Visual fatigue evaluation system construction method and device

Abstract

The invention relates to an asthenopia evaluation system construction method and device. The method comprises the following steps: acquiring asthenopia test data of a plurality of tested objects in different test environments; drawing an asthenopia index comparison map according to the asthenopia test data of each tested object and a plurality of candidate asthenopia evaluation indexes; the asthenopia index comparison map is used for representing data differences of the candidate asthenopia evaluation indexes in the different test environments; based on a data statistical result of the visual fatigue index comparison map, screening the plurality of candidate visual fatigue evaluation indexes to obtain a target visual fatigue evaluation index; the target asthenopia evaluation index is used for constructing the asthenopia evaluation system. By adopting the method, the evaluation standard can be objectively quantified, and the systematic evaluation system is constructed for the standard range of the test index.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and particularly to a method, device, computer device, computer-readable storage medium, and computer program product for constructing a visual fatigue evaluation system. Background Art

[0002] With the development of electronic products, visual fatigue caused by long-term use of electronic screens has become increasingly common. Visual fatigue can lead to discomfort symptoms such as dry eyes, blurred vision, dizziness, headache, intolerance to long-term vision, and sore and tearful eyes, and can also cause various psychological diseases such as insomnia and irritability, seriously affecting the work and quality of life of visual fatigue patients.

[0003] There are many factors causing visual fatigue, including factors such as eye function, physical constitution, mental state, and environment, and the influencing factors of visual fatigue have great variability. For visual fatigue, it is usually judged manually according to the severity of symptoms, which is difficult to measure quantitatively and lacks objective and clear evaluation criteria. Therefore, how to construct a visual fatigue evaluation system is an urgent problem to be solved at present. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for constructing a visual fatigue evaluation system that can objectively quantify the evaluation criteria.

[0005] In a first aspect, the present application provides a method for constructing a visual fatigue evaluation system, the method comprising:

[0006] Obtaining visual fatigue test data of multiple test subjects in different test environments;

[0007] According to the visual fatigue test data of each test subject and multiple candidate visual fatigue evaluation indicators, drawing a visual fatigue index comparison map; the visual fatigue index comparison map is used to characterize the data differences of the multiple candidate visual fatigue evaluation indicators in different test environments;

[0008] Based on the data statistical results of the visual fatigue index comparison map, screening the multiple candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators; the target visual fatigue evaluation indicators are used to construct the visual fatigue evaluation system.

[0009] In one of the embodiments, the multiple candidate visual fatigue evaluation indicators include a contrast sensitivity index, a flicker fusion frequency index, and a blink frequency index. The drawing of the visual fatigue index comparison map according to the visual fatigue test data of each test subject and the multiple candidate visual fatigue evaluation indicators includes:

[0010] For the contrast sensitivity index, the mean value of the area under the contrast sensitivity curve in each of the test environments is determined using the visual fatigue test data of each of the test subjects.

[0011] For the flicker fusion frequency index, the mean value of the flicker fusion frequency in each of the test environments is determined using the visual fatigue test data of each of the test subjects.

[0012] For the blink frequency index, the mean value of the blink frequency in each of the test environments is determined using the visual fatigue test data of each of the test subjects.

[0013] Based on the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blink frequency in multiple test environments, the contrast atlas of the visual fatigue index is integrated.

[0014] In one embodiment, the visual fatigue test data includes contrast sensitivity test data. The step of determining the mean value of the area under the contrast sensitivity curve in each of the test environments using the visual fatigue test data of each of the test subjects includes:

[0015] According to the contrast sensitivity test data of each of the test subjects, a contrast sensitivity curve of each of the test subjects in each of the test environments is generated.

[0016] Based on the contrast sensitivity curves of each of the test subjects, the mean value of the area under the contrast sensitivity curve in each of the test environments is determined.

[0017] In one embodiment, the visual fatigue test data further includes flicker fusion frequency test data. The step of determining the mean value of the flicker fusion frequency in each of the test environments using the visual fatigue test data of each of the test subjects includes:

[0018] According to the flicker fusion frequency test data of each of the test subjects, the flicker fusion critical frequency of each of the test subjects in each of the test environments is determined.

[0019] Based on the flicker fusion critical frequencies of each of the test subjects, the mean value of the flicker fusion frequency in each of the test environments is obtained.

[0020] In one embodiment, the visual fatigue test data further includes blink video data. The step of determining the mean value of the blink frequency in each of the test environments using the visual fatigue test data of each of the test subjects includes:

[0021] According to the blink video data of each of the test subjects, the blink frequency of each of the test subjects in each of the test environments is determined.

[0022] Based on the blink frequencies of each of the test subjects, the mean value of the blink frequency in each of the test environments is obtained.

[0023] In one embodiment, the method for screening a plurality of candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators based on the data statistical results of the visual fatigue index comparison atlas includes:

[0024] Performing repeated measures analysis of variance based on the visual fatigue index comparison atlas to obtain data statistical results;

[0025] According to the data statistical results, determining the contrast sensitivity index and the flicker fusion frequency index whose index data vary significantly with the electronic screen usage time as the target visual fatigue evaluation indicators.

[0026] In a second aspect, the present application further provides a device for constructing a visual fatigue evaluation system, the device includes:

[0027] A test data acquisition module, configured to acquire visual fatigue test data of a plurality of test subjects under different test environments;

[0028] A comparison atlas drawing module, configured to draw a visual fatigue index comparison atlas according to the visual fatigue test data of each test subject and a plurality of candidate visual fatigue evaluation indicators; the visual fatigue index comparison atlas is used to characterize the data differences of the candidate visual fatigue evaluation indicators under different test environments;

[0029] A target evaluation index acquisition module, configured to screen and process the plurality of candidate visual fatigue evaluation indicators based on the data statistical results of the visual fatigue index comparison atlas to obtain target visual fatigue evaluation indicators; the target visual fatigue evaluation indicators are used to construct the visual fatigue evaluation system.

[0030] In a third aspect, the present application further provides a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0031] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0032] In a fifth aspect, the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0033] The above method, device, computer device, computer-readable storage medium, and computer program product for constructing a visual fatigue evaluation system obtain visual fatigue test data of multiple test subjects in different test environments, draw a comparison atlas of visual fatigue indicators according to the visual fatigue test data of each test subject and multiple candidate visual fatigue evaluation indicators. The comparison atlas of visual fatigue indicators is used to characterize the data differences of each candidate visual fatigue evaluation indicator in different test environments. Based on the statistical results of the comparison atlas of visual fatigue indicators, screening processing is performed on multiple candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators, which are used to construct a visual fatigue evaluation system, realizing the construction of an evaluation system for the standard range of test indicators, being able to objectively quantify the evaluation criteria, and helping to improve the accuracy of visual fatigue evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for the description in the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0035] Figure 1 It is a schematic flow chart of a method for constructing a visual fatigue evaluation system in an embodiment;

[0036] Figure 2 It is a schematic diagram of a test environment in an embodiment;

[0037] Figure 3 It is a schematic diagram of a contrast sensitivity index test in an embodiment;

[0038] Figure 4 It is a schematic diagram of a critical flicker fusion frequency index test in an embodiment;

[0039] Figure 5a It is a schematic diagram of a contrast sensitivity index comparison chart in an embodiment;

[0040] Figure 5b It is a schematic diagram of a critical flicker fusion frequency index comparison chart in an embodiment;

[0041] Figure 5c It is a schematic diagram of a blink frequency index comparison chart in an embodiment;

[0042] Figure 5d It is a schematic diagram of another blink frequency index comparison chart in an embodiment;

[0043] Figure 6 It is a schematic flow chart of a method for constructing a visual fatigue evaluation system in another embodiment;

[0044] Figure 7 It is a structural block diagram of a device for constructing a visual fatigue assessment system in an embodiment;

[0045] Figure 8 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0046] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] In an exemplary embodiment, as Figure 1 shown, a method for constructing a visual fatigue assessment system is provided. In this embodiment, an example is given where this method is applied to a terminal. It can be understood that this method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps 101 to 103. Among them:

[0048] Step 101, obtaining visual fatigue test data of multiple test subjects under different test environments;

[0049] As an example, the test environment can be different indoor environments. For example, different environmental factors such as temperature, humidity, wind speed, wind force, and environmental brightness are set in the indoor environment for testing.

[0050] Among them, the visual fatigue test data can include contrast sensitivity test data, flicker fusion frequency test data, blink video data, and can also include other test data related to visual fatigue, which is not specifically limited in this embodiment.

[0051] In practical applications, multiple test subjects (i.e., multiple test objects) can be selected for visual fatigue testing based on factors such as gender, age, vision or corrected vision. Exemplarily, as Figure 2 shown, the test subjects can wear frame glasses throughout the process and conduct tests in a dark room environment with the best corrected vision; by obtaining the visual fatigue test data of each test subject, the influence of the electronic screen time on the evaluation of visual fatigue indicators under different indoor environments can be compared. Different test environments can be as shown in Table 1:

[0052] Table 1 Test conditions

[0053]

[0054] In one example, under all conditions, the indoor temperature can be set to remain at 26.0 °C, and the humidity can be set to 40% and 60%; specifically, under the condition of 40% humidity, a fan can be used to blow a gentle breeze towards the subject's face, and the wind speed can be 1.3 m / s; there is no wind under 60% humidity. During the experiment, the subject is in a dark room environment throughout the process. An opaque black curtain is used to separate the experimenter from the subject. The experimenter can record the blink video data of the subject during the test through an infrared camera and analyze the blink frequency offline.

[0055] In another example, after adapting to the dark room environment for 5 minutes, the subject can use an electronic device to watch the images on the electronic screen for 120 minutes throughout the process; CSF (contrast sensitivity curve) and flicker fusion frequency tests can be performed at 0 minutes, 30 minutes, 60 minutes, 90 minutes, and 120 minutes of eye use respectively, and the infrared monitoring can be used to record the subject's blinking situation during the test. Optionally, the subject's responses in the contrast sensitivity and flicker fusion frequency tests can be collected through a mouse and keyboard.

[0056] Step 102: According to the visual fatigue test data of each of the test subjects and multiple candidate visual fatigue evaluation indicators, draw a visual fatigue index comparison map.

[0057] As an example, the multiple candidate visual fatigue evaluation indicators can include contrast sensitivity indicators, flicker fusion frequency indicators, blink frequency indicators, and can also include other evaluation indicators related to visual fatigue, which are not specifically limited in this embodiment.

[0058] Among them, the visual fatigue index comparison map can be used to characterize the data differences of each candidate visual fatigue evaluation indicator under different test environments.

[0059] In a specific implementation, the contrast sensitivity test data, flicker fusion frequency test data, and blink video data of each test subject can be used to perform data statistical processing based on the contrast sensitivity indicator, flicker fusion frequency indicator, and blink frequency indicator, and draw a visual fatigue index comparison map. For example, a comparison map of indicator data under different test environments can be obtained for each candidate visual fatigue evaluation indicator.

[0060] Step 103: Based on the data statistical results of the visual fatigue index comparison map, perform a screening process on the multiple candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators; the target visual fatigue evaluation indicators are used to construct the visual fatigue evaluation system.

[0061] After obtaining the visual fatigue index comparison atlas, statistical analysis can be performed on the visual fatigue index comparison atlas, and then multiple candidate visual fatigue evaluation indicators can be screened according to the data statistical results. The contrast sensitivity index and the flicker fusion frequency index, for which the index data change significantly with the electronic screen usage time, are used as the target visual fatigue evaluation indicators to construct a visual fatigue evaluation system.

[0062] Compared with the traditional method, the technical solution of this embodiment can draw the visual fatigue index and electronic screen usage time atlas of the subjects by means of the test methods and technical requirements based on the contrast sensitivity curve and the flicker fusion frequency, and design special experimental scenarios (such as controlling humidity, temperature, illuminance, wind speed, etc.). It has established an evaluation standard for visual fatigue measurement indicators, and can construct a systematic evaluation system for the standard range of the indicators measured by the test method, so as to objectively quantify the influence degree of the corresponding detection indicators on visual fatigue judgment, and provide an effective basis for evaluating the sensitivity and reference value of the detection indicators in the test method for visual fatigue.

[0063] In the above method for constructing a visual fatigue evaluation system, by obtaining the visual fatigue test data of multiple test subjects under different test environments, and then according to the visual fatigue test data of each test subject and multiple candidate visual fatigue evaluation indicators, a visual fatigue index comparison atlas is drawn. Furthermore, based on the data statistical results of the visual fatigue index comparison atlas, multiple candidate visual fatigue evaluation indicators are screened to obtain the target visual fatigue evaluation indicators, realizing the construction of a systematic evaluation system for the standard range of the test indicators, being able to objectively quantify the evaluation criteria, and helping to improve the accuracy of visual fatigue evaluation.

[0064] In an exemplary embodiment, the multiple candidate visual fatigue evaluation indicators include a contrast sensitivity index, a flicker fusion frequency index, and a blink frequency index. The steps of drawing the visual fatigue index comparison atlas according to the visual fatigue test data of each test subject and multiple candidate visual fatigue evaluation indicators may include the following:

[0065] For the contrast sensitivity index, use the visual fatigue test data of each test subject to determine the mean value of the area under the contrast sensitivity curve in each test environment; for the flicker fusion frequency index, use the visual fatigue test data of each test subject to determine the mean value of the flicker fusion frequency in each test environment; for the blink frequency index, use the visual fatigue test data of each test subject to determine the mean value of the blink frequency in each test environment; integrate the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blink frequency in multiple test environments to obtain the visual fatigue index comparison atlas.

[0066] In practical applications, contrast sensitivity is a characteristic index for measuring the ability of a subject to distinguish spatial contrast. For the quick contrast sensitivity function (qCSF), that is, the contrast sensitivity index, the contrast sensitivity curve (CSF) of the subject at different test time points can be obtained through a quick contrast sensitivity measurement algorithm. Then, by calculating the area under the contrast sensitivity curve (AULCSF), the degree of visual fatigue of the subject can be understood. For example, when the value of the area under the contrast sensitivity curve decreases, it can indicate that the subject has visual fatigue.

[0067] The flicker fusion frequency is also known as the critical flicker frequency or the critical fusion frequency (critical flicker frequency), which can reflect the limit of the visual system's ability to distinguish time and the level of people's ability to distinguish flickers. For the flicker fusion frequency index, the degree of visual fatigue of the subject can be understood by measuring the critical flicker frequency. For example, the larger the value of the flicker fusion threshold, the relatively higher the degree of visual fatigue can be represented.

[0068] In the test, an infrared camera is used to record the blinking situation of the subject, and the blinking frequency of each subject is analyzed offline. For the blinking frequency index, the blinking frequency can be defined as the number of blinks within 1 minute. For example, the larger the blinking frequency, the relatively higher the degree of visual fatigue can be represented.

[0069] In an example, based on the results of the change of the mean value of the area under the contrast sensitivity curve, the change of the mean value of the flicker fusion frequency, and the change of the mean value of the blinking frequency over time in different test environments, a contrast map of visual fatigue indicators can be obtained, such as a comparison chart of the index data of each candidate visual fatigue evaluation index in different test environments.

[0070] In this embodiment, for the contrast sensitivity index, the mean value of the area under the contrast sensitivity curve in each test environment is determined by using the visual fatigue test data of each subject. For the flicker fusion frequency index, the mean value of the flicker fusion frequency in each test environment is determined by using the visual fatigue test data of each subject. For the blinking frequency index, the mean value of the blinking frequency in each test environment is determined by using the visual fatigue test data of each subject. Furthermore, a contrast map of visual fatigue indicators is integrated based on the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blinking frequency in multiple test environments, providing data support for further constructing a systematic index evaluation system and being able to effectively quantify the evaluation criteria.

[0071] In an exemplary embodiment, the visual fatigue test data includes contrast sensitivity test data, and the method of using the visual fatigue test data of each of the test subjects to determine the mean area under the contrast sensitivity curve under each of the test environments may include the following steps:

[0072] According to the contrast sensitivity test data of each of the subjects, a contrast sensitivity curve of each of the subjects under each of the test environments is generated; based on the contrast sensitivity curve of each of the subjects, a mean area under the contrast sensitivity curve under each of the test environments is determined.

[0073] In a specific implementation, contrast sensitivity testing can be performed using a sinusoidal grating orientation discrimination task. For example, the stimulus used in the test can be a sinusoidal grating rotated 45° clockwise (-) / counterclockwise (+) relative to vertical 90°.

[0074] For example, Figure 3 As shown, in one trial of the test, the program first gives a short prompt sound, and then a cross cursor will appear in the center of the screen for 250ms to indicate the central fixation point, and then a blank screen will be presented for 375ms (at this time, it is a gray screen), and then a target stimulus of 167ms will appear (such as a grating in either clockwise or counterclockwise direction), and then after the stimulus presentation, a blank screen will be presented for 500ms (at this time, it is a gray screen), and then the subject can be waited for to judge the direction of the target stimulus (grating) to obtain the contrast sensitivity test data of each subject. For example, if the subject perceives that the grating is in a counterclockwise direction, he can press the "left key" on the keyboard, and if he perceives that the grating is in a clockwise direction, he can press the "right key" on the keyboard.

[0075] In an optional embodiment, for different trials, the spatial frequency and contrast of the grating can be automatically selected according to the Bayesian adaptive algorithm, so that the contrast sensitivity curve can be measured quickly and accurately. Among them, the sampling range of the spatial frequency can be 0.5 to 20 cycles / degree, which can be divided into 16 value points in logarithmic units; the contrast range can be 0 to 100%. The measurement of each contrast sensitivity curve can include 100 trials and takes about 5 minutes to complete.

[0076] In this embodiment, by generating a contrast sensitivity curve for each subject under each test environment based on the contrast sensitivity test data of each subject, and then based on the contrast sensitivity curve of each subject, determining the mean area under the contrast sensitivity curve under each test environment, data support is provided for further establishing an evaluation standard for contrast sensitivity indicators.

[0077] In an exemplary embodiment, the visual fatigue test data further includes flicker fusion frequency test data. Determining the mean flicker fusion frequency under each test environment by using the visual fatigue test data of each subject may include the following steps:

[0078] Based on the flicker fusion frequency test data of each subject, determine the flicker fusion critical frequency of each subject under each test environment; based on the flicker fusion critical frequency of each subject, obtain the mean flicker fusion frequency under each test environment.

[0079] In practical applications, the stimulus used in the flicker fusion frequency test can be a circular light spot. For example, the gray value of the light spot is 0.3, the size is 1.23° in diameter, and the position is 1.5° to the left / right of the center point of the cross. As Figure 4 shown, in one trial of the test, first, a brighter cross (such as a gray value of 0.9) will be presented in the center of the screen for 800 ms, and then the cross will become darker (such as a gray value of 0.3), indicating that the stimulus is about to appear; after the cross becomes darker for 1000 - 1500 ms, a light spot stimulus will appear.

[0080] Specifically, in different trials, the light spot stimulus event can randomly flash twice or once. The subject judges the number of stimulus flashes according to the instruction: 1. When a light spot stimulus of 8 ms is presented between two light spot stimulus events, since the light spot stimulus is presented continuously, the subject perceptually perceives it as 1 flash; 2. When a cross with a gray value of 0.3 is presented between two light spot stimulus times, the subject perceptually perceives it as 2 flashes. The cross presentation time (such as the interval time between two light spot stimulus events, ISI) is controlled by the staircase method (3-up / 1-down), and then the minimum ISI value required for the subject to correctly report two flashes can be obtained, such as the subject's flicker fusion threshold, that is, the flicker fusion frequency test data of each subject. The test can include 100 trials (two flashes × 80 + one flash × 20), and each experiment is completed in about 5 minutes.

[0081] In this embodiment, by determining the flicker fusion critical frequency of each subject under each test environment according to the flicker fusion frequency test data of each subject, and then obtaining the mean flicker fusion frequency under each test environment based on the flicker fusion critical frequency of each subject, it provides data support for further establishing the evaluation criteria for the flicker fusion frequency index.

[0082] In an exemplary embodiment, the visual fatigue test data further includes blink video data. Determining the mean blink frequency under each test environment by using the visual fatigue test data of each subject may include the following steps:

[0083] Based on the blink video data of each subject, determine the blink frequency of each subject in each test environment; based on the blink frequency of each subject, obtain the average blink frequency in each test environment.

[0084] In one example, by using an infrared camera during the test to record the blinking situation of the subjects, the blink video data of each subject can be obtained. Furthermore, the blink frequency of each subject can be analyzed based on this blink video data. For example, if the blink frequency is defined as the number of blinks within 1 minute, the greater the blink frequency, the relatively higher the degree of visual fatigue can be represented.

[0085] In this embodiment, by determining the blink frequency of each subject in each test environment based on the blink video data of each subject, and then obtaining the average blink frequency in each test environment based on the blink frequency of each subject, it provides data support for further establishing the evaluation criteria of the blink frequency index.

[0086] In an exemplary embodiment, the step of screening the multiple candidate visual fatigue evaluation indicators based on the data statistical results of the visual fatigue index comparison atlas to obtain the target visual fatigue evaluation indicator may include the following steps:

[0087] Perform repeated measures analysis of variance based on the visual fatigue index comparison atlas to obtain the data statistical results; according to the data statistical results, determine the contrast sensitivity index and the flicker fusion frequency index whose index data changes significantly with the use time of the electronic screen as the target visual fatigue evaluation indicators.

[0088] In practical applications, by statistically analyzing the area under the contrast sensitivity curve, flicker fusion frequency, and blink frequency obtained from the test, repeated measures analysis of variance (Repeated Measures ANOVA) can be performed with different indoor environments and multiple (such as 5) electronic screen use times as independent variables, and the area under the contrast sensitivity curve, flicker fusion frequency, and blink frequency as dependent variables. Furthermore, it can be determined whether the visual fatigue index is affected by time and test conditions, and whether there is an interaction between multiple within-group factors, with P < 0.05 as the statistical significance criterion.

[0089] For example, for the results of the change of the average area under the contrast sensitivity curve (AULCSF) with time under different test environments, as Figure 5a shown, taking two different test environments (2 levels) and time (5 levels) as independent variables and AULCSF as the dependent variable for repeated measures analysis of variance, the statistical results are shown in Table 2.

[0090] Table 2 Results of the analysis of variance of the AULCSF mean

[0091]

[0092] It can be seen from the results of the analysis of variance that the contrast sensitivity index is marginally significant (P = 0.052) in the time dimension (4 points before and after using the electronic screen). Combining Figure 5a the results, the mean value of AULCSF is 30 min, showing an upward trend and then a downward trend at 60 min. The possible reason is that the contrast sensitivity test has a learning effect, causing the mean value of the AULCSF to first increase and then decrease due to visual fatigue. However, there is no significant difference between the two different test environments (P > 0.05), and there is also no significant difference in the interaction between different indoor environments and the time dimension (P > 0.05).

[0093] For another example, the mean value of the critical flicker fusion frequency changing with time in different test environments is as Figure 5b shown. The higher the critical flicker fusion frequency value, the more fatigued the subject is. Taking different test environments and five time dimensions as independent variables and the critical flicker fusion frequency as the dependent variable for repeated analysis of variance, the statistical results are shown in Table 3.

[0094] Table 3 Results of the analysis of variance of the critical flicker fusion frequency in different environments

[0095]

[0096] From Figure 5b the results, it can be seen that when the mean value of the critical flicker fusion frequency is at 60 min, 90 min, and 120 min, the result of 60% RH + no wind is higher than that of 40% RH + gentle breeze. However, the results of the analysis of variance indicate that there is no significant difference between the two environments (P > 0.05); the critical flicker fusion frequency index has a significant difference in the time dimension (P < 0.001), and the mean values of the post-test points after using the electronic screen are all higher than those of the pre-test points (0 min), indicating that using electronic devices in a dark room will cause a certain degree of visual fatigue to the subjects. There is a significant difference in the interaction between different test environments and the time dimension in the experiment (P = 0.023). By conducting a separate effect analysis on the critical flicker fusion frequency index in different test environments, it is found that at 90 min and 120 min, the mean value of the critical flicker fusion frequency under the condition of 40% RH + gentle breeze is lower than that under the condition of 60% RH + no wind (P < 0.01, P < 0.05), indicating that the environment of 60% RH + no wind may be more likely to cause fatigue.

[0097] For another example, by defining the blink frequency as the number of blinks within 1 minute after timing starts 30 s after the subject starts the test. The blink frequency index changing with time in different test environments is as Figure 5cAs shown, with different test environments (2 levels) and time (5 levels) as independent variables and blink frequency as the dependent variable, a repeated measures analysis of variance was performed, and the statistical results are shown in Table 4.

[0098] Table 4 Results of analysis of variance of blink frequency in different environments

[0099]

[0100] From the results of the analysis of variance, it can be seen that the mean blink frequency is slightly higher in the 40%RH + gentle breeze environment than in the 60%RH + no wind environment, but there is no significant difference (P > 0.1), indicating that different indoor environments have no significant effect on blink frequency. Similarly, in the time dimension, there is also no significant difference in the blink frequency index (P > 0.1), and there is no significant difference in the interaction between different indoor environments and the time dimension (P > 0.1).

[0101] Due to the large individual differences in blink frequency, statistical analysis can also be performed on the results of the blink frequency change rate. The change rate = (post - test blink frequency - pre - test blink frequency) / pre - test blink frequency × 100%. The mean results of the blink frequency change rate in different test environments are as Figure 5d shown, and the results of the analysis of variance are shown in Table 5.

[0102] Table 5 Results of analysis of variance of blink frequency change rate in different environments

[0103]

[0104] From the results of the analysis of variance, it can be seen that there is no significance in the mean blink frequency change rate in different test environments (P > 0.05), there is no significance in the mean blink frequency change rate in the time dimension (P > 0.05), and there is also no significant difference in the interaction between the environment and the time dimension (P > 0.05).

[0105] In an alternative embodiment, by plotting the graphs of different visual fatigue indicators of normal people against the electronic screen usage time, based on the data statistical results, it can be found that the critical flicker fusion frequency changes significantly with the electronic screen usage time, and the interaction between the environment and time is significant, indicating that the critical flicker fusion frequency is a relatively sensitive test index for visual fatigue; the contrast sensitivity changes marginally significantly with the electronic screen usage time, indicating that the contrast sensitivity can also be used as a visual fatigue test index; while the blink frequency is not significant under the action of the environment and time, indicating that for the normal population, the blink frequency is less sensitive as a visual fatigue test index than the aforementioned indexes, that is, the target visual fatigue evaluation indexes are screened.

[0106] In this embodiment, by performing repeated analysis of variance based on the visual fatigue index comparison map, the data statistical results are obtained. Then, based on the data statistical results, the contrast sensitivity index and the flicker fusion frequency index, for which the index data vary significantly with the electronic screen usage time, are determined as the target visual fatigue evaluation indexes, which can objectively quantify the influence degree of the indexes on visual fatigue judgment and effectively screen out the target visual fatigue evaluation indexes to construct a visual fatigue evaluation system.

[0107] In an exemplary embodiment, as Figure 6 shown, a schematic flow chart of another method for constructing a visual fatigue evaluation system is provided. In this embodiment, the method includes the following steps:

[0108] In step 601, visual fatigue test data of multiple test subjects in different test environments are obtained. In step 602, for the contrast sensitivity index, according to the contrast sensitivity test data of each test subject, a contrast sensitivity curve of each test subject in each test environment is generated, and based on the contrast sensitivity curves of each test subject, the mean value of the area under the contrast sensitivity curve in each test environment is determined. In step 603, for the flicker fusion frequency index, according to the flicker fusion frequency test data of each test subject, the flicker fusion critical frequency of each test subject in each test environment is determined, and based on the flicker fusion critical frequencies of each test subject, the mean value of the flicker fusion frequency in each test environment is obtained. In step 604, for the blink frequency index, according to the blink video data of each test subject, the blink frequency of each test subject in each test environment is determined, and based on the blink frequencies of each test subject, the mean value of the blink frequency in each test environment is obtained. In step 605, a visual fatigue index comparison map is integrated based on the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blink frequency in multiple test environments. In step 606, repeated analysis of variance is performed based on the visual fatigue index comparison map to obtain data statistical results. In step 607, according to the data statistical results, the contrast sensitivity index and the flicker fusion frequency index, for which the index data vary significantly with the electronic screen usage time, are determined as the target visual fatigue evaluation indexes; the target visual fatigue evaluation indexes are used to construct a visual fatigue evaluation system.

[0109] It should be noted that the specific limitations of the above steps can be referred to the specific limitations of a method for constructing a visual fatigue evaluation system above, and will not be elaborated here.

[0110] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0111] Based on the same inventive concept, an embodiment of the present application further provides a device for constructing a visual fatigue evaluation system for implementing the above-mentioned method for constructing a visual fatigue evaluation system. The solution provided by this device for solving problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device for constructing a visual fatigue evaluation system provided below can refer to the limitations on the method for constructing a visual fatigue evaluation system in the above text, and will not be repeated here.

[0112] In an exemplary embodiment, as Figure 7 shown, a device for constructing a visual fatigue evaluation system is provided, including:

[0113] A test data acquisition module 701, configured to acquire visual fatigue test data of multiple test subjects under different test environments;

[0114] A comparison atlas drawing module 702, configured to draw a visual fatigue index comparison atlas according to the visual fatigue test data of each of the test subjects and multiple candidate visual fatigue evaluation indexes; the visual fatigue index comparison atlas is used to characterize the data differences of the candidate visual fatigue evaluation indexes under different test environments;

[0115] A target evaluation index obtaining module 703, configured to perform screening processing on the multiple candidate visual fatigue evaluation indexes based on the data statistical results of the visual fatigue index comparison atlas, and obtain a target visual fatigue evaluation index; the target visual fatigue evaluation index is used to construct the visual fatigue evaluation system.

[0116] In one embodiment, the multiple candidate visual fatigue evaluation indicators include a contrast sensitivity indicator, a flicker fusion frequency indicator, and a blink frequency indicator. The contrast map drawing module 702 is specifically configured to, for the contrast sensitivity indicator, use the visual fatigue test data of each subject to determine the mean value of the area under the contrast sensitivity curve in each test environment; for the flicker fusion frequency indicator, use the visual fatigue test data of each subject to determine the mean value of the flicker fusion frequency in each test environment; for the blink frequency indicator, use the visual fatigue test data of each subject to determine the mean value of the blink frequency in each test environment; and integrate the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blink frequency in multiple test environments to obtain the visual fatigue indicator contrast map.

[0117] In one embodiment, the visual fatigue test data includes contrast sensitivity test data. The contrast map drawing module 702 is specifically further configured to generate a contrast sensitivity curve of each subject in each test environment according to the contrast sensitivity test data of each subject; and determine the mean value of the area under the contrast sensitivity curve in each test environment based on the contrast sensitivity curves of each subject.

[0118] In one embodiment, the visual fatigue test data further includes flicker fusion frequency test data. The contrast map drawing module 702 is specifically further configured to determine the flicker fusion critical frequency of each subject in each test environment according to the flicker fusion frequency test data of each subject; and obtain the mean value of the flicker fusion frequency in each test environment based on the flicker fusion critical frequencies of each subject.

[0119] In one embodiment, the visual fatigue test data further includes blink video data. The contrast map drawing module 702 is specifically further configured to determine the blink frequency of each subject in each test environment according to the blink video data of each subject; and obtain the mean value of the blink frequency in each test environment based on the blink frequencies of each subject.

[0120] In one embodiment, the target evaluation indicator obtaining module 703 is specifically configured to perform a repeated measures analysis of variance based on the visual fatigue indicator contrast map to obtain a data statistical result; and determine the contrast sensitivity indicator and the flicker fusion frequency indicator whose indicator data changes significantly with the electronic screen usage time according to the data statistical result as the target visual fatigue evaluation indicators.

[0121] Each module in the above visual fatigue assessment system construction device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of the processor in a computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0122] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 8 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for the processor to exchange information with external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. The computer program, when executed by the processor, implements a method for constructing a visual fatigue assessment system. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0123] Those skilled in the art can understand that Figure 8 the structure shown in

[0124] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0124] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0125] Obtain visual fatigue test data of multiple test subjects under different test environments;

[0126] According to the visual fatigue test data of each of the test subjects and multiple candidate visual fatigue evaluation indicators, a visual fatigue index comparison map is drawn; the visual fatigue index comparison map is used to characterize the data differences of the candidate visual fatigue evaluation indicators in different test environments;

[0127] Based on the data statistical results of the visual fatigue index comparison map, screening processing is performed on the multiple candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators; the target visual fatigue evaluation indicators are used to construct the visual fatigue evaluation system.

[0128] In one embodiment, when the processor executes the computer program, the steps of the visual fatigue evaluation system construction method in the above-mentioned other embodiments are also implemented.

[0129] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0130] Obtain the visual fatigue test data of multiple test subjects in different test environments;

[0131] According to the visual fatigue test data of each of the test subjects and multiple candidate visual fatigue evaluation indicators, a visual fatigue index comparison map is drawn; the visual fatigue index comparison map is used to characterize the data differences of the candidate visual fatigue evaluation indicators in different test environments;

[0132] Based on the data statistical results of the visual fatigue index comparison map, screening processing is performed on the multiple candidate visual fatigue evaluation indicators to obtain target visual fatigue evaluation indicators; the target visual fatigue evaluation indicators are used to construct the visual fatigue evaluation system.

[0133] In one embodiment, when the computer program is executed by a processor, the steps of the visual fatigue evaluation system construction method in the above-mentioned other embodiments are also implemented.

[0134] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0135] Obtain the visual fatigue test data of multiple test subjects in different test environments;

[0136] According to the visual fatigue test data of each of the test subjects and multiple candidate visual fatigue evaluation indicators, a visual fatigue index comparison map is drawn; the visual fatigue index comparison map is used to characterize the data differences of the candidate visual fatigue evaluation indicators in different test environments;

[0137] Based on the data statistical results of the visual fatigue index comparison atlas, screening processing is performed on the multiple candidate visual fatigue evaluation indexes to obtain a target visual fatigue evaluation index; the target visual fatigue evaluation index is used to construct the visual fatigue evaluation system.

[0138] In one embodiment, when the computer program is executed by the processor, the steps of the visual fatigue evaluation system construction method in the above other embodiments are also implemented.

[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0141] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope recorded in this application.

[0142] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for constructing a visual fatigue evaluation system, characterized in that The method includes: Obtaining visual fatigue test data of multiple subjects in different test environments; Drawing a visual fatigue index comparison map according to the visual fatigue test data of each subject and multiple candidate visual fatigue evaluation indexes; the visual fatigue index comparison map is used to characterize the data differences of the candidate visual fatigue evaluation indexes in different test environments; Based on the data statistical results of the visual fatigue index comparison map, screening the multiple candidate visual fatigue evaluation indexes to obtain a target visual fatigue evaluation index; the target visual fatigue evaluation index is used to construct the visual fatigue evaluation system.

2. The method according to claim 1, wherein The multiple candidate visual fatigue evaluation indexes include a contrast sensitivity index, a flicker fusion frequency index, and a blink frequency index. Drawing a visual fatigue index comparison map according to the visual fatigue test data of each subject and the multiple candidate visual fatigue evaluation indexes includes: For the contrast sensitivity index, using the visual fatigue test data of each subject to determine the mean value of the area under the contrast sensitivity curve in each test environment; For the flicker fusion frequency index, using the visual fatigue test data of each subject to determine the mean value of the flicker fusion frequency in each test environment; For the blink frequency index, using the visual fatigue test data of each subject to determine the mean value of the blink frequency in each test environment; Integrating the mean value of the area under the contrast sensitivity curve, the mean value of the flicker fusion frequency, and the mean value of the blink frequency in multiple test environments to obtain the visual fatigue index comparison map.

3. The method according to claim 2, wherein The visual fatigue test data includes contrast sensitivity test data. Using the visual fatigue test data of each subject to determine the mean value of the area under the contrast sensitivity curve in each test environment includes: Generating a contrast sensitivity curve for each subject in each test environment according to the contrast sensitivity test data of each subject; Based on the contrast sensitivity curves of each subject, determining the mean value of the area under the contrast sensitivity curve in each test environment.

4. The method according to claim 2, characterized in that The visual fatigue test data further includes flicker fusion frequency test data. Using the visual fatigue test data of each subject to determine the mean value of the flicker fusion frequency in each test environment includes: Determining the flicker fusion critical frequency of each subject in each test environment according to the flicker fusion frequency test data of each subject; Based on the flicker fusion critical frequencies of each subject, obtaining the mean value of the flicker fusion frequency in each test environment.

5. The method according to claim 2, characterized in that, The visual fatigue test data further includes blink video data. Using the visual fatigue test data of each subject to determine the mean value of the blink frequency in each test environment includes: Determining the blink frequency of each subject in each test environment according to the blink video data of each subject; Based on the blink frequencies of each subject, obtaining the mean value of the blink frequency in each test environment.

6. The method according to claim 1, characterized in that, Based on the data statistical results of the visual fatigue index comparison map, screening the multiple candidate visual fatigue evaluation indexes to obtain a target visual fatigue evaluation index includes: Perform repeated measures analysis of variance based on the visual fatigue index comparison atlas to obtain the data statistical results; Based on the data statistical results, determine the contrast sensitivity index and the flicker fusion frequency index whose index data change significantly with the electronic screen usage time as the target visual fatigue evaluation indexes.

7. An apparatus for constructing a visual fatigue assessment system, characterized in that The device includes: A test data acquisition module, configured to acquire visual fatigue test data of multiple subjects under different test environments; A comparison atlas drawing module, configured to draw a visual fatigue index comparison atlas according to the visual fatigue test data of each subject and multiple candidate visual fatigue evaluation indexes; the visual fatigue index comparison atlas is used to characterize the data differences of each candidate visual fatigue evaluation index under different test environments; A target evaluation index acquisition module, configured to perform screening processing on the multiple candidate visual fatigue evaluation indexes based on the data statistical results of the visual fatigue index comparison atlas to obtain a target visual fatigue evaluation index; the target visual fatigue evaluation index is used to construct the visual fatigue evaluation system.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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