Trajectory analysis method, device and storage medium based on self-test vision chart

Abstract

The present invention relates to the technical field of eye chart trajectory generation, and specifically discloses a trajectory analysis method, device, and storage medium based on a self-test eye chart. The method comprises: determining a trainable range on the self-test eye chart based on a user's vision data; generating a training trajectory on the self-test eye chart based on the trainable range; controlling the self-test eye chart to perform a corresponding sight mark indication action based on a preset training time and the training trajectory; obtaining training feedback information from the user regarding the sight mark indication action; and storing the training feedback information. By determining the trainable range based on the user's vision data, a personalized training plan can be formulated based on each user's actual vision condition, making the training more targeted and improving the training effect.

Description

Technical Field

[0001] The present invention relates to the technical field of eye chart trajectory generation, and in particular to a trajectory analysis method, device and storage medium based on a self-test eye chart. Background Art

[0002] With the changes in modern lifestyles, people use electronic devices for a long time, resulting in increasingly common vision problems. Vision training is of great significance for improving vision and preventing vision loss. Traditional vision training methods often lack pertinence and scientificity, and it is difficult to formulate personalized training plans based on the user's actual vision conditions. Some existing vision training methods lack rationality in the design of training trajectories and cannot effectively train the flexibility of the user's eyeballs; in terms of training effect evaluation, there is also a lack of comprehensive and accurate feedback mechanisms, making it difficult to accurately understand the user's vision change trends and eye health conditions. Therefore, there is an urgent need for a vision training method that can conduct personalized training based on the user's vision data and effectively evaluate the training effect. Summary of the Invention

[0003] In order to overcome the above-mentioned technical problems existing in the prior art, the embodiments of the present invention provide a trajectory analysis method, device and storage medium based on a self-test vision chart. By determining the trainable range based on the user's vision data, a personalized training plan can be formulated according to the actual vision of each user, making the training more targeted and improving the training effect.

[0004] In order to achieve the above-mentioned purpose, an embodiment of the present invention provides a trajectory analysis method based on a self-test vision chart, the method comprising: determining a trainable range on the self-test vision chart based on the user's vision data; generating a training trajectory on the self-test vision chart based on the trainable range; controlling the self-test vision chart to perform a corresponding sight mark indication action based on a preset training time and the training trajectory; obtaining training feedback information from the user regarding the sight mark indication action; and storing the training feedback information.

[0005] Preferably, the determining of the trainable range on the self-test vision chart based on the user's vision data includes: determining a corresponding visual sight mark row based on the vision data; expanding the visual sight mark row based on a preset expansion rule to determine a minimum sight mark row; determining a maximum sight mark row, obtaining sight mark information of all sight marks from the minimum sight mark row to the maximum sight mark row, the five-point record value corresponding to the maximum sight mark row being smaller than the five-point record value corresponding to the minimum sight mark row; and determining the trainable range based on the sight mark information.

[0006] Preferably, generating a training track on the self-test vision chart based on the trainable range includes: determining the optotype position corresponding to each optotype based on the optotype information; generating a random position table based on the optotype position; and generating a training track based on the random position table.

[0007] Preferably, the method further includes: before generating a training trajectory based on the random position table, determining the eye movement amplitude based on the position of each visual mark in the random position table; judging whether the preset movement amplitude requirement is met based on the eye movement amplitude; if the preset movement amplitude requirement is not met, adjusting the random position table to generate a first adjusted random position table; and generating a training trajectory based on the first adjusted random position table.

[0008] Preferably, the method further includes: before generating a training trajectory based on the random position table, obtaining the frequency of occurrence of each sight mark in the random position table; judging whether there is a memory sight mark that is easy to remember based on a preset memory rule and the frequency of occurrence; if the memory sight mark exists, adjusting the random position table based on the preset memory rule to generate a second adjusted random position table; and generating a training trajectory based on the second adjusted random position table.

[0009] Preferably, the training feedback information includes the finger direction, and the method further includes: obtaining the indication direction of the indicator indicated by the visual mark indication action corresponding to the finger direction; obtaining the consistency between the finger direction and the indication direction; analyzing the user's vision change trend based on the consistency to generate a vision analysis result; storing and feeding back the vision analysis result.

[0010] Preferably, the training feedback information also includes eye tracking information, and the method further includes: determining the vision direction based on the eye tracking information; obtaining the position of the sight mark of the indicator indicated by the sight mark indicating action corresponding to the vision direction; obtaining the matching result between the vision direction and the sight mark position; performing strabismus analysis on the user based on the matching result to generate a strabismus analysis result; and storing and feeding back the strabismus analysis result.

[0011] Preferably, the method also includes: before determining the trainable range, determining the degree of blurred vision based on the vision data; determining the optimal contrast for vision training based on the degree of blurred vision; adjusting the display brightness of the self-test vision chart based on the optimal contrast; determining the optimal background color for vision training; and controlling the self-test vision chart to perform corresponding background color adjustment operations based on the optimal background color.

[0012] Correspondingly, the present invention also provides a trajectory analysis device based on a self-test vision chart, and the trajectory analysis device includes: a range determination module, used to determine the trainable range on the self-test vision chart based on the user's vision data; a trajectory generation module, used to generate a training trajectory on the self-test vision chart based on the trainable range; an indication module, used to control the self-test vision chart to perform a corresponding sight mark indication action based on a preset training time and the training trajectory; a feedback acquisition module, used to obtain the user's training feedback information for the sight mark indication action; and a storage module, used to store the training feedback information.

[0013] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the method provided by an embodiment of the present invention when the program is executed by a processor.

[0014] The technical solution provided by the present invention has at least the following technical effects:

[0015] 1. By determining the trainable range based on the user's vision data, a personalized training plan can be developed according to each user's actual vision, making the training more targeted and improving the training effect.

[0016] 2. During the training trajectory generation process, by analyzing and adjusting the amplitude of eye movements and the frequency of sight mark appearance, we ensure that the training trajectory can not only effectively train eye flexibility, but also prevent users from reducing training effectiveness due to memorizing the positions of sight marks, thereby improving the scientific nature and effectiveness of training.

[0017] 3. By obtaining training feedback information such as the user's finger direction and eye tracking information, it can analyze the user's vision change trend and strabismus, provide users with a comprehensive vision status assessment, and enable users to understand their eye health in a timely manner

[0018] 4. Adjust the display brightness and background color of the self-test eye chart according to the user's degree of blurred vision, providing users with a more comfortable and conducive visual environment for vision training, further improving training results.

[0019] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0021] Figure 1 This is a specific implementation flow chart of a trajectory analysis method based on a self-test vision chart provided in an embodiment of the present application;

[0022] Figure 2 Schematic diagram of the structure of a trajectory analysis device based on a self-test vision chart provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0024] The terms "system" and "network" in the embodiments of the present invention can be used interchangeably. "Multiple" refers to two or more. In view of this, "multiple" can also be understood as "at least two" in the embodiments of the present invention. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / ", unless otherwise specified, generally indicates that the previous and next associated objects are in an "or" relationship. In addition, it should be understood that in the description of the embodiments of the present invention, words such as "first" and "second" are only used to distinguish the purpose of description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0025] In existing technologies, self-testing eye charts usually have unified maximum values, minimum values, line spacing, etc., but due to the different personal conditions of different users, their usage needs are also different, so it is impossible to arbitrarily adjust them according to the usage needs of different users.

[0026] See Figure 1 , an embodiment of the present invention provides a trajectory analysis method based on a self-test vision chart, the method comprising:

[0027] S10: determining a trainable range on the self-test vision chart based on the user's vision data;

[0028] S20: generating a training track on the self-test vision chart based on the trainable range;

[0029] S30: controlling the self-test vision chart to perform corresponding sight mark indication actions based on the preset training time and the training trajectory;

[0030] S40: Obtaining training feedback information of the user regarding the sight mark indicating action;

[0031] S50: Storing the training feedback information.

[0032] In one embodiment, the current visible sight mark row is located by the naked eye vision value or historical training data input by the user, and then the minimum sight mark row that the user can train is determined according to the preset expansion rules, and finally the maximum sight mark row is combined to generate the user trainable range.

[0033] By determining the trainable range based on user vision data, personalized training plans can be developed based on each user's actual vision, making training more targeted and improving training effectiveness. Multimodal feedback enables quantitative evaluation of the training process. Conventional technology often determines the trainable range directly based on the user's vision. However, for users with poor vision, such as a 4.5 vision score, the trainable range is typically between 4.5 and 4.0. Because this range contains fewer sight marks and a smaller fluctuation range, the effectiveness of vision training is reduced, failing to meet the actual needs of businesses.

[0034] In actual use, on the one hand, users of different age groups will have different thresholds for vision fluctuations. For example, when watching electronic products for a long time, since the vision of teenagers is more easily affected than that of middle-aged and elderly people, teenagers' vision will generally experience a temporary decline, while middle-aged and elderly people will not experience a particularly obvious decline. In addition, different users' eye habits will also lead to different ranges of vision fluctuations. On the other hand, although users' vision cannot clearly see visual marks below their vision value, they can see the indicator lights for the visual marks. Therefore, in vision training scenarios, the trainable range can be appropriately expanded according to the user's vision to increase the range of eye movement and improve the training effect.

[0035] In an embodiment of the present invention, determining the trainable range on the self-test vision chart based on the user's vision data includes: determining a corresponding visual sight mark row based on the vision data; expanding the visual sight mark row based on a preset expansion rule to determine the minimum sight mark row; determining the maximum sight mark row, obtaining sight mark information of all sight marks from the minimum sight mark row to the maximum sight mark row, the five-point record value corresponding to the maximum sight mark row being smaller than the five-point record value corresponding to the minimum sight mark row; and determining the trainable range based on the sight mark information.

[0036] In one embodiment, the corresponding visual sight mark row is first determined based on the vision data input by the user. For example, if the user's current vision is 4.8, the visual sight mark row can be determined based on the corresponding relationship of the standard vision chart. Then, the visual sight mark row is expanded based on the preset expansion rules to determine the minimum sight mark row. The preset expansion rule can be to expand a certain number of rows downward on the basis of the visual sight mark row to cover sight marks of slightly lower difficulty, to ensure that the training has a certain degree of challenge and room for improvement, for example, 5.0 is selected as the minimum sight mark row. Next, the maximum sight mark row is determined. If the five-point record value corresponding to the maximum sight mark row is less than the five-point record value corresponding to the minimum sight mark row, the sight mark information of all sight marks from the minimum sight mark row to the maximum sight mark row is obtained, and finally the trainable range is determined based on the sight mark information. The specific number of lines to expand downward can be adjusted according to the user's age group. Because the vision of younger users varies greatly, their training range can be increased to better protect / recover and optimize their eyes. The vision of older users varies less, so their training range can be reduced to ensure that their eyes can be optimized in the best visual segment, which mainly plays a role in maintaining vision.

[0037] In this way, the range of visual marks suitable for training can be accurately determined according to the user's actual vision, personalized training can be achieved, and the range of visual marks can be adaptively adjusted according to the purpose of training required by the user's age group.

[0038] At this time, the sight mark is randomly selected within the trainable range to generate a trajectory sequence including the sight mark position, display duration, and switching path. In actual use, since the present invention is mainly used for vision training, it requires the user to move their eyes as much as possible during the training process, so the training trajectory on the eye chart also needs to be specially set.

[0039] In an embodiment of the present invention, generating a training trajectory on the self-test vision chart based on the trainable range includes: determining the sight mark position corresponding to each sight mark based on the sight mark information; generating a random position table based on the sight mark position; and generating a training trajectory based on the random position table.

[0040] In one possible implementation, based on all the visual mark information within the above-mentioned trainable range, the visual mark information includes but is not limited to the direction, position and other information of each visual mark, and then a random position table is generated according to the visual mark position. Since in the embodiment of the present invention, the time for vision training may be long (for example, 5 minutes of training is generally required), the random position table must contain some repeated visual marks, that is, each visual mark is randomly generated to ensure the randomness of the training and improve the training effect, and then a training trajectory is generated according to the random position table.

[0041] However, in actual application, the purpose of this scheme is to achieve the best strength training effect, but the randomly generated random position table will inevitably have two or more adjacent sight marks close to each other, which will greatly reduce the amplitude of eye movement and reduce the vision training effect.

[0042] In order to solve the above technical problems, in an embodiment of the present invention, the method also includes: before generating a training trajectory based on the random position table, determining the eye movement amplitude based on the position of each visual mark in the random position table; judging whether the preset movement amplitude requirement is met based on the eye movement amplitude; if the preset movement amplitude requirement is not met, adjusting the random position table to generate a first adjusted random position table; and generating a training trajectory based on the first adjusted random position table.

[0043] In one possible implementation, after obtaining the random position table, the eye movement amplitude is further determined based on each sight mark position in the random position table. Specifically, the corresponding eye angle is determined based on the user's standing position (generally 5 meters in front of the self-test eye chart) and the sight mark position, and then the eye movement amplitude is determined based on the change in the sight mark position. Based on the eye movement amplitude, it is determined whether the preset movement amplitude requirement is met. For example, in an embodiment of the present invention, assuming that the horizontal spacing between two adjacent sets of sight marks is 10 cm, the eye rotation angle is 5° when observing the two sets of sight marks. Based on the above setting, the preset movement amplitude requirement in this embodiment is 10°, that is, the minimum spacing between two adjacent sight marks is 1 line. This can more likely enable the user to maintain a wide range of eye movement during training, thereby achieving a better training effect.

[0044] Based on this, if it is found that there are sight mark positions in the random position table that do not meet the preset movement amplitude requirements, the random position table is adjusted according to the preset movement amplitude requirements to generate a first adjusted random position table, and further generate a corresponding training trajectory, thereby ensuring sufficient training effect on the eyeballs during the training process.

[0045] However, in actual application, technicians found that if a certain sight mark appears too frequently, for example, 5 times within 1 minute, the direction and position of the sight mark may be remembered by the user. In subsequent training or testing, even if the user's eyesight deteriorates, they can still "get away with it", thereby reducing the training and testing effect.

[0046] In order to solve the above technical problems, in an embodiment of the present invention, the method further includes: before generating a training trajectory based on the random position table, obtaining the frequency of occurrence of each visual mark in the random position table; judging whether there is a memory visual mark that is easy to remember based on the preset memory rules and the frequency of occurrence; if the memory visual mark exists, adjusting the random position table based on the preset memory rules to generate a second adjusted random position table; and generating a training trajectory based on the second adjusted random position table.

[0047] In one possible implementation, based on the generated random position table, the frequency of occurrence of each optotype in the random position table is further detected. A determination is made based on preset memory rules to determine whether there are any easily memorized optotypes, such as those with a frequency of less than 10 occurrences per half minute or less than 2 occurrences per 10 optotypes. If a memorized optotype exists, it is immediately adjusted and a training trajectory is further generated, such as by replacing it with an optotype that appears less frequently to reduce the user's memorization effect.

[0048] In an embodiment of the present invention, by further adjusting the generated random vision chart according to the user's memory effect, the phenomenon of the visual signs being remembered by the user can be effectively avoided, thereby improving the accuracy and reliability of subsequent user vision training and testing.

[0049] After the training trajectory is generated, when the training begins, the target sight mark is highlighted by the LED module of the vision chart according to the training trajectory within the preset training time, and / or the target sight mark is indicated by a dynamic indicator mark. The preset training time can be a fixed time, preferably, the fixed time is 5-10 minutes, and can also be customized according to the user's vision data. For example, the higher the user's vision score, the longer the training time, and the lower the vision score, the shorter the training time. In the process of indicating the sight mark, the user's training feedback information for the sight mark indication action is also obtained in real time. The training feedback information includes but is not limited to the user's gesture action information, eye movement information, sound feedback information, and body movement information. For example, in one embodiment, the user identifies the finger direction through a gesture recognition device or captures the viewpoint coordinates through an eye tracking camera, and obtains training feedback information, wherein the training feedback information includes response time (the time difference from the display of the sight mark to the user's response), direction accuracy, etc. After obtaining the training feedback information, it is stored for subsequent analysis of the training effect and tracking and analysis of the user's vision changes. For example, it is used to establish a user training database, record the feedback data of each visual mark in each training, and generate a vision change curve chart through time series analysis to evaluate the training effect.

[0050] In an embodiment of the present invention, the training feedback information includes the finger direction, and the method further includes: obtaining the indication direction of the indicator indicated by the visual mark indication action corresponding to the finger direction; obtaining the consistency between the finger direction and the indication direction; analyzing the user's vision change trend based on the consistency to generate a vision analysis result; and storing and feeding back the vision analysis result.

[0051] In one possible implementation, the direction of the sight mark indicated by the sight mark indicating action corresponding to the finger direction is obtained, the consistency between the finger direction and the marked direction is obtained, and the user's vision change trend is analyzed based on the consistency to generate a vision analysis result. For example, according to the previous test results, the user's vision value is 4.8. During this vision training process, it is found that the user can also have a certain degree of recognition accuracy for the 4.9 sight mark, and the recognition accuracy is gradually increasing with the increase in the number of training sessions. Therefore, the user's strength change trend can be generated, and the corresponding analysis results can be generated, which is convenient for subsequent tracking of the user's strength and dynamic adjustment of treatment or training plans, and for enterprises to collect more vision optimization methods and phenomena, improve the subsequent vision treatment effect, and meet the actual needs of enterprises.

[0052] Furthermore, in an embodiment of the present invention, the training feedback information also includes eye tracking information, and the method also includes: determining the vision direction based on the eye tracking information; obtaining the position of the sight mark of the indicator indicated by the sight mark indication action corresponding to the vision direction; obtaining the matching result of the vision direction and the sight mark position; performing strabismus analysis on the user based on the matching result to generate a strabismus analysis result; and storing and feeding back the strabismus analysis result.

[0053] In one possible implementation, the visual direction is determined based on eye tracking information, the position of the optotype indicated by the optotype indicating action corresponding to the visual direction is obtained, a matching result between the visual direction and the optotype position is obtained, and a strabismus analysis is performed on the user based on the matching result to generate a strabismus analysis result. For example, if the eye tracking data reveals a deviation between the angle between the optotype position and the eye and the actual rotation angle of the eye, for example, if the deviation reaches 3°, then the user may be determined to be at risk of strabismus, and a strabismus warning may be immediately generated and fed back.

[0054] In an embodiment of the present invention, by obtaining training feedback information such as the user's finger direction and eye tracking information, the user's vision change trend and strabismus situation can be analyzed, and a comprehensive vision status assessment can be provided to the user, so that the user can understand his or her eye health status in a timely manner. At the same time, it can facilitate doctors to detect the user's eye defects early and follow up on treatment, so that the user's defects can be quickly optimized and resolved in the early stages, thereby improving the treatment efficacy.

[0055] In actual use, different contrasts will have different degrees of impact on the user's vision training, and appropriately increasing the contrast according to the user's own degree of blurred vision can also enable the user to increase his or her own visual range, thereby increasing the training range, which can effectively improve the training effect.

[0056] In an embodiment of the present invention, the method also includes: before determining the trainable range, determining the degree of blurred vision based on the vision data; determining the optimal contrast for vision training based on the degree of blurred vision; adjusting the display brightness of the self-test vision chart based on the optimal contrast; determining the optimal background color for vision training; and controlling the self-test vision chart to perform corresponding background color adjustment operations based on the optimal background color.

[0057] In one possible implementation, before determining the trainable range, the degree of blurred vision is determined based on the vision data, and the optimal contrast for vision training is determined based on the blurred vision. The display brightness of the self-testing eye chart is adjusted based on the optimal contrast. For example, the contrast design can be as follows: the corresponding visual target row is determined based on the vision data input by the user as the basic target row, and the background contrast is linearly increased toward the maximum target row and the minimum target row with the basic target row as the anchor point, and the contrast difference between adjacent rows is less than or equal to 10%. Then, the optimal background color for vision training is determined. Specifically, in the field of vision testing, the optimal background color is white and the target is black. However, in the field of vision training, because green light is the softest on vision, it has the best vision training effect. Therefore, the background color of the self-testing eye chart can be set to green. In the subsequent display process, the self-testing eye chart is controlled based on the optimal background color to perform corresponding background color adjustment operations.

[0058] By adjusting the display brightness and background color, on the one hand, the contrast of the display is increased to improve the range in which users can clearly see the actions indicated by the sight marks, thereby allowing the trainable range to be further expanded, so that the user's vision training range is further expanded. Especially for users with poor eyesight, they are not limited to the few rows of sight marks at the top of the self-test eye chart, but can also conduct vision training within a larger range of sight marks, thereby further improving the vision training effect. At the same time, combined with a softer background color, it can effectively relieve visual pressure, provide users with a more comfortable and more conducive visual environment for vision training, and further improve the training effect.

[0059] A trajectory analysis device based on a self-test vision chart provided by an embodiment of the present invention will be described below with reference to the accompanying drawings.

[0060] See Figure 2Based on the same inventive concept, an embodiment of the present invention provides a trajectory analysis device including: a range determination module, used to determine a trainable range on the self-test vision chart based on the user's vision data; a trajectory generation module, used to generate a training trajectory on the self-test vision chart based on the trainable range; an indication module, used to control the self-test vision chart to perform a corresponding sight mark indication action based on a preset training time and the training trajectory; a feedback acquisition module, used to obtain training feedback information of the user for the sight mark indication action; and a storage module, used to store the training feedback information.

[0061] Furthermore, an embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which implements the method described in the embodiment of the present invention when the program is executed by a processor.

[0062] The above describes in detail the optional implementation methods of the embodiments of the present invention in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above implementation methods. Within the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the scope of protection of the embodiments of the present invention.

[0063] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0064] Those skilled in the art will understand that all or part of the steps in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a program. The program is stored in a storage medium and includes a number of instructions for causing a single-chip microcomputer, chip, or processor to execute all or part of the steps in the methods described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0065] In addition, various implementations of the embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A trajectory analysis method based on a self-test vision chart, characterized in that: The method comprises: determining a trainable range on the self-test vision chart based on the user's vision data; generating a training track on the self-test vision chart based on the trainable range; Controlling the self-test vision chart to perform corresponding sight mark indicating actions based on the preset training time and the training trajectory; Obtaining training feedback information from the user regarding the action indicated by the sight mark; storing the training feedback information; The determining of the trainable range on the self-test vision chart based on the user's vision data includes: Determining a corresponding row of visual targets based on the vision data; Expanding the visible optotype row based on a preset expansion rule to determine a minimum optotype row; Determine the maximum optotype row, obtain optotype information of all optotypes from the minimum optotype row to the maximum optotype row, wherein the five-point record value corresponding to the maximum optotype row is smaller than the five-point record value corresponding to the minimum optotype row; determining a trainable range based on the visual mark information; The method of generating a training trajectory on the self-test vision chart based on the trainable range includes: determining the position of each sight mark corresponding to each sight mark based on the sight mark information; generating a random position table based on the sight mark position; determining the eye movement amplitude based on the position of each sight mark in the random position table, judging whether the eye movement amplitude meets the preset movement amplitude requirement based on the eye movement amplitude, and if not, adjusting the random position table to generate a first adjusted random position table, and generating a training trajectory based on the first adjusted random position table.

2. The method according to claim 1, characterized in that The method further comprises: Before generating a training trajectory based on the random position table, obtaining the frequency of occurrence of each visual mark in the random position table; Determining whether there is a memory sight mark that is easy to remember based on the preset memory rules and the frequency of occurrence; If the memory sight mark exists, adjusting the random position table based on the preset memory rule to generate a second adjusted random position table; A training trajectory is generated based on the second adjusted random position table.

3. The method according to claim 1, characterized in that The training feedback information includes finger direction, and the method further includes: Obtaining the direction of the indicator indicated by the visual mark indicating action corresponding to the finger direction; Obtaining consistency between the finger direction and the marked direction; Analyzing the user's vision change trend based on the consistency and generating a vision analysis result; The vision analysis results are stored and fed back.

4. The method according to claim 1, wherein The training feedback information further includes eye tracking information, and the method further includes: determining a vision direction based on the eye tracking information; Acquiring the position of the sight mark of the indicator indicated by the sight mark indicating action corresponding to the vision direction; Obtaining a matching result between the visual direction and the sight mark position; Performing a squint analysis on the user based on the matching result to generate a squint analysis result; The strabismus analysis result is stored and fed back.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: Before determining the trainable range, determining a degree of blurred vision based on the vision data; determining an optimal contrast for performing vision training based on the degree of blurred vision; adjusting the display brightness of the self-testing vision chart based on the optimal contrast; Determine the best background color for vision training; The self-test vision chart is controlled to perform a corresponding background color adjustment operation based on the optimal background color.

6. A trajectory analysis device based on a self-test vision chart, characterized in that: The method according to any one of claims 1 to 5, wherein the training device comprises: A range determination module is configured to determine a trainable range on the self-testing vision chart based on the user's vision data; the range determination module comprising: Determining a corresponding row of visual targets based on the vision data; Expanding the visible optotype row based on a preset expansion rule to determine a minimum optotype row; Determine the maximum optotype row, obtain optotype information of all optotypes from the minimum optotype row to the maximum optotype row, wherein the five-point record value corresponding to the maximum optotype row is smaller than the five-point record value corresponding to the minimum optotype row; determining a trainable range based on the visual mark information; A trajectory generation module is configured to generate a training trajectory on the self-test vision chart based on the trainable range, wherein the generating of the training trajectory on the self-test vision chart based on the trainable range includes: determining an optotype position corresponding to each optotype based on the optotype information; generating a random position table based on the optotype position; determining an eye movement amplitude based on the position of each optotype in the random position table; determining whether a preset movement amplitude requirement is met based on the eye movement amplitude; if not, adjusting the random position table to generate a first adjusted random position table; and generating a training trajectory based on the first adjusted random position table. An indication module, configured to control the self-test vision chart to perform a corresponding sight mark indication action based on a preset training time and the training trajectory; A feedback acquisition module, used to obtain training feedback information of the user for the sight mark indication action; A storage module is used to store the training feedback information.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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