Training system for gathering and diverging flexibility of human eyes

Abstract

The invention relates to the technical field of ophthalmology medicine, in particular to a human eye convergence and divergence flexibility training system which comprises a display device used for displaying a training image which comprises two split view patterns; the split lens device is arranged at the preset distance of the display device and is used for a trainer to watch the training image displayed by the display device through the split lens device; the feedback device is used for receiving response information after the trainee watches the training image; and the analysis device is in communication connection with the display device and the feedback device and is used for generating the training image displayed by the display device and adjusting the offset distance of the two split view patterns in the newly generated training image according to the accuracy of the response information so as to adjust the equivalent prism degree when the trainee watches the training image. Fine adjustment can be carried out according to the required prism degree, the flexibility of prism degree adjustment is effectively improved, and the accuracy of the training process is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of ophthalmic medical technology, and more particularly to a training system for the convergence and divergence flexibility of the human eye. Background Technology

[0002] When dealing with near vision, the human visual system primarily achieves optical adaptation through precise neuromuscular control. When focusing on a near target, the ciliary muscle contracts, increasing the curvature of the lens and enhancing the refractive power of the eye's refractive system. This ensures the image is precisely focused on the fovea centralis of the retina. This function of altering the refractive state to adapt to near vision is called accommodation. Accompanying this process is the convergence reflex, a coordinated mechanism of binocular movement. This involves synchronized introrotation of both eyes, adjusting the angle between the visual axes to achieve precise alignment of the visual axes with the target object. Based on this physiological characteristic, clinical visual function training can be implemented through a progressive approach: "strengthening monocular accommodation → improving binocular convergence / divergence → integrating binocular accommodation and convergence." This systematic training establishes a robust binocular coordination mechanism, effectively improving visual impairments such as blurred vision and diplopia.

[0003] However, existing visual function training methods suffer from operational complexity and susceptibility to interference in training results, impacting accuracy and efficiency in clinical applications. Specifically, current techniques typically involve trainees wearing lenses with a specific prism power. Once the trainee can clearly see the visual target under that prism power, the lenses are switched to lenses with different prism powers for further training. Since the prism power of each lens is fixed, the gradient of prism power changes between lenses is significant for economic reasons. This results in poor flexibility in prism power adjustment during training, hindering finer adjustments and reducing the accuracy of the training process. Furthermore, traditional training methods only record the overall convergence training cycle and the final result of the eye's convergence and divergence abilities for each round of training, adjusting subsequent training strategies based on the overall cycle and final result. This approach fails to capture the individualized details of the trainee's condition during training, making subsequent training strategies less tailored to the trainee's specific situation and reducing training efficiency. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a training system for the convergence and divergence flexibility of the human eye, which solves the technical problem that the prior art has poor prism power adjustment flexibility during the training process and cannot achieve fine adjustment.

[0006] (II) Technical Solution

[0007] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0008] This invention provides a training system for human eye convergence and divergence flexibility, used to train the human eye's ability to quickly switch between convergence and divergence, including:

[0009] A display device for displaying training images, the training images comprising two split-view patterns;

[0010] A split-viewing lens device is set at a preset distance from the display device, allowing the trainee to view the training images displayed on the display device through the split-viewing lens device;

[0011] Feedback device, used to receive the trainee's response information after viewing the training images;

[0012] The analysis device is communicatively connected to the display device and the feedback device, respectively, for generating training images displayed on the display device, and adjusting the offset distance between two sub-view patterns in the newly generated training images according to the accuracy of the response information, so as to adjust the equivalent prism power when the trainee views the training images.

[0013] Optionally, in the analysis apparatus, adjusting the offset distance between two split-view patterns in the newly generated training image to adjust the equivalent prism power when the trainee views the training image includes: Adjust the offset distance between the two sub-view patterns in the training image according to formula (1); (1);

[0014] The equivalent prism power is represented by B, which represents the preset distance between the split-view lens device and the display device, in meters; A represents the offset distance between the two split-view patterns displayed by the display device, in centimeters; wherein, the initial position of the two split-view patterns is the position where they coincide, and the offset distance is the relative distance between the geometric centers of the two split-view patterns.

[0015] Optionally, the split-viewing lens device includes: a frame, and a split-viewing lens frame disposed on the frame;

[0016] The split-view frame has red and blue lenses on the left and right sides, respectively.

[0017] The training image has two split-view patterns, including a red split-view pattern and a blue split-view pattern. The red split-view pattern and the blue split-view pattern are superimposed in the trainee's field of vision after being viewed through the split-view frame to form a visual pattern.

[0018] When the training images are used for ensemble ability training or ensemble ability testing, the left-right positional relationship between the red and blue sub-patterns is the same as the left-right positional relationship between the red and blue lenses.

[0019] When the training images are used for divergence training or divergence testing, the left-right positional relationship between the red and blue split-view patterns is the opposite of the left-right positional relationship between the red and blue lenses.

[0020] Optionally, the analysis device includes: a basic inspection module, a training module, and a training image generation module; The basic inspection module is used to call the training image generation module to generate training images with gradually increasing offset distances of the split-view patterns, and to determine the maximum value of the trainee's basic assembling ability and the maximum value of the basic diverging ability based on the accuracy of the response information corresponding to the training images.

[0021] The training module determines the initial offset distance between the two split-view patterns in the training image based on the maximum value of the basic set capability and the maximum value of the basic divergence capability, calls the training image generation module to generate the corresponding training image, and increases or decreases the offset distance between the two split-view patterns in the next training image according to the accuracy of the response information corresponding to the training image, and sends the newly generated next training image to the display device for display; and / or, counts down the second viewing time of the trainee viewing the training image; and / or, adds positive or negative lenses in front of or behind the split-view frame.

[0022] Optionally, the split-viewing lens device (20) further includes: a positive and negative lens frame disposed on the frame body coaxially with the split-viewing lens frame;

[0023] The positive and negative lens frame includes two discs and a rotation drive device. The center of the discs is rotatably connected to the frame body. Multiple positive or negative lenses with different refractive powers are set on the discs, and the distance from the geometric center of each positive or negative lens to the center of the disc is equal. The discs are driven by the rotation drive device. The rotation drive device is communicatively connected to the analysis device.

[0024] When the rotary drive device receives a control command from the analysis device to add a positive or negative lens in front of or behind the split-view frame, the rotary drive device controls the rotary drive device to drive the wheel to rotate, so that the geometric center of the positive or negative lens of the corresponding diopter is rotated to the optical axis position corresponding to the split-view frame.

[0025] Optionally, the basic inspection module includes:

[0026] The basic capability check unit is used to call the training image generation module to generate a training image with a split view pattern at the first offset distance and send it to the display device for display, and to determine whether the response information corresponding to the training image is received within a preset first viewing time, and whether the response information is correct.

[0027] If so, increase the first offset distance of the training image by the first preset step size, and jump to the starting position of the basic set capability check unit, and check again according to the updated first offset distance;

[0028] If not, determine whether the number of times the corresponding response information for the training image is not received within the preset first viewing time or the number of times the response information is incorrect is greater than or equal to 2; if not, maintain the first offset distance of the current training image and jump to the starting position of the basic ensemble capability check unit, and check again according to the current first offset distance; if yes, take the current first offset distance as the maximum value of the basic ensemble capability or the maximum value of the basic divergence capability.

[0029] When the basic capability checking unit is used to check the maximum value of the user's basic set capability, the left-right position relationship of the red sub-view pattern and the blue sub-view pattern in the training image it generates is the same as the left-right position relationship of the red lens and the blue lens.

[0030] When the basic ability checking unit is used to check the user's basic divergence maximum value, the left-right position relationship of the red and blue split-view patterns in the training image it generates is opposite to the left-right position relationship of the red and blue lenses.

[0031] Optionally, the training module includes: an initialization unit, a single-set training unit, and a single-spread training unit;

[0032] The initialization unit is used to set the initial value of the second offset distance to be the product of the maximum value of the basic aggregation capability and the first preset percentage, and to set the initial value of the third offset distance to be the product of the maximum value of the basic dispersion capability and the second preset percentage.

[0033] The single-set training unit is used to call the training image generation module to generate a training image with a split view pattern of the second offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current second offset distance by a second preset step size and jumps to the single-spread training unit; if not, it...

[0034] Keeping the current second offset distance unchanged, the training image generation module is called again to generate a training image with the split view pattern of the second offset distance and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current second offset distance is increased by a second preset step and the process jumps to the single spread training unit. If no, the current second offset distance is decreased by a third preset step and the process jumps to the single spread training unit.

[0035] The single-shot divergence training unit is used to call the training image generation module to generate a training image with a split view pattern of the third offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current third offset distance by a fourth preset step and jumps to the single-shot ensemble training unit; if not, it...

[0036] Keeping the current third offset distance unchanged, the training image generation module is called again to generate a training image with the third offset distance as the split view pattern and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current third offset distance is increased by a fourth preset step and the process jumps to the single set training unit. If no, the current third offset distance is decreased by a fifth preset step and the process jumps to the single set training unit.

[0037] The determination condition is that the response information corresponding to the currently displayed training image is correct.

[0038] Optionally, the training module further includes:

[0039] A configuration unit is used to configure parameters in a single assembly training unit and a single divergence training unit based on preset training items; the training items include: assembly ability-focused training, divergence ability-focused training, and binocular balance training;

[0040] When the training project is focused on ensemble ability training, the parameter configuration in the single ensemble training unit and the single divergence training unit is as follows: the second preset step size is greater than the third preset step size, the second preset step size is greater than the fourth preset step size, and the fourth preset step size is equal to the fifth preset step size.

[0041] When the training project focuses on spreading ability training, the parameter configuration in the single assembly training unit and the single spreading training unit is as follows: the fourth preset step size is greater than the fifth preset step size, the fourth preset step size is greater than the second preset step size, and the second preset step size is equal to the third preset step size.

[0042] When the training program is binocular balance training, the parameter configuration in the single convergence training unit and the single divergence training unit is as follows: the second preset step size, the third preset step size, the fourth preset step size, and the fifth preset step size are all equal.

[0043] Optionally, the training module further includes: a first upgrade training unit and a second upgrade training unit;

[0044] The first upgrade training unit is configured to, when both the second offset distance and the third offset distance reach a preset maximum value, reset the second offset distance to the ensemble training starting value, reset the third offset distance to the divergent training starting value, and reset the judgment condition to: receiving response information corresponding to the currently displayed training image within a preset second viewing time, and the response information corresponding to the currently displayed training image is correct; and,

[0045] When both the second and third offset distances reach their preset maximum values ​​again, the second offset distance is reset to the ensemble training starting value, the third offset distance is reset to the spread training starting value, and the second viewing duration is reduced by a sixth preset step; and,

[0046] When the second viewing time decreases to the preset minimum value, and the second offset distance and the third offset distance both reach the preset maximum value again, the process jumps to the second upgrade training unit.

[0047] The second upgrade training unit is used to add a positive or negative lens with a preset diopter to the front or back of the split-vision frame.

[0048] Optionally, the training image generation module includes:

[0049] The image generation unit is configured to, based on the calls to the basic inspection module and the training module, respectively draw a red random dot plot and a blue random dot plot, insert a target pattern into the red random dot plot and the blue random dot plot in the same random direction, add red random dots above the target pattern of the red random dot plot to obtain a red split-view pattern, add blue random dots above the target pattern of the blue random dot plot to obtain a blue split-view pattern; and, based on the current first offset distance, second offset distance, or third offset distance, adjust the offset distance of the red split-view pattern and the blue split-view pattern to obtain a new training image for display.

[0050] (III) Beneficial Effects

[0051] The training system proposed in this invention includes a display device for displaying a training image, the training image comprising two split-view patterns; a split-view lens device disposed at a preset distance from the display device for the trainee to view the training image displayed by the display device through the split-view lens device; a feedback device for receiving response information from the trainee after viewing the training image; and an analysis device communicatively connected to the display device and the feedback device, for generating the training image displayed by the display device, and adjusting the offset distance between the two split-view patterns in the newly generated training image based on the accuracy of the response information, thereby adjusting the equivalent prism power when the trainee views the training image.

[0052] Based on the above training system, when trainees are training their eye convergence and divergence flexibility, the analysis device can adjust the offset distance between the two split-view patterns in the training image displayed on the display device according to the accuracy of the response information. This adjusts the equivalent prism power when the trainee views the training image, thus eliminating the dependence on a physical prism. Moreover, the specific offset distance between the two split-view patterns can be finely adjusted according to the required prism power. Compared with the existing technology that can only adjust the prism power with a fixed value based on a physical prism, this effectively improves the flexibility of prism power adjustment and ensures the accuracy of the training process. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the architecture of a training system for human eye convergence and divergence flexibility provided in the embodiment;

[0055] Figure 2 This is a schematic diagram of the split-view lens device provided in the embodiment;

[0056] Figure 3 A schematic diagram of the training images generated by the training image generation module;

[0057] Figure 4 for Figure 3 A schematic diagram of the image seen by the trainee after a fusion process based on binocular disparity;

[0058] Figure 5 This is a schematic diagram of the architecture of the analysis device provided in the embodiment;

[0059] Figure 6 A flowchart illustrating the workflow of the basic inspection module;

[0060] Figure 7 This is a flowchart illustrating the workflow of the training module. Detailed Implementation

[0062] To better explain and facilitate understanding of the invention, exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention can be understood more clearly and thoroughly, and that the scope of the invention can be fully conveyed to those skilled in the art.

[0063] Example 1

[0064] like Figure 1As shown, this embodiment of the invention provides a training system for human eye convergence and divergence flexibility, used to train the human eye's ability to quickly switch between convergence and divergence (i.e., convergence and divergence flexibility), including a display device, a split-viewing lens device, a feedback device, and an analysis device, as detailed below.

[0065] The display device 10 is used to display training images, which include two split-view patterns. Specifically, the display device may be a display screen.

[0066] The split-view lens device 20 is positioned at a preset distance from the display device, and is used by the trainee to view the training images displayed on the display device through the split-view lens device.

[0067] The feedback device 30 is used to receive response information from the trainee after viewing the training image. Specifically, the feedback device can be a handle or a keyboard. The trainee inputs response information into the training system by manipulating the handle or keyboard. The response information can specifically be the trainee's judgment on the information contained in the training image. For example, when the training image is the visual target letter E, the response information can be the trainee's judgment on the orientation of the opening of the visual target letter E, which can be input into the training system by pressing the "↑", "↓", "←", and "→" keys on the handle or keyboard.

[0068] The analysis device 40 is communicatively connected to the display device and the feedback device, respectively, and is used to generate training images displayed on the display device, and to adjust the offset distance between the two sub-view patterns in the newly generated training images according to the accuracy of the response information, so as to adjust the equivalent prism power when the trainee views the training images.

[0069] Based on the above training system, when trainees are training their eye convergence and divergence flexibility, the analysis device can adjust the offset distance between the two split-view patterns in the training image displayed on the display device according to the accuracy of the response information. This adjusts the equivalent prism power when the trainee views the training image, thus eliminating the dependence on a physical prism. Moreover, the specific offset distance between the two split-view patterns can be finely adjusted according to the required prism power. Compared with the existing technology that can only adjust the prism power with a fixed value based on a physical prism, this effectively improves the flexibility of prism power adjustment and ensures the accuracy of the training process.

[0070] In one specific implementation of this embodiment, the method by which the analysis device adjusts the offset distance between two split-view patterns in the newly generated training image to adjust the equivalent prism power when the trainee views the training image includes:

[0071] Adjust the offset distance between the two sub-view patterns in the training image according to formula (1);

[0072] (1);

[0073] The equivalent prism power is represented by B, which represents the preset distance between the split-view lens device and the display device, in meters; A represents the offset distance between the two split-view patterns displayed by the display device, in centimeters; wherein, the initial position of the two split-view patterns is the position where they coincide, and the offset distance is the relative distance between the geometric centers of the two split-view patterns.

[0074] Example 2

[0075] To better understand the training system provided in Embodiment 1, the structure of the split-view lens device in this embodiment will be described in detail.

[0076] like Figure 2 As shown, the split-viewing lens device includes: a frame, and positive and negative lens frames and split-viewing lens frames 204 coaxially disposed on the frame.

[0077] The positive and negative lens frame includes two discs 201 and a rotation drive device. The discs 201 are rotatably connected to the frame body. Multiple positive lenses 202 or negative lenses 203 with different diopter values ​​are arranged on the discs 201, and the distance from the geometric center of each positive lens 202 or negative lens 203 to the center of the disc 201 is equal. The discs 201 are driven by the rotation drive device. The rotation drive device is communicatively connected to the analysis device.

[0078] When the rotary drive device receives a control command from the analysis device to add a positive lens 202 or a negative lens 203 in front of or behind the split-view frame, the rotary drive device controls the rotary drive device to drive the wheel 201 to rotate, so that the geometric center of the positive lens 202 or negative lens 203 corresponding to the diopter is rotated to the optical axis position corresponding to the split-view frame.

[0079] Specifically, the split-viewing frame is provided with a left lens 205 and a right lens 206. One wheel 201 of the positive and negative frame is located in front of the left lens 205, and the other wheel 201 is located in front of the right lens 206. "In front" refers to the direction in which the split-viewing frame is close to the display device 10, and "back" refers to the direction in which the split-viewing frame is away from the display device 10. The two wheels 201 can be synchronously controlled to rotate synchronously by a single rotary drive device, or they can be configured with independent rotary drive devices to independently and precisely control the rotation of the wheels.

[0080] To enhance the training effect and engagement, a split-viewing lens device can be used, based on the principle of red-blue split-viewing, to allow users to observe stereoscopic visual targets. Specifically, the split-viewing frame has red and blue lenses positioned on the left and right sides, respectively. The training image consists of two split-view patterns: a red split-view pattern and a blue split-view pattern. These two patterns, viewed through the split-viewing frame, are superimposed in the trainee's field of vision to form a stereoscopic visual pattern.

[0081] Specifically, the lenses on the split-view frame can be set to red on the left and blue on the right, or blue on the left and red on the right.

[0082] When the training images are used for convergence training or convergence testing, the left-right positional relationship between the red and blue split-view patterns is the same as the left-right positional relationship between the red and blue lenses. That is, if the lenses on the split-view frame are left-red and right-blue, then the two split-view patterns used for convergence training or convergence testing are also left-red and right-blue; if the lenses on the split-view frame are left-blue and right-red, then the two split-view patterns used for convergence training or convergence testing are also left-blue and right-red.

[0083] When the training image is used for divergence training or divergence testing, the left-right position relationship of the red and blue split-view patterns is the opposite of the left-right position relationship of the red and blue lenses. That is, if the lenses on the split-view frame are red on the left and blue on the right, then the two split-view patterns used for divergence training or testing are also blue on the left and red on the right; if the lenses on the split-view frame are blue on the left and red on the right, then the two split-view patterns used for divergence training or testing are also red on the left and blue on the right. Specifically, a schematic diagram of a training image with the red split-view pattern on the left and the blue split-view pattern on the right is shown below. Figure 3 As shown.

[0084] During training, the background color of the training image, that is, the color of the non-split-view pattern area in the training image, will affect the pattern seen by the trainee through the red and blue lenses. Generally, if the background color is white, the trainee sees the blue split-view pattern through the red lens and the red split-view pattern through the blue lens; if the background color is black, the trainee sees the red split-view pattern through the red lens and the blue split-view pattern through the blue lens.

[0085] Specifically, taking a white background in the training image as an example, a blue lens is placed on the left and a red lens on the right. When the trainee observes the complementary red and blue split-view images through the split-view lenses, the trainee's left eye sees the red split-view image through the blue lens, and the right eye sees the blue split-view image through the red lens. This spectral separation mechanism allows the left and right eyes to receive different two-dimensional image information with horizontal parallax. At the visual nervous system level, the differential visual signals input from both eyes are transmitted to the visual cortex through the optic nerve. After information integration by the lateral geniculate body, the brain center performs stereo matching and depth calculation on these two planar images with parallax angles. This fusion process based on binocular parallax can reconstruct stereoscopic visual perception with depth information, enabling the trainee not only to identify the morphological features of the target but also to accurately determine its three-dimensional spatial position. This training mode, by repeatedly stimulating the fusion function of the visual center, can effectively improve stereoscopic acuity and the coordination ability of the convergence-divergence-accommodation system. For example, when the trainee views through the training system... Figure 3 When training images are shown, after undergoing a binocular disparity-based fusion process, the images that the user perceives as being viewed are... Figure 4 The 3D image shown.

[0086] Example 3

[0087] To better understand the training system provided in Embodiment 1, this embodiment provides a detailed description of the architecture of the analysis device.

[0088] like Figure 5 As shown, the analysis device includes: a basic inspection module, a training module, and a training image generation module, as detailed below:

[0089] The basic inspection module is used to call the training image generation module to generate training images with gradually increasing offset distances of the split-view patterns. Based on the accuracy of the response information corresponding to the training images, the maximum value of the trainee's basic ensemble ability and the maximum value of the basic divergence ability are determined.

[0090] The training module determines the initial offset distance between the two split-view patterns in the training image based on the maximum value of the basic set capability and the maximum value of the basic divergence capability, calls the training image generation module to generate the corresponding training image, and increases or decreases the offset distance between the two split-view patterns in the next training image according to the accuracy of the response information corresponding to the training image, and sends the newly generated next training image to the display device for display; and / or, counts down the second viewing time of the trainee viewing the training image; and / or, adds positive or negative lenses in front of or behind the split-view frame.

[0091] In one specific implementation of this embodiment, the basic inspection module includes:

[0092] The basic capability check unit is used to call the training image generation module to generate a training image with a split view pattern at the first offset distance and send it to the display device for display, and to determine whether the response information corresponding to the training image is received within a preset first viewing time, and whether the response information is correct.

[0093] If so, increase the first offset distance of the training image by the first preset step size, and jump to the starting position of the basic set capability check unit, and check again according to the updated first offset distance;

[0094] If not, determine whether the number of times the corresponding response information for the training image is not received within the preset first viewing time or the number of times the response information is incorrect is greater than or equal to 2; if not, maintain the first offset distance of the current training image and jump to the starting position of the basic ensemble capability check unit, and check again according to the current first offset distance; if yes, take the current first offset distance as the maximum value of the basic ensemble capability or the maximum value of the basic divergence capability.

[0095] When the basic capability checking unit is used to check the maximum value of the user's basic set capability, the left-right position relationship of the red and blue sub-patterns in the training image it generates is the same as the left-right position relationship of the red and blue lenses.

[0096] When the basic ability checking unit is used to check the user's basic divergence maximum value, the left-right position relationship of the red and blue split-view patterns in the training image it generates is opposite to the left-right position relationship of the red and blue lenses.

[0097] The workflow diagram of the above basic inspection module is as follows: Figure 6 As shown. The logic implemented by the basic check module is as follows: It displays training images to the user and requires the trainee to provide correct feedback within the first viewing time. If the trainee provides correct feedback within the first viewing time, it means the trainee has passed the test of the prism degree (i.e., test difficulty) corresponding to the current first offset distance. The module then increases the first offset distance by a first preset step size and jumps back to the starting position of the basic ability check unit to display training images corresponding to a larger first offset distance (i.e., higher test difficulty), until the user does not provide correct feedback within the first viewing time. At this point, the basic check module maintains the current first offset distance and jumps back to the starting position of the basic divergence ability check unit to re-execute. That is, it maintains the current check difficulty, giving the trainee a second opportunity to view training images of the same difficulty. If the trainee passes the second test at the current difficulty, the test difficulty is further increased. If the trainee fails the second test at the current difficulty, the prism degree corresponding to the current first offset distance is determined to be the trainee's maximum basic ensemble ability or maximum basic divergence ability.

[0098] In another specific implementation of this embodiment, the training module includes: an initialization unit, a single-set training unit, and a single-spread training unit.

[0099] The initialization unit is used to set the initial value of the second offset distance to be the product of the maximum basic convergence ability and the first preset percentage, and to set the initial value of the third offset distance to be the product of the maximum basic divergence ability and the second preset percentage. Specifically, the first preset percentage and the second preset percentage are both [30%, 70%], more preferably, the first preset percentage and the second preset percentage are both 50%, that is, the initial value of the second offset distance is set to half of the trainee's maximum basic convergence ability, and the initial value of the third offset distance is set to half of the trainee's maximum basic divergence ability. Subsequently, the training difficulty is gradually increased through single convergence training units and single divergence training units to train the convergence and divergence flexibility of the human eye.

[0100] The single-set training unit is used to call the training image generation module to generate a training image with a split view pattern of the second offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current second offset distance by a second preset step size and jumps to the single-spread training unit; if not, it...

[0101] Keeping the current second offset distance unchanged, the training image generation module is called again to generate a training image with the split view pattern of the second offset distance and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current second offset distance is increased by a second preset step and the process jumps to the single spread training unit. If no, the current second offset distance is decreased by a third preset step and the process jumps to the single spread training unit.

[0102] The single-shot divergence training unit is used to call the training image generation module to generate a training image with a split view pattern of the third offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current third offset distance by a fourth preset step and jumps to the single-shot ensemble training unit; if not, it...

[0103] Keeping the current third offset distance unchanged, the training image generation module is called again to generate a training image with the third offset distance as the split view pattern and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current third offset distance is increased by a fourth preset step and the process jumps to the single set training unit. If no, the current third offset distance is decreased by a fifth preset step and the process jumps to the single set training unit.

[0104] The determination condition is that the response information corresponding to the currently displayed training image is correct.

[0105] The workflow diagram of the above training module is as follows: Figure 7 As shown. The logic implemented by the above training module is as follows: Based on the single ensemble training unit, a training image of initial training difficulty is first shown to the trainee for training ensemble ability, giving the trainee two opportunities to view and recognize it. If the trainee passes the training at the current training difficulty (the judgment condition is true), the second offset distance is increased by a second preset step size (increasing the training difficulty of the next time). If the trainee fails the training at the current difficulty after two viewings, the current second offset distance is decreased by a third preset step size (lowering the training difficulty of the next time), and the process jumps to the single divergence training unit. Similar to the single-set training unit, the single-spread training unit first presents the trainee with a training image of initial difficulty for training spread-out ability, giving the trainee two opportunities to view and recognize it. If the trainee passes the training at the current difficulty level (the judgment condition is true), the third offset distance is increased by a fourth preset step (increasing the training difficulty of the next time). If the trainee fails the training at the current difficulty level after both views, the current third offset distance is decreased by a fifth preset step (decreasing the training difficulty of the next time), and the system jumps back to the single-set training unit. The second offset distance in the single-set training unit has already been readjusted (increasing or decreasing the training difficulty) during the previous set-out ability training process, and is used to train the trainee's set-out ability again. Then, the system jumps back to the single-spread training unit. The third offset distance of the single-spread training unit has been readjusted (increased or decreased in training difficulty) during the previous spread ability training, and is used to train the trainee to spread ability again. In this way, the single-gathering training unit and the single-spreading training unit cycle back and forth, so as to train the trainee's flexibility in gathering and spreading.

[0106] The stopping condition for the loop between the single ensemble training unit and the single divergent training unit can be limited to a countdown of a preset training duration. When the countdown ends, the training module is completed.

[0107] Preferably, in order to provide more targeted training for the convergence and divergence flexibility of the human eye, the training module provided in this embodiment can also configure the parameters in the single convergence training unit and the single divergence training unit according to different pre-selected projects. Specifically, the training module further includes:

[0108] The configuration unit is used to configure the parameters in the single assembly training unit and the single divergence training unit based on preset training items; the training items include: assembly ability-focused training, divergence ability-focused training, and binocular balance training.

[0109] When the training project is focused on ensemble ability training, the parameter configuration in the single ensemble training unit and the single divergence training unit is as follows: the second preset step size is greater than the third preset step size, the second preset step size is greater than the fourth preset step size, and the fourth preset step size is equal to the fifth preset step size.

[0110] In other words, the training difficulty of a single ensemble training unit is increased more each time than that of a single scatter training unit, thereby training the trainee's ensemble ability over a relatively larger range.

[0111] When the training project focuses on spreading ability training, the parameter configuration in the single assembly training unit and the single spreading training unit is as follows: the fourth preset step size is greater than the fifth preset step size, the fourth preset step size is greater than the second preset step size, and the second preset step size is equal to the third preset step size.

[0112] In other words, the training difficulty of each single spread training unit is increased to be greater than that of each single assembly training unit, thereby training the trainee's spread ability over a relatively larger range.

[0113] When the training program is binocular balance training, the parameter configuration in the single convergence training unit and the single divergence training unit is as follows: the second preset step size, the third preset step size, the fourth preset step size, and the fifth preset step size are all equal.

[0114] In other words, the training difficulty of each single spread-out training unit is increased to be equal to the training difficulty of each single assembly training unit, so that the trainee's assembly and spread-out abilities are trained in a balanced way.

[0115] The lengths of the first, second, third, fourth, and fifth preset step sizes can be set based on a unit step size. For example, the unit length can be set as the offset distance that needs to be adjusted for two sub-view patterns corresponding to a change in the prism power of the preset size. The first, second, third, fourth, and fifth preset step sizes are then set as different multiples of the unit step size according to the specific training project, thereby achieving the setting of the aforementioned different step sizes. Preferably, the prism power of the preset size can be taken between [0.5, 10].

[0116] Specifically, taking a preset prism power of 1 and a preset distance of 2 meters between the split-view lens device and the display device as an example, the unit step size is 2 centimeters, which is the offset distance that needs to be adjusted to correspond to the two split-view patterns when changing 1 prism power. When the training project focuses on convergence ability training, the parameter configuration requirements are: the second preset step size is greater than the third preset step size, the second preset step size is greater than the fourth preset step size, and the fourth preset step size is equal to the fifth preset step size. The first to fifth preset step sizes can be set as follows: the second preset step size is configured as twice the unit step size, i.e., 4 centimeters, and the third, fourth, and fifth preset step sizes are configured as once the unit step size, i.e., 2 centimeters. The configuration method of the first to fifth preset step sizes when the training projects focus on divergence ability training and binocular balance training is the same. Based on the unit step size, the unit length of the corresponding multiple can be determined according to the corresponding parameter configuration requirements.

[0117] In addition, to further improve the training effect, the training difficulty in the training process can be upgraded, so as to conduct more thorough training on the flexibility of trainees' gathering and dispersal. Specifically, the training module also includes: a first upgraded training unit and a second upgraded training unit.

[0118] The first upgrade training unit is configured to, when both the second offset distance and the third offset distance reach a preset maximum value, reset the second offset distance to the ensemble training starting value, reset the third offset distance to the divergent training starting value, and reset the judgment condition to: receiving response information corresponding to the currently displayed training image within a preset second viewing time, and the response information corresponding to the currently displayed training image is correct; and,

[0119] When both the second and third offset distances reach their preset maximum values ​​again, the second offset distance is reset to the ensemble training starting value, the third offset distance is reset to the spread training starting value, and the second viewing duration is reduced by a sixth preset step; and,

[0120] When the second viewing time decreases to the preset minimum value, and the second offset distance and the third offset distance both reach the preset maximum value again, the system jumps to the second upgrade training unit.

[0121] That is, when the trainee can pass the training within all variations of the second and third offset distances (both the second and third offset distances reach their preset maximum values), the training system trains the trainee's reaction speed by shortening the second viewing duration. Preferably, the initial value of the second viewing duration can range from 2 to 15 seconds, and the sixth preset step size can range from 1 to 5 seconds. Preferably, the preset maximum value of the second offset distance can be set to the offset distance corresponding to the mean or median of convergence ability corresponding to the convergence and divergence flexibility of normal human eyes, and the preset maximum value of the third offset distance can be set to the offset distance corresponding to the mean or median of divergence ability corresponding to the convergence and divergence flexibility of normal human eyes; more preferably, the maximum value of the second offset distance is the offset distance corresponding to 30 prism diopters, and the maximum value of the third offset distance is the offset distance corresponding to 20 prism diopters. The maximum values ​​of the second and third offset distances can also be further increased according to the training objective to give the trainee's eyes better convergence and divergence flexibility.

[0122] The second upgrade training unit is used to add a positive or negative lens with a preset diopter to the front or back of the split-vision frame.

[0123] In other words, after the trainee has completed all the training sessions with limited second viewing time, the training system can further train the eye's accommodative ability by adding positive or negative lenses. Specifically, when the training focuses on convergence, a positive lens is added in front of or behind the split-view frame; when the training focuses on divergence, a negative lens is added in front of or behind the split-view frame; and when the training focuses on binocular balance, no positive or negative lenses are added. Positive lenses primarily train the eye's accommodative relaxation ability. When a positive lens is added, the extraocular muscles also relax. This relaxation causes the eyes to turn outward, that is, towards the temporal side, thus making the eyes appear relatively divergent, thereby training the trainee's accommodative ability during convergence training. Conversely, negative lenses primarily train the eye's accommodative tension ability. When a negative lens is added, the extraocular muscles will tighten accordingly. This tension will pull the eyes inward, towards the nose, ultimately causing the eyes to converge relatively inward. This trains the random accommodation ability of trainees who are undergoing divergence training.

[0124] Preferably, the adjustment of training difficulty in the training module using positive and negative lenses is similar to the implementation logic of the first upgraded training unit. The training difficulty can also be changed by adjusting the diopter of the positive and negative lenses. More preferably, the diopter of the positive lens can be set to +2 or +3 according to the training difficulty from low to high, and the diopter of the negative lens can be set to -1, -2, -3, or -4 according to the training difficulty from low to high. Based on the limitation of the second viewing time, even after adding both positive and negative lenses, the judgment condition remains: receiving the response information corresponding to the currently displayed training image within the preset second viewing time, and the response information corresponding to the currently displayed training image is correct.

[0125] Based on the aforementioned basic inspection module and training module, in one specific implementation of this embodiment, the training image generation module includes:

[0126] The image generation unit is configured to, based on the calls to the basic inspection module and the training module, respectively draw a red random dot plot and a blue random dot plot, insert a target pattern into the red random dot plot and the blue random dot plot in the same random direction, add red random dots above the target pattern of the red random dot plot to obtain a red split-view pattern, add blue random dots above the target pattern of the blue random dot plot to obtain a blue split-view pattern; and, based on the current first offset distance, second offset distance, or third offset distance, adjust the offset distance of the red split-view pattern and the blue split-view pattern to obtain a new training image for display.

[0127] Furthermore, to expand the functionality of the training system provided in this embodiment and improve its practicality, the analysis device provided in this embodiment also includes a relaxation module, a pre-configuration module, and a data statistics module, as detailed below:

[0128] The relaxation module is used to call the relaxation training unit to perform relaxation training after the training module has been completed, thereby improving the comfort of the trainee after training.

[0129] The relaxation training unit is used to call the training image generation module to generate a training image with a split view pattern at the fourth offset distance and send it to the display device for display. It then determines whether the response information corresponding to the currently displayed training image is correct. If correct, it increases the current fourth offset distance by a seventh preset step and jumps back to the starting position of the relaxation training unit to re-execute; otherwise, it decreases the current fourth offset distance by a seventh preset step and jumps back to the starting position of the relaxation training unit to re-execute. Furthermore, in the training image generated by the relaxation training unit calling the training image sound field module, the left-right position relationship between the red and blue split view patterns is opposite to the left-right position relationship between the red and blue lenses.

[0130] The stopping condition for the relaxation training unit mentioned above can be limited to a countdown of a preset relaxation duration. Once the countdown ends, the training module is completed.

[0131] The pre-configuration module is used by doctors to configure training parameters based on the trainee's initial visual function parameters before the trainee begins training; the training parameters include one or more of the following: training items and training duration.

[0132] The visual function parameters specifically include: the maximum value of the assembling ability and the maximum value of the diverging ability determined by the trainee through a basic convergence and divergence flexibility check before starting training.

[0133] Based on the above pre-configured modules, the training process can be more tailored to individual needs, improving the relevance and effectiveness of the training.

[0134] The data statistics module is used to collect real-time response data of trainees based on response information, so that doctors can optimize the training parameters according to the real-time response data. The real-time response data includes one or more of the following: the time for each assembly judgment, the time for each dispersal judgment, the number of dispersal training responses, the number of assembly training responses, the maximum value of the assembly, the first preset duration corresponding to the maximum value of the assembly, the maximum value of the dispersal, the second preset duration corresponding to the maximum value of the dispersal, the number of assembly and dispersal training cycles, and the total training time.

[0135] The data statistics module can be integrated into the analysis device, which can accurately record real-time response data during the training process. That is, compared to existing technologies that can only record the overall training cycle and the final result of the human eye's convergence and divergence abilities for each training session, the analysis device in this embodiment also records real-time response data during the training process. This provides a more accurate quantitative basis for the formulation of training plans, indicating the focus of the training plan (emphasis on convergence / divergence / bidirectional balance), providing a data foundation for targeted training plans based on individual trainees, and improving training efficiency. For example, to match the trainee's progress speed, at the start of each training session, the initial value of the second offset distance can be set as the product of the maximum convergence value recorded by the trainee in the previous training session and a first preset percentage; the initial value of the third offset distance can be set as the product of the maximum divergence value recorded by the trainee in the previous training session and a second preset percentage.

[0136] Furthermore, the aforementioned data statistics module also provides reliable data support. The training system can record and analyze data in real time, providing reliable data support for ophthalmological medicine, visual science research, and the development of visual aids. This helps promote development and innovation in related fields. Simultaneously, the data statistics module also supports remote uploading and querying of test data, facilitating remote monitoring and management by doctors and contributing to the modernization and intelligentization of ophthalmological medical services.

[0137] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0139] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0140] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0141] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0142] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A training system for human eye convergence and divergence flexibility, used to train the human eye's ability to quickly switch between convergence and divergence, characterized in that, include: Display device (10) for displaying training images, the training images including two split view patterns; The split-view lens device (20) is set at a preset distance from the display device, and is used by the trainee to view the training image displayed on the display device through the split-view lens device; Feedback device (30) is used to receive the trainee's response information after viewing the training images; The analysis device (40) is communicatively connected to the display device and the feedback device, respectively, for generating the training image displayed by the display device, and adjusting the offset distance between the two sub-view patterns in the newly generated training image according to the accuracy of the response information, so as to adjust the equivalent prism power when the trainee views the training image.

2. The training system according to claim 1, wherein in the analysis device, adjusting the offset distance between two split-view patterns in the newly generated training image to adjust the equivalent prism power when the trainee views the training image includes: Adjust the offset distance between the two sub-view patterns in the training image according to formula (1); （1）； The equivalent prism power is represented by B, which represents the preset distance between the split-view lens device and the display device, in meters; A represents the offset distance between the two split-view patterns displayed by the display device, in centimeters; wherein, the initial position of the two split-view patterns is the position where they coincide, and the offset distance is the relative distance between the geometric centers of the two split-view patterns.

3. The training system according to claim 1, characterized in that, The split-viewing lens device includes: a frame, and a split-viewing lens frame disposed on the frame; The split-view frame has red and blue lenses on the left and right sides, respectively. The training image has two split-view patterns, including a red split-view pattern and a blue split-view pattern. The red split-view pattern and the blue split-view pattern are superimposed in the trainee's field of vision after being viewed through the split-view frame to form a visual pattern. When the training images are used for ensemble ability training or ensemble ability testing, the left-right positional relationship between the red and blue sub-patterns is the same as the left-right positional relationship between the red and blue lenses. When the training images are used for divergence training or divergence testing, the left-right positional relationship between the red and blue split-view patterns is the opposite of the left-right positional relationship between the red and blue lenses.

4. The training system according to claim 1, characterized in that, The analysis device includes: a basic inspection module, a training module, and a training image generation module; The basic inspection module is used to call the training image generation module to generate training images with gradually increasing offset distances of the split-view patterns, and to determine the maximum value of the trainee's basic assembling ability and the maximum value of the basic diverging ability based on the accuracy of the response information corresponding to the training images. The training module determines the initial offset distance between the two split-view patterns in the training image based on the maximum value of the basic set capability and the maximum value of the basic divergence capability, calls the training image generation module to generate the corresponding training image, and increases or decreases the offset distance between the two split-view patterns in the next training image according to the accuracy of the response information corresponding to the training image, and sends the newly generated next training image to the display device for display; and / or, counts down the second viewing time of the trainee viewing the training image; and / or, adds positive or negative lenses in front of or behind the split-view frame.

5. The training system according to claim 4, characterized in that, The split-viewing lens device (20) further includes: a positive and negative lens frame that is coaxially mounted on the frame with the split-viewing lens frame; The positive and negative lens frame includes two discs and a rotation drive device. The center of the discs is rotatably connected to the frame body. Multiple positive or negative lenses with different refractive powers are set on the discs, and the distance from the geometric center of each positive or negative lens to the center of the disc is equal. The discs are driven by the rotation drive device. The rotation drive device is communicatively connected to the analysis device. When the rotary drive device receives a control command from the analysis device to add a positive or negative lens in front of or behind the split-view frame, the rotary drive device controls the rotary drive device to drive the wheel to rotate, so that the geometric center of the positive or negative lens of the corresponding diopter is rotated to the optical axis position corresponding to the split-view frame.

6. The training system according to claim 4, characterized in that, The basic inspection module includes: The basic capability check unit is used to call the training image generation module to generate a training image with a split view pattern at the first offset distance and send it to the display device for display, and to determine whether the response information corresponding to the training image is received within a preset first viewing time, and whether the response information is correct. If so, increase the first offset distance of the training image by the first preset step size, and jump to the starting position of the basic set capability check unit, and check again according to the updated first offset distance; If not, determine whether the number of times the corresponding response information for the training image is not received within the preset first viewing time or the number of times the response information is incorrect is greater than or equal to 2; if not, maintain the first offset distance of the current training image and jump to the starting position of the basic ensemble capability check unit, and check again according to the current first offset distance; if yes, take the current first offset distance as the maximum value of the basic ensemble capability or the maximum value of the basic divergence capability. When the basic capability checking unit is used to check the maximum value of the user's basic set capability, the left-right position relationship of the red sub-view pattern and the blue sub-view pattern in the training image it generates is the same as the left-right position relationship of the red lens and the blue lens. When the basic ability checking unit is used to check the user's basic divergence maximum value, the left-right position relationship of the red and blue split-view patterns in the training image it generates is opposite to the left-right position relationship of the red and blue lenses.

7. The training system according to claim 4, characterized in that, The training module includes: an initialization unit, a single-set training unit, and a single-spread training unit; The initialization unit is used to set the initial value of the second offset distance to be the product of the maximum value of the basic aggregation capability and the first preset percentage, and to set the initial value of the third offset distance to be the product of the maximum value of the basic dispersion capability and the second preset percentage. The single-set training unit is used to call the training image generation module to generate a training image with a split view pattern of the second offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current second offset distance by a second preset step size and jumps to the single-spread training unit; if not, it... Keeping the current second offset distance unchanged, the training image generation module is called again to generate a training image with the split view pattern of the second offset distance and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current second offset distance is increased by a second preset step and the process jumps to the single spread training unit. If no, the current second offset distance is decreased by a third preset step and the process jumps to the single spread training unit. The single-shot divergence training unit is used to call the training image generation module to generate a training image with a split view pattern of the third offset distance and send it to the display device for display. It then determines whether the judgment condition is true; if so, it increases the current third offset distance by a fourth preset step and jumps to the single-shot ensemble training unit; if not, it... Keeping the current third offset distance unchanged, the training image generation module is called again to generate a training image with the third offset distance as the split view pattern and send it to the display device for display. It is determined whether the judgment condition is true. If yes, the current third offset distance is increased by a fourth preset step and the process jumps to the single set training unit. If no, the current third offset distance is decreased by a fifth preset step and the process jumps to the single set training unit. The determination condition is that the response information corresponding to the currently displayed training image is correct.

8. The training system according to claim 7, characterized in that, The training module also includes: A configuration unit is used to configure parameters in a single assembly training unit and a single divergence training unit based on preset training items; the training items include: assembly ability-focused training, divergence ability-focused training, and binocular balance training; When the training project is focused on ensemble ability training, the parameter configuration in the single ensemble training unit and the single divergence training unit is as follows: the second preset step size is greater than the third preset step size, the second preset step size is greater than the fourth preset step size, and the fourth preset step size is equal to the fifth preset step size. When the training project focuses on spreading ability training, the parameter configuration in the single assembly training unit and the single spreading training unit is as follows: the fourth preset step size is greater than the fifth preset step size, the fourth preset step size is greater than the second preset step size, and the second preset step size is equal to the third preset step size. When the training program is binocular balance training, the parameter configuration in the single convergence training unit and the single divergence training unit is as follows: the second preset step size, the third preset step size, the fourth preset step size, and the fifth preset step size are all equal.

9. The training system according to claim 7, characterized in that, The training module further includes: a first upgrade training unit and a second upgrade training unit; The first upgrade training unit is configured to, when both the second offset distance and the third offset distance reach a preset maximum value, reset the second offset distance to the ensemble training starting value, reset the third offset distance to the divergent training starting value, and reset the judgment condition to: receiving response information corresponding to the currently displayed training image within a preset second viewing time, and the response information corresponding to the currently displayed training image is correct; and, When both the second and third offset distances reach their preset maximum values ​​again, the second offset distance is reset to the ensemble training starting value, the third offset distance is reset to the spread training starting value, and the second viewing duration is reduced by a sixth preset step; and, When the second viewing time decreases to the preset minimum value, and the second offset distance and the third offset distance both reach the preset maximum value again, the process jumps to the second upgrade training unit. The second upgrade training unit is used to add a positive or negative lens with a preset diopter to the front or back of the split-vision frame.

10. The training system according to claims 4 to 9, characterized in that, The training image generation module includes: The image generation unit is configured to, based on the calls to the basic inspection module and the training module, respectively draw a red random dot plot and a blue random dot plot, insert a target pattern into the red random dot plot and the blue random dot plot in the same random direction, add red random dots above the target pattern of the red random dot plot to obtain a red split-view pattern, add blue random dots above the target pattern of the blue random dot plot to obtain a blue split-view pattern; and, based on the current first offset distance, second offset distance, or third offset distance, adjust the offset distance of the red split-view pattern and the blue split-view pattern to obtain a new training image for display.

Images