Eye appendage simulation model based on sensor technology and use method thereof

Abstract

The invention discloses an eye appendage simulation model based on a sensor technology and a using method thereof.The eye appendage simulation model comprises a simulation device and a simulation training system, the simulation device is a head model constructed according to a human body structure in a simulated mode and is provided with a simulated eyeball front section structure and an eye appendage structure, and the simulation training system is connected with the simulation training system. The eyeball front section structure comprises bulbar conjunctiva and cornea, the eye accessory device structure comprises eyelids, meibomian glands, conjunctiva, lacrimal devices, extraocular muscles and eye sockets, pressure sensors are arranged in parts included by the eye accessory device, and the simulation training system can perform detailed analysis on the massage training process by processing sensor signals. And scoring the training result, and judging whether the massage cleaning technique is skilled and appropriate or not and whether proper force can be used during massage cleaning or not on the basis of the scoring result, so that the eye accessory is prevented from being damaged during treatment, and the purposes of investigating and training the operation technique and professional level of the medical personnel are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of medical equipment and teaching aids, and in particular to an eye appendage simulation model based on sensor technology and a use method thereof. Background Art

[0002] The ocular appendages (including eyelids, meibomian glands, conjunctiva, lacrimal apparatus, extraocular muscles and orbits, etc.) have the function of protecting, supporting and moving the eyeball, but they are also relatively fragile and sensitive: for example, the meibomian glands are located in the upper and lower eyelids, the eyelid skin is thin and loose, and the blood circulation is rich, while the bulbar conjunctiva and palpebral conjunctiva are thin and fragile. The cornea that may be touched during physical therapy of the eyelids is even more sensitive and fragile, and the extraocular muscles are covered with nerves and blood vessels. Therefore, improper operation (such as excessive force, incorrect angle, etc.) in physical therapy such as meibomian gland massage and eyelid margin cleaning can easily cause discomfort to patients, which not only cannot effectively relieve dry eyes, but may even cause other eye risks and injuries. Modern hospitals require attention to patient diagnosis and treatment experience and the quality of nursing services. Due to the complex, fragile and sensitive structure of the eye, the requirements for the techniques of eye physical therapy operators should be more stringent.

[0003] In the prior art, training aids for dry eyelid meibomian gland massage, deep eyelid margin cleaning, etc. are very scarce. Even if they exist, it is difficult to get good and obvious effect feedback because it is impossible to accurately judge the strength and pressing effect (such as patent CN213582598U, a meibomian gland pressing nursing teaching demonstration device and patent CN216362006U, an ophthalmic meibomian gland massage teaching tool). To this end, we propose an eye appendage simulation model based on sensor technology and its use method. Summary of the invention

[0004] The object of the present invention is to provide an eye appendage simulation model based on sensor technology and a method of using the same to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an eye appendage simulation model based on sensor technology and a method of using the same, the eye appendage simulation model comprising a simulation device and a simulation training system, the simulation device being a head model constructed according to the imitation of the human body structure, having a simulated anterior segment structure of the eyeball and an eye appendage structure, the anterior segment structure of the eyeball comprising the bulbar conjunctiva and the cornea, the eye appendage structure comprising the eyelid, meibomian gland, conjunctiva, lacrimal apparatus, extraocular muscles and eye socket, and pressure sensors are provided in the parts included in the eye appendages, the simulation training system is used to process the signal output by the pressure sensor in the simulation device, comprising a preset layer, a collection layer, an analysis layer and a feedback layer, and the simulation training system can perform a detailed analysis of the massage training process and score the training results by processing the sensor signal.

[0006] The simulation device includes a first conductive layer, a second conductive layer, a fixing layer, and a simulated skin layer. The fixing layer is arranged on the inner layer. Conductors are arranged inside the first conductive layer and the second conductive layer. The simulated skin layer is arranged on the outermost layer. The conductor layers are linear strips. The conductors of the first conductive layer and the second conductive layer are respectively arranged crosswise on the upper part of the fixing layer. The conductor includes a first flexible insulating substrate, a second flexible insulating substrate, a first wire, a second wire, a sealing port, a first serrated layer, a second serrated layer, and a conductive filler. The first serrated layer and the second serrated layer are arranged on the relative inner sides of the first flexible insulating substrate and the second flexible insulating substrate. The surfaces of the first serrated layer and the second serrated layer are coated with a graphene conductive coating. The conductive filler is arranged in the cavity between the first serrated layer and the second serrated layer. The two sides of the cavity between the first serrated layer and the second serrated layer are sealed by the sealing port so that the conductive filler is distributed in the cavity. The conductive filler is liquid metal. The conductors on the first conductive layer and the second conductive layer are arranged vertically and horizontally. The graphene conductive coating on the first serrated layer is electrically connected to the first wire, and the graphene conductive coating on the second serrated layer is electrically connected to the second wire. The resistance change between the two graphene conductive coatings and the conductive filler is measured through the second wire and the first wire. The measuring method is as follows: the second conductive layer measurement is the X-axis, and the first conductive layer is the Y-axis; the X-axis is only used as a positioning point, and the Y-axis is used to measure the pressure magnitude.

[0007] Preferably, the conductors of the first conductive layer and the second conductive layer are perpendicularly crossed when projected onto a plane. The simulated skin layer is semi-transparent and made of soft silicone.

[0008] Preferably, the first flexible insulating substrate and the second flexible insulating substrate are formed by dispensing insulating glue. The insulating glue is one or a combination of polyester, epoxy, polyurethane, polybutadienoic acid, or silicone. The conductive filler is gallium-based liquid metal. Its preparation method is as follows: put gallium ingots into a vacuum drying oven at 60 °C and heat for 3 h to convert them into a liquid state, then weigh the raw materials according to the mass ratio of gallium: indium: tin = 67:20.5:12.5, add them into a graphite crucible, and transfer them into an atmosphere furnace. First, use a vacuum pump to evacuate the furnace to -80 Pa, then introduce argon gas, and keep the pressure in the atmosphere furnace stable at 5 - 10 Pa. Heat the temperature to 500 °C and keep it for 1 h. After smelting is completed, wait until it cools to room temperature.

[0009] Preferably, the preset layer includes a data import module and a data verification module. The data import module is used to initialize the underlying calculation data, including the cycle time of a single training, the structures of the adnexa oculi, and their scoring coefficients under different massage pressure ranges. The scoring coefficient is used to evaluate the comfort level of the massage force on the human body, and its value range is [0, 1]. The larger the value, the more comfortable the massage force. Different calculation data are formulated according to the vulnerability and sensitivity of the eyelids, tarsal glands, conjunctiva, lacrimal apparatus, extraocular muscles, and orbital regions included in the adnexa oculi, that is, the scoring coefficients corresponding to different pressure ranges; the data verification module is used to perform integrity verification on the imported data, including whether the parts of the adnexa oculi and their pressure ranges are completely imported and whether the scoring coefficients are within the formulated range.

[0010] Preferably, the acquisition layer includes a signal collection module and a signal induction module. The acquisition layer can access the data initialized by the preset layer. The signal collection module is connected to the signal output end of the pressure sensor of the simulation device and sets the parameters for data acquisition, such as the sampling frequency, sampling accuracy, and pulse timer. This module records the real-time massage pressure values and durations of the eyelids, tarsal glands, conjunctiva, lacrimal apparatus, extraocular muscles, and orbital regions in the adnexa oculi, and the output result is a set of discrete data mixed with multiple dimensions.

[0011] Preferably, the signal induction module classifies and summarizes the real-time data collected by the signal collection module according to the pressure range data initialized by the preset layer, and calculates the total duration of different parts of the adnexa oculi under different massage pressure ranges during this training.

[0012] Preferably, the analysis layer includes a data analysis module. The data analysis module includes a score calculation unit and a timing analysis unit. The score calculation unit uses the data output by the preset layer and the acquisition layer to calculate the scoring situations of different parts during the massage of the adnexa oculi respectively, and finally summarizes the scores of different parts to obtain the total score. The calculation formula for the score of each part is as follows:

[0013]

[0014] In the formula, S a is the score of a certain part, T0 to T n represents the massage duration under different pressure ranges, T is the total duration of a single training, a0 to a n represents the scoring coefficient of the corresponding pressure range of this part of the adnexa oculi. The formula for calculating the total score:

[0015] S sum = S a + S b + S c +…;

[0016] In the formula, Ssum is the total score, S a , S b , S c … are the scores of each part of the adnexa of the eye. By adding up the scores of each part, the total score of this training can be obtained.

[0017] Preferably, the timing analysis unit is used to output the data generated during the massage training cycle in a timed manner. The output data of this unit will be used to make a training timing diagram, record the pressure conditions generated by the massage training at each moment, and mark the parts massaged at that moment. Through the data processing of the timing analysis unit, it assists the trainer to review the process of the adnexa of the eye massage training.

[0018] Preferably, the analysis layer further includes a data storage module, which is used to upload the inductive data, the score data of each part of the adnexa of the eye, and the timing analysis data generated by this training to the cloud, and the services on the cloud perform persistent storage on the data.

[0019] Preferably, the feedback layer is used to display the process information and score situation of each training, and visually display the analysis results, by means of drawing charts, making animations or generating reports, etc.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] The present invention provides an eye adnexa simulation model based on sensor technology that can provide feedback on the pressing force and range at different sites, enabling intuitive observation of whether various feedback indicators meet the standards during the simulated operation by the operator. Based on this, it can be judged whether the massage and cleaning techniques are proficient and appropriate, and whether the appropriate force can be used during massage and cleaning to avoid damage to the adnexa of the eye during treatment, achieving the purpose of examining and training the operation techniques and professional levels of medical staff. Brief Description of the Drawings

[0022] Figure 1 is the hierarchical schematic diagram of the device of the present invention;

[0023] Figure 2 is the external view of the device of the present invention;

[0024] Figure 3 is the schematic diagram of the eye;

[0025] Figure 4 is the schematic diagram of the conductor structure;

[0026] Figure 5 is the schematic diagram of the first conductive layer structure;

[0027] Figure 6 is the schematic diagram of the second conductive layer structure;

[0028] Figure 7 It is a schematic diagram of the overall structure of the simulation training system;

[0029] Figure 8 It is a diagram of the preset layer data example.

[0030] In the figure: the first conductive layer 1, the conductor 2, the first flexible insulating substrate 21, the second flexible insulating substrate 22, the first wire 23, the second wire 24, the sealing port 25, the first serrated layer 26, the second serrated layer 27, the conductive filler 28, the second conductive layer 3, the fixing layer 4, the simulated skin layer 5. Specific implementation manner

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0032] Please refer to Figure 1-8 , the present invention provides a technical solution: an accessory of the eye simulation model based on sensor technology and its use method, the accessory of the eye simulation model includes a simulation device and a simulation training system, the simulation device is a head model imitated according to the human body structure, and has a simulated anterior segment structure of the eyeball and an accessory structure of the eye, the anterior segment structure of the eyeball includes the bulbar conjunctiva and the cornea, and the accessory structure of the eye.

[0033] Embodiment 1:

[0034] The overall simulation is in the shape of a human face, including the first conductive layer 1, the second conductive layer 3, the fixing layer 4, and the simulated skin layer 5. The fixing layer 4 is arranged on the inner layer, and the conductors 2 are arranged inside the first conductive layer 1 and the second conductive layer 3. The conductors 2 are linearly strip-shaped, and the conductors 2 of the first conductive layer 1 and the conductors 2 of the second conductive layer 3 are respectively arranged crosswise on the upper part of the fixing layer 4. The conductors 2 of the first conductive layer 1 and the conductors 2 of the second conductive layer 3 are preferably perpendicular to each other and cross on the plane. In this way, when there are multiple point cross-presses, it is convenient to calculate the pressure distribution of each press point through an algorithm, thereby simplifying the algorithm. The simulated skin layer 5 is arranged on the outermost layer, and facial feature components such as eyes and mouth can be arranged on the simulated skin layer 5. The first conductive layer 1 and the second conductive layer 3 of the present invention change the sensor resistance value according to the change of the external pressure. The external feedbacks the pressing force and range of different positions according to the change of the measured resistance value. Based on this, it is judged whether the massage and cleaning technique is proficient and appropriate, whether it can effectively press and clean in place and play a role in relieving dry eye, so as to achieve the purpose of inspecting and training the operation techniques and professional levels of medical staff.

[0035] The eyelid structure is the outer layer of skin, beneath which are the orbicularis oculi muscle and fat, and further beneath is the tarsal gland, which is similar to ear cartilage and not hard bone. Further down is the palpebral conjunctiva on the inner surface. I think the sensor should be placed under the skin and under the palpebral conjunctiva, suitable for evaluation during tarsal gland massage. Additionally, there should also be one at the eyelid margin, suitable for detection during eyelid margin cleaning.

[0036] The fixing layer can be a rigid framework layer.

[0037] The simulated skin layer 5 of the present invention can be semi-transparent, simulating the structure of the human skin layer, made of soft silicone, and having a touch similar to that of the human skin layer when pressed, so that the first conductive layer 1 and the second conductive layer 3 can sense the pressure condition of the upper simulated skin layer 5 even.

[0038] The eye adnexa simulation device based on sensor technology of the present invention has an overall model established according to 1:1 for an adult head. According to the 1:1 model, the model can be closer to the human body structure, enabling the operator to simulate operations more realistically, achieving a more intuitive training effect, obtaining more effective feedback data and conducting investigations based on this. When the simulation device of the present invention is in use, the whole simulation device is in a supine position for easy operation.

[0039] As Figures 3 to 5 shown, the conductor 2 of the present invention includes a first flexible insulating substrate 21, a second flexible insulating substrate 22, a first wire 23, a second wire 24, a sealing port 25, a first serrated layer 26, a second serrated layer 27, and a conductive filler 28. The first serrated layer 26 and the second serrated layer 27 are arranged on the relative inner sides of the first flexible insulating substrate 21 and the second flexible insulating substrate 22. The surfaces of the first serrated layer 26 and the second serrated layer 27 are coated with a graphene conductive coating, and the conductive filler 28 is arranged in the cavity between the first serrated layer 26 and the second serrated layer 27. The two sides of the cavity between the first serrated layer 26 and the second serrated layer 27 are sealed with the sealing port 25 so that the conductive filler 28 is distributed in the cavity. The conductive filler 28 of the present invention is a liquid metal, which has high conductivity, good fluidity and low toxicity. Injecting it into the pipeline formed by the first flexible insulating substrate 21 and the second flexible insulating substrate 22 can resist folding and large deformation amounts, so that the conductor 2 can be flexibly installed according to facial signs. As Figure 4 and Figure 5As shown, the conductors 2 on the first conductive layer 1 and the second conductive layer 3 of the present invention are arranged vertically and horizontally. In this way, when the device of the present invention is pressed down, the conductive filler 28 between the first serrated layer 26 and the second serrated layer 27 gradually decreases, and the resistance gradually decreases with the increase of pressure, and the whole system is bendable. When the first serrated layer 26 and the second serrated layer 27 are in full contact and the contact pressure is large, the resistance is the smallest. The serrated structure design can ensure a large contact area during contact, and at the same time can ensure that the liquid conductive filler 28 is in full contact with the upper and lower graphene electrocoats, and the resistance is changed according to the thickness change of the weakest part of the conductive filler 28. The fixing layer 4 is set according to the face shape, and the conductor 2 can be laid according to the radian of the fixing layer 4. The simulated skin layer 5 is laid on the outermost layer, so that the device of the present invention can more realistically simulate the human face structure and can measure the pressure at each point.

[0040] The graphene conductive coating on the first serrated layer 26 of the present invention is electrically connected to the first wire 23, and the graphene conductive coating on the second serrated layer 27 is electrically connected to the second wire 24. The resistance change between the two graphene conductive coatings and the conductive filler 28 can be measured through the second wire 24 and the first wire 23. For example, when a voltage is applied between the first wire 23 and the second wire 24, the resistance change of the conductive filler 28 can cause a corresponding current change.

[0041] The first flexible insulating substrate 21 and the second flexible insulating substrate 22 of the present invention can be formed by dispensing an insulating glue. The insulating glue can be one or a combination of polyester, epoxy, polyurethane, polybutadienoic acid or silicone. After the insulating glue is bonded, the whole conductor 2 maintains good flexibility and can be laid according to the human face shape.

[0042] The conductive filler 28 of the present invention can be a gallium-based liquid metal, and its preparation method is as follows: put the gallium ingot into a vacuum drying oven at 60°C and heat it for 3h to convert it into a liquid state, and then weigh the raw materials according to the mass ratio of gallium: indium: tin = 67:20.5:12.5 (the purity of the metal raw materials is 4N), add them to a clean graphite crucible, and transfer them into an atmosphere furnace. First, use a vacuum pump to evacuate the furnace to -80Pa, and then introduce argon to ensure that the pressure in the atmosphere furnace is stable at 5-10Pa, and heat at a temperature of 500°C for 1h. After the smelting is completed, wait until it cools to room temperature, take out the crucible and pour it into polytetrafluoroethylene for encapsulation and use. The liquid metal of the present invention can also be other forms of liquid metal as long as it has good fluidity at room temperature and good electrical conductivity.

[0043] An eye adnexa simulation device based on sensor technology of the present invention can provide feedback on the pressing force and range at different positions. The specific measurement method is as follows: The first conductive layer 1 and the second conductive layer 3 of the present invention can cross-induce. During measurement, for example, the second conductive layer 3 between the two ears is measured as the X-axis, and the first conductive layer 1 in the direction of the nose is the Y-axis. When massaging the eye adnexa simulation device of the present invention, it is generally possible to massage synchronously in the reverse direction of the X-axis. For example, two pressures or multiple pressures act on a conductive body 2 in the X-axis direction simultaneously, while there is only one point of pressure in the Y-axis, that is, only one pressure acts on a conductive body 2 simultaneously. The change in the resistance of the conductive body 2 on the Y-axis causes a change in current. To simplify the algorithm, the X-axis of the present invention is only used as a positioning point, and the Y-axis is used to measure the pressure magnitude, so as to realize the positioning of the magnitude and position of each pressure and measure and analyze the pressure at each point.

[0044] Embodiment 2:

[0045] An eye adnexa simulation model based on sensor technology and its usage method. The eye adnexa simulation model includes a simulation training system. The simulation training system is used to process the signals output by the pressure sensors in the simulation device, and includes a preset layer, a collection layer, an analysis layer, and a feedback layer. By processing and processing the sensor signals, the simulation training system can analyze the process of massage training in detail and score the training results. The simulation training system is a software system integrating data analysis, data storage, and data visualization, used for human-computer interaction with the trainer, and can be developed using WEB technology compatible with various terminals, facilitating the trainer to retrieve training information.

[0046] The preset layer includes a data import module and a data verification module. The data import module is used to initialize the underlying calculation data, including the cycle time of one training, the structure of the eye adnexa, and its scoring coefficient under different massage pressure ranges. The scoring coefficient is used to judge the comfort level caused by the massage force to the human body, and its value range is [0, 1]. The larger the value, the more comfortable the massage force. It can be evenly valued {0, 0.2, 0.4, 0.6, 0.8, 1}. A scoring coefficient of 0 means that the massage does not generate pressure or the generated pressure has exceeded the human tolerance range. The value range of the pressure range can be divided according to the output specifications of the pressure sensor. For example, for a pressure sensor that outputs current pulses, the interval range corresponding to the scoring coefficient can be divided, such as {0|>100, (0, 10]|[90, 100), (10, 20]|[80, 90), (20, 30]|[70, 80), (30, 40]|[60, 70), (40, 50]|[50, 60)}, and the unit is mA.

[0047] In addition, different calculation data need to be formulated according to the vulnerability and sensitivity levels of the eyelid, tarsal gland, conjunctiva, lacrimal apparatus, extraocular muscle, and orbital region included in the adnexa of the eye, that is, the score coefficients corresponding to different pressure ranges. The bulbar conjunctiva region is generally more vulnerable and sensitive to the pressure generated by massage, so a smaller pressure range interval is required for monitoring. For example, the pressure range of the bulbar conjunctiva is set as {0|>50,(0,5]|[45,50),(5,10]|[40,45),(10,15]|[35,40),(15,20]|[30,35),(20,25]|[25,30)}, so that more accurate feedback information can be obtained.

[0048] The data verification module is used to perform integrity verification on the imported data, including whether the parts of the adnexa of the eye and their pressure ranges are imported completely and whether the score coefficients are within the formulated range. The input range of the score coefficients should be [0,1], and the pressure range should include the complete interval range without missing the unmonitored intervals.

[0049] Embodiment 3:

[0050] Embodiment 3 further illustrates a simulation model of the adnexa of the eye based on sensor technology and its usage method proposed by the present invention.

[0051] The acquisition layer includes a signal collection module and a signal induction module. The acquisition layer can access the data initialized by the preset layer. The signal collection module is connected to the signal output end of the pressure sensor of the simulation device and sets the parameters for data acquisition, such as the sampling frequency, sampling accuracy, and pulse timer. This module records the real-time massage pressure values and durations of the eyelid, tarsal gland, conjunctiva, lacrimal apparatus, extraocular muscle, and orbital region in the adnexa of the eye. The output result is a set of discrete data mixed with multiple dimensions. The calculation method is as follows: compared with the previous pulse signal, if it is not within the pressure range interval specified by the preset layer, a set of data is recorded, and at the same time, the pulse timer is reset. The recorded data includes the adnexa of the eye part, the pressure signal value, and the signal duration. The adnexa of the eye part can be identified from the received sensor signal, the pressure signal value is the numerical value of the pulse signal transmitted by the sensor, and the duration can be obtained from the signal timer.

[0052] The signal induction module classifies and summarizes the real-time data collected by the signal collection module according to the pressure range data initialized by the preset layer, and calculates the total duration of different parts of the adnexa of the eye under different massage pressure ranges during this training.

[0053] The analysis layer includes a data analysis module, and the data analysis module includes a score calculation unit and a time series analysis unit. The score calculation unit uses the data output by the preset layer and the acquisition layer to calculate the scores of different parts during the massage of the adnexa of the eye respectively, and finally summarizes the scores of different parts to obtain the total score. The calculation formula for the score of each part is as follows:

[0054]

[0055] In the formula, S a is the score of a certain part, T0 to T n represents the massage duration according to different pressure ranges, T is the total duration of one training, and a0 to a n represent the score coefficients corresponding to the pressure ranges of the adnexa of the eye part. The formula for calculating the total score:

[0056] S sum = S a + S b + S c +…;

[0057] In the formula, S sum is the total score, S a , S b , S c … are the scores of each part of the adnexa of the eye. By adding the scores of each part, the total score of this training can be obtained. In specific implementation, the pressure signal value can be specially processed. If its value is too large, the total score can be considered as 0, because a too large pressure signal value means that it is very likely to cause damage to the adnexa of the eye during pressing, which seriously does not meet the standards of training operations.

[0058] The time series analysis unit is used to output the data generated during the massage training cycle in a time series. The output data of this unit will be used to make a training time series diagram, record the pressure situation generated by the massage training at each moment, and mark the part massaged at that moment. Through the data processing of the time series analysis unit, it helps the trainer review the process of the adnexa of the eye massage training, which is convenient for the trainer to find and correct some wrong operations and improve the training effect.

[0059] The analysis layer also includes a data storage module, which is used to upload the inductive data, the score data of each part of the adnexa of the eye, and the time series analysis data generated by this training to the cloud, and the services on the cloud perform persistent storage on the data.

[0060] The feedback layer is used to display the process information and score situation of each training, and visually display the analysis results, which is carried out by means of drawing charts, making animations or generating reports, etc., so that the trainer can better understand the data and have a clear understanding of his own training situation.

[0061] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0062] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An accessory eye structure simulation model based on sensor technology, characterized in that: The eye appendage simulation model includes a simulation device and a simulation training system. The simulation device is a head model constructed according to the human body structure, and has a simulated anterior eye structure and an eye appendage structure. The anterior eye structure includes the bulbar conjunctiva and the cornea. The eye appendage structure includes the eyelid, meibomian gland, conjunctiva, lacrimal apparatus, extraocular muscles and eye sockets. Pressure sensors are provided in the parts included in the eye appendages. The simulation training system is used to process the signal output by the pressure sensor in the simulation device, and includes a preset layer, a collection layer, an analysis layer and a feedback layer. The simulation training system can perform a detailed analysis of the massage training process and score the training results by processing the sensor signal. The simulation device comprises a first conductive layer (1), a second conductive layer (3), a fixed layer (4), and a simulated skin layer (5), wherein the fixed layer (4) is arranged in the inner layer, a conductor (2) is arranged inside the first conductive layer (1) and the second conductive layer (3), and the simulated skin layer (5) is arranged in the outermost layer, and is characterized in that: the conductor (2) is in the shape of a linear strip, and the conductor (2) of the first conductive layer (1) and the conductor (2) of the second conductive layer (3) are respectively interlaced on the upper part of the fixed layer (4); the conductor (2) comprises a first flexible insulating substrate (21), a second flexible insulating substrate (22), a first wire (23), a second wire (24), a sealing port (25), a first sawtooth layer (26), a second sawtooth layer (27), and a conductive filler (28), and the first flexible insulating substrate (21) and the second flexible insulating substrate (22) are arranged with a first sawtooth layer (26) and a second sawtooth layer (27) on the inner sides thereof, and the first sawtooth layer (26) and the second sawtooth layer (27) are arranged with a conductive filler (28) on the inner sides thereof. 7) is coated with a graphene conductive coating, and a conductive filler (28) is arranged in the cavity between the first sawtooth layer (26) and the second sawtooth layer (27); the two sides of the cavity between the first sawtooth layer (26) and the second sawtooth layer (27) are sealed by sealing ports (25) so that the conductive filler (28) is distributed in the cavity; the conductive filler (28) is liquid metal, and the conductors (2) on the first conductive layer (1) and the second conductive layer (3) are arranged in a crisscross pattern; the graphene conductive coating on the first sawtooth layer (26) is electrically connected to the first wire (23), and the graphene conductive coating on the second sawtooth layer (27) is electrically connected to the second wire (24), and the resistance change between the two layers of graphene conductive coating and the conductive filler (28) is measured through the second wire (24) and the first wire (23); the measurement method is: the second conductive layer (3) is measured as the X axis, and the first conductive layer (1) is measured as the Y axis; the X axis is only used as a positioning point, and the Y axis is used as the pressure magnitude for measurement.

2. The simulation model of the adnexa oculi based on sensor technology according to claim 1, wherein: The conductors (2) of the first conductive layer (1) and the conductors (2) of the second conductive layer (3) are projected onto a plane and intersect each other perpendicularly. The simulated skin layer (5) is translucent and made of soft silicone.

3. The simulation model of adnexa oculi based on sensor technology according to claim 2, wherein: The first flexible insulating substrate (21) and the second flexible insulating substrate (22) are formed by dispensing insulating glue; the insulating glue is composed of one or several combinations of polyester, epoxy, polyurethane, polybutadienoic acid, or silicone, and the conductive filler (28) is gallium-based liquid metal. Its preparation method is as follows: Put gallium ingots into a vacuum drying oven at 60 °C and heat for 3 h to convert them into a liquid state. Then, weigh the raw materials according to the mass ratio of gallium: indium: tin = 67:20.5:12.5, add them to a graphite crucible, and transfer them into an atmosphere furnace. First, use a vacuum pump to evacuate the furnace to -80 Pa, then introduce argon gas, and keep the pressure in the atmosphere furnace stable at 5 - 10 Pa. Heat at a temperature of 500 °C and hold for 1 h. After smelting is completed, wait until it cools to room temperature.

4. The method for using an accessory organ of eye simulation model based on sensor technology according to claim 1, wherein: The preset layer includes a data import module and a data verification module. The data import module is used to initialize the underlying calculation data, including the cycle time of one training, the structure of the adnexa of the eye, and the scoring coefficients under different massage pressure ranges. The scoring coefficients are used to evaluate the comfort level caused by the massage force to the human body, and their value range is [0, 1]. The larger the value, the more comfortable the massage force. Different calculation data are formulated according to the vulnerability and sensitivity of the eyelids, tarsal glands, conjunctiva, lacrimal apparatus, extraocular muscles, and orbital parts included in the adnexa of the eye, that is, the scoring coefficients corresponding to different pressure ranges; the data verification module is used to perform integrity verification on the imported data, including whether the parts of the adnexa of the eye and their pressure ranges are imported completely and whether the scoring coefficients are within the formulated range.

5. The usage method of an accessory organ of eye simulation model based on sensor technology according to claim 4, characterized in that: The acquisition layer includes a signal collection module and a signal induction module. The acquisition layer can access the data initialized by the preset layer. The signal collection module is connected to the signal output end of the pressure sensor of the simulation device and sets the parameters for data acquisition, such as sampling frequency, sampling accuracy, and pulse timer. This module records the real-time massage pressure values and durations of the eyelids, tarsal glands, conjunctiva, lacrimal apparatus, extraocular muscles, and orbital parts in the adnexa of the eye, and the output result is a set of discrete data mixed with multiple dimensions.

6. The usage method of an accessory organ of eye simulation model based on sensor technology according to claim 5, characterized in that: The signal induction module classifies and summarizes the real-time data collected by the signal collection module according to the pressure range data initialized by the preset layer, and calculates the total duration of different parts of the adnexa of the eye under different massage pressure ranges during this training.

7. The method for using an accessory organ of eye simulation model based on sensor technology according to claim 6, characterized in that: The analysis layer includes a data analysis module. The data analysis module includes a score calculation unit and a timing analysis unit. The score calculation unit uses the data output by the preset layer and the acquisition layer to calculate the scoring situations of different parts during the massage of the adnexa of the eye respectively. Finally, the scores of different parts are summarized to obtain the total score. The calculation formula for the score of each part is as follows: Where, S a is the score of a certain part, T0 to T n represent the massage duration according to different pressure ranges, T is the total duration of one training, a0 to a n represent the score coefficients corresponding to the pressure ranges of the accessory organ of the eye. The formula for calculating the total score: S sum = S a + S b + S c + …; Where S sum is the total score, and S a , S b , S c … are the scores of each part of the adnexa of the eye. By adding up the scores of each part, the total score of this training can be obtained.

8. The method for using an accessory organ of eye simulation model based on sensor technology according to claim 7, wherein: The timing analysis unit is used to output the data generated during the massage training cycle in a timed manner. The output data of this unit will be used to make a training timing diagram, record the pressure situation generated by the massage training at each moment, and mark the part massaged at that moment. Through the data processing of the timing analysis unit, it assists the trainer to review the process of the adnexa of the eye massage training.

9. The usage method of an accessory organ of eye simulation model based on sensor technology according to claim 8, characterized in that: The analysis layer further includes a data storage module, which is used to upload the inductive data generated by this training, the score data of each part of the adnexa of the eye, and the time series analysis data to the cloud, and the services on the cloud perform persistent storage on the data.

10. The method for using an accessory organ of eye simulation model based on sensor technology according to claim 9, characterized in that: The feedback layer is used to display the process information and score situation of each training, and visually display the results obtained by analysis, by means of drawing charts, making animations or generating reports, etc.

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