Non-invasive continuous blood glucose measuring device and method based on OCTA

Abstract

The invention discloses a non-invasive continuous blood glucose measuring device and method based on OCTA. The device comprises an optical coherence tomography device, a mechanical arm, an infrared multi-view camera set and an infrared LED. A sample arm of the optical coherence tomography device is carried on a mechanical arm, the tail end of the sample arm presses a sample to be detected, and an infrared multi-view camera set and an infrared LED are both arranged on one side of the tail end of the sample arm. The method comprises the following steps: guiding the sample arm to be aligned with a target tissue area of a to-be-detected sample, aligning an imaging focal plane of the optical coherence tomography device with the surface of the target tissue area of the to-be-detected sample, scanning and imaging to obtain a blood glucose measurement curve, and scanning for multiple times to monitor the blood glucose concentration. According to the invention, pixel-level positioning of an imaging view field is realized, and the advantage of accurate and non-invasive detection of blood glucose concentration based on OCTA is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical detection, and particularly relates to a non-invasive continuous blood glucose measurement device and method based on OCTA. Background Art

[0002] Diabetes is a chronic metabolic disease that can cause serious complications such as heart disease, kidney problems, and stroke. Monitoring blood glucose levels is crucial for the overall health of patients. Blood glucose concentration is usually measured using enzyme-based electrochemical devices, which require blood samples to be collected from finger pricks or forearm stings, potentially causing discomfort, infection risk, and poor compliance.

[0003] In recent years, some researchers have proposed to use optical coherence tomography (OCT) technology to achieve non-invasive monitoring of blood glucose concentration in skin tissue. This method utilizes the correlation between tissue optical attenuation coefficient and blood glucose concentration, combined with optical coherence tomography angiography (OCTA) technology, to preliminarily achieve non-invasive monitoring of the dynamic changes in blood glucose concentration in blood and interstitial fluid. However, the correlation between the optical attenuation coefficient and blood glucose concentration in different tissue regions is different. Therefore, this method needs to ensure that the imaging position is highly consistent each time. In addition, the pressure change applied by the OCT imaging probe to the skin tissue will cause changes in the blood vessel density in the OCTA image, thereby affecting the extraction of the optical scattering coefficient in the blood flow region and ultimately affecting the detection accuracy of blood glucose concentration. Finally, the skin tissue has an irregular plane. Therefore, under fixed-position scanning, a single focal plane will cause imaging defocus, further affecting the detection accuracy of blood glucose concentration. Summary of the Invention

[0004] Aiming at the problems existing in the background art, the purpose of the present invention is to propose a non-invasive continuous blood glucose measurement device and method based on OCTA. The present invention is based on the correlation between tissue optical attenuation coefficient and glucose concentration, uses an infrared camera to achieve pixel-level positioning of the imaging field of view, guides the robotic arm carrying the OCT sample arm to accurately displace, avoids the calculation of the tissue attenuation coefficient in the blood flow region due to changes in the imaging field of view offset and defocus, and realizes accurate and non-invasive detection of blood glucose concentration based on OCTA.

[0005] The technical solutions adopted by the present invention include:

[0006] I. A non-invasive continuous blood glucose measurement device based on OCTA

[0007] It includes an optical coherence tomography device, a robotic arm, an infrared multi-camera group, and an infrared LED; the sample arm of the optical coherence tomography device is mounted on the robotic arm, the infrared multi-camera group and the infrared LED are both arranged on one side of the end of the sample arm, and the infrared multi-camera group is communicatively connected to the robotic arm; the infrared light emitted by the infrared LED is reflected by the sample to be measured and received by the infrared multi-camera group, the infrared multi-camera group obtains the three-dimensional position information of the sample to be measured and transmits it to the robotic arm, and the robotic arm controls the movement according to the three-dimensional position information.

[0008] The robotic arm is a six-degree-of-freedom robotic arm and internally mounts a control and processing unit.

[0009] The infrared multi-camera group includes a lateral infrared binocular camera and an opposing infrared camera; the lateral infrared binocular camera is arranged on the front side of the sample to be measured, the opposing infrared camera is arranged directly opposite the sample to be measured, and both the lateral infrared binocular camera and the opposing infrared camera are communicatively connected to the robotic arm.

[0010] II. A non-invasive continuous blood glucose measurement method based on OCTA

[0011] S1. Use the infrared multi-camera group to guide the robotic arm carrying the sample arm to move so that the sample arm is aligned with the target tissue area of the sample to be measured.

[0012] S2. Build an eye-in-hand calibration system and control the robotic arm to adjust the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the target tissue area of the sample to be measured.

[0013] S3. Perform OCT scanning imaging on the target tissue area of the sample to be measured to obtain an OCT signal.

[0014] S4. Generate the three-dimensional scattering coefficient and three-dimensional microvascular distribution of the target tissue area according to the OCT signal, and process and obtain the blood scattering coefficient according to the three-dimensional scattering coefficient and three-dimensional microvascular distribution.

[0015] S5. Obtain a blood glucose measurement curve according to the linear fitting relationship between the blood scattering coefficient and the blood glucose concentration.

[0016] S6. Repeat steps S1 - S5, perform multiple scans on the target tissue area of the sample to be measured, continuously obtain blood glucose measurement curves, and thus realize the monitoring of blood glucose concentration.

[0017] The specific content of step S1 is as follows:

[0018] Use the infrared multi-camera group to collect the three-dimensional position information of the sample to be measured, and transmit the three-dimensional position information to the robotic arm. The robotic arm adjusts the pose of the mounted sample arm according to the three-dimensional information of the sample to be measured so that the sample arm is aligned with the target tissue area of the sample to be measured.

[0019] The specific steps of step S2 are as follows:

[0020] S21. The robotic arm controls the focus at the end of the sample arm to align with the tip set on the sample to be measured, and an orthogonal B-scan image is generated using a cross-scanning protocol. When the tip is stably located at the center of the image, the posture of the robotic arm is recorded as the first posture.

[0021] S22. The robotic arm controls the sample arm to align with the sample to be measured from multiple perspectives and perform scanning, so as to obtain a multi-perspective 3D image of the sample to be measured. The surface point cloud data of the sample to be measured is extracted from the multi-perspective 3D image of the sample to be measured. The spatial transformation relationship between different perspectives is calculated by the iterative closest point algorithm based on the surface point cloud data of the sample to be measured. The pose of the focus of the optical coherence tomography device is obtained by processing according to the spatial transformation relationship between different perspectives and the first posture using the hand-eye calibration equation.

[0022] S23. The coordinate transformation relationship between the robotic arm and the sample arm is obtained according to the pose of the focus of the optical coherence tomography device and the first posture.

[0023] S24. According to the coordinate transformation relationship between the robotic arm and the sample arm, the robotic arm controls and adjusts the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the sample to be measured.

[0024] One of the following methods is adopted for OCT scanning and imaging of the target tissue area of the sample to be measured in step S3:

[0025] The time-domain OCT imaging method of changing the optical path of the reference arm by scanning;

[0026] Or the spectral-domain OCT imaging method of recording the spectral interference signal using a spectrometer;

[0027] Or the swept-source OCT imaging method of recording the spectral interference signal using a swept-source light.

[0028] The specific steps of step S4 include: using the depth attenuation characteristic of OCT to extract the three-dimensional scattering coefficient of the target tissue area in the OCT signal; generating the three-dimensional microvascular distribution of the target tissue area according to the OCT signal; after performing image binarization on the three-dimensional microvascular distribution, a blood vessel mask and a tissue mask are obtained, and after performing a dot product operation on the three-dimensional scattering coefficient and the blood vessel mask, the blood scattering coefficient is obtained.

[0029] The innovation of the present invention lies in adopting a structural method of guiding the robotic arm carrying the OCT sample arm to move using an infrared camera, achieving the beneficial effect of pixel-level positioning of the imaging field of view, avoiding the calculation of the tissue attenuation coefficient of the blood flow area due to the change of imaging field of view offset and defocus, and obtaining the advantages of accurate and non-invasive detection of blood glucose concentration based on OCTA.

[0030] The beneficial effects of the present invention are as follows:

[0031] 1. The present invention uses an infrared camera to guide the precise displacement of the robotic arm carrying the OCT sample arm, achieving pixel-level positioning of the imaging field of view.

[0032] 2. The present invention avoids the calculation of the tissue attenuation coefficient of the blood flow area due to the change of the imaging field of view offset and defocus, and realizes accurate and non-invasive detection of blood glucose concentration based on OCTA. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a structural diagram of the device in an exemplary embodiment of the present invention.

[0034] Figure 2 It is a structural diagram of the robotic arm probe module in an exemplary embodiment of the present invention.

[0035] Among them, light source 11, fiber optic coupler 12, polarization controller 13, first collimator 14, focusing lens 15, planar high reflector 16, robotic arm probe module 17, sample to be measured 18, detector 19, workstation 20, second collimator 31, two-dimensional scanning galvanometer 32, first doublet lens 33, dichroic mirror 34, objective lens 35, infrared LED 37, second doublet lens 39, third doublet lens 40, opposing infrared camera 41, and lateral infrared binocular camera 42. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The following describes the present invention in more detail with reference to the drawings and embodiments. However, the present invention is not limited thereto. For those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as within the protection scope of the present invention. The content not described in detail in this specification belongs to the prior art well known to those skilled in the art.

[0037] The non-invasive continuous blood glucose measurement device based on OCTA of the present invention includes an optical coherence tomography device, a robotic arm, an infrared multi-eye camera group, and an infrared LED 37; the sample arm of the optical coherence tomography device is mounted on the robotic arm, the infrared multi-eye camera group and the infrared LED 37 are both arranged on one side of the end of the sample arm of the optical coherence tomography device, and the infrared multi-eye camera group is communicatively connected to the robotic arm; the infrared light emitted by the infrared LED 37 is reflected by the sample to be measured 18 and received by the infrared multi-eye camera group, the infrared multi-eye camera group obtains the three-dimensional position information of the sample to be measured 18 and transmits it to the robotic arm, and the robotic arm controls the movement according to the three-dimensional position information, thereby realizing the positioning of the sample to be measured 18.

[0038] It further includes a workstation 20, which is connected to the optical coherence tomography device. The optical coherence tomography device is a device implemented by optical coherence tomography (OCT) scanning technology.

[0039] The optical coherence tomography device includes a light source 11, an optical fiber coupler 12, a reference arm, a sample arm, and a detector 19; the detection light emitted by the light source 11 enters the optical fiber coupler 12 through the optical fiber. The optical fiber coupler 12 divides the detection light into two beams of light. One beam of light enters the reference arm through the optical fiber, and the other beam of light enters the sample arm through the optical fiber. The backward scattered light from the reference arm and the sample arm interferes through the optical fiber coupler 12 and is collected by the detector 19 through the optical fiber and transmitted to the workstation 20.

[0040] The sample arm includes a second collimator 31, a two-dimensional scanning galvanometer 32, a first doublet lens 33, a dichroic mirror 34, and an objective lens 35; the light entering the sample arm separated by the optical fiber coupler first enters the second collimator 31, and then successively passes through the two-dimensional scanning galvanometer 32, the first doublet lens 33, the dichroic mirror 34, and the objective lens 35, and then irradiates the surface of the sample to be measured 18.

[0041] The robotic arm is a six-degree-of-freedom robotic arm and internally carries a control and processing unit. The infrared multi-camera group includes a lateral infrared binocular camera 42 and an opposing infrared camera 41; the lateral infrared binocular camera 42 is arranged on the front side of the target tissue area of the sample to be measured 18, and the opposing infrared camera 41 is arranged directly opposite the target tissue area of the sample to be measured 18, and forms an optical path with the objective lens 35 and the dichroic mirror 34 in the sample arm of the optical coherence tomography device. Both the lateral infrared binocular camera 42 and the opposing infrared camera 41 are communicatively connected to the robotic arm.

[0042] The lateral infrared binocular camera 42 receives the infrared light reflected laterally by the sample to be measured 18, thereby collecting the lateral position information of the sample to be measured; the opposing infrared camera 41 receives the infrared light emitted forward by the sample to be measured 18, thereby collecting the opposing position information of the sample to be measured; the lateral position information and the opposing position information are fused to obtain three-dimensional position information, and the three-dimensional position information is transmitted to the control and processing unit inside the robotic arm.

[0043] Further, when the opposing infrared camera 41 is arranged directly opposite the sample to be measured 18, a second doublet lens 39 and a third doublet lens 40 are also arranged between the dichroic mirror 34 and the opposing infrared camera 41, so that the opposing infrared camera 41 can receive the infrared light reflected forward by the sample to be measured 18.

[0044] The device of the present invention is implemented according to the following measurement method:

[0045] S1. Use the infrared multi-camera group to guide the robotic arm carrying the sample arm to move so that the sample arm is aligned with the same target tissue area of the sample to be measured.

[0046] Specifically, an infrared multi-camera array is used to collect the three-dimensional position information of the sample 18 to be measured, and the three-dimensional position information is transmitted to the robotic arm. The robotic arm adjusts the pose of the sample arm carried thereon according to the three-dimensional information of the sample 18 to be measured, so that the sample arm is aligned with the target tissue area of the sample to be measured, thereby realizing the tracking of the imaging field of view.

[0047] S2. Construct a hand-eye calibration system and control the robotic arm to adjust the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the target tissue area of the sample 18 to be measured.

[0048] Specifically: S21. The robotic arm controls the focus at the end of the sample arm to align with the tip of the needle provided on the sample 18 to be measured, and an orthogonal B-scan image is generated using a cross-scanning protocol. When the tip of the needle is stably located at the center of the image, the pose of the robotic arm is recorded as the first pose.

[0049] S22. The robotic arm controls the sample arm to align with the sample 18 to be measured at multiple perspectives and perform scanning, so as to obtain multi-perspective 3D imaging of the sample 18 to be measured. The surface point cloud data of the sample 18 to be measured is extracted from the multi-perspective 3D imaging of the sample 18 to be measured. The spatial transformation relationship between different perspectives is calculated according to the surface point cloud data of the sample 18 to be measured by using the iterative closest point algorithm. The pose of the focus of the optical coherence tomography device is obtained by processing according to the spatial transformation relationship between different perspectives and the first pose using the hand-eye calibration equation.

[0050] S23. Obtain the coordinate transformation relationship between the robotic arm and the sample arm according to the pose of the focus of the optical coherence tomography device and the first pose.

[0051] S24. According to the coordinate transformation relationship between the robotic arm and the sample arm, the robotic arm controls and adjusts the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the sample 18 to be measured.

[0052] S3. Perform OCT scanning imaging on the target tissue area of the sample 18 to be measured to obtain an OCT signal.

[0053] One of the following methods is used to perform OCT scanning imaging on the target tissue area of the sample 18 to be measured:

[0054] The time-domain OCT imaging method of changing the optical path of the reference arm by scanning;

[0055] Or the spectral-domain OCT imaging method of using a spectrometer to record the spectral interference signal;

[0056] Or the swept-source OCT imaging method of using a swept-source to record the spectral interference signal.

[0057] S4. Generate the three-dimensional scattering coefficient and three-dimensional microvascular distribution of the target tissue region based on the OCT signal, and process the three-dimensional scattering coefficient and three-dimensional microvascular distribution to obtain the blood scattering coefficient.

[0058] Specifically, it includes: using the depth attenuation characteristic of OCT to extract the three-dimensional scattering coefficient of the target tissue region in the OCT signal; generating the three-dimensional microvascular distribution of the target tissue region based on the OCT signal; after performing image binarization on the three-dimensional microvascular distribution, obtaining a blood vessel mask and a tissue mask, and multiplying the three-dimensional scattering coefficient by the blood vessel mask to obtain the blood scattering coefficient.

[0059] The calculation of the three-dimensional scattering coefficient of the target region from the OCT depth attenuation signal is achieved through the following formula:

[0060]

[0061] Among them, x represents the fast scanning direction in the OCT three-dimensional scan, y represents the slow scanning direction in the OCT three-dimensional scan, z represents the depth direction in the OCT three-dimensional scan, and the depth direction is perpendicular to the plane formed by the fast scanning direction and the slow scanning direction. μ(x, y, z) is the optical scattering coefficient at the pixel position of (x, y, z), I(x, y, z) represents the compensated OCT signal intensity at the pixel position of (x, y, z), n is the refractive index of the target tissue region of the sample to be measured, and Δz is the actual size in air corresponding to each pixel in the depth direction.

[0062] Generating the three-dimensional microvascular distribution of the target tissue region based on the OCT signal specifically includes: analyzing the amplitude or phase or both the amplitude and phase of the OCT signal using the OCT blood flow signal extraction method to obtain the three-dimensional microvascular distribution of the target tissue region.

[0063] The OCT blood flow signal extraction methods include: differential calculation, speckle variance operation, decorrelation calculation, or eigen-decomposition calculation.

[0064] After performing image binarization on the three-dimensional microvascular distribution to obtain a blood vessel mask and a tissue mask, and multiplying the three-dimensional scattering coefficient by the blood vessel mask to obtain the blood scattering coefficient, specifically includes:

[0065] Select a suitable threshold to perform binarization on the three-dimensional microvascular distribution (i.e., the three-dimensional microvascular matrix). Specifically, set the pixel values of all blood flow regions in the three-dimensional microvascular distribution to 1 and the pixel values of non-blood flow regions to 0 to obtain the blood vessel mask, and then multiply the blood vessel mask by the three-dimensional scattering coefficient to extract and obtain the blood flow scattering coefficient.

[0066] S5. Obtain the blood glucose measurement curve based on the linear fitting relationship between the blood scattering coefficient and the blood glucose concentration.

[0067] S6. Repeat steps S1 - S5 to scan the target tissue area of the test sample 18 multiple times, continuously obtain blood glucose measurement curves, and thus achieve the monitoring of blood glucose concentration.

[0068] Figure 1 Shown is an exemplary embodiment of the present invention disclosed herein. The non-invasive continuous blood glucose measurement device based on OCTA includes an optical coherence tomography device, a robotic arm, an infrared multi-eye camera group, an infrared LED 37, and a workstation 20; the optical coherence tomography device includes a light source 11, an optical fiber coupler 12, a reference arm, a sample arm, and a detector 19; the reference arm includes a polarization controller 13, a first collimator 14, a focusing lens 15, and a planar high reflector 16; the sample arm includes a second collimator 31, a two-dimensional scanning galvanometer 32, a first doublet lens 33, a dichroic mirror 34, and an objective lens 35; the infrared multi-eye camera group includes a lateral infrared binocular camera 42, an opposing infrared camera 41, a second doublet lens 39, and a third doublet lens 40; the sample arm, the robotic arm, the infrared multi-eye camera group, and the infrared LED 37 form a robotic arm probe module 17, as Figure 2 shown.

[0069] The light emitted by the light source 11 used in the device of the present invention enters the optical fiber coupler 12 with a splitting ratio of 80:20 through the optical fiber. The light emitted from the optical fiber coupler 12 is divided into two sub-beams: one beam of light enters the reference arm and passes through the polarization controller 13, the first collimator 14, and the focusing lens 15 in sequence, and then returns along the original path through the planar high reflector 16. The other beam of light enters the sample arm, passes through the robotic arm probe module 17, and is transmitted to the test sample 18. The return light from the reference arm and the sample arm returns along the original path to the optical fiber coupler 12 to generate interference, and then is transmitted to the detector 19 and enters the workstation 20 for data processing.

[0070] Specifically, in the robotic arm probe module 17, the OCT detection light passes through the second collimator 31, the two-dimensional scanning galvanometer 32, the first doublet lens 33, the dichroic mirror 34, and the objective lens 35 in sequence, and then irradiates the surface of the test sample 18. The light emitted by the infrared LED 37 is reflected by the test sample 18 and enters the lateral infrared binocular camera 42, or passes through the objective lens 35, the dichroic mirror 34, the second doublet lens 39, and the third doublet lens 40 in sequence, and then enters the opposing infrared camera 41 to achieve the positioning and tracking of the imaging field of view.

[0071] By using the device of the present invention to dynamically monitor the change of the scattered signal in the blood flow area of the target tissue area of the same test sample in the oral glucose tolerance test, the non-invasive and high-precision monitoring of blood glucose concentration is achieved.

[0072] The above-described embodiments are only preferred embodiments cited to fully illustrate the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art on the basis of the present invention are all within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A non-invasive continuous blood glucose measurement device based on OCTA, characterized in that: It includes an optical coherence tomography device, a robotic arm, an infrared multi-camera group, and an infrared LED (37); the sample arm of the optical coherence tomography device is mounted on the robotic arm, and both the infrared multi-camera group and the infrared LED (37) are arranged on one side of the end of the sample arm. The infrared multi-camera group is communicatively connected to the robotic arm; the infrared light emitted by the infrared LED (37) is reflected by the sample to be measured (18) and received by the infrared multi-camera group. The infrared multi-camera group obtains the three-dimensional position information of the sample to be measured (18) and transmits it to the robotic arm, and the robotic arm controls the movement according to the three-dimensional position information.

2. The non-invasive continuous blood glucose measurement device based on OCTA according to claim 1, characterized in that: The robotic arm is a six-degree-of-freedom robotic arm and internally carries a control and processing unit.

3. The non-invasive continuous blood glucose measurement device based on OCTA according to claim 1, characterized in that: The infrared multi-camera group includes a lateral infrared binocular camera (42) and an opposing infrared camera (41); the lateral infrared binocular camera (42) is arranged on the front side of the sample to be measured (18), and the opposing infrared camera (41) is arranged directly opposite the sample to be measured (18). Both the lateral infrared binocular camera (42) and the opposing infrared camera (41) are communicatively connected to the robotic arm.

4. A non-invasive continuous blood glucose measurement method based on OCTA using the device according to any one of claims 1-3, characterized in that, It includes the following steps: S1. Use the infrared multi-camera group to guide the robotic arm carrying the sample arm to move so that the sample arm is aligned with the target tissue area of the sample to be measured; S2. Build an eye-in-hand calibration system and control the robotic arm to adjust the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the target tissue area of the sample to be measured (18); S3. Perform OCT scanning imaging on the target tissue area of the sample to be measured (18) to obtain OCT signals; S4. Generate the three-dimensional scattering coefficient and three-dimensional microvascular distribution of the target tissue area according to the OCT signals, and process and obtain the blood scattering coefficient according to the three-dimensional scattering coefficient and three-dimensional microvascular distribution; S5. Obtain the blood glucose measurement curve according to the linear fitting relationship between the blood scattering coefficient and the blood glucose concentration; S6. Repeat steps S1 - S5, perform multiple scans on the target tissue area of the sample to be measured (18), and continuously obtain the blood glucose measurement curve, so as to realize the monitoring of the blood glucose concentration.

5. The non-invasive continuous blood glucose measurement method based on OCTA according to claim 4, characterized in that, The specific content of step S1 is: Use the infrared multi-camera group to collect the three-dimensional position information of the sample to be measured (18), and transmit the three-dimensional position information to the robotic arm. The robotic arm adjusts the pose of the carried sample arm according to the three-dimensional information of the sample to be measured (18) so that the sample arm is aligned with the target tissue area of the sample to be measured.

6. The non-invasive continuous blood glucose measurement method based on OCTA according to claim 4, wherein The specific content of step S2 is: S21. The robotic arm controls the focus at the end of the sample arm to align with the tip set on the sample to be measured (18), and uses a cross-scanning protocol to generate an orthogonal B-scan image. When the tip is stably located at the center of the image, record the pose of the robotic arm as the first pose; S22. The robotic arm controls the sample arm to align with the sample to be measured (18) from multiple perspectives and perform scanning, so as to obtain multi-perspective 3D imaging of the sample to be measured (18). The surface point cloud data of the sample to be measured (18) is extracted according to the multi-perspective 3D imaging of the sample to be measured (18). The spatial transformation relationship between different perspectives is calculated according to the surface point cloud data of the sample to be measured (18) by using the iterative closest point algorithm. The pose of the focus of the optical coherence tomography device is obtained by processing according to the spatial transformation relationship between different perspectives and the first pose using the hand-eye calibration equation; S23. The coordinate transformation relationship between the robotic arm and the sample arm is obtained according to the pose of the focus of the optical coherence tomography device and the first pose; S24. According to the coordinate transformation relationship between the robotic arm and the sample arm, the robotic arm controls and adjusts the pose of the sample arm so that the imaging focal plane of the optical coherence tomography device is aligned with the surface of the sample to be measured (18).

7. The non-invasive continuous blood glucose measurement method based on OCTA according to claim 4, wherein In step S3, one of the following methods is used to perform OCT scanning imaging on the target tissue area of the sample to be measured (18): The time-domain OCT imaging method of changing the optical path of the reference arm by scanning; Or the spectral-domain OCT imaging method of using a spectrometer to record the spectral interference signal; Or the swept-source OCT imaging method of using a swept-source to record the spectral interference signal.

8. The non-invasive continuous blood glucose measurement method based on OCTA according to claim 4, characterized in that, Step S4 specifically includes: Utilize the depth attenuation characteristic of OCT to extract the three-dimensional scattering coefficient of the target tissue area in the OCT signal; generate the three-dimensional microvascular distribution of the target tissue area according to the OCT signal; after performing image binarization on the three-dimensional microvascular distribution, obtain a blood vessel mask and a tissue mask, and multiply the three-dimensional scattering coefficient by the blood vessel mask point by point to obtain the blood scattering coefficient.

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