System and apparatus for testing analyte

Abstract

The invention provides an analyte detection system and device, and belongs to the field of optical analysis, the detection system comprises a light source, an imaging spectrum detection device and a controller, the controller is in electric connection or communication connection with the light source and the imaging spectrum detection device, and the light source can provide light in a preset wavelength range; under the action of the controller, the light source provides light in a preset wavelength range for a designated area, and the imaging spectrum detection device images the designated area to obtain a corresponding image and / or spectral data. The controller controls the light source and the imaging spectrum detection device to image the imaging area to obtain the corresponding image and / or spectrum data, the operation is simple, and the device can be integrated in a portable device and is high in applicability.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202410951561.3 (22) Application Date 2024.07.16 (71) Applicant Guangzhou Ruixin Microelectronics Co., Ltd. Address 510535 Room 1703, No. 188, Kaitai Avenue, Huangpu District, Guangzhou City, Guangdong Province (72) Inventor Zheng Hongzhi (74) Patent Agency Shanghai Duan & Duan Law Firm 31334 Patent Attorney Li Yuan (51) Int.Cl. A61B 5 / 1455 (2006.01) A61B 5 / 145 (2006.01) (54) Invention Title Analyte Detection System and Device (57) Abstract This invention provides an analyte detection system and device, Belonging to the field of optical analysis, the detection system includes a light source, an imaging spectral detection device, and a controller. The controller is electrically or communicatively connected to both the light source and the imaging spectral detection device. The light source provides light within a preset wavelength range. Under the control of the controller, the light source provides light within the preset wavelength range to a designated area, and the imaging spectral detection device images the designated area to obtain corresponding images and / or spectral data. This application uses a controller to control the light source and imaging spectral detection device to image the corresponding area and obtain corresponding images and / or spectral data. It is simple to operate, can be integrated into portable devices, and has strong applicability. Claims 1 page, Description 11 pages, Drawings 7 pages, CN 121337346 A 2026.01.16 CN 1 21 33 73 46 A 1. An analyte detection system, characterized in that it comprises a light source (201), an imaging spectral detection device (202), and a controller (203), wherein the controller (203) is electrically or communicatively connected to the light source (201) and the imaging spectral detection device, respectively, and the light source (201) is capable of providing light within a preset wavelength range; under the action of the controller (203): the light source (201) provides light within a preset wavelength range to a designated area, and the imaging spectral detection device images the designated area to obtain corresponding images and / or spectral data. 2. The analyte detection system as claimed in claim 1, characterized in that a first bandpass filter (204) is disposed between the light source (201) and the designated area, the first bandpass filter (204) having an annular shape, the first bandpass filter (204) allowing light within a preset wavelength range to pass through, while blocking light outside the preset wavelength range. 3. The analyte detection system as claimed in claim 1, characterized in that a second bandpass filter (206) is disposed between the imaging spectral detection device (202) and the lens (205), the second bandpass filter (206) allowing light within a preset wavelength range to pass through.Light within the specified range passes through, while light outside the preset wavelength range is blocked. 4. The analyte detection system as claimed in claim 1, characterized in that the imaging spectral detection device, the light source (201), and the designated area are arranged sequentially along a specified direction; an optical path is provided between the imaging spectral detection device and the designated area, and the light source (201) is located between the imaging spectral detection device and the designated area; the shape of the light source (201) includes a ring, and the optical path passes through the middle of the ring light source (201). 5. The analyte detection system as claimed in claim 4, characterized in that, under the action of the controller (203): the light provided by the light source (201) enters the designated area through the first bandpass filter (204), and the reflected signal or excitation signal generated by the analyte in the designated area after being irradiated by the light passes sequentially along the optical path through the middle of the ring of the first bandpass filter (204), the middle of the ring of the light source (201), the lens (205), and the second bandpass filter (206) before entering the imaging spectral detection device. 6. The analyte detection system as claimed in claim 1, wherein the light source (201) comprises a single light source (201), and the wavelength range of the light provided by the single light source (201) simultaneously covers the wavelength range capable of acquiring data on the distribution of the analyte and the wavelength range capable of acquiring spectral data of the analyte. 7. The analyte detection system as claimed in claim 1, wherein the light source (201) comprises two light sources (201), wherein one light source (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. 8. The analyte detection system as claimed in claim 1, wherein the imaging spectral detection device comprises a sensor and a periodic pixel-level filter structure, the periodic pixel-level filter structure being disposed on the surface of the sensor; the periodic pixel-level filter structure spectrally modulates the incoming light signal, and the sensor generates an image containing the spectral information to be measured. 9. The analyte detection system as claimed in claim 8, characterized in that the optical signal acquired by the imaging spectral detection device includes a reflection signal generated by the analyte being irradiated by light in a designated area and an excitation signal generated by the analyte being irradiated by light. 10. An analyte detection device, characterized in that it integrates the analyte detection system as claimed in any one of claims 1-9, and the detection device includes a portable device. Claims 1 / 1 page 2 CN 121337346 A Analyte Detection System and Device Technical Field

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

[0002] With the changes in modern people's dietary habits and lifestyles, the incidence of diabetes has increased rapidly, and it has become a domestic problem.Ten major causes of blood sugar problems. Therefore, people are gradually recognizing the importance of blood sugar control. Currently, blood glucose meters sold on the market mainly use glucose oxidase electrode measurement and glucose dehydrogenase electrode measurement methods. However, both of these methods are invasive. Each measurement requires a lancet to collect blood from the fingertip, and then the blood is dropped onto a test strip before the blood sugar value can be measured.

[0003] However, this implementation method has the following problems: the test strips are not easy to preserve and are prone to deterioration due to the storage environment, which is detrimental to measurement. Furthermore, users may easily mix other brands of test strips with the blood glucose meter or cause the test strips to expire. In addition, blood collection is an invasive procedure, and not all test subjects can tolerate the brief stinging sensation during blood collection. The lancet can only be used once and must be discarded after use, resulting in a waste of resources.

[0004] Patent document CN108354614A discloses a blood glucose detection method, a blood glucose detection calibration method, and a blood glucose detection device. The detection device includes: a housing having a detection area and a test strip placement port; and a blood glucose meter disposed within the housing and aligned with the test strip placement port, which receives a blood glucose test strip through the test strip placement port and generates a calibration blood glucose value. When performing detection, this device requires the use of a blood glucose test strip to provide a calibration blood glucose value to calibrate the collected data, necessitating a manual control, making the operation complex.

[0005] Patent document CN107064048A discloses a rapid non-invasive blood glucose detection method and device, which requires prior blood glucose content measurement using a needle prick method to obtain the blood glucose value measured by a conventional minimally invasive blood glucose meter, making the operation cumbersome before the actual detection.

[0006] Patent document CN109490248A discloses a blood glucose spectral detection system and method based on modulation anti-phase cancellation, including a light source group, a phase modulator group, a mirror group, and a blood glucose analysis unit; the light source group includes a first light source and a second light source, the phase modulator group includes a first phase modulator and a second phase modulator, the modulation phase of the first phase modulator and the modulation phase of the second phase modulator differ by 180°; the mirror group includes a total reflection mirror and a half reflection mirror; the first light source, the first phase modulator, and the total reflection mirror are arranged sequentially, and the second light source, the second phase modulator, and the half reflection mirror are arranged sequentially. Phase difference adjustment is required, and the optical path structure is complex. Summary of the Invention

[0007] In view of the defects in the prior art, the purpose of the present invention is to provide an analyte detection system and device.

[0008] An analyte detection system according to the present invention includes a light source, an imaging spectral detection device, and a controller. The controller is electrically or communicatively connected to the light source and the imaging spectral detection device, respectively. The light source is capable of providing light within a preset wavelength range. Under the action of the controller: the light source provides light within the preset wavelength range to a designated area, and the imaging spectral detection device images the designated area to obtain corresponding images and / or spectral data.

[0009] Further, a first bandpass filter is provided between the light source and the designated area. The first bandpass filter has an annular shape and allows light within a preset wavelength range to pass through, while light outside the preset wavelength range is blocked.

[0010] Further, a second bandpass filter is provided between the imaging spectral detection device and the light source. The second bandpass filter allows light within a preset wavelength range to pass through, while light outside the preset wavelength range is blocked.

[0011] Further, the imaging spectral detection device, the light source, and the designated area are arranged sequentially along a specified direction; an optical path is provided between the imaging spectral detection device and the designated area, and the light source is located between the spectral detection device and the designated area; the light source has an annular shape, and the optical path passes through the center of the annular light source.

[0012] Further, under the action of the controller: the light provided by the light source enters the designated area through the first bandpass filter, and the reflected signal or excitation signal generated by the analyte in the designated area being irradiated by the light passes sequentially along the optical path through the annular center of the first bandpass filter, the annular center of the light source, the second bandpass filter, and the lens before entering the imaging spectral detection device.

[0013] 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 data on the distribution of the analyte and the wavelength range capable of acquiring spectral data of the analyte.

[0014] Further, the light source includes two types of light sources, one of which provides infrared light with a wavelength range of 800 nm to 1000 nm; the other light source provides ultraviolet light with a wavelength range of 300 nm to 390 nm.

[0015] Further, the imaging spectral detection device includes a sensor and a periodic pixel-level filter structure, the periodic pixel-level filter structure being disposed on the surface of the sensor; the periodic pixel-level filter structure performs spectral modulation on the incoming light signal, and the sensor generates an image containing the spectral information to be measured.

[0016] Further, the light signal acquired by the imaging spectral detection device includes a reflection signal generated by the analyte in the specified area being irradiated by light, and an excitation signal generated by the analyte being irradiated by light.

[0017] According to an analyte detection device provided by the present invention, the detection device includes a portable device.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] 1. The present application uses a controller to control the light source and the imaging spectral detection device to image the imaging area to obtain the corresponding image and / or spectral data, without the need for electrochemical reaction with the analyte, making the detection method more convenient, especially when detecting analytes in living organisms, it can achieve the purpose of non-invasive detection.

[0020] 2. This application utilizes the non-uniform distribution of analytes in the imaging region to obtain spectral data from different regions. Since the distribution of components other than the analytes in the imaging region is relatively uniform, the differences in spectral data from different regions can directly reflect the information related to the analytes and spectral data after essentially excluding the influence of non-analytes, such as the concentration of the analytes.

[0021] 3. This application uses fluorescence spectroscopy for detection, avoiding the traditional method of measuring analytes using Raman spectroscopy, thereby achieving low cost and miniaturization of the detection system, and achieving the purpose of real-time detection.

[0022] 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:

[0023] FIG1 is a schematic diagram of the structure of an analyte detection device provided in Embodiment 1;

[0024] FIG2 is a schematic diagram of the structure of a watch provided in Embodiment 1;

[0025] FIG3 is an exploded view of the internal structure of a watch provided in Embodiment 1;

[0026] FIG4 is a schematic diagram of the wearing structure of a watch provided in Embodiment 1;

[0027] FIG5 is a schematic diagram of the back structure of a watch provided in Embodiment 1; Specification 2 / 11 pages 4 CN 121337346 A

[0028] FIG6 is a flowchart of Embodiment 2;

[0029] FIG7 is a schematic diagram of the first image acquired in Embodiment 3;

[0030] FIG8 is a schematic diagram of the second image acquired in Embodiment 3;

[0031] FIG9 is a schematic diagram of the detection model of Embodiment 3;

[0032] FIG10 is a schematic diagram of the detection point-reference point spectral data obtained in Embodiment 3;

[0033] Figure 11 shows the experimental results of the accuracy of the analysis results of the analysis model;

[0034] Figure 12 is a schematic diagram of the structure of the electronic device provided in Example 6.

[0035] In the figure:

[0036] 100: Imaging area; 200: Detection device;

[0037] 201: Light source; 202: Imaging spectrum detection device;

[0038] 203: Controller; 204: First bandpass filter;

[0039] 205: Lens; 206: Second bandpass filter;

[0040] 207: Circuit board 207; 501: Processor;

[0041] 502: Memory. Detailed Embodiments

[0042] 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.

[0043] Example 1

[0044] Figure 1 is a structural diagram of this embodiment. This embodiment provides an analyte detection system, including a light source 201, an imaging spectral detection device, and a controller 203. The controller 203 is electrically or communicatively connected to the light source 201 and the imaging spectral detection device, respectively. The light source 201 can provide light within a preset wavelength range. Under the action of the controller 203: the light source 201 provides light within a preset wavelength range to a designated area, and the imaging spectral detection device images the designated area to obtain corresponding images and / or spectral data. The designated area is the imaging area 100 when the detection system is working.

[0045] The light source 201 can provide light within a preset wavelength range. The light source 201 may include a single type of light source 201, and 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 may also include two types of light sources 201, one of which 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. Since different wavelength ranges of light are needed to obtain analyte distribution data and spectral data, there are two possible implementation methods: one light source 201 that can provide light with a large wavelength range; or two light sources 201 that each provide light with a smaller wavelength range. When there is only 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 for obtaining analyte distribution data and the wavelength range for obtaining analyte spectral data, such as a halogen lamp. When there are two types of light sources 201, the two light sources 201 provide different light, with one light covering the wavelength range for obtaining analyte distribution data and the other covering the wavelength range for obtaining analyte spectral data, such as an infrared lamp combined with an ultraviolet lamp, or a visible light lamp combined with an ultraviolet lamp.

[0046] To ensure uniform illumination of the imaging area 100, a ring light source 201 can be used. The light source 201 has multiple light-emitting modules that 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.

[0047] The imaging spectral detection device is capable of imaging the imaging area 100 according to instructions to obtain a corresponding image, and is also capable of obtaining corresponding spectral data according to instructions. The imaging spectral detection device includes a sensor and a periodic pixel-level filter structure, the periodic pixel-level filter structure being disposed on the surface of the sensor. The periodic pixel-level filter structure is used for spectral modulation of the incoming light signal, so that the sensor can generate an image containing the spectral information to be measured.

[0048] The periodic pixel-level filter structure includes multiple filter pixel channels with different pixel-level structures, multiple...Each filter pixel channel has the same size and is uniformly arranged, with its length and width being integer multiples of the pixel size within the image sensor. Filter pixel channels with different pixel-level filter structures 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. The light signal acquired by the imaging spectral detection device includes the reflection signal generated by the analyte being irradiated by light in the specified area and the excitation signal generated by the analyte being irradiated by light.

[0049] The controller 203 is configured to control the light source 201 to provide light within a preset wavelength range to irradiate the first area, and to control the imaging spectral detection device to image the first area to obtain an image of the imaging area 100, and to control the imaging spectral detection device to acquire spectral data from the image reflecting the uneven distribution of the reflection signal or excitation signal generated by the analyte being irradiated by light in the imaging area 100. Information about the analytes in the imaging region 100 is obtained based on the acquired spectral data. This information includes the correlation between the analytes 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, and similarly, when the second type of light source 201 is on, the first type of light source 201 is off, and they do not interfere with each other.

[0050] A first bandpass filter 204 is provided between the light source 201 and the designated region. The first bandpass filter 204 has an annular shape and allows light within a preset wavelength range to pass through, while blocking light outside the preset wavelength range. A second bandpass filter 206 is provided on the side of the lens 205 near the imaging spectral detection device 202. The second bandpass filter 206 allows light within a preset wavelength range to pass through, while blocking light outside the preset wavelength range. The imaging spectral detection device, the light source 201, and the designated region are arranged sequentially along a specified direction. An optical path is provided between the imaging spectral detection device and the designated area, and the light source 201 is located between the spectral detection device and the designated area. The shape of the light source 201 includes a ring, and the optical path passes through the middle of the ring-shaped light source 201.

[0051] Under the action of the controller 203: the light provided by the light source 201 enters the designated area through the first bandpass filter 204, and the reflected signal or excitation signal generated by the analyte in the designated area when irradiated by the light passes sequentially along the optical path through the middle of the ring of the first bandpass filter 204, the middle of the ring of the light source 201, the lens 205, and the second bandpass filter 206 before entering the imaging spectral detection device 202.

[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 (page 4 / 11, CN 121337346 A 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 detection system can be integrated on the detection device 200, and can be a separate detection device 200 or integrated into a portable device, such as a watch or mobile phone, so as to realize 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, and 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, and an opening area is formed on the back of the watch case to fit with the skin of the user's wrist. During detection, the area where the opening area on the back of the watch fits with 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 spectral 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 spectral 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 area is acquired from the image using an imaging spectral detection device. 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. (Instruction manual, page 5 / 11, CN 121337346 A)

[0063] Analysis step: Information about the analyte in the imaging area is obtained based on the acquired spectral data. This information includes the association between the analyte and the spectral data. Because the distribution of the analyte differs in different partitions, 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 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 greater than 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 obtain high-quality effective fluorescence spectral signals.Effective fluorescence spectral signals are extracted to eliminate interference from the spectral signals of the excitation light. 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 grayscale 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 acquired respectively. Specifically, based on the grayscale values ​​of pixels in the second image, a pixel with a grayscale value meeting preset requirements 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 on page 6 / 11 of the second image specification (CN 121337346 A). 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 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), 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 will directly affect the spectral data of the reference point. The first image cannot distinguish the areas affected by these factors. By setting a preset deviation range for the gray values, these influencing factors can be effectively eliminated. Furthermore, the fact that the gray values ​​of the reference point and the selected detection point are within a 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 generating radiometric calibration coefficients through prior radiometric calibration, and then calculating the spectral lines 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 that detection point can be the average of the fluorescence spectral data of these pixels. 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 spectral data of the acquired 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 the intermediate hidden layer, which outputs the final predicted blood glucose concentration value after feature combination through deep learning via convolution operations. The Output layer can also output a neuron instruction manual after feature combination through deep learning via convolution operations.Page 7 / 11, CN 121337346 A Output1 is used as an intermediate result value. The intermediate result value Output1 and two infrared IR feature brightness values ​​are used for model training 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 setting of different parameters 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 law 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 concentration 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 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 the detection model's results. 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, since the color of the area where the vein is located differs from the color of the area where the non-vein is located, the imaging area can be easily divided into the area where the vein is located and the area where the non-vein is located.

[0084] 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 excitation light wavelength 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 excitation light wavelength is greater than 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 excitation light's spectral signal and extract the effective fluorescence spectral signal. After absorbing ultraviolet light in the 300-390 nm wavelength range, glucose in veins can emit fluorescence radiation signals in the 400-800 nm visible light band. This band is within the effective response range of the imaging spectral detection device, and the characteristic spectral intensity of this fluorescence radiation signal is positively correlated with the glucose concentration, exhibiting high fluorescence excitation efficiency.

[0085] Spectral acquisition steps: Based on the grayscale distribution of pixels in the first image, the imaging area is divided into areas where veins are located and areas where non-vein vessels are located. Detection points are selected from areas where veins are located, and reference points are selected from areas where non-vein vessels are located. The spectral data of the detection points and the spectral data of the reference points are acquired respectively. Specifically, based on the grayscale values ​​of pixels in the second image, a pixel with a grayscale value that meets the preset requirements or a combination of the pixel and its neighboring pixels is selected from the areas where veins are located as a detection point. A pixel with a grayscale value within the preset deviation range of the selected detection point or a combination of the pixel and multiple neighboring pixels is selected from the areas where non-vein vessels are located as a reference point. The fluorescence spectral data of the detection points and the fluorescence spectral data of the reference points are calculated. The reason why the gray values ​​of the reference points and the selected detection points 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 will directly affect the spectral data of the reference points. 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 the average value of the fluorescence spectral data of all reference points can be calculated separately.

[0087] Analysis steps: After preprocessing, the spectral data of the acquired detection points and reference points are input into the trained detection model, which outputs the glucose concentration. 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 of the detection model, and the blood test results are used as the output of the detection model to train 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 in the activation function layer is the ReLU function.

[0089] 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 through the activation function. The Flatten layer flattens the output of the convolutional layer into a one-dimensional vector, facilitating connection to subsequent fully connected layers, resulting in a final output dimension of 1. During model training, the Adam optimizer is used, with mean squared error as the loss function and mean absolute error as the performance metric for model evaluation.

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

[0091] The training level of the detection model needs to be set with different parameters as required. Multiple extracted glucose feature values ​​will continuously learn according to the different parameter settings until the error between the output and the standard glucose value of the aforementioned label value meets the requirements, at which point training stops to obtain the detection model.

[0092] Through multiple iterative training iterations, neurons learn the corresponding variation patterns between different glucose concentrations and the 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 subject based on fluorescence spectroscopy and obtains the glucose detection result based on this 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 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 analyte detection specification is 9 / 11 pages, CN 121337346 AThe 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 know that, in addition to implementing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code manner, the method steps can be logically programmed to enable the present invention to provide...The system and its various devices, modules, and units implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. 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 interconnect buses and bridges as described on pages 10 / 11 of the specification, CN 121337346 A. The bus connects 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 described further in this invention. 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 can 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 analytes.

[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.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 121337346 A Figure 1 Instruction manual Figure 1 / 7 page 14 CN 121337346 A Figure 2 Figure 3 Instruction manual Figure 2 / 7 page 15 CN 121337346 A Figure 4 Figure 5 Instruction manual Figure 3 / 7 page 16 CN 121337346 A Figure 6 Figure 7 Instruction manual Figure 4 / 7 page 17 CN 121337346 A Figure 8 Figure 9 Instruction manual Figure 5 / 7 page 18 CN 121337346 A Figure 10 Figure 11 Instruction manual Figure 6 / 7 page 19 CN 121337346 A Figure 12 Instruction manual Figure 7 / 7 page 20 CN 121337346 A Abstract The present invention belongs to the field of optical analysis, and provides a system and an apparatus for testing an analyzer. The system for testing includes a light source, animaging spectrum detection apparatus, and a controller. The controller establishes an electric connection or communication connection with the light source and the imaging spectrum detection apparatus separately, and the light source is capable of providing light within a preset wavelength range; and under the effect of the controller, the light source provides the light within the preset wavelength range to a specified area, and the imaging spectrum detection apparatus images the specified area to obtain a corresponding image and / or spectral data. According to the present invention, the light source is controlled by the controller, and the imaging spectrum detection apparatus images the imaging area, to obtain the corresponding image and / or spectral data, so that the system is easy to operate, can be integrated into a portable device, and has strong applicability.

Claims

1. An analyte detection system, characterized by, The system comprises a light source (201), an imaging spectral detection device (202), and a controller (203), the controller (203) is electrically connected or in communication connection with the light source (201) and the imaging spectral detection device, the light source (201) can provide light in a preset wavelength range; Under the action of the controller (203), the light source (201) provides light in a preset wavelength range to a designated area, and the imaging spectral detection device images the designated area to obtain corresponding image and / or spectral data.

2. The analyte detection system of claim 1, wherein, A first band-pass filter (204) is arranged between the light source (201) and the designated area, the shape of the first band-pass filter (204) comprises a ring shape, the first band-pass filter (204) allows light in a preset wavelength range to pass through, and light in a non-preset wavelength range is cut off.

3. The analyte detection system of claim 1, wherein, A second band-pass filter (206) is arranged between the imaging spectral detection device (202) and the lens (205), the second band-pass filter (206) allows light in a preset wavelength range to pass through, and light in a non-preset wavelength range is cut off.

4. The analyte detection system of claim 1, wherein, The imaging spectral detection device, the light source (201), and the designated area are arranged in a designated direction in sequence. An optical path is arranged between the imaging spectral detection device and the designated area, and the light source (201) is located between the imaging spectral detection device and the designated area. The shape of the light source (201) comprises a ring shape, and the optical path passes through the middle part of the ring-shaped light source (201).

5. The analyte detection system of claim 4, wherein, Under the action of the controller (203), the light provided by the light source (201) enters the designated area through the first band-pass filter (204), and the reflection signal or excitation signal generated by the analyte in the designated area under the irradiation of the light sequentially passes through the middle part of the ring-shaped first band-pass filter (204), the middle part of the ring-shaped light source (201), the lens (205), and the second band-pass filter (206) along the optical path, and then enters the imaging spectral detection device.

6. The analyte detection system of claim 1, wherein, The light source (201) comprises a single light source (201), and the wavelength range of the light provided by the single light source (201) simultaneously covers the wavelength range capable of obtaining analyte distribution data and the wavelength range capable of obtaining analyte spectral data.

7. The analyte detection system of claim 1, wherein, The light source (201) comprises two kinds of light sources (201), one of which provides infrared light with a wavelength range of 800 nanometers to 1000 nanometers; The other light source (201) provides ultraviolet light with a wavelength range of 300 nanometers to 390 nanometers.

8. The analyte detection system of claim 1, wherein, The imaging spectral detection device comprises a sensor and a periodic pixel-level filter structure, and the periodic pixel-level filter structure is arranged on the surface of the sensor. The periodic pixel-level filter structure performs spectral modulation on the incoming light signal, and the sensor generates an image containing the to-be-measured spectral information.

9. The analyte detection system of claim 8, wherein, The light signal obtained by the imaging spectral detection device includes a reflection signal generated by the analyte in the designated area under the irradiation of the light and an excitation signal generated by the analyte under the irradiation of the light.

10. An analyte detection device, characterized by, The detection device is integrated with the analyte detection system of any one of claims 1-9, and the detection device comprises a portable device.

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