Non-contact intraocular pressure visual calibration method

Abstract

The invention belongs to the technical field of micro electro mechanical systems, and particularly relates to a non-contact type intraocular pressure visual calibration method, which comprises the following steps of: by virtue of a human eye simplified AI model and an intraocular pressure deformation quantity detection device, combining an MEMS (Micro Electro Mechanical System) technology and a visual analysis theory, carrying out real-time and dynamic simulation on the human eye pressure, and carrying out data acquisition by an optical or image sensor; therefore, accurate monitoring of cornea deformation is realized, a more accurate intraocular pressure evaluation means is provided, and effective verification of the non-contact tonometer is realized. Compared with the prior art, the system has the beneficial effects that data acquisition is carried out by means of an optical sensor or an image sensor and the like, accurate monitoring of cornea deformation can be realized, an integration technology is adopted, cornea deformation quantity calculation and an analysis algorithm are integrated in the MEMS sensor, accurate monitoring of human cornea pressure can be realized, and the system is suitable for popularization and application. And dynamic monitoring can be realized.

Description

Technical Field

[0001] The present invention belongs to the field of micro-electro mechanical systems (MEMS) technology, and in particular relates to a non-contact intraocular pressure vision calibration method. Background Art

[0002] Intraocular pressure (IOP) refers to the pressure exerted by the contents of the eye on the wall of the eye and is an important physiological indicator of eye health. The normal range of intraocular pressure is usually between 10-21 mmHg. Fluctuations in intraocular pressure may reflect the occurrence of eye diseases, such as glaucoma, retinal diseases, etc. Abnormal intraocular pressure levels, especially persistently elevated intraocular pressure, is one of the main pathological characteristics of glaucoma, which can cause damage to the optic nerve and may eventually lead to irreversible vision loss. Therefore, accurate monitoring of intraocular pressure is of great significance for the early detection and treatment of glaucoma.

[0003] Micro-Electro-Mechanical Systems (MEMS) technology is a miniaturized system technology that integrates multidisciplinary technologies such as microelectronics, mechanical engineering, and materials science. The advantages of MEMS technology include small size, light weight, low power consumption, low cost, and high precision, which make it widely used in sensor and actuator design. In recent years, MEMS technology has developed rapidly in the medical field, especially in physiological monitoring equipment, such as pressure sensors and accelerometers. The intraocular pressure sensor designed using MEMS technology can realize a miniaturized, low-power, non-contact monitoring system, enhancing patient comfort and compliance.

[0004] Currently, intraocular pressure monitoring technology can be roughly divided into two categories: contact and non-contact. Contact tonometers, such as the Goldmann applanation tonometer, are devices that measure intraocular pressure by directly contacting the cornea of ​​the eye. This device calculates the intraocular pressure value by measuring the degree of deformation of the cornea. Although it has high accuracy, contact tonometers usually require anesthesia of the eye to reduce discomfort and may cause problems such as corneal abrasion and infection.

[0005] Non-contact tonometers (such as airflow tonometers) measure intraocular pressure by flattening the cornea with a slight jet of air. This method avoids direct contact with the cornea, reduces the risk of infection, and does not require the use of anesthetics. Non-contact tonometers are generally high-value and expensive equipment in medical institutions, which require regular inspection and calibration. The existing calibration technologies mainly include iris images (an intraocular pressure testing method with application number 202310832210.6) or liquid pressure detection (non-contact tonometer accuracy inspection and calibration device and inspection and calibration method with application number 201610118850.0). Affected by factors such as corneal thickness, curvature and ambient light, the measurement data is unstable and inaccurate. Summary of the invention

[0006] The purpose of the present invention is to provide a non-contact intraocular pressure visual calibration method, which overcomes the shortcomings of the prior art, combines MEMS technology with visual analysis theory, and aims to achieve accurate monitoring of corneal deformation through real-time and dynamic simulation of human eye pressure, with the help of optical or image sensors for data collection, so as to provide a more accurate means of intraocular pressure assessment, realize effective calibration of non-contact tonometers, and improve the reference value of clinical applications of non-contact tonometers.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions:

[0008] A non-contact intraocular pressure visual calibration method is characterized in that, with the help of a simplified AI model of the human eye and an intraocular pressure deformation detection device, combined with MEMS technology and visual analysis theory, through real-time and dynamic simulation of human eye pressure, data collection by optical or image sensors, accurate monitoring of corneal deformation is achieved, a more accurate intraocular pressure assessment method is provided, and effective calibration of the non-contact tonometer is achieved. The specific process is as follows:

[0009] Step 1: Place the bionic eye into the intraocular pressure deformation detection device, embed it into the fixed base, apply glue to seal the periphery, take the corneal center of the bionic eye as the origin O, add multiple observation points on the cornea, and record them;

[0010] Step 2: Place the intraocular pressure deformation detection device under the electron microscope objective;

[0011] Step 3: Start the liquid injection metering pump to inject artificial aqueous humor into the bionic eye, monitor the left and right deviation angles and the up and down deviation angles of each observation point, and obtain the corneal central thickness deformation of the bionic eye;

[0012] Step 4: Send the corneal central thickness deformation information to the data analysis terminal to obtain the intraocular pressure data of the bionic eye and calibrate the reading of the non-contact tonometer.

[0013] Furthermore, the simplified AI model of the human eye is obtained by a deep learning method based on an image recognition neural network. An observation point is first set on the cornea, and the cornea is photographed when the intraocular pressure is normal. When the intraocular pressure rises, the cornea is photographed again. The observation points in the photographs are offset, and these offsets are used as a basis for neural network learning and discrimination, thereby achieving accurate feedback of the intraocular pressure by analyzing the corneal images before and after the intraocular pressure changes.

[0014] Furthermore, the intraocular pressure deformation amount detection device includes a fixed base, a liquid injection metering pump and a data analysis terminal. The fixed base is provided with a bionic eye positioning groove, and a heater, a water supply channel and a drainage channel are provided at the bottom of the groove. The water supply channel is connected to the liquid injection metering pump through a pipeline, and the drainage channel is connected to the pressure test chamber. A pressure sensor is provided in the pressure test chamber. A temperature sensor is provided on the fixed base. The pressure sensor and the temperature sensor are respectively connected to the data analysis terminal through data cables.

[0015] Furthermore, the top of the water supply channel is connected to the center of the bottom of the bionic eye through a dispersion sheet, and the upper surface of the dispersion sheet is provided with a micropore array, the micropore size is 0.1-0.3mm, the distance between adjacent holes is 10-18 degrees, and there are 20-36 micropores in total.

[0016] Furthermore, the top of the drainage channel is connected to the bottom periphery of the bionic eye, the bottom of the drainage channel is connected to the pressure test chamber through a collecting pipe, and a drain valve is provided at the bottom of the pressure test chamber.

[0017] Furthermore, the distribution of the observation points adopts a geographic coordinate system, the latitude and longitude division accuracy is 0.1-0.5mm, and the division lines are ablated on the corneal surface of the bionic eye by a laser marking machine.

[0018] Furthermore, the electron microscope is a scanning electron microscope or a confocal microscope.

[0019] Furthermore, the bionic eye is a hydrogel artificial eye or the "bionic eye" of the German company Retina Implant AG; the pressure sensor is a MEMS pressure sensor; the intraocular pressure deformation detection device is 3D printed, and the heater is a hollow structure with heating oil filled inside. After the heating oil is baked, dried and solidified, it is connected to a power supply through two wires with a power of 4-10W.

[0020] Furthermore, the artificial aqueous humor is a mixed solution of physiological saline and sodium bicarbonate, wherein the physiological saline is 125 mM and the sodium bicarbonate is 24 mM.

[0021] Furthermore, the operation process of the liquid injection metering pump in step 3) is as follows: 1) injecting imitation aqueous humor at a rate of 3×10 - 6cm / s speed to inject into the fixed base. When the artificial aqueous humor fills the fixed base, record the injection time, corneal deformation information and pressure value; 2) While ensuring that the overall injection time remains unchanged, increase the injection speed by 1% and record the corneal central thickness deformation information and pressure value; 3) When the pressure reaches the upper limit of high intraocular pressure 30mmHg, stop the injection.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1) The present invention is based on an image recognition neural network deep learning method, uses optical or image sensors to collect data, and uses corneal deformation as an indicator for monitoring intraocular pressure changes. Through accurate monitoring of corneal deformation, accurate monitoring of human corneal pressure can be achieved, and dynamic monitoring can be achieved;

[0024] 2) Under the condition of fully considering the structure of the eyeball and the biomechanics of human tissue, the present invention uses a method combining numerical simulation with experimental verification using COMSOL software to determine the area with the maximum deformation of the patient's cornea when the pressure changes, and designs a software algorithm for calculating and analyzing the corneal deformation based on this. The algorithm is then used to analyze the central thickness of the patient's cornea (when the intraocular pressure is within the normal range, that is, less than 21 mmHg, the central corneal thickness is the mean ± standard deviation: 0.545 ± 0.033 mm, and when suffering from high intraocular pressure, the central corneal thickness of the patient is about 0.592 ± 0.039 mm, that is, the intraocular pressure and the central corneal thickness are nonlinearly correlated), thereby obtaining the precise changes in the patient's intraocular pressure and providing a more reliable and accurate dynamic assessment of intraocular pressure;

[0025] 3) The complex intraocular structure was simplified into a simplified model consisting of only three parts: a bionic artificial cornea, a liquid injection structure, and a liquid discharge structure, in order to reduce the difficulty of preparing the detection device. On this basis, a liquid discharge outlet flow resistance model was established in combination with mathematical equations such as microfluidics and solid mechanics. The COMSOL simulation software was used to analyze the differences in eyeball structure of patients, the influence of internal factors such as corneal thickness and elasticity of liquid discharge outlet tissue, and external factors such as ambient temperature and human posture on the correspondence between intraocular pressure and corneal deformation, and the quantitative relationship and change law between intraocular pressure and corneal deformation were obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the structure of an embodiment of the present invention;

[0027] Figure 2 This is a schematic diagram of the structure of an intraocular pressure deformation amount detection device in an embodiment of the present invention;

[0028] Figure 3 for Figure 2 A top view of

[0029] Figure 4 for Figure 2 Exploded diagram of the structure;

[0030] Figure 5 This is a schematic diagram of the water supply channel structure in an embodiment of the present invention;

[0031] Figure 6 This is a schematic diagram of the distribution of drainage channels in an embodiment of the present invention;

[0032] Figure 7 This is a schematic diagram of the structure of a heater in an embodiment of the present invention;

[0033] Figure 8 This is a schematic diagram of the structure of the pressure test chamber in an embodiment of the present invention;

[0034] Fig. 9 Schematic diagram of the reference line of the geographic coordinate system on the cornea in an embodiment of the present invention;

[0035] Fig.10 It is the deviation curve of the measured value of the embodiment of the present invention and the standard pressure.

[0036] In the figure: 1-bionic eye; 2-fixed base; 3-data analysis terminal; 4-liquid injection metering pump; 5-power supply; 6-electron microscope; 7-bionic eye positioning groove; 8-heater; 9-water supply channel; 10-drainage channel; 11-electrode; 12-collecting pipe; 13-pressure test chamber; 14-pressure sensor; 15-temperature sensor; 16-dispersion sheet. DETAILED DESCRIPTION

[0037] The technical solution of the present invention will be clearly and completely described below in conjunction with specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0038] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the specific embodiments required to be used in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the specific embodiments described below are some implementation methods of the present invention. For ordinary technicians in this field, other specific embodiments can be obtained based on these specific embodiments without paying creative work.

[0039] The components of the embodiments of the present invention generally described and shown in the specific embodiments herein can be arranged and designed in countless different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the specific embodiments is not intended to limit the scope of the invention claimed, but only represents selected embodiments of the present invention.

[0040] See Figure 1-8, is a schematic diagram of the structure of an embodiment of a non-contact intraocular pressure visual calibration method of the present invention. With the help of a simplified AI model of the human eye and an intraocular pressure deformation detection device, combined with MEMS technology and visual analysis theory, through real-time and dynamic simulation of human eye pressure, optical or image sensors are used to collect data to achieve accurate monitoring of corneal deformation, provide a more accurate means of intraocular pressure assessment, and achieve effective calibration of non-contact tonometers. The specific process is as follows:

[0041] Step 1: Place the bionic eye 1 into the intraocular pressure deformation detection device, embed it into the fixed base 2, seal it with glue around it, take the corneal center of the bionic eye 1 as the origin O, add multiple observation points on the cornea, and record them;

[0042] Step 2: placing the intraocular pressure deformation amount detection device under the objective lens of the electron microscope 6;

[0043] Step 3: Start the liquid injection metering pump 4 to inject artificial aqueous humor into the bionic eye 1, monitor the left and right deviation angles and the up and down deviation angles of each observation point at the center of the cornea, and obtain the deformation of the central thickness of the cornea of ​​the bionic eye 1; the operation process of the liquid injection metering pump 4 is as follows: 1) inject artificial aqueous humor at 3×10 -6 1) Inject the artificial aqueous humor into the fixed base 2 at a speed of 100 cm / s. When the artificial aqueous humor fills the fixed base 2, record the injection time, corneal deformation information and pressure value; 2) While ensuring that the overall injection time remains unchanged, increase the injection speed by 1% and record the corneal deformation information and pressure value; 3) Stop the injection when the pressure reaches the upper limit of high intraocular pressure 30 mmHg;

[0044] Step 4: Send the corneal deformation information to the data analysis terminal 3 to obtain the intraocular pressure data of the bionic eye and calibrate the reading of the non-contact tonometer. The whole system is powered by the power supply 5.

[0045] In an embodiment of the present invention, a simplified AI model of the human eye is obtained by a deep learning method based on an image recognition neural network. An observation point is first set on the cornea, and the cornea is photographed when the intraocular pressure is normal. When the intraocular pressure rises, the cornea is photographed again. The observation points in the photographs are offset, and these offsets are used as a basis for neural network learning and discrimination, thereby achieving accurate feedback of the intraocular pressure by analyzing the corneal images before and after the intraocular pressure changes.

[0046] The intraocular pressure deformation amount detection device includes a fixed base 2, a liquid injection metering pump 4 and a data analysis terminal 3. The fixed base 2 is provided with a bionic eye positioning groove 7, and the bottom of the groove is provided with a heater 8 and a water supply channel 9 and a drainage channel 10. The water supply channel 9 is connected to the liquid injection metering pump 4 through a pipeline, and the drainage channel 10 is connected to the pressure test chamber 13. The pressure test chamber 13 is provided with a pressure sensor 14. The fixed base 2 is provided with a temperature sensor 15. The pressure sensor 14 and the temperature sensor 15 are respectively connected to the data analysis terminal 3 through data cables.

[0047] All components of the intraocular pressure deformation detection device in the embodiment of the present invention are made by QbeamLab type commercial open source electron beam metal 3D printing equipment. According to the application environment of the device and comprehensive consideration of cost factors, a copper alloy with good corrosion resistance and low price is selected as the main material of the device. First, COMSOL software is used for modeling, and then the three-dimensional model of the device is cut into a series of cross-sectional slices along the selected molding direction by the GMslicer slicing software supporting the 3D printer, and the sliced ​​device is imported into the printer memory. (GMslicer software, the software has automatic layout and pattern arrangement function, uses efficient parallel algorithm for slicing, and can output multiple layer formats including CLI and STL.) The process control software metaBuild is used to optimize the process of the CLI layer file or STL three-dimensional model file output by the GMslicer slicing software. (The metaBuild software is open source for 7 groups of more than 100 process parameters, allowing users to program, and the process parameter packages of all models can be specified separately to improve the efficiency of process optimization).

[0048] The water supply channel 9 opens directly to the bionic eye positioning groove 7 . The bionic eye 1 is placed in the bionic eye positioning groove 7 and its periphery is sealed. The gap between the bionic eye positioning groove 7 and the bionic eye 1 is filled with simulated aqueous humor.

[0049] The top of the water supply channel 9 is connected to the center of the bottom of the bionic eye through the dispersion sheet 16. The upper surface of the dispersion sheet 16 is provided with a micropore array, the micropore size is 0.1-0.3mm, the distance between adjacent holes is 10 degrees, and there are 36 in total. The water supply channel 9 and the dispersion sheet 16 can make the simulated aqueous humor evenly distributed in the bionic eye positioning groove 7.

[0050] The top of the drainage channel 10 is connected to the bottom periphery of the bionic eye 1, and the bottom of the drainage channel 10 is connected to the pressure test chamber 13 through the collection pipe 12. The bottom of the pressure test chamber 13 is provided with an emptying valve. The drainage channel 10 is a liquid discharge channel inside the bionic eye 1, and the drainage channel 10 simulates the liquid discharge port structure in a real human eye; the drainage channel 10 is a 1mm diameter hollow pipe, and the drainage channel 10 is evenly distributed above the collection pipe 12. The collection pipe 12 is a ring structure. There is a gap between the bionic eye positioning groove 7 and the bionic eye 1. When the bionic eye positioning groove 7 is filled with imitation aqueous humor, the pressure will force the imitation aqueous humor to be discharged from the drainage channel 10 and flow into the collection pipe 12. When the gap is full, the imitation aqueous humor will flow into the pressure test chamber 13 and exert pressure on the pressure sensor 14.

[0051] The pressure sensor 14 can be a differential pressure sensor, a vector pressure sensor or a capacitive pressure sensor, wherein: Differential pressure sensor: suitable for measuring a small range of pressure of 5-60 mmHg, with a measurement accuracy of up to 0.1%. Vector pressure sensor: also suitable for measuring pressure of 5-60 mmHg, and can measure multiple pressure values ​​at the same time, with an accuracy of about 0.5%. Capacitive pressure sensor: the measurement range is 0-100 mmHg, with an accuracy of up to 0.2%.

[0052] See Fig. 9 The corneal surface uses geographic coordinate system division lines, and the latitude and longitude division accuracy is 0.1-0.5mm, preferably 0.2mm. The division lines are ablated on the corneal surface of the bionic eye by a laser marking machine. The observation points are used to simulate the specific distribution of cell positions in the microscopic image of the corneal endothelium or epithelium.

[0053] In the embodiment, the electron microscope is a scanning electron microscope or a confocal microscope. The bionic eye is the "bionic eye" of the German company Retina Implant AG. The pressure sensor is a MEMS pressure sensor; the artificial aqueous humor is a mixed solution of physiological saline and sodium bicarbonate, wherein the physiological saline is 125mM and the sodium bicarbonate is 24mM.

[0054] The intraocular pressure deformation detection device of the present invention is 3D printed. The heater 8 is a hollow structure, prepared by MEMS technology and conductive slurry, and filled with heating oil (CN5001 heating oil of Xinghongyang Technology Co., Ltd.). After the heating oil is baked, dried and solidified, it is connected to the power supply through two electrodes 11. The heating power is 8W. After the power is turned on, the voltage is adjusted to between 5V and 6V, which can make the bionic eye 1 warm up to 37° to simulate the patient's body temperature changes.

[0055] See Fig.10, is the deviation curve between the measured value of the embodiment of the present invention and the standard pressure. It can be seen that the error of the present invention is linearly related to the central corneal thickness. When the central corneal thickness is within a reasonable range, the present invention can well infer the patient's intraocular pressure based on the central corneal thickness, thereby realizing non-contact intraocular pressure calibration.

[0056] The present invention can determine the area with the maximum deformation of the patient's cornea when the pressure changes by combining numerical simulation with experimental verification using COMSOL simulation software, taking into full consideration the influence of individual differences of patients such as eyeball structure and human tissue biomechanics, as well as external factors such as ambient temperature and human posture on the correspondence between intraocular pressure and central corneal thickness deformation, and design a software algorithm for calculating and analyzing the corneal deformation based on this. Subsequently, the algorithm is used to analyze the relative position changes of cells distributed in microscopic photographs of the patient's corneal epithelium or endothelium to calculate the patient's corneal deformation, thereby obtaining the accurate changes in the patient's intraocular pressure.

[0057] The 3D printing equipment used in this embodiment is a commercial open source electron beam metal 3D printing equipment of the QbeamLab type. The QbeamLab commercial open source electron beam metal 3D printing equipment is an open source electron beam metal 3D printer with multiple advantages such as open source process parameters, modular customizability, active powder supply, grid scanning heating, electron beam automatic calibration, and process online monitoring. It supports a variety of metal materials such as titanium alloys, high temperature alloys, high melting point alloys, and copper alloys. The main technical parameters of the QbeamLab commercial open source electron beam metal 3D printing equipment are as follows: maximum forming size 200×200×240mm3, accuracy ±0.2mm, maximum electron beam power 3kW, electron beam acceleration voltage 60kV, electron beam current 0-50mA, cathode type is tungsten filament direct heating, minimum beam spot diameter 200μm, maximum electron beam jump speed 10,000m / s, ultimate vacuum 10-2Pa, helium partial pressure 0.05-1.0Pa adjustable, grid scanning method is used to heat the powder bed, the powder bed surface temperature can reach 1100℃, active cooling blocks are used for part cooling, and optical cameras are used for process monitoring.

[0058] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A non-contact intraocular pressure visual calibration method, characterized in that: With the help of a simplified AI model of the human eye and an intraocular pressure deformation detection device, combined with MEMS technology and visual analysis theory, through real-time and dynamic simulation of human eye pressure, data collection by optical or image sensors can be achieved to accurately monitor corneal deformation, provide a more accurate means of intraocular pressure assessment, and achieve effective calibration of non-contact tonometers. The specific process is as follows: Step 1: Place the bionic eye into the intraocular pressure deformation detection device, embed it into the fixed base, seal it with glue around it, take the corneal center of the bionic eye as the origin O, add multiple observation points on the cornea, and record them; Step 2: Place the intraocular pressure deformation detection device under the electron microscope objective; Step 3: Start the liquid injection metering pump to inject artificial aqueous humor into the bionic eye, monitor the left and right deviation angles and the up and down deviation angles of each observation point, and obtain the corneal central thickness deformation of the bionic eye; Step 4: Send the corneal central thickness deformation information to the data analysis terminal to obtain the intraocular pressure data of the bionic eye and calibrate the reading of the non-contact tonometer.

2. A non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The simplified AI model of the human eye is obtained by a deep learning method based on an image recognition neural network. First, an observation point is set on the cornea. When the intraocular pressure is normal, a photo is taken of the center of the cornea. When the intraocular pressure rises, the center of the cornea is photographed again. The observation points in the photographs are offset. These offsets are used as a basis for neural network learning and discrimination, so that accurate feedback of the intraocular pressure is achieved by analyzing the image of the thickness change in the center of the cornea before and after the intraocular pressure changes.

3. The non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The intraocular pressure deformation amount detection device includes a fixed base, a liquid injection metering pump and a data analysis terminal. The fixed base is provided with a bionic eye positioning groove, and a heater, a water supply channel and a drainage channel are provided at the bottom of the groove. The water supply channel is connected to the liquid injection metering pump through a pipeline, and the drainage channel is connected to a pressure test chamber. A pressure sensor is provided in the pressure test chamber. A temperature sensor is provided on the fixed base. The pressure sensor and the temperature sensor are respectively connected to the data analysis terminal through a data cable.

4. The non-contact intraocular pressure visual calibration method according to claim 3, characterized in that: The top of the water supply channel is connected to the center of the bottom of the bionic eye through a dispersion sheet. The upper surface of the dispersion sheet is provided with a micropore array with a size of 0.1-0.3 mm, a spacing between adjacent holes of 10-18 degrees, and a total of 20-36 micropores.

5. The non-contact intraocular pressure visual calibration method according to claim 3, characterized in that: The top of the drainage channel is connected to the bottom periphery of the bionic eye, the bottom of the drainage channel is connected to the pressure test chamber through a collecting pipe, and a drain valve is provided at the bottom of the pressure test chamber.

6. The non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The distribution of the observation points adopts a geographic coordinate system, the latitude and longitude division accuracy is 0.1-0.5mm, and the division lines are ablated on the corneal surface of the bionic eye by a laser marking machine.

7. The non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The electron microscope is a scanning electron microscope or a confocal microscope.

8. The non-contact intraocular pressure visual calibration method according to claim 3, characterized in that: The bionic eye is a hydrogel artificial eye or the "bionic eye" of the German company Retina Implant AG; the pressure sensor is a MEMS pressure sensor; the intraocular pressure deformation detection device is 3D printed, and the heater is a hollow structure with heating oil filled in it. After the heating oil is baked, dried and solidified, it is connected to a power supply through two wires with a power of 4-10W.

9. The non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The artificial aqueous humor is a mixed solution of physiological saline and sodium bicarbonate, wherein the physiological saline is 125 mM and the sodium bicarbonate is 24 mM.

10. The non-contact intraocular pressure visual calibration method according to claim 1, characterized in that: The operation process of the liquid injection metering pump in step 3) is as follows: 1) injecting imitation aqueous humor at 3×10 -6 cm / s speed to inject into the fixed base. When the artificial aqueous humor fills the fixed base, record the injection time, corneal deformation information and pressure value; 2) While ensuring that the overall injection time remains unchanged, increase the injection speed by 1% and record the corneal deformation information and pressure value; 3) When the pressure reaches the upper limit of high intraocular pressure 30mmHg, stop the injection.

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