Eye model for training a machine to determine refractive state

Abstract

The present invention relates to a mechanical eye model mimicking a human eye. The eye model comprises an anterior chamber with an artificial cornea, an artificial pupil, and an artificial lens, a fluid filled chamber to mimic an eyeball, with an artificial retina at the back of the fluid filled chamber. The artificial retina is movable along a channel attached to one side of the fluid filled channel, thereby changing the distance between the artificial retina and the anterior chamber, mimicking changes in axial length and diopter of a human eye.

Description

EYE MODEL FOR TRAINING A MACHINE TO DETERMINE REFRACTIVESTATEBACKGROUND

[0001] Myopia is a growing epidemic around the world, with roughly 36% of children in the United States identified as having myopia. In Asia, the ratio of children with myopia is higher, with South Korea having a rate of 79% in children with myopia.

[0002] There are two (2) prevailing thoughts on the causes on myopia: spending more time indoors, which means looking at close objects more often, causing the human eyes to adapt to make these distances more comfortable; and lack of sunlight, which causes an increase in chemical signals causing the retina to keep growing.

[0003] Myopia is a preventable problem. However, it requires early identification and monitoring of the treatment, both of which currently require a visit to an eye care professional for an eye exam. Current myopia monitoring can be infrequent, usually a few times per year, more often once per year. Fast onset myopia can develop rapidly in a little as a couple of months, in which case it would not be identified early enough with sporadic check-ups. In the U.S., current business models in the ophthalmic industry are centered around retailing of spectacles and contact lenses. Therefore, having multiple myopia check-ups (resulting in no new spectacle or contact lenses sales sales) does not bring in revenue equivalent to servicing regular patients.

[0004] There exists a demand for detecting and monitoring development of myopia at home with a high degree of frequency and accuracy, and monitoring and confirming that myopia has slowed down. The present invention addresses this and other related needs in the art.SUMMARY

[0005] According to frequently included embodiments, there is provided a mechanical eye model, comprising: an anterior chamber comprising an artificial cornea, an artificial pupil, and an artificial lens arranged in the same order as in a human eye; a fluid filled chamber in substantially cylindrical shape attached to one end of the anterior chamber behind the artificial lens; a channel in substantially cylindrical shape attached to the fluid filled chamber; an artificial retina attached to a piston, the piston having a length longer than the channel and is configured to move along the channel; anda fluid overflow chamber connected to the fluid filled chamber by a pipe capable of conducting fluid, the fluid overflow chamber configured to store fluid, wherein the artificial retina is configured in substantially dome shape and is dimensioned to cap the fluid filled chamber on a side opposite the anterior chamber, wherein the channel and the fluid filled chamber are dimensioned to have the same diameter. wherein the fluid overflow chamber has a fluid storage capacity larger than the fluid storage capacity of the channel.

[0006] According to often included embodiments, there is provided a mechanical eye model as above, wherein the artificial pupil is an empty space through which lights enter the anterior chamber.

[0007] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the artificial cornea and the artificial lens are made of plastic capable of receiving light and conducting light therethrough.

[0008] According to often included embodiments, there is provided a mechanical eye model as above, wherein the artificial cornea and the artificial lens are made of acrylic and acrylate polymers.

[0009] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the artificial retina comprises a cylindrical shape having a dome shape depression at one end and is configured to attach to the piston at the other end.

[0010] According to often included embodiments, there is provided a mechanical eye model as above, wherein the artificial retina is of flesh color.

[0011] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the artificial retina is made of polyurethane.

[0012] According to often included embodiments, there is provided a mechanical eye model as above, wherein the anterior chamber, the fluid filled chamber, the channel, and the fluid overflow chamber are enclosed in an enclosure.

[0013] According to frequently included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a fluid retainer between the fluid filled chamber and the anterior chamber to prevent fluid from entering the anterior chamber.

[0014] According to often included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further compnses a sliding part attached to the piston, the sliding part attached to a railway and capable of moving on the railway.

[0015] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the sliding part is attached to the piston via a piston connector and a plate adapter.

[0016] According to often included embodiments, there is provided a mechanical eye model as above, wherein the piston connector and the plate adapter are connected via a push plate.

[0017] According to frequently included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a motorized stage configured to move on the railway.

[0018] According to often included embodiments, there is provided a mechanical eye model as above, wherein the motorized stage is configured to push the sliding part to move on the railway.

[0019] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the motorized stage is capable of an incremental repeatable movement of 0.8 pm.

[0020] According to often included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a stage base, wherein the railway rests on the stage base.

[0021] According to frequently included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a controller configured to control the motorized stage.

[0022] According to often included embodiments, there is provided a mechanical eye model as above, wherein the controller is configured to control the motorized stage automatically.

[0023] According to frequently included embodiments, there is provided a mechanical eye model as above, wherein the controller is a personal computer.

[0024] According to often included embodiments, there is provided a mechanical eye model as above, wherein the motorized stage is configured to interact with the controller via an USB interface.

[0025] According to frequently included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a general platform for all parts to rest on.

[0026] According to often included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises legs on the general platform.

[0027] According to frequently included embodiments, there is provided a mechanical eye model as above, the mechanical eye model further comprises a variable optic block simulating a corrective eyeglass situated in front of the anterior chamber.

[0028] According to often included embodiments, there is provided a system, comprising: the model eye according to the above; and a camera with picture capturing capabilities.

[0029] According to frequently included embodiments, there is provided a system as above, the system further comprises a flashlight for picture capturing.

[0030] According to often included embodiments, there is provided a system above, wherein the camera and the flashlight are provided as part of a smartphone.

[0031] According to frequently included embodiments, there is provided a system as above, the system further comprises a platform to place the smartphone such that the camera can capture pictures of the artificial retina within the model eye.

[0032] According to frequently included embodiments, there is provided a system as above, the system further comprises an optical assembly situated in front of the camera and the flashlight to filter and reflect light.

[0033] According to frequently included embodiments, there is provided a system as above, wherein the optical assembly comprises a polarizer and a mirror to deflect light from the flashlight to a beam splitter to split light before reaching an object to be photographed, and a polarizer and lens to filter light coming from the obj ect to be photographed before reaching the camera.

[0034] According to frequently included embodiments, there is provided a method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system as above; using an interface on the controller and moving the piston at an increment and stopping the piston; taking a picture of the model eye using the camera; and saving the picture as digital data.

[0035] According to often included embodiments, there is provided a method as above, wherein the flashlight is turned on before the picture is taken.

[0036] These and other embodiments, features, and advantages will become apparent to those skilled in the art when taken with reference to the following more detailed description of various exemplary embodiments of the present disclosure in conjunction with the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The skilled person in the art will understand that the drawings, described below, are for illustration purposes only.

[0038] FIG. 1 depicts perspective view of an eye model for generation of images simulating a refractive state of an eye.

[0039] FIG. 2 depicts another perspective view of the eye model in FIG. 1.

[0040] FIG. 3 depicts an exploded view of the eye model in FIG. 1.

[0041] FIG. 4 depicts a cross-sectional view of the eye model in FIG. 1.

[0042] FIG. 5 depicts a side view of the same eye model in FIG. 1.

[0043] FIG. 6 depicts a perspective view of a model eye according to embodiments herein with a smartphone having an optical assembly attachment situated in front of the model eye.

[0044] FIG. 7 depicts a perspective view of the model eye set up in FIG. 6, but with prescription glasses placed in front of the model eye to simulate refractive error.

[0045] FIG. 8 depicts a perspective view of an optical assembly attachment according to embodiments herein, as attached to a smartphone.

[0046] FIG. 9 depicts a cross-sectional view of the optical assembly attachment as attached to the smartphone, shown in FIG. 8.

[0047] FIG. 10 is a graph showing the axial length of the model eye, as simulated by moving the piston and as measured by Zeiss OIL Master 300.

[0048] FIG. 11 is a graph showing the Bland-Altmann plot of the axial length of the model eye, as simulated by moving the piston and as measured by Zeiss OIL Master 300.

[0049] FIG. 12 is a graph showing the refractive error of the model eye, as simulated by moving the piston and as measured by Shin Nippon K900.

[0050] FIG. 13 is a graph showing the Bland- Altmann plot of the refractive error of the model eye, as simulated by moving the piston and as measured by Shin Nippon K900.

[0051] FIG. 14 is a plot showing Support Vector Machine performance against number of features in refractive error measurement data analysis.

[0052] FIG. 15 is a graph showing Support Vector Machine performance against linear, quadratic, and cubic functions in refractive error measurement data analysis.

[0053] FIG. 16 is a plot showing Support V ector Machine performance against Gaussian Kernel Scale in refractive error measurement data analysis.

[0054] FIG. 17 is a plot showing Support Vector Machine performance against number of features in axial length measurement data analysis.

[0055] FIG. 18 is a graph showing Support Vector Machine performance against linear, quadratic, and cubic functions in axial length measurement data analysis.

[0056] FIG. 19 is a plot showing Support V ector Machine performance against Gaussian Kernel Scale in axial length measurement data analysis.DETAILED DESCRIPTION

[0057] For clarity of disclosure, and not by way of limitation, the detailed description of the invention is divided into the subsections that follow.

[0058] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of ordinary skill in the art to which this invention belongs. All patents, applications, published applications and other publicationsreferred to herein are incorporated by reference in their entirety. If a definition set forth in this section is contrary to or otherwise inconsistent with a definition set forth in the patents, applications, published applications and other publications that are herein incorporated by reference, the definition set forth in this section prevails over the definition that is incorporated herein by reference.

[0059] As used herein, “a” or “an” means “at least one" or “one or more.”

[0060] As used herein, the term “and / or” may mean “and.” it may mean “or,” it may mean “exclusive-or,” it may mean “one,” it may mean “some, but not all,” it may mean “neither,” and / or it may mean “both.”

[0061] In embodiments, the present invention discloses a mechanical eye model to mimic a human eye, such that pictures taken of this eye model are similar to pictures taken of a human eye. The eye model comprises mechanical parts mimicking a cornea, a pupil, a lens, and a movable retina in a fluid filled chamber. The eye model also comprises a motorized linear stage with other parts to move the movable retina.

[0062] FIG. 1 depicts a perspective view of the model eye 20. Model eye 20 comprises an enclosure 3, which encloses an anterior chamber 21 with artificial parts equivalent to a cornea, a pupil, and a lens in a human eye and are arranged in the same order as a cornea, a pupil, and a lens in a human eye. The anterior chamber 21 thus is equivalent to the front part of a human eye. The artificial cornea and the artificial lens are made of plastic capable of receiving light and conducting light therethrough in a similar manner with the front of human eyes, such as acrylic and acrylate polymers. The artificial pupil is an empty space through which lights enter the anterior chamber 21. At the top of enclosure 3 is atop plate 5. which is attached to the enclosure but is removable for cleaning of the chambers inside. The enclosure 3 is made of impervious material to keep fluid inside.

[0063] FIG. 2 depicts another perspective view of the model eye 20. Piston 9 is connected to sliding part 11 via piston connector 13. which is connected to plate adapter 15, and plate adapter 15 connects to sliding part 11. As motorized linear stage 12 moves along stage base 10 on a railway and pushes piston 9 back and forth, thereby moving movable retina 16 along fluid filled chamber 25. Motorized linear stage 12 is controlled by stage controller 17.

[0064] FIG. 3 depicts an exploded view of the eye model 20. The front part of the eye model 20 mimics a human eye with a pupil, a cornea, and a lens composite 2 in the front of ananterior chamber containing fluid, and a retina 16 in the back of the anterior chamber. Anterior chamber 21 refers to an empty space at the front of the model eye enclosure 3. The pupil, cornea, and lens composite 2 attaches to model eye enclosure 3 at anterior chamber 21 via cornea retaining ring 1 with an O-ring 7 embedded between cornea retaining ring 1 and O-ring 7 for sealing. A front plate 4 fits on the rim of the pupil, a cornea, and a lens composite 2 and attaches to model eye enclosure 3 with screws. Other attachment mechanisms are contemplated.

[0065] Within model eye enclosure 3 are a fluid filled chamber and a fluid overflow chamber 23, which are depicted in FIG. 4. The top of model eye enclosure 3 has a top plate 5, which is attached to model eye enclosure 3. An O-ring 6 is placed between the top plate 5 and the model eye enclosure 3 to seal when the top plate 5 is attached to the model eye enclosure 3. Underneath the top plate 5 is the fluid overflow chamber, and the top plate 5 is provided such that it can be removed for cleaning the fluid overflow chamber. The model eye enclosure 3 rests on a base 8, which rests on the general platform 18.

[0066] Behind the anterior chamber 21 is a fluid filled chamber with a moveable retina 16 at the back of the fluid filled chamber, which is filled with fluid to simulate the inside of an eyeball. The moveable retina 16 is in generally a cylindrical shape with one side having a dome like depression mimicking the shape of a retina. The artificial retina 16 is made of plastic, such as polyurethane, and has a flesh color to mimic the color of a human retina. The back of the artificial retina 16 is configured to be attached to a piston 9, such that the artificial retina 16 is moveable by movement of the piston 9. The piston 9 is connected to a connector plate 13. which is connected to a plate adapter 15 via a push plate 14. Plate adapter 15 attaches to sliding part 11, which slides on arailing and moves linearly alongthe railing. The sliding part 11 is connected to a motorized linear stage 12, which is controlled by a stage controller 17.

[0067] All parts of the mechanical eye model 20 rest on a general platform 18, which provides space and structural stability for the eye model 20 parts. The general platform 18 shown in the drawings herein is of substantial rectangular shape and comprises a flat surface resting on four legs 19. The general platform 18 connects the eye model 20 parts into one physical unit that can be moved around easily, thereby allowing use of the eye model 20 at different locations, in different lighting conditions, and by different personnel.

[0068] FIG. 4 depicts a cross-sectional view of the model eye 20. The fluid filled chamber 25 serves the function of the eyeball in this eye model 20. Inside the fluid filled chamber 25 is fluid, such as purified demineralized water, to mimic the optical condition inside a humaneyeball. The fluid filled chamber 25 is dimensioned to track the dimension of a human eye, with the operating length of the fluid filled chamber 25 changing with movement of an artificial retina 16, which is described below.

[0069] An artificial retina 16 is located at the back of the fluid filled chamber 25 in a similar fashion to a natural retina is located at the back of an eyeball. The artificial retina 16 is of half dome shape to mimic the shape of a human retina. The artificial retina 16 is made of materials that are rigid and coated to reflect light in similar manner to a human retina. In an embodiment, the artificial retina 16 is made of anodized aluminum and coated with a mixture of paint with light reflection properties similar to a human retina. The artificial retina 16 is dimensioned to mimic a human eye. The artificial retina 16 fits the back of the fluid filled chamber 25.

[0070] To move the artificial retina 16. a substantially cylindrical channel 30 is provided. The channel 30 starts at the end of the fluid filled chamber 25 and extends backward, creating a space in which the artificial retina 16 moves. The channel 30 is dimensioned such that it has the same diameter and perimeter as the fluid filled chamber 25. The artificial retina 16 in one state is attached to the end of the fluid filled chamber 25, which is also the attachment point on the channel 30 and the fluid filled chamber 25. The channel 30 is of the same diameter as the fluid filled chamber 25 but may have a different length than the fluid filled chamber 25.

[0071] A piston 9 is inserted into this cylindrical channel 30 in a similar fashion to a piston, and the piston 9 is movable along the channel 30. At one end of the piston 9 is the artificial retina 16. As the piston 9 moves along the channel 30, the artificial retina 16 moves along with it, simulating different axial lengths of eyes. A movable artificial retina 16 thus allows the eye model 20 to simulate eyes of different sizes and axial length. When pictures of the eye model 20 are taken with the artificial retina 16 at different locations within the channel 30, different axial length eyes are simulated, thereby increasing the data set that can be obtained from this eye model 20. The piston 9 is preferably made of similar material to the artificial arena. In an embodiment, the piston 9 is made of anodized aluminum, and the artificial retina 16 is also made of anodized aluminum.

[0072] As the piston 9 moves along the cylindrical channel 30, two set of rings are present within the cylindrical channel 30 to seal the cylindrical channel 30. such that fluid does not move out of the cylindrical channel as the piston 9 moves. These rings act like fluid retainers and prevent spillage into other parts of the eye model 20.

[0073] The back of the piston 9, which is the side of the piston 9 not attached to the artificial retina 16. is attached to a connector 13, which attaches to a plate adapter 15 via a push plate 14. The plate adapter 15 then attaches to a sliding part 11 sitting on a railway 12 at one end. At the other end of railway 12, a motorized stage 31 is provided. The motorized stage 31 can move along the railway 12. and upon making contact with the sliding part 11, can push the piston 9 forward. Upon activation of the motorized stage 31. the motorized stage 31 pushes the sliding part 11, causing it to move on the railway 12, thereby pushing the piston 9 forward, which in turn moves the artificial retina 16 along the channel 30. When the motorized stage 31 moves backward, it releases the sliding part 11 to move backward, thereby moving the artificial retina 16 away from the anterior chamber 21. The motorized stage 31, the sliding part 11 and the railway 12 are constructed to drive the piston 9 back and forth along the channel 30, in other words, in a linear movement direction.

[0074] The motorized stage 31 is controlled by a stage controller 17 located next to the motorized stage 31. The stage controller 17 is operationally connected to the motorized stage 31 and can control the range of movement and speed of movement of the piston 9 and in turn, of the artificial retina 16. The stage controller 17 is operationally connected to the motorized stage 31, and the motorized stage 31 and can be controlled manually or by automatic control using a computer programming product developed for the purpose. A computer programming product may be used to control the motorized stage 31 through the stage controller 17.

[0075] As the artificial retina 16 moves back and forth within the channel 30, fluid in the fluid filled channel 30 also moves to ensure a sufficient quantity of fluid present in the channel 30 to mimic an eye, a fluid overflow chamber 23 is provided. The fluid overflow chamber 106 is located at the top of the fluid filled chamber 25. An opening connecting the fluid overflow chamber 23 with the fluid filled chamber 25. When the artificial retina 16 is drawn away from the anterior chamber 21. more fluid from the fluid overflow chamber 23 flows down to fill the channel 30, such that the eye model 20 as a whole mimics an eye. When the artificial retina 16 is pushed towards the anterior chamber 31, fluid is pushed into the fluid overflow chamber 23. The fluid overflow chamber 23 is dimensioned to contain enough fluid to allow adequate fluid to fill the channel 30. Some headspace in the fluid overflow chamber 23 is also provided, such that there is empty space within the fluid overflow chamber 23 to account for any expansion and prevent over pressurized fluid. Therefore, the fluid overflow chamber 23 has a fluid storage capacity larger than the fluid storage capacity of the channel 30.

[0076] A fluid retainer 32 is provided between the fluid filled chamber 25 and the anterior chamber 21 to prevent fluid from spilling into the anterior chamber 21. The fluid retainer 32 is made of flexible and impervious plastic. In an embodiment, the fluid retainer 32 is made of nitril rubber.

[0077] FIG. 5 depicts a side view of the model eye 20. The eye portion of the eye model 20 rests on a platform 8 such that the piston 9 can move in the channel 30 along the length of the channel 30. The platform 8 thus raises the eye portion of the eye model 20 to the same height as the sliding part 11. The platform 8 also lines the eye portion of the eye model 20 with the railway 12 on the motorized linear stage 31 in one straight line.

[0078] FIG. 6 depicts a model eye 20 according to embodiments herein with a camera 26 and an optical assembly 27 to direct light for photo capturing. Pictures can be captured by any available electronic cameras. As shown in FIG. 6, the camera is embedded in a smartphone and the smartphone rests on a camera platform 29. A flashlight can also be provided with the camera. In smartphones, flashlights for picture capturing are typically provided with the smartphones.

[0079] In particular, for pictures to be used as training data for a computer programming product to be used on a smartphone, pictures taken by the same type of smartphone can be used. Pictures of the eye model 20 simulating various retina positions can be taken and data from the pictures can be extracted for training of a computer programming product. For each picture taken and stored in red green blue color scheme, data on the pixels and colors on the pixel can be extracted and correlated with the position of the artificial retina, thereby establishing statistical relationship between the data and the axial length of the eye model 20. Such data can be used in training, such that the computer programming product can deduce characteristics of a human eye using a picture stored in red green blue color scheme.

[0080] The optical assembly comprises a polarizer and mirror situated in front of a flashlight, a beam splitter, a polarizer and a lens situated between the camera and the object to the photographed, in this case, the front part of the eye model. The optical assembly filters light from the flashlight before sending it to the artificial pupil of eye model, and filters light from the eye model coming back to the camera. As depicted in FIG. 6, the optical assembly 27 is situated in front of the smartphone such that functional parts cover the flashlight and the camera on the smartphone, as appropriate.

[0081] FIG. 7 depicts a model eye 20 according to embodiments herein with an optic block 28 functioning like eyeglasses. Optic block 28 can be equipped with glasses equivalent to corrective lens worn by humans with various degrees of myopia. When positioned in front of the anterior chamber, the optic block 28 works like eyeglasses in front of a human eye. The optic block 28 can also be a variable power optical system, such as a phoropter or a fluid optical system that changes power. The optic block 28 together with the eye model 20 simulate a human eye while wearing eyeglasses. Pictures of the eye model 20 can be captured from the front of the variable optic block 28, and as such the pictures obtained are through the variable optic block 28. Alternatively, pictures of the eye model 20 may also be captured in front of the anterior chamber 21 without a variable optic block 28.

[0082] In embodiments, the model eye utilized a linear stage motor (Thorlabs MTS-M- Z8) with an incremental repeatable movement of 0.8 pm for movement of the piston. The motor has a controller with USB interface, allowing for the motor to be controlled from a personal computer (PC) and is closed loop. The motor interacts with the PC via Thorlabs APT software. The system was controlled by a Matlab program which connected to the APT software via Microsoft’s ActiveX. The software allows for the axial length to be set directly or to be specified as a refractive error in diopters, this is converted to an axial length via Equation 1, as below.

[0083] To calibrate the model eye chamber was loosened, allowing the chamber to move, and the motor was homed and set to 0 mm position. Vernier calipers are used to determine the overall length of the moveable retina assembly. A slip gauge was then used to set the position of the moveable retina and the model eye casing. This allows for determination of the exact position of the retina in relation the comeal apex

[0084] FIG. 8 depicts an optical assembly attachment 27 as attached to a smartphone 26 having a built in camera and a built in flashlight. This smartphone 26 with an optical assembly attachment 27 set up also depicted in FIG. 6 & 7, as resting on optical block platform 29.

[0085] FIG. 9 depicts a cross-sectional view of FIG. 8. A first linear polarizer 101 is situated within the body of the optical assembly attachment 27 such that it is placed directly above the flashlight on a smartphone when the optical assembly attachment 27 is attached to the smartphone 26. Above the first linear polarizer 101 is an aperture 110 for light to pass through before hitting a flash mirror 102, the flash mirror 102 is located above the first linear polarizer 101 at an angle above the first linear polarizer 101. A 50 / 50 beam splitter 105 is situated opposite to the flash mirror 102 and at the same angle with the flash mirror 102, such that the 50 / 50 beamspliter 105 and the flash mirror 102 are parallel to each other. Below the 50 / 50 beam spliter 105 and towards the smartphone, a second linear polarizer 103 is located such that it is placed above the converging lens 104 of the smartphone camera. A chamber with a light trap 106 is located to the side of the 50 / 50 beam spliter, opposite from the flash mirror. Components of the body is enclosed within a housing.

[0086] In an embodiment, the model eye is based on an OEMI-7 model eye from Ocular Instruments, and consists of a cornea and a lens, both made from acrylic. Acrylic has a refractive index of 1.49 (at 632.8 nm) which is significantly higher than a human eye. Various models have been created to model the refractive index of the human eye; one such model is the Gullstrand model eye. The cry stalline lens is given two (2) refractive indexes, as it is understood that the refractive index increases towards the center of the lens. These changes in refractive indexes between the model eye and human eye result in different focal lengths and hence different axial lengths for the emmetropic eye, with the human eye on average being 23.5 mm and the model eye being 25.8 mm.

[0087] To determine the refractive error of the system, the axial length must be converted. There is no standard method for converting between the two, this required a mathematical model to be developed which showed the relationship between axial length and refractive error. The mathematical model simulated the OEMI-7 model eye and the change in refractive index with wavelength, with the refractive error on the eye being induced by simulating a lens in front of the model eye in the same method as normal ocular corrections. The refractive error was altered by changing the power of the lens, which would change the focal length. This focal length can be used to determine the axial length (with the axial length resulting in the induced refractive error). The following relationship was determined.

[0088] Equation

[0089] Where:

[0090] D is the refractive error in diopters

[0091] x is the axial length in mm

[0092] Xois the axial length of the emmetropic model eye in mm (25.8 mm)

[0093] Therefore, every 1 mm is equivalent to 2.6392 diopters. It should be noted that due to differences between the 0EM1-7 model eye and human eye. that this only applies to the model eye and a different relationship would need to be determined for the human eye.Model Eye Verification Experiment

[0094] A model eye as described above was developed to facilitate rapid testing of ophthalmic instruments by changing the refractive error and axial length of the model eye. To verify the model eye optical performance, the retina was moved to different locations to simulate a change in axial length of the eye using the linear stage motor controlled by a software. Axial length at each location is then measured by Zeiss IOL Master 300. The retina on the model eye is moved along the axial length to simulate axial length of 28.07 mm to 23.52 mm at 0.19 mm intervals, which is equivalent to -6 to +6 D at 0.5 D intervals, with the IOL Master 300 taking 5 measurements at each location. In particular, the model eye was moved to the positions, a singular measurement from the IOL Master 300 was recorded, the model eye was then moved to next position and repeated until all positions were recorded. This sequence was repeated 5 times, with an average of the results of all positions being determined. At each point, the axial length set by the software and the axial length measured by Zeiss IOL Master 300 are collected. The data was subject to a paired T-test Model Eye / IOL Master 300 and a Bland- Altman.

[0095] Data analysis was conducted in GraphPad Prism 10 and Microsoft Excel. The data was tested for normality with the Kolmogorov-Smirnov test. Correlation was tested with R- squared, a paired t-test was used to verify that there was a significant difference in the means, and a Bland-Altmann was used to verify agreement.

[0096] Results

[0097] Normal its': A one sample Kolmogorov-Smirnov test was performed, with a D value of 24 and a P-value greater than 0.05, meaning the null hypothesis was not rejected and the data is normally distributed.

[0098] Correlation: The coefficient of determination (R squared) at a D value of 24 was calculated at 0.9998. Therefore, the data is highly correlated and is shown by FIG. 10.

[0099] T-test: A paired T-test was performed on the data. Model Eye (M=25.8, SD =1.39) IOL Master 300 (M=25.98, SD=1.41) which had a t(24)=31.85, p=<0.0001, showing there is a significant difference, as such the null hypothesis can be rejected. The t-test showsthere is a significant difference in the mean values between the data, therefore the data is not random and both methods are statistically measuring the same variable at a confidence level of 95%. The t-test indicates a significant difference in the mean values between the data, suggesting that the data is not random.

[0100] Agreement and bias: Agreement was verified by a Bland-Altmann. The Bland- Altmann shows the low axial lengths are being over-estimated and high axial lengths are being under-estimated. Most of the data is within ±1.96 std which gives a confidence level of 95%, thus showing good agreement. Bland-Altman plot is provided in FIG. 11.

[0101] Discussion

[0102] The results show that there is a good correlation and agreement between the axial length measurements from the IOL Master 300 and the known axial lengths produced by the model eyes. Thus, the model eye is performing similarly to a real eye and is valid for accessing the performance of ophthalmic instruments that measure axial length. The model exhibited some bias at low and high axial lengths, over-estimating and under-estimating respectively. However, it is predictable, rather than random variations, thus can be calibrated for. The use of the model eye as a datum and source of data for developing axial length measurement devices will allow performance to be tracked back to industry standard measurement devices.Model Eye Auto-Refractor Verification Experiment

[0103] The same model eye as above was used for rapid testing of ophthalmic instruments by changing the refractive error and axial length of the model eye to act as an analogue for a human eye. The model also has the facility for optics to be placed in front of the anterior eye assembly.

[0104] The refractive error of the eye is induced by changing the axial length of the eye. However, to determine the refractive error of the system, the axial length must be converted. There is no standard method for converting between the two, this required a mathematical model to be developed which showed the relationship between axial length and refractive error. Since this model uses OEMI-7 model eye anterior, the relationship between refractive error and axial length is determined by Equation 1, as above.

[0105] To verify the physical model eye, it was tested with a Shin Nippon K900 autorefractor. The Shin Nippon K900 autorefractor relies on the measurement of a reflectedinfrared ring (expanding cone of light) based on the Scheiner principle. The size of the reflected ring can be directly related to the refracted error present in the system and the eccentricity of the ring related to astigmatism.

[0106] Testing was conducted in the range of -15D to +8 D at 1.0 D intervals. The model eye was moved to the positions, a singular measurement from the Shin Nippon K900 was recorded, the model eye was then moved to next position and repeated until all positions were recorded. This sequence was repeated 3 times, with an average of the results of all positions being determined.

[0107] Data analysis was conducted in GraphPad Prism 10 and Microsoft Excel. The data was tested for normality with the Kolmogorov-Smirnov test. Correlation was tested with R- squared, a paired t-test was used to verify that there was a significant difference in the means and a Bland-Altmann was used to verify agreement.

[0108] Results

[0109] Normality': A one sample Kolmogorov-Smirnov test was performed, with a D value of 24 and a P-value greater than 0.05, meaning the null hypothesis was not rejected and the data is normally distributed.

[0110] Correlation: The coefficient of determination (R squared) at a D value of 24 was calculated at 0.9985. Therefore, the data is highly correlated and is shown by FIG. 12.

[0111] T-test: The paired T test result for myopia (negative values, <0.0D) data was Model Eye (M=-7.5, SD =4.76) K900 (M=-7.83, SD=5.02) which had at(15)=4.669, p=<0.0001. The paired T test result for hyperopia (positive values, >0.0D) data was Model Eye (M=4, SD =2.74) K900 (M=4.57, SD=3.37) which had a t(8)=2.574, p=<0.0001. There is a significant difference both the hyperopia and myopia data, as such the null hypothesis can be rejected. The t-test shows there is a significant difference in the mean values between the data, therefore the data is not random and both methods are statistically measuring the same variable at a confidence level of 95%. The t-test indicates a significant difference in the mean values between the data, suggesting that the data is not random.

[0112] Agreement and Bias: Agreement was verified by a Bland- Altmann. The Bland- Altmann shows negative powers are being over-estimated and higher lengths are being underestimated. The data is within ±1.96 std which gives a confidence level of 95%, thus showing good agreement. The Bland-Altman plot is shown in FIG. 13.

[0113] Discussion

[0114] The results show that there is a good correlation and agreement between the refractive error measured by the K.900 Autorefractor and the known refractive errors produced by the model eyes. Thus, the model eye is performing similarly to a real eye and is valid for accessing the performance of ophthalmic instruments that measure refractive error.

[0115] The model exhibited some bias at low and high refractive errors, over-estimating and under-estimating respectively. However, it is predictable, rather than random variations, thus can be calibrated for. The use of the model eye as a datum and sources of data for developing refractive error measurement devices will allow performance to be tracked back to industry standard measurement devices and techniques.Model Eye Over-refraction Verification Experiment

[0116] The same model eye as above was used for determination of over-refraction induced refractive error from color imaging. The refractive error in the system was induced by manually changing prescriptions glasses in front of the model eye. The image capturing was software controlled from a computer. Testing was conducted at a prescription range of -3 to +3D at 0.5D intervals, with 15 images captured for each prescription to form a set. There was a total of 15 sets, with a dataset size of 3900.

[0117] The capturing device was an iPhone 14 pro, using the telephoto camera with a mechanical attachment. The phone flashlight was used to increase the brightness of the pupil and generate a bright pupil response. The optical assembly attachment (detailed in FIGS. 8 & 9) allowed for the telephoto camera to focus on 120mm, providing a high number of pixels covering the pupil of the model eye amount 360,000. It also ensured the torch light was co-axial with the camera, this was required due to the close distance to the object being captured to ensure a fully lit pupil. The attachment consists of 10 D (f= 100mm) condensing lens, a cold front surface mirror, a 50 / 50 beam splitter, 2 polarizers (for iPhone 14 pro telephoto camera and iPhone 14 pro flashlight) and an aperture for the flashlight. The attachment is mounted to an iPhone 14 pro case through mechanical fastenings.

[0118] The refraction of the system was adjusted manually through changing the prescription of the glasses in front of the model eye. This set up is shown in FIG. 7. Testing was conducted in the range of -3 to +3 D at 0.5D intervals. The capture process consisted of the flash being turned on and the camera capturing 3 images, the flash was then turned off. This wasrepeated 5 times for a total of 15 images, with the prescription glasses being changed after. This was completed for each pair of glasses until all have been captured, which was a complete set of data. A total of 20 sets were performed and a total image number of 3900.

[0119] The captured images went through a processing pipeline consisting of: locating the pupil; cropping the image to the pupil size; masking the pupil so all pixels outside the pupil were set to 0; separating RGB channels from the raw image (cameras have a Bayer pattern, where each pixel in an RGB camera only measures red. green or blue light) and creating a new image for each channel; extracting features from the RGB channels.

[0120] The extracted features consisted of standard statistical properties such as mean, median, geomean and standard deviation. Further features were generated by comparing these properties between channels, such as ratio of red and blue mean and the difference between red and blue mean. This process was repeated for all the images captured and stored in a table.

[0121] Initial attempts at modelling the data were performed with Polynomial Regression Models, whereby a single feature was selected from all the data e.g. ratio of red to blue mean, this was compared against the recorded axial length, a Polynomial Regression Model was then generated to describe the data. However, this failed to provide sufficient accuracy, as such Support Vector Machines (SVM) were used. SVMs are supervised classification and regression models were designed for binary classifications but could be expanded for multi-class and regression applications. SVM is a Kemelized algorithm, which clusters a features space based on named labels with maximum distance between the clusters’ borders.

[0122] The functions that were implemented and evaluated within this study are Linear, 2ndOrder Polynomial (Quadratic). 3rdOrder Polynomial (Cubic) and Gaussian Kernel functions. Twenty -four arbitrary Kernel scales were selected and evaluated in the cross-validation process (0.005, 0.01, 0.015, 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 1, 1.4, 2, 3, 4, 5, 5.7).

[0123] A total of 45 features were extracted from the raw images, to speed up processing time it was important to minimize the number of features. The features were selected using minimal-redundancy-maximal-relevance (MRMR) technique. This technique finds the most optimum subset of features that characterize the recorded axial length. Using MRMR Shannon’s Entropy, features were identified that are minimally redundant (mutually exclusive) but highly relevant to the classification clusters (mutually inclusive, specifically axial length clusters). These features were then utilized in the SVM.

[0124] In this study, the accuracy of the Support Vector Machine (SVM) was evaluated using both cross-validation accuracy and the Fl score. The cross-validation accuracy ensured that the model's performance was consistent across different subsets of the data, while the Fl score provided a nuanced measure of the model's precision and recall balance. By employing these metrics, the study ensured a comprehensive evaluation of the model's classification capabilities.

[0125] The Fl score is a crucial metric for evaluating classification models, particularly in cases where the dataset is imbalanced. It is the harmonic mean of precision and recall, providing a balanced measure that considers both false positives and false negatives. Precision represents the proportion of true positive predictions out of all positive predictions made by the model, while recall measures the proportion of true positive predictions out of all actual positives in the dataset. The Fl score is beneficial because it balances these two aspects, offering a single metric that ensures both high precision and high recall.

[0126] Cross-validation accuracy is used to assess the performance of a model in a more robust manner. This technique involves splitting the dataset into 'k' folds, training the model on 'k-T folds, and testing it on the remaining fold. This process is repeated 'k' times, with each fold serving as the test set once. The average accuracy from these iterations is the cross-validation accuracy, providing a reliable estimate of the model's generalizability and performance on unseen data.

[0127] Results

[0128] Number of Features: The cross validation and Fl score of the SVM model improved with the number of features as shown by FIG. 14. with it levelling off after 5 features.

[0129] SVM Function Comparison: The cross validation and F 1 score of the SVM model increased with higher order functions as shown by FIG. 15, although there was less than 2% between the linear, quadratic and cubic function. The best performance with gaussian filter was best achieved at a Kernel scale of 3 with 92% performance for both Fl Score and cross validation average, as shown in FIG. 16. However, the linear, quadratic and cubic functions both had better performance at over 98% performance for both Fl Score and cross validation average.

[0130] Discussion

[0131] The SVM model developed was able to achieve a performance of near 100% for both Fl Score and cross validation accuracy. This was achieved for both the quadratic and cubicfunctions, with the cubic function having marginally better performance. This demonstrates that a machine learning model can predict effectively refractive error induced through incorrect prescription glasses.Model Eye Axial Length Verification Experiment

[0132] The same model eye as above was used for determining the axial length of the model eye from color imaging. This was repeated 7 times, with a total dataset size of 3840. A number Support Vector Machine (SVM) model was implemented with different functions. The model with the best performance was the cubic function, with cross validation and Fl score of 99.38% and 100% respectively. This shows that the model is highly accurate at determining the correct axial length from an image of the model eye.

[0133] The capturing device was an iPhone 14 pro, using the telephoto camera with a mechanical attachment. The phone flashlight was used to increase the brightness of the pupil and generate a bright pupil response.

[0134] The optical assembly attachment (shown in FIGS. 8 & 9) allowed for the telephoto camera to focus on 120mm, providing a high number of pixels covering the pupil of the model eye amount 360,000. It also ensured the torch light was co-axial with the camera, this was required due to the close distance to the object being captured to ensure a fully lit pupil. The attachment consists of 10 D (f= 100mm) condensing lens, a cold front surface mirror, a 50 / 50 beam splitter, 2 polarizers (for iPhone 14 pro telephoto camera and iPhone 14 pro flashlight) and an aperture for the flashlight. The attachment is mounted to an iPhone 14 pro case through mechanical fastenings.

[0135] The iPhone 14 pro is mounted on a base in front of the model eye. this ensured that the iPhone 14 pro was stable and remained in the location throughout the testing. This set up is shown in FIG. 6. The iPhone 14 pro was controlled from a computer, which communicated to an app installed on the iPhone through Wi-Fi. This allowed for the camera settings to be set and trigger the capture. It was not possible to use the in-built flash functionality of the iPhone, due to it triggering auto-focus and auto-exposure of the camera, it is not possible to disable this. Therefore, to use the flashlight, it had to be manually turned on and off, this requires precise timing as the flashlight needs to be fully lit before the image has begun capturing. The process typically involved turning on the flashlight, capturing multiple images (3 images as standard) and then turning off the flashlight. The captured images were then sent to the computer over WiFi.

[0136] Analysis

[0137] The system simulated and captured images in an axial length range of 24.663 mm to 26.937 mm at 0.038 mm intervals. Although the model eye can do greater ranges, this was chosen to reduce data size. The data was recorded in sets, with each set consisting of 3 images at each axial length location. There was a random pause between each axial length position of between 10 to 60 seconds. This was due to the phone increasing in temperature with small pause times, which would affect the intensity of the pixels in captured images. Therefore, by having a random time there is a diverse dataset that can be fed into the model. Once a set was complete, a new set would be commenced, with there being a total of 7 sets which resulted in a total data size of 3840 images.

[0138] The captured images went through a processing pipeline which consisted of locating the pupil; cropping the image to the pupil size; masking the pupil so all pixels outside the pupil were set to 0; separating RGB channels from the raw image (cameras have a bayer pattern, where each pixel in an RGB camera only measures red, green or blue light), and create new image for each channel; extracting features from the RGB channels.

[0139] The extracted features consisted of standard statistical properties such as mean, median, geomean and standard deviation. Further features were generated by comparing these properties between channels, such as ratio of red and blue mean and the difference between red and blue mean. This process was repeated for all the images captured and stored in a table.

[0140] Initial attempts at modelling the data were performed with Polynomial Regression Models, whereby a single feature was selected from all the data e.g. ratio of red to blue mean, this was compared against the recorded axial length, a Polynomial Regression Model was then generated to describe the data.

[0141] However, this failed to provide sufficient accuracy, as such Support Vector Machines (SVM) were used. SVMs are supervised classification and regression models were designed for binary classifications but could be expanded for multi-class and regression applications. SVM is a Kemehzed algonthm. which clusters a features space based on named labels with maximum distance between the clusters’ borders.

[0142] The functions that were implemented and evaluated within this study are Linear, 2ndOrder Polynomial (Quadratic), 3rdOrder Polynomial (Cubic) and Gaussian Kernel functions. Twenty-four arbitrary Kernel scales were selected and evaluated in the cross-validation process(0.005, 0.01, 0.015, 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 1. 1.4, 2, 3, 4, 5. 5.7).

[0143] A total of 45 features were extracted from the raw images, to speed up processing time it was important to minimize the number of features. The features were selected using minimal-redundancy-maximal-relevance (MRMR) technique. This technique finds the most optimum subset of features that characterize the recorded axial length. Using MRMR Shannon's Entropy, features were identified that are minimally redundant (mutually exclusive) but highly relevant to the classification clusters (mutually inclusive, specifically axial length clusters). These features were then utilized in the SVM.

[0144] In this study, the accuracy of the Support Vector Machine (SVM) was evaluated using both cross-validation accuracy and the Fl score. The cross-validation accuracy ensured that the model's performance was consistent across different subsets of the data, while the Fl score provided a nuanced measure of the model's precision and recall balance. By employing these metrics, the study ensured a comprehensive evaluation of the model's classification capabilities.

[0145] The Fl score is a crucial metric for evaluating classification models, particularly in cases where the dataset is imbalanced. It is the harmonic mean of precision and recall, providing a balanced measure that considers both false positives and false negatives. Precision represents the proportion of true positive predictions out of all positive predictions made by the model, while recall measures the proportion of true positive predictions out of all actual positives in the dataset. The Fl score is beneficial because it balances these two aspects, offering a single metric that ensures both high precision and high recall.

[0146] Cross-validation accuracy is used to assess the performance of a model in a more robust manner. This technique involves splitting the dataset into 'k' folds, training the model on 'k-1 ' folds, and testing it on the remaining fold. This process is repeated 'k' times, with each fold serving as the test set once. The average accuracy from these iterations is the cross-validation accuracy, providing a reliable estimate of the model's generalizability and performance on unseen data.

[0147] Results

[0148] Number of Features: The cross validation and Fl score of the SVM model improved with the number of features as shown by FIG. 17, with it levelling off after 10 features.

[0149] SVM Function Comparison: The cross validation and F 1 score of the SVM model increased with higher order functions as shown by FIG. 18. although the difference between quadratic and cubic was less than 0.5%. The performance of the Gaussian function improved with Kernel scale up till 3 with it falling after, as shown in FIG. 19.

[0150] Discussion

[0151] Initial attempts at creating a model using Polynomial Regression Models was unsuccessful. The Polynomial Regression Models were generated based a singular feature, with no feature producing a model with sufficient accuracy. This is due to the features having a relatively small change over the entire data set, for example the red mean has a variable of 389, which is only 9.5% of the range for a 12bit number (iPhone Camera is 12bit RGB). Therefore, any small changes in features can result in incorrect classification. However, what was noted is that multiple features would change at the same time, which implies they could be linked. As such, SVM was investigated as it allowed multiple features to be considered as part of the model.

[0152] The SVM model that performed the best was the cubic function which has a cross validation and Fl score of 99.38% and 100% respectively. This shows that the model is highly accurate at determining the correct axial lengthAssessments from the Model Eye Experiments

[0153] The Experiments above show the model eye developed for data collection for use in training the Al model is effective. The model eye can be used to simulate a human eye, from which auto-refraction, over refraction, and axial length can be measured by photo capturing and color imaging. Images and data collected from photo capturing this model eye accurately reflect the same data from human eyes, and thus can be used to train an Al model to recognize pixel patterns for the purpose of measuring refractive state of a human eye.

[0154] In a first embodiment, a mechanical eye model is provided, comprising: an anterior chamber comprising an artificial cornea, an artificial pupil, and an artificial lens arranged in the same order as in a human eye; a fluid filled chamber in substantially cylindrical shape attached to one end of the anterior chamber behind the artificial lens; a channel in substantially cylindrical shape attached to the fluid filled chamber; an artificial retina attached to a piston, the piston having a length longer than the channel and is configured to move along the channel; anda fluid overflow chamber connected to the fluid filled chamber by a pipe capable of conducting fluid, the fluid overflow chamber configured to store fluid, wherein the artificial retina is configured in substantially dome shape and is dimensioned to cap the fluid filled chamber on a side opposite the anterior chamber, wherein the channel and the fluid filled chamber are dimensioned to have the same diameter. wherein the fluid overflow chamber has a fluid storage capacity larger than the fluid storage capacity of the channel.

[0155] In a second embodiment, the first embodiment includes the artificial pupil is an empty space through which lights enter the anterior chamber.

[0156] In a third embodiment, each of the first and second embodiment includes the artificial cornea and the artificial lens are made of plastic capable of receiving light and conducting light therethrough.

[0157] In a fourth embodiment, each of the first to second embodiment includes the artificial cornea and the artificial lens are made of acrylic and acrylate polymers.

[0158] In a fifth embodiment, each of the first to second embodiment includes the artificial retina comprises a cylindrical shape having a dome shape depression at one end and is configured to attach to the piston at the other end.

[0159] In a sixth embodiment, each of the first to second embodiment includes the artificial retina is of flesh color.

[0160] In a seventh embodiment, each of the first to second embodiment includes the artificial retina is made of poly urethane.

[0161] In an eighth embodiment, each of the first to second embodiment includes the anterior chamber, the fluid filled chamber, the channel, and the fluid overflow chamber are enclosed in an enclosure.

[0162] In the ninth embodiment, each of the first to second embodiment includes the fluid overflow chamber comprises atop plate removably attached to the enclosure.

[0163] In the tenth embodiment, each of the first to second embodiment further comprises a fluid retainer between the fluid filled chamber and the anterior chamber to prevent fluid from entering the anterior chamber.

[0164] In the eleventh embodiment, each of the first to second embodiment further comprises a sliding part attached to the piston, the sliding part attached to a railway and capable of moving on the railway.

[0165] In the twelfth embodiment, the eleventh embodiment includes the sliding part is attached to the piston via a piston connector and a plate adapter.

[0166] In the thirteenth embodiment, the twelfth embodiment includes the piston connector and the plate adapter are connected via a push plate.

[0167] In the fourteenth embodiment, the eleventh embodiment further comprises a motorized stage configured to move on the railway.

[0168] In the fifteenth embodiment, the fourteenth embodiment includes the motorized stage is configured to push the sliding part to move on the railway.

[0169] In the sixteenth embodiment, each of the fourteenth and the fifteenth embodiment includes the motorized stage is capable of an incremental repeatable movement of 0.8 pm.

[0170] In the seventeenth embodiment, each of the twelfth to the fifteenth embodiment further comprises a stage base, wherein the railway rests on the stage base.

[0171] In the eighteenth embodiment, the seventeenth embodiment further comprises a controller configured to control the motorized stage.

[0172] In the nineteenth embodiment, the eighteenth embodiment includes the controller is configured to control the motorized stage automatically.

[0173] In the twentieth embodiment, each of the eighteenth and nineteenth embodiment includes the controller is a personal computer.

[0174] In the twenty first embodiment, each of the eighteenth and nineteenth embodiment includes the motorized stage is configured to interact with the controller via an USB interface.

[0175] In the twenty second embodiment, each of the eighteenth and nineteenth embodiment further comprises a general platform for all parts to rest on.

[0176] In the twenty third embodiment, the twenty second embodiment further comprises legs on the general platform.

[0177] In the twenty fourth embodiment, each of the first, second, twelfth, thirteenth, fourteenth, fifteenth, eighteenth, nineteenth, and twenty third embodiment further comprises a variable optic block simulating a corrective eyeglass situated in front of the anterior chamber.

[0178] In the twenty fifth embodiment, a system to capture pictures of a model eye is provided, comprising: the model eye of the twenty' first embodiment; and a camera with picture capturing capabilities.

[0179] In the twenty sixth embodiment, the twenty fifth embodiment further comprises a flashlight for picture capturing.

[0180] In the twenty seventh embodiment, the twenty sixth embodiment includes the camera and the flashlight are provided as part of a smartphone.

[0181] In the twenty eighth embodiment, the twenty' sixth embodiment further comprises a platform to place the smartphone such that the camera can capture pictures of the artificial retina within the model eye.

[0182] In the twenty ninth embodiments, each of the twenty' fifth to twenty eighth embodiment further comprises an optical assembly situated in front of the camera and the flashlight to filter and reflect light.

[0183] In the thirtieth embodiments, the twenty ninth embodiment includes the optical assembly comprises a polarizer and a mirror to deflect light from the flashlight to a beam splitter to split light before reaching an object to be photographed, and a polarizer and lens to filter light coming from the obj ect to be photographed before reaching the camera.

[0184] In the thirty first embodiment, a system to capture pictures of a model eye is provided, comprising: the model eye of the twenty fourth embodiment; and a camera with picture capturing capabilities.

[0185] In the thirty second embodiment, the thirty first embodiment further comprises a flashlight for picture capturing.

[0186] In the thirty third embodiment, the thi rty first embodiment further comprises the camera and the flashlight are provided as part of a smartphone.

[0187] In the thirty fourth embodiment, the thirty first embodiment further comprises a platform to place the smartphone such that the camera can capture pictures of the artificial retina within the model eye.

[0188] In the thirty fifth embodiment, each of the thirty first to thirty’ fourth embodiment further comprises an optical assembly attachment situated in front of the camera and the flashlight to filter and reflect light.

[0189] In the thirty sixth embodiment, the thirty fifth embodiment includes the optical assembly comprises a polarizer and a mirror to deflect light from the flashlight to a beam splitter to split light before reaching an object to be photographed, and a polarizer and lens to filter light coming from the object to be photographed before reaching the camera.

[0190] In the thirty seventh embodiment, a method to capture pictures of a model eye for statistical analysis is provided, the method comprises: providing a system of the twenty sixth embodiment; using an interface on the controller and moving the piston at an increment and stopping the piston; taking a picture of the model eye using the camera; and saving the picture as digital data.

[0191] In the thirty eighth embodiment, the thirty^ seventh embodiment includes the flashlight is turned on before the picture is taken.

[0192] In the thirty ninth embodiment, a method to capture pictures of a model eye for statistical analysis is provided, the method comprises: providing a system of the thi rty second embodiment; using an interface on the controller and moving the piston at an increment and stopping the piston; taking a picture of the model eye using the camera; and saving the picture as digital data.

[0193] In the fortieth embodiment, the thirty' ninth embodiment includes the flashlight is turned on before the picture is taken.

[0194] In the forty first embodiment, a method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system of the thirty third embodiment;using an interface on the controller and moving the piston at an increment and stopping the piston; and taking a picture of the model eye using the camera

[0195] In a forty second embodiment, the forty first embodiment includes the flashlight is turned on before the picture is taken.

[0196] In a forty' third embodiment, a method to capture pictures of a model eye for statistical analysis is provided, the method comprises: providing a system of the thirty’ fifth embodiment; using an interface on the controller and moving the piston at an increment and stopping the piston; and taking a picture of the model eye using the camera.

[0197] In a forty7fourth embodiment, the forty third embodiment includes the flashlight is turned on before the picture is taken.

[0198] According to each of the embodiments described and contemplated herein, this mechanical eye model may further comprise a system for measurement of refractive state for operable use together to collect data and train the algorithm within the system. An exemplary system for measurement of refractive state is described in concurrently filed Patent Cooperation Treaty Application entitled “REFRACTIVE STATE DETERMINATIONS AND RELATED METHODS AND APPARATUS,” and assigned Attorney Docket No OCU1PCT, which is incorporated herein by reference in its entirety7.

[0199] Other features and advantages of the invention will be apparent from the following detailed description, and from the claims.

[0200] The above examples are included for illustrative purposes only and are not intended to limit the scope of the invention. Many variations to those described above are possible. Since modifications and variations to the examples described above will be apparent to those of skill in this art, it is intended that this invention be limited only by' the scope of the appended claims.

Claims

CLAIMSWe claim:

1. A mechanical eye model, comprising: an anterior chamber comprising an artificial cornea, an artificial pupil, and an artificial lens arranged in the same order as in a human eye; a fluid filled chamber in substantially cylindrical shape attached to one end of the anterior chamber behind the artificial lens; a channel in substantially cylindrical shape attached to the fluid filled chamber; an artificial retina attached to a piston, the piston having a length longer than the channel and is configured to move along the channel; and a fluid overflow chamber connected to the fluid filled chamber by a pipe capable of conducting fluid, the fluid overflow chamber configured to store fluid, wherein the artificial retina is configured in substantially dome shape and is dimensioned to cap the fluid filled chamber on a side opposite the anterior chamber, wherein the channel and the fluid filled chamber are dimensioned to have the same diameter, wherein the fluid overflow chamber has a fluid storage capacity larger than the fluid storage capacity of the channel.

2. The mechanical eye model of any of claim 1, wherein the artificial pupil is an empty space through which lights enter the anterior chamber.

3. The mechanical eye model of any of claims 1 to 2, wherein the artificial cornea and the artificial lens are made of plastic capable of receiving light and conducting light therethrough.

4. The mechanical eye model of any of claims 1 to 2, wherein the artificial cornea and the artificial lens are made of acrylic and acrylate polymers.

5. The mechanical eye model of any of claims 1 to 2, wherein the artificial retina comprises a cylindrical shape having a dome shape depression at one end and is configured to attach to the piston at the other end.

6. The mechanical eye model of any of claims 1 to 2, wherein the artificial retina is of flesh color.

7. The mechanical eye model of any of claims 1 to 2, wherein the artificial retina is made of polyurethane.

8. The mechanical eye model of any of claims 1 to 2, wherein the anterior chamber, the fluid filled chamber, the channel, and the fluid overflow chamber are enclosed in an enclosure.

9. The mechanical eye model of any of claims 1 to 2, wherein the fluid overflow chamber comprises a top plate removably attached to the enclosure.

10. The mechanical eye model of any of claims 1 to 2, further comprising a fluid retainer between the fluid filled chamber and the anterior chamber to prevent fluid from entering the anterior chamber.

11. The mechanical eye model of any of claims 1 to 2, further comprising a sliding part attached to the piston, the sliding part attached to a railway and capable of moving on the railway.

12. The mechanical eye model of claim 11, wherein the sliding part is attached to the piston via a piston connector and a plate adapter.

13. The mechanical eye model of claim 12, wherein the piston connector and the plate adapter are connected via a push plate.

14. The mechanical eye model of claim 11, further comprising a motorized stage configured to move on the railway.

15. The mechanical eye model of claim 14, wherein the motorized stage is configured to push the sliding part to move on the railway.

16. The mechanical eye model of any of claims 14 to 15, wherein the motorized stage is capable of an incremental repeatable movement of 0.8 pm.

17. The mechanical eye model of any of claims 12 to 15, further comprising a stage base, wherein the railway rests on the stage base.

18. The mechanical eye model of claim 17, further comprising a controller configured to control the motorized stage.

19. The mechanical eye model of claim 18, wherein the controller is configured to control the motorized stage automatically.

20. The mechanical eye model of claim 18 or 19, wherein the controller is a personal computer.

21. The mechanical eye model of claim 18 or 19, wherein the motorized stage is configured to interact with the controller via an USB interface.

22. The mechanical eye model of claim 18 or 19, further comprising a general platform for all parts to rest on.

23. The mechanical eye model of claim 22, further comprising legs on the general platform.

24. The mechanical eye model of any of claims 1. 2, 12, 13, 14, 15, 18, 19, and 23, further comprising a variable optic block simulating a corrective eyeglass situated in front of the anterior chamber.

25. A system to capture pictures of a model eye. comprising: the model eye of claim 21 ; and a camera with picture capturing capabilities.

26. The system of claim 25, further comprising a flashlight for picture capturing.

27. The system of claim 26, wherein the camera and the flashlight are provided as part of a smartphone.

28. The system of claim 26, further comprising a platform to place the smartphone such that the camera can capture pictures of the artificial retina within the model eye.

29. The system of any of claims 25 to 28, further comprising an optical assembly situated in front of the camera and the flashlight to filter and reflect light.

30. The system of claim 29, wherein the optical assembly comprises a polarizer and a mirror to deflect light from the flashlight to a beam splitter to split light before reaching an object to be photographed, and a polarizer and lens to filter light coming from the object to be photographed before reaching the camera.

31. A system to capture pictures of a model eye, comprising: the model eye of claim 24; and a camera with picture capturing capabilities.

32. The system of claim 31, further comprising a flashlight for picture capturing.

33. The system of claim 31, wherein the camera and the flashlight are provided as part of a smartphone.

34. The system of claim 31, further comprising a platform to place the smartphone such that the camera can capture pictures of the artificial retina within the model eye.

35. The system of any of claims 31 to 34, further comprising an optical assembly attachment situated in front of the camera and the flashlight to filter and reflect light.

36. The system of claim 35, wherein the optical assembly comprises a polarizer and a mirror to deflect light from the flashlight to a beam splitter to split light before reaching an object to be photographed, and a polarizer and lens to filter light coming from the object to be photographed before reaching the camera.

37. A method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system of claim 26;using an interface on the controller and moving the piston at an increment and stopping the piston; taking a picture of the model eye using the camera; and saving the picture as digital data.

38. The method of claim 37 , wherein the flashlight is turned on before the picture is taken.

39. A method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system of claim 32; using an interface on the controller and moving the piston at an increment and stopping the piston; taking a picture of the model eye using the camera; and saving the picture as digital data.

40. The method of claim 39, wherein the flashlight is turned on before the picture is taken.

41. A method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system of claim 33; using an interface on the controller and moving the piston at an increment and stopping the piston; and taking a picture of the model eye using the camera.

42. The method of claim 41 , wherein the flashlight is turned on before the picture is taken.

43. A method to capture pictures of a model eye for statistical analysis, the method comprises: providing a system of claim 35; using an interface on the controller and moving the piston at an increment and stopping the piston; and taking a picture of the model eye using the camera.

44. The method of claim 43, wherein the flashlight is turned on before the picture is taken.

Images