyte distribution data, and the other of which provides light in a wavelength range that covers a wavelength range capable of obtaining analyte spectral data.

5. The analyte illumination system of claim 4, wherein, The two light sources (201) each include a plurality of light-emitting modules, and the plurality of light-emitting modules of the two light sources (201) are alternately arranged on the same circumference and are uniformly distributed on the same circumference.

6. The analyte illumination system of claim 4, wherein, One of the light sources (201) provides infrared light with a wavelength range of 800 nm to 1000 nm; The other light source (201) provides ultraviolet light with a wavelength range of 300 nm to 390 nm.

7. The analyte illumination system of claim 1, wherein, The shell further comprises a first band-pass filter (204) located between the light source (201) and the imaging area (100). The first band-pass filter (204) allows light in a preset wavelength range to pass through and cuts off light in a non-preset wavelength range.

8. The analyte illumination system of claim 1, wherein, The shape and material of the shell allow the shell to be attached to the skin around the detection site of the subject.

9. An analyte detection system characterized by, An analyte illumination system according to any one of claims 1-8.

10. An analyte detection system characterized by, Further comprising a portable device, and the analyte illumination system is integrated on the portable device.

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