A high-precision micro infrared multi-spectral blood glucose measurement device and its measurement method

Abstract

The present invention relates to a blood glucose measurement device and method, specifically to a high-precision miniature infrared multi-spectral blood glucose measurement device and its measurement method, which solves the technical problem that the current near-infrared non-invasive blood glucose measurement technology is difficult to effectively extract a high-purity human infrared multi-spectral scattering signal, resulting in low measurement accuracy. The infrared multi-spectral blood glucose measurement device provided by the present invention uses a narrow-band infrared light source module to obtain an infrared multi-spectral scattering signal with higher information purity, improving the accuracy of blood glucose measurement; and uses a human scattered light enhancement module to enhance the infrared spectral absorption intensity of human tissues, increasing the difference between the infrared multi-spectral scattering signal generated by human tissues and the background light signal of no-load measurement, thereby further improving the measurement accuracy. At the same time, the present invention also provides a blood glucose measurement method. Combining the multi-level metric learning-neural network method of infrared multi-spectral scattering signals can retain effective infrared multi-spectral scattering signals and achieve high-precision blood glucose measurement.

Description

Technical Field

[0001] The present invention relates to a blood glucose measuring device and method, and particularly to a high-precision micro infrared multi-spectral blood glucose measuring device and its measuring method. Background Art

[0002] With the rapid development of social economy and the increasing living standards of people, the number of diabetes patients is increasing year by year globally, and the blood glucose monitoring field shows a huge market demand. As a device that can monitor blood glucose without the need to puncture the skin to obtain a blood sample, non-invasive blood glucose meters have received extensive attention from many research institutions and enterprises. The optical detection method usually focuses a beam of light on human tissue, and based on the relationship between optical information such as intensity, phase, polarization angle, frequency, and the scattering coefficient of the target tissue and blood glucose concentration, the change of optical information is analyzed to obtain blood glucose concentration information. The optical non-invasive blood glucose measuring device benefits from the advantages of low cost, rich functions, and easy integration with various sensor functions, and has a huge market application demand.

[0003] Near-infrared spectroscopy is based on the spectral absorption characteristics of the chemical bonds C-H, O-H, and C=O of glucose (C6H 12 O6) molecules themselves in the near-infrared band, as well as the strong penetration ability of near-infrared light in human tissue. Many studies have been carried out on constructing near-infrared non-invasive blood glucose measuring devices using inexpensive near-infrared light sources LED and LD. For example, Chinese Patent CN116019448A discloses a blood glucose meter that uses a four-in-one Y-shaped optical fiber to modulate laser signals of different wavelengths, and indirectly measures blood glucose through the upper computer data software according to the different spectral absorption coefficients of blood glucose in different bands; Chinese Patent CN115633957A discloses a blood glucose prediction method and system based on high-order and fractional lower-order statistics. By decomposing the noisy signal, a denoised signal is obtained to provide a reliable signal data source, and then the eigenvalue of the high-order statistic and the fractional lower-order statistic is extracted to construct a blood glucose prediction model; Chinese Patent CN111599470A discloses a method for improving the accuracy of near-infrared non-invasive blood glucose detection. By establishing a general mathematical model between the detection site and the true blood glucose value, and establishing a sample set based on the user's true blood glucose information, the change law of the non-invasive detection value is obtained by training with a machine learning algorithm in combination with the sample set, and a blood glucose prediction model is established.

[0004] However, due to the complex overlap of the intrinsic absorption peaks of various biochemical substances (such as water, fat, protein, etc.) and glucose in human tissue in the infrared band, large individual differences in humans, and the complexity of the actual measurement background, it is difficult for current near-infrared non-invasive blood glucose measurement technology to effectively extract high-purity human infrared multi-spectral scattering signals and achieve high-precision human near-infrared non-invasive blood glucose measurement. Summary of the Invention

[0005] The object of the present invention is to solve the technical problem that the current non-invasive near-infrared blood glucose measurement technology is difficult to effectively extract a high-purity human infrared multi-spectral scattering signal, resulting in low measurement accuracy, and to provide a high-precision micro-infrared multi-spectral blood glucose measurement device and its measurement method.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A high-precision micro-infrared multi-spectral blood glucose measurement device, characterized in that it includes a narrow-band infrared light source module, a human body scattered light enhancement module, a detector module, and a data processing module;

[0008] The narrow-band infrared light source module is used to generate N narrow-band infrared lights with different central wavelengths. The central wavelengths of the narrow-band infrared lights include the human tissue background absorption spectral band and the glucose absorption spectral band, where N is an integer and N≥2;

[0009] The human body scattered light enhancement module is arranged on the outgoing light path of the narrow-band infrared light and is arranged on the human tissue during measurement, and is used to enhance the infrared spectral absorption intensity of the human tissue;

[0010] The detector module is arranged on the transmission light path of the infrared multi-spectral scattering signal generated by the reflection of the human tissue and is electrically connected to the data processing module, and is used to detect the infrared multi-spectral scattering signal and the no-load measurement background light signal, and send them to the data processing module. The data processing module calculates the blood glucose concentration according to the infrared multi-spectral scattering signal and the no-load measurement background light signal;

[0011] The narrow-band infrared light source module includes N narrow-band infrared semiconductor lasers distributed in an annular belt shape, and the central wavelength of each narrow-band infrared semiconductor laser is different;

[0012] Alternatively, the narrow-band infrared light source module includes a light source module for generating a detection beam and a narrow-band infrared multi-spectral filtering module arranged on the outgoing light path of the detection beam; the narrow-band infrared multi-spectral filtering module includes N narrow-band infrared filter elements with different central wavelengths distributed in an annular belt shape, and the narrow-band infrared filter elements are on the outgoing light path of the detection beam during measurement.

[0013] Furthermore, the included angle between the human body scattered light enhancement module and the outgoing light path of the narrow-band infrared light is 45 to 80 degrees; if the included angle is too small, the scattered light on the human body surface directly irradiates the human body scattered light enhancement module, resulting in large background noise; if the included angle is too large, the infrared multi-spectral scattering signal generated by the human tissue attenuates too fast, and it is difficult to obtain an effective signal;

[0014] Alternatively, the human body scattered light enhancement module is arranged perpendicular to the narrowband infrared light emission optical path, the detector module is arranged at the center of the annular structure formed by N narrowband infrared semiconductor lasers or at the center of the annular structure formed by N narrowband infrared filter elements, and the photosensitive surface of the detector module is arranged at the proximal end of the human body scattered light enhancement module.

[0015] Furthermore, the light source module includes a broadband infrared light source and a coupling lens arranged on the emission optical path of the broadband infrared light source;

[0016] The broadband infrared light source includes N infrared light sources with different central wavelengths distributed in an annular shape, and the coupling lens includes N coupling lens elements corresponding to the N infrared light sources; the N coupling lens elements are respectively arranged corresponding to the N narrowband infrared filter elements, and the central wavelength of the infrared light source is the same as that of its corresponding narrowband infrared filter element;

[0017] Alternatively, the broadband infrared light source includes one infrared light source, and the coupling lens includes one coupling lens element corresponding to the one infrared light source.

[0018] Furthermore, the narrowband infrared filter element adopts an integrated micro-nano superstructure filter unit or a discrete thin film filter element mounted on a rotating wheel, and the rotating wheel is driven by a motor to rotate.

[0019] Furthermore, the full width at half maximum of the narrowband infrared filter element is less than or equal to 12 nm.

[0020] Furthermore, the human body scattered light enhancement module is a plasmonic metal nanoparticle infrared enhancement film;

[0021] The plasmonic metal nanoparticle infrared enhancement film adopts a composite metal plasmonic structure composed of gold nanoparticles, silver nanoparticles and aluminum nanoparticles.

[0022] Furthermore, the detector module includes an imaging lens and a photodetector arranged in sequence along the infrared multi-spectral scattering signal transmission direction.

[0023] Furthermore, the photodetector is a single-point detector or a planar array detector; when the photodetector is a single-point detector, a germanium, indium, gallium or arsenic single-point detector is adopted.

[0024] The present invention also provides a measurement method for the above-mentioned high-precision micro infrared multi-spectral blood glucose measurement device, which is characterized in that it includes the following steps:

[0025] Step 1, turn on the detector module, detect the no-load measurement background light signal, and send it to the data processing module;

[0026] Step 2: Place the human body scattered light enhancement module on the human body tissue, and then turn on the narrowband infrared light source module;

[0027] Step 3: The N narrowband infrared lights generated by the narrowband infrared light source module are incident on the human body tissue through the human body scattered light enhancement module. The human body tissue reflects to generate an infrared multi-spectral scattering signal, and then the detector module detects the infrared multi-spectral scattering signal, obtaining a total of N infrared multi-spectral scattering signals and sending them to the data processing module;

[0028] Step 4: The data processing module calculates the blood glucose concentration based on the N infrared multi-spectral scattering signals and the no-load measurement background light signal to complete the blood glucose measurement.

[0029] Further, Step 4 is specifically:

[0030] Step 4.1: Calculate the normalized human multi-spectral infrared signals in the background absorption spectrum band and the glucose absorption spectrum band of the human body tissue respectively according to the following formula:

[0031]

[0032]

[0033]

[0034] Among them, represents the central wavelength of the i th narrowband infrared light, 1 ≤ i ≤ N, represents the normalized human multi-spectral infrared signal when the central wavelength of the narrowband infrared light is , represents the infrared multi-spectral scattering signal when the central wavelength of the narrowband infrared light is , represents the no-load measurement background light signal, represents the exponential operation, represents the extinction factor of the human body tissue when the central wavelength of the narrowband infrared light is , represents the concentration of biochemical substances in the human body tissue, represents the optical path length of the narrowband infrared light with the central wavelength of in the human body tissue, represents the light intensity of the narrowband infrared light with the central wavelength of , represents the sensing background, which is the intrinsic loss of the test optical path;

[0035] Step 4.2: Sequentially adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform first-level metric learning on the normalized human multi-spectral infrared signals in the human tissue background absorption spectral band, and obtain the one-dimensional human absorption background signal TData1;

[0036] Step 4.3: Sequentially adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform second-level metric learning on the normalized human multi-spectral infrared signals in the glucose absorption spectral band, and obtain the three-dimensional human glucose absorption signal GData3;

[0037] Step 4.4: Sequentially adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform third-level metric learning on the one-dimensional human absorption background signal TData1 and the three-dimensional human glucose absorption signal GData3, and obtain the three-dimensional high-purity human glucose absorption signal MData3;

[0038] Step 4.5: Input the three-dimensional high-purity human glucose absorption signal MData3 into the input layer of the BP neural network. The BP neural network processes it and outputs the predicted blood glucose concentration to complete blood glucose measurement.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] 1. A high-precision micro infrared multi-spectral blood glucose measurement device provided by the present invention adopts a narrow-band infrared light source module, which can avoid the defect that it is difficult for a broadband filter structure to effectively eliminate the interference of various complex substances, obtain an infrared multi-spectral scattering signal with a relatively high information purity, and improve the accuracy of blood glucose measurement; adopt a human scattered light enhancement module to enhance the infrared spectral absorption intensity of human tissues, improve the intensity of the infrared multi-spectral scattering signal generated by human tissues, and realize the efficient perception of the change of the multi-spectral infrared weak signal in human blood glucose measurement, so as to make up for the defect that the intensity of the narrow-band infrared light signal generated by the narrow-band infrared light source module is weak, resulting in a weak intensity of the infrared multi-spectral scattering signal generated by human tissues, increase the difference between the infrared multi-spectral scattering signal generated by human tissues and the background light signal of no-load measurement, and further improve the measurement accuracy, meeting the requirements of a non-invasive infrared multi-spectral blood glucose measurement device for high-precision detection of weak human signals;

[0041] 2. A high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention uses a light source module and a narrow-band infrared multi-spectral filtering module to form a narrow-band infrared light source module, which can broaden the working wavelength band of the narrow-band infrared light source module to cover the human tissue background absorption peak and the glucose absorption peak, avoiding the disadvantage that the response spectral band of traditional infrared multi-spectral sensors is relatively narrow, making it difficult to completely collect the infrared light absorption characteristics of complex human tissues, and meeting the development requirements of non-invasive infrared multi-spectral blood glucose measurement for wide spectral band, high precision and high purity information measurement;

[0042] 3. A high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention uses N narrow-band infrared semiconductor lasers to directly form a narrow-band infrared light source module with an annular structure, which can achieve high-integration on-chip array control of N narrow-band infrared lights with different central wavelengths;

[0043] 4. For a high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention, the angle between the human body scattered light enhancement module and the narrow-band infrared light incident optical path is 45° to 80°, which can avoid the direct interference of the human body surface scattered light and further improve the accuracy of blood glucose measurement;

[0044] 5. A high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention has the human body scattered light enhancement module perpendicular to the narrow-band infrared light incident optical path, and the detector module is integrated in the center of the narrow-band infrared light source module, which can reduce the volume of the blood glucose measurement device, realize the integrated control and detection of micro high-integration planar multi-spectral infrared information, and its manufacturing process is mature, convenient, inexpensive and easy to realize batch industrial production, meeting the market requirements of miniaturization, light weight and portability for non-invasive blood glucose measurement;

[0045] 6. For a high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention, the full width at half maximum of the narrow-band infrared filter element is less than or equal to 12 nm, which can achieve fine spectral detection and avoid the defect that traditional broadband filter structures are difficult to effectively eliminate the interference of various complex substances;

[0046] 7. A measurement method of a high-precision micro-infrared multi-spectral blood glucose measurement device provided by the present invention uses a multi-level non-linear self-reference metric learning method for infrared multi-spectral scattered signals. By normalizing the infrared multi-spectral scattered signals and the no-load measurement background light signals, the interference noise is eliminated by the self-reference method of multi-spectral signals, and three-level metric learning is combined to retain the effective infrared multi-spectral scattered signals, obtain high-purity human glucose infrared absorption information, and then combined with the neural network big data learning ability, the accuracy of non-invasive human blood glucose measurement can be improved. Description of the Drawings

[0047] Figure 1Schematic diagram of the high-precision micro infrared multi-spectral blood glucose measurement device according to the first embodiment of the present invention (the data processing module is not shown);

[0048] Figure 2 Schematic diagram of the narrow-band infrared multi-spectral filtering module in the high-precision micro infrared multi-spectral blood glucose measurement device according to the first embodiment of the present invention;

[0049] Figure 3 Flow chart of step 4 in the measurement method of the high-precision micro infrared multi-spectral blood glucose measurement device according to the first embodiment of the present invention;

[0050] Figure 4 Schematic diagram of the results of blood glucose measurement using the first embodiment of the present invention. Among them, (a) is the Bland-Altman analysis chart of the predicted blood glucose concentration, and (b) is the Clarke error analysis chart of the predicted blood glucose concentration;

[0051] Figure 5 Schematic diagram of the high-precision micro infrared multi-spectral blood glucose measurement device according to the second embodiment of the present invention (the data processing module is not shown);

[0052] Figure 6 Schematic diagram of the narrow-band infrared multi-spectral filtering module and the detector module in the high-precision micro infrared multi-spectral blood glucose measurement device according to the second embodiment of the present invention;

[0053] Figure 7 Schematic diagram of the high-precision micro infrared multi-spectral blood glucose measurement device according to the third embodiment of the present invention (the data processing module is not shown);

[0054] Figure 8 Schematic diagram of the narrow-band infrared light source module and the detector module in the high-precision micro infrared multi-spectral blood glucose measurement device according to the third embodiment of the present invention;

[0055] Explanation of the reference numerals is as follows:

[0056] 1 - Narrow-band infrared light source module, 2 - Human body scattered light enhancement module, 3 - Detector module, 4 - Light source module, 5 - Narrow-band infrared multi-spectral filtering module, 6 - Narrow-band infrared semiconductor laser, 7 - Broad-spectrum infrared light source, 8 - Coupling lens, 9 - Narrow-band infrared filter element, 10 - Imaging lens, 11 - Photoelectric detector. Detailed implementation manners

[0057] The following further elaborates in detail on a high-precision micro infrared multi-spectral blood glucose measurement device and its measurement method proposed by the present invention in conjunction with the accompanying drawings and specific implementation manners. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of the present invention, and the purpose is not to limit the protection scope of the present invention.

[0058] Embodiment 1

[0059] A high-precision micro infrared multi-spectral blood glucose measurement device, as Figure 1 shown, includes a narrowband infrared light source module 1, a human body scattered light enhancement module 2, a detector module 3, and a data processing module. The narrowband infrared light source module 1 is used to generate N beams of narrowband infrared light with different central wavelengths, where N is an integer and 2 ≤ N ≤ 6. In this embodiment, N = 6 is taken. The central wavelengths of the narrowband infrared light include the human tissue background absorption spectral band and the glucose absorption spectral band. Among them, the human tissue background absorption spectral band is selected as 850 nm and 940 nm, and the glucose absorption spectral band is selected as 1300 nm, 1400 nm, 1550 nm, and 1640 nm, which can cover the entire near-infrared wide spectral response range of 850 nm to 1640 nm.

[0060] In this embodiment, the narrowband infrared light source module 1 includes a light source module 4 for generating a detection beam and a narrowband infrared multi-spectral filtering module 5 arranged in the exit direction of the detection beam. Among them, the light source module 4 includes a broadband infrared light source 7 and a coupling lens 8 arranged on the light path of the exit light of the broadband infrared light source 7. The broadband infrared light source 7 includes an infrared light source. Correspondingly, the coupling lens 8 also includes a coupling lens element correspondingly arranged with an infrared light source. The broadband infrared light source 7 uses a halogen lamp or an LED lamp.

[0061] As Figure 2 shown, the narrowband infrared multi-spectral filtering module 5 includes 6 narrowband infrared filter elements 9 with different central wavelengths distributed in an annular belt shape, which are used to generate 6 beams of narrowband infrared light with different central wavelengths and incident on the human body scattered light enhancement module 2. By adjusting the positions of the 6 narrowband infrared filter elements 9, they are sequentially arranged on the exit light path of the detection beam, so as to sequentially generate narrowband infrared light with different central wavelengths. The full width at half maximum of the narrowband infrared filter element 9 is less than or equal to 12 nm, which can avoid the problem that the broadband filtering structure of traditional infrared measurement devices is difficult to effectively eliminate the interference of various complex substances, and realize the fine detection of infrared spectral signals. The narrowband infrared filter element 9 uses an integrated micro-nano superstructure filter unit or a discrete thin film filter element installed on a rotating wheel. The rotating wheel can be driven by a motor to rotate, and 6 narrowband infrared filter elements 9 with different central wavelengths are sequentially selected in the light path, corresponding to generating six narrowband infrared lights of I0(850), I0(940), I0(1300), I0(1400), I0(1550), and I0(1640).

[0062] The human body scattered light enhancement module 2 is arranged on the outgoing light path of the narrowband infrared light, and the included angle with the narrowband infrared light outgoing light path is 45 degrees, which can avoid the direct interference of the scattered light on the human body surface. When measuring, the human body scattered light enhancement module 2 is arranged on the human tissue, and is used to enhance the infrared spectrum absorption intensity of the human tissue, so as to increase the difference between the infrared multi-spectral scattered signal generated by the human tissue and the background light signal of the no-load measurement. The human body scattered light enhancement module 2 includes a plasmonic metal nanoparticle infrared enhancement film, and the plasmonic metal nanoparticle infrared enhancement film adopts a composite metal plasmonic structure composed of metal nanoparticles such as gold nanoparticles, silver nanoparticles and aluminum nanoparticles. The human body scattered light enhancement module 2 uses the plasmonic metal nanoparticle infrared enhancement film to enhance the infrared spectrum absorption intensity of the human tissue through the surface plasmon resonance absorption effect, increases the difference between the infrared multi-spectral scattered signal generated by the human tissue and the background light signal of the no-load measurement, thereby improving the measurement accuracy.

[0063] The detector module 3 is arranged on the transmission light path of the infrared multi-spectral scattered signal generated by the reflection of the human tissue, and is electrically connected to the data processing module, and is used to detect the infrared multi-spectral scattered signal, and detect the background light signal of the no-load measurement, and send it to the data processing module, and the data processing module calculates the blood glucose concentration according to the infrared multi-spectral scattered signal and the background light signal of the no-load measurement. The detector module 3 includes an imaging lens 10 and a photodetector 11 arranged in sequence along the transmission direction of the infrared multi-spectral scattered signal. Since a single infrared light source is adopted in this embodiment, and 6 narrowband infrared filter elements 9 are sequentially gated to generate 6 narrowband infrared lights with different central wavelengths in a time-sharing manner, the photodetector 11 can be selected as a germanium, indium, gallium or arsenic single-point detector.

[0064] For the high-precision micro infrared multi-spectral blood glucose measurement device provided in this embodiment, first, the detector module 3 is used to detect the background light signal of the no-load measurement, then the human body scattered light enhancement module 2 is arranged on the human tissue, the light source module 4 is turned on to generate a collimated parallel detection beam and incident on the gated area of the narrowband infrared multi-spectral filtering module 5, so as to generate a narrowband infrared light with a specific central wavelength and irradiate the human body scattered light enhancement module 2. The human body scattered light enhancement module 2 uses the plasmonic metal nanoparticle scattered light enhancement film to enhance the infrared multi-spectral absorption intensity of the human tissue, and the included angle with the narrowband infrared light outgoing light path can reduce the interference of the scattered light generated by the direct specular reflection on the human tissue surface; the detector module 3 detects the infrared multi-spectral scattered signal, and the data processing module is used to calculate the blood glucose concentration according to the infrared multi-spectral scattered signal and the background light signal of the no-load measurement.

[0065] This embodiment also provides a measurement method for the above-mentioned high-precision micro infrared multi-spectral blood glucose measurement device, including the following steps:

[0066] Step 1: Turn on the detector module 3, detect the background light signal under no-load measurement, and send it to the data processing module.

[0067] Step 2: Set the human body scattered light enhancement module 2 on the human tissue, and then turn on the narrowband infrared light source module 1.

[0068] In this embodiment, the specific method for the narrowband infrared light source module 1 to generate 6 beams of narrowband infrared light is as follows: The light source module 4 in the narrowband infrared light source module 1 generates a detection beam, and adjusts the narrowband infrared multi-spectral filtering module 5 so that 6 narrowband infrared filter elements 9 are successively in the outgoing light path of the detection beam, and 6 beams of narrowband infrared light with different central wavelengths are generated in sequence.

[0069] Step 3: The 6 beams of narrowband infrared light generated by the narrowband infrared light source module 1 are incident on the human tissue through the human body scattered light enhancement module 2. The human tissue reflects to generate an infrared multi-spectral scattering signal. Then, use the detector module 3 to detect the infrared multi-spectral scattering signal, obtain 6 infrared multi-spectral scattering signals, and send them to the data processing module.

[0070] Step 4: The data processing module calculates the blood glucose concentration based on the 6 infrared multi-spectral scattering signals and the background light signal under no-load measurement to complete the blood glucose measurement. As Figure 3 shown, step 4 is specifically as follows:

[0071] Step 4.1: Calculate the normalized human multi-spectral infrared signals in the background absorption spectrum band and the glucose absorption spectrum band of the human tissue respectively according to the following formula:

[0072]

[0073]

[0074]

[0075] Where represents the central wavelength of the i th beam of narrowband infrared light, 1 ≤ i ≤ N, represents the normalized human multi-spectral infrared signal when the central wavelength of the narrowband infrared light is , represents the infrared multi-spectral scattering signal when the central wavelength of the narrowband infrared light is , represents the background light signal under no-load measurement;

[0076] represents the exponential operation, represents the extinction factor of the human tissue when the central wavelength of the narrowband infrared light is , represents the central wavelength of The optical path length of narrow-band infrared light in human tissues is long, which represents the concentrations of biochemical substances (such as water, fat, protein, etc.) in human tissues;

[0077] represents the central wavelength of the narrow-band infrared light intensity, represents the sensing background, which is the intrinsic loss of the test optical path;

[0078] Step 4.2: Successively adopt the SNE (Stochastic Neighbor Embedding), Diffusion maps, and Factor analysis algorithms to perform the first-level metric learning on the normalized human multi-spectral infrared signals in the human tissue background absorption spectrum segment, and obtain the one-dimensional human absorption background signal TData1;

[0079] Step 4.3: Successively adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform the second-level metric learning on the normalized human multi-spectral infrared signals in the glucose absorption spectrum segment, and obtain the three-dimensional human glucose absorption signal GData3;

[0080] Step 4.4: Successively adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform the third-level metric learning on the one-dimensional human absorption background signal TData1 and the three-dimensional human glucose absorption signal GData3, and obtain the three-dimensional high-purity human glucose absorption signal MData3;

[0081] Step 4.5: Input the three-dimensional high-purity human glucose absorption signal MData3 into the input layer of the BP neural network. The BP neural network processes it and outputs the predicted blood glucose concentration, completing the blood glucose measurement.

[0082] The hidden layer of the BP neural network (Back Propagation Netural Network) has 36 layers. The input of the input layer is the three-dimensional high-purity human glucose absorption signal MData3, and the output of the output layer is the predicted blood glucose concentration. The predicted blood glucose concentration can be obtained through the BP neural network.

[0083] In this embodiment, in step 4, a composite multi-level metric learning-neural network method is used to calculate the blood glucose concentration. The self-reference method of the multi-spectral signal is used to eliminate interference noise, so as to retain the effective infrared multi-spectral scattering signal, thereby obtaining high-purity human glucose infrared absorption information. Then, combined with the big data learning ability of the neural network, the non-invasive blood glucose measurement accuracy of the human body can be improved. At the same time, due to the complex non-linear absorption characteristics of the human body background, the SNE, Diffusionmaps, and Factoranalysis algorithms are used to construct TData1, GData 3, and MData 3, which can avoid the large errors of traditional linear algorithms and further improve the measurement accuracy.

[0084] As Figure 4 shown, it is an analysis diagram of the blood glucose measurement results obtained by using the method of this embodiment. It can be seen that the predicted blood glucose concentrations output by the BP neural network are all located in areas A and B of the Clarke error network, and the results of the Bland-Altman analysis meet the requirements of human blood glucose measurement.

[0085] Embodiment 2

[0086] On the basis of Embodiment 1, in this embodiment, the broadband infrared light source 7 and the coupling lens 8 in the light source module 4 are extended to an annular structure matching the narrowband infrared multi-spectral filtering module 5, and the detector module 3 is set at the center position of the narrowband infrared multi-spectral filtering module 5. The human body scattered light enhancement module 2 is set perpendicular to the incident light path of the narrowband infrared light to realize the integrated common-path regulation and detection of 6 narrowband infrared lights with different central wavelengths.

[0087] Specifically, as Figure 5 shown, the broadband infrared light source 7 includes 6 infrared light sources with different central wavelengths distributed in an annular shape; the coupling lens 8 includes 6 coupling lens elements respectively corresponding to the 6 infrared light sources, which are used to form collimated parallel light. The 6 coupling lens elements are respectively corresponding to 6 narrowband infrared filter elements 9, and the central wavelength of the infrared light source is the same as that of its corresponding narrowband infrared filter element 9. The central wavelengths of the 6 infrared light sources are 850nm, 940nm, 1300nm, 1400nm, 1550nm, and 1640nm respectively, and together with the 6 coupling lens elements and 6 narrowband infrared filter elements 9 at the back end, they form a highly integrated narrowband infrared light source module 1 with an annular structure. The light source module 4 and the narrowband infrared multi-spectral filtering module 5 form a highly integrated narrowband infrared light source module 1 with an annular structure, realizing the on-chip matrix integration regulation of 6 narrowband infrared lights with different central wavelengths.

[0088] In this embodiment, the time-division operation of six infrared light sources can be achieved through the time-division electrical control method, and the six infrared light sources can also work simultaneously. When the six infrared light sources operate in a time-division manner, a single-point detector can be selected for the photodetector 11, which has a simple process and low cost. Moreover, the generation and detection of narrowband infrared light with different central wavelengths can be regulated in a time-division manner, without mechanical rotation, which can further improve the measurement accuracy and reduce the volume of the infrared multi-spectral blood glucose measurement device. When the six infrared light sources work simultaneously, a planar array detector is selected for the photodetector 11, which can realize the simultaneous measurement of infrared multi-spectral scattering signals generated by six narrowband infrared light beams passing through human tissues. The measurement efficiency is high, and there is no need to control the infrared light sources or gate the narrowband infrared filter elements 9, which simplifies the overall structure of the infrared multi-spectral blood glucose measurement device and also reduces the volume.

[0089] As Figure 5 , Figure 6 shown, the human scattered light enhancement module 2 is arranged perpendicular to the incident light path of the narrowband infrared light. The detector module 3 is arranged at the center of the annular structure formed by six narrowband infrared filter elements 9, and its photosensitive surface is arranged at the proximal end of the human scattered light enhancement module 2, which can realize the direct detection of the infrared multi-spectral scattering signal with a large angle formed by the reflection of narrowband infrared light by human tissues. At the same time, it can avoid the interference of the incident light on the detection signal of the photosensitive surface of the detector module 3 and realize on-chip integrated detection.

[0090] In this embodiment, by reasonably setting the spatial positions of the detector module 3 and the narrowband infrared filter elements 9, the direct interference of the scattered light on the surface of human tissues can be avoided. At the same time, by combining the incident light path and the detection light path into one, the volume of the infrared multi-spectral blood glucose measurement device can be further reduced, which conforms to the development trend of the miniaturization of the infrared multi-spectral blood glucose measurement device.

[0091] Embodiment III

[0092] On the basis of Embodiment II, this embodiment uses six narrowband infrared semiconductor lasers 6 to form the narrowband infrared light source module 1, thereby directly generating six narrowband infrared light beams with different central wavelengths. As Figure 7 shown, the narrowband infrared light source module 1 includes six narrowband infrared semiconductor lasers 6 distributed in an annular shape, and the central wavelength of each narrowband infrared semiconductor laser 6 is different. In this embodiment, six narrowband infrared semiconductor lasers are used to replace the light source module 4 and the narrowband infrared multi-spectral filtering module 5, directly forming a highly collimated integrated narrowband infrared light source module 1 with an annular structure, realizing the on-chip planar array high-integration regulation of six narrowband infrared light beams with different central wavelengths. As Figure 8 shown, the detector module 3 is arranged at the center of the annular structure formed by six narrowband infrared semiconductor lasers 6, realizing the on-chip integrated detection of the infrared multi-spectral scattering signal formed by the reflection of narrowband infrared light by human tissues, and further reducing the volume of the infrared multi-spectral blood glucose measurement device.

[0093] Similar to Embodiment 2, in this embodiment, either the time-division electrical control method can be used to sequentially generate six narrow-band infrared lights I0(850), I0(940), I0(1300), I0(1400), I0(1550) and I0(1640) with different center wavelengths by six narrow-band infrared semiconductor lasers 6, or the six narrow-band infrared semiconductor lasers 6 can work simultaneously.

Claims

1. A high-precision micro-infrared multi-spectral blood glucose measurement device, characterized in that: It includes a narrowband infrared light source module (1), a human body scattered light enhancement module (2), a detector module (3), and a data processing module; The narrowband infrared light source module (1) is used to generate N narrowband infrared lights with different central wavelengths. The central wavelengths of the narrowband infrared lights include the human tissue background absorption spectrum band and the glucose absorption spectrum band, where N is an integer and N≥2; The human body scattered light enhancement module (2) is arranged on the outgoing light path of the narrowband infrared light and is arranged on the human tissue during measurement, and is used to enhance the infrared spectrum absorption intensity of the human tissue; the included angle between the human body scattered light enhancement module (2) and the outgoing light path of the narrowband infrared light is 45 to 80 degrees; alternatively, the human body scattered light enhancement module (2) is arranged perpendicular to the outgoing light path of the narrowband infrared light, the detector module (3) is arranged at the center of the annular structure formed by N narrowband infrared semiconductor lasers (6) or at the center of the annular structure formed by N narrowband infrared filter elements (9), and the photosensitive surface of the detector module (3) is arranged at the proximal end of the human body scattered light enhancement module (2); The detector module (3) is arranged on the transmission light path of the infrared multi-spectral scattered signal generated by the reflection of the human tissue and is electrically connected to the data processing module, and is used to detect the infrared multi-spectral scattered signal and the no-load measurement background light signal, and send them to the data processing module. The data processing module calculates the blood glucose concentration according to the infrared multi-spectral scattered signal and the no-load measurement background light signal; The narrowband infrared light source module (1) includes N narrowband infrared semiconductor lasers (6) distributed in an annular shape, and the central wavelength of each narrowband infrared semiconductor laser (6) is different; Alternatively, the narrowband infrared light source module (1) includes a light source module (4) for generating a detection beam and a narrowband infrared multi-spectral filtering module (5) arranged on the outgoing light path of the detection beam; the narrowband infrared multi-spectral filtering module (5) includes N narrowband infrared filter elements (9) with different central wavelengths distributed in an annular shape, and the narrowband infrared filter elements (9) are on the outgoing light path of the detection beam during measurement; where the light source module (4) includes a broadband infrared light source (7) and a coupling lens (8) arranged on the outgoing light path of the broadband infrared light source (7); the broadband infrared light source (7) includes N infrared light sources with different central wavelengths distributed in an annular shape, and the coupling lens (8) includes N coupling lens elements corresponding to the N infrared light sources; the N coupling lens elements are respectively arranged corresponding to the N narrowband infrared filter elements (9), and the central wavelength of the infrared light source is the same as that of its corresponding narrowband infrared filter element (9); alternatively, the broadband infrared light source (7) includes one infrared light source, and the coupling lens (8) includes one coupling lens element corresponding to the one infrared light source.

2. The high-precision micro-infrared multi-spectral blood glucose measurement device according to claim 1, characterized in that: The narrowband infrared filter element (9) adopts an integrated micro-nano superstructure filter unit or a discrete thin film filter element installed on a rotating wheel, and the rotating wheel is driven by a motor to rotate.

3. The high-precision micro-infrared multi-spectral blood glucose measurement device according to claim 2, wherein: The full width at half maximum of the narrowband infrared filter element (9) is less than or equal to 12 nm.

4. A high-precision micro infrared multi-spectral blood glucose measurement device according to claim 3, characterized in that: The human body scattered light enhancement module (2) is a surface plasmon metal nanoparticle infrared enhancement film.

5. The high-precision micro-infrared multi-spectral blood glucose measurement device according to claim 4, characterized in that: The detector module (3) includes an imaging lens (10) and a photodetector (11) arranged in sequence along the transmission direction of the infrared multi-spectral scattering signal.

6. The high-precision micro-infrared multi-spectral blood glucose measurement device according to claim 5, characterized in that: The photodetector (11) is a single-point detector or a focal plane array detector.

7. A measuring method of the high-precision micro-infrared multi-spectral blood glucose measuring device according to any one of claims 1-6, characterized in that, It includes the following steps: Step 1: Turn on the detector module (3), detect the background light signal under no-load measurement, and send it to the data processing module; Step 2: Set the human body scattering light enhancement module (2) on the human tissue, and then turn on the narrowband infrared light source module (1); Step 3: N narrowband infrared lights generated by the narrowband infrared light source module (1) are incident on the human tissue through the human body scattering light enhancement module (2). The human tissue reflects to generate an infrared multi-spectral scattering signal. Then, use the detector module (3) to detect the infrared multi-spectral scattering signal, obtain N infrared multi-spectral scattering signals, and send them to the data processing module; Step 4: The data processing module calculates the blood glucose concentration based on the N infrared multi-spectral scattering signals and the background light signal under no-load measurement to complete the blood glucose measurement.

8. The measurement method of a high-precision micro infrared multi-spectral blood glucose measurement device according to claim 7, characterized in that, Step 4 is specifically: Step 4.1: Calculate the normalized human multi-spectral infrared signals in the background absorption spectrum band and the glucose absorption spectrum band of the human tissue respectively according to the following formula: I sig (λ i ) = I0(λ i ) exp[ε sig (λ i ) cL(λ i ) + G] I ref = I0(λ i )exp[G] Among them, λ i represents the central wavelength of the i-th narrowband infrared light beam, 1 ≤ i ≤ N, NI SR (λ i ) represents the normalized human multi-spectral infrared signal when the central wavelength of the narrowband infrared light is λ i , I sig (λ i ) represents the infrared multi-spectral scattering signal when the central wavelength of the narrowband infrared light is λ i , I ref represents the background light signal measured without load, exp[] represents the exponential operation, ε sig (λ i ) represents the extinction factor of human tissue when the central wavelength of the narrowband infrared light is λ i , c represents the concentration of biochemical substances in human tissue, L(λ i ) represents the optical path length of the narrowband infrared light with a central wavelength of λ i in human tissue, I0(λ i ) represents the light intensity of the narrowband infrared light with a central wavelength of λ i , G represents the sensing background, which is the intrinsic loss of the test optical path; Step 4.2: Successively adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform the first-level metric learning on the normalized human multi-spectral infrared signals in the background absorption spectrum band of the human tissue to obtain a one-dimensional human absorption background signal TData1; Step 4.3: Successively adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform the second-level metric learning on the normalized human multi-spectral infrared signals in the glucose absorption spectrum band to obtain a three-dimensional human glucose absorption signal GData3; Step 4.4: Successively adopt the SNE, Diffusion maps, and Factor analysis algorithms to perform the third-level metric learning on the one-dimensional human absorption background signal TData1 and the three-dimensional human glucose absorption signal GData3 to obtain a three-dimensional high-purity human glucose absorption signal MData3; Step 4.5: Input the three-dimensional high-purity human glucose absorption signal MData3 into the input layer of the BP neural network. The BP neural network processes it and outputs the predicted blood glucose concentration to complete the blood glucose measurement.

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