Visual fatigue detection method and device, electronic equipment and storage medium

Abstract

The invention provides an asthenopia detection method and device, electronic equipment and a storage medium, and relates to the technical field of visual testing, and the method comprises the steps: obtaining first test data and second test data corresponding to a plurality of tested persons, carrying out the product height processing of the test data in a preset watching time period, obtaining a corresponding product height function, and obtaining the first test data and the second test data; the product height processing comprises the steps of performing integration on the physical sign index monitoring data in a preset watching time period, and calculating a ratio between an integration result and the preset watching time period; and performing inverse transformation based on the product height function to obtain an ideal state function which is corresponding to the test data and is subjected to noise influence elimination, and determining the visual fatigue detection speed based on the ideal state functions corresponding to different test data. The asthenopia speed is determined through the product height function which is created based on the fatigue test data and is used for eliminating noise interference, non-systematic errors are eliminated, and the asthenopia speed accuracy is improved.

Description

Technical Field

[0001] The present application relates to the field of visual testing technology, and in particular to a method, device, electronic device and storage medium for detecting visual fatigue. Background Art

[0002] With the rapid development of science and technology, the number of electronic products continues to increase, providing more ways for people to read. However, with the increasing number of electronic products, the quality of the display devices of electronic products cannot be guaranteed, causing certain harm to the eyes of browsing users. In order to enable users to better understand the effect of the display device of the reading device used, it is necessary to perform a visual fatigue test on the display device.

[0003] Most of the existing visual fatigue testing methods use direct test values ​​as processing source data. Due to the differences in test environment, test equipment, subjects and test persons, certain noise disturbances will be generated during each test, resulting in different test errors in the final test values. Most of the existing technologies rely on increasing the number of test data samples to shield errors, but this method not only increases the cost for users, but also increases the complexity of the data processing process due to the test samples. Summary of the invention

[0004] For ease of understanding, we first introduce the definitions of product height function and noise function.

[0005] The product height function is defined as follows:

[0006]

[0007] F(t) is the product function of function y(t).

[0008] Its inverse transformation is recorded as: Right now

[0009] y(t)=[F(t)×T] ′ =F(t)+F(t) ′ ×T

[0010] Preferably, the change of a state quantity over time is tested, and the test result of the change of the state quantity over time is defined as the test source function y(t).

[0011] Considering that the data in this test result is actually interfered by noise, the test source function can be expressed as the sum of the ideal state function g(t) and the noise function noise(t), that is: y(t) = g(t) + noise(t).

[0012] Specifically, in this application, the noise function noise(t) is defined to have the following characteristics:

[0013] ① Limited randomness: The sub-noise function corresponding to each test noise fluctuates within a certain target value range, that is, the i-th sub-noise function noise i (t)={-Δ, +Δ}, Δ is a relatively small real number, and △ represents the maximum noise monitored by multiple test subjects during the viewing test within a preset viewing time period.

[0014] ② Self-cancellation: The sum of the sub-noise functions, that is, the noise function noise(t), also fluctuates within the target value range, and its value is a random value between {-Δ, +Δ}, that is, -Δ≤noise(t)≤+Δ.

[0015] On the other hand, the ideal state function g(t) can be expressed as a power function:

[0016]

[0017] The following is the high-level denoising method:

[0018] The test source function y(t) is composed of a number of discrete points, so its product height function can be calculated using the following formula:

[0019]

[0020] Where ΔT is the time interval between two adjacent tests, and T is the total test time. In this application, T can be When Δt is small enough and T is large enough, ΔT / T can be ignored. According to the property ② of the noise function, we have:

[0021]

[0022] C K It can be obtained from the power function fitting curve of the product height function F(t) curve.

[0023] Therefore, according to C K =A K / (K+1), the coefficient of the ideal state function is:

[0024] A K =(K+1)×C K

[0025] It can be seen that by product-height transformation or product-height processing and then ignoring the noise term, the ideal state function can be obtained as:

[0026]

[0027] In view of the background situation, the purpose of this application is to at least provide a visual fatigue detection method, device, electronic device and storage medium, determine the visual fatigue speed by creating a product-height function of fatigue test data, eliminate non-systematic errors, and improve the accuracy of visual fatigue speed.

[0028] This application mainly includes the following aspects:

[0029] In a first aspect, an embodiment of the present application provides a method for detecting visual fatigue, the method comprising:

[0030] First test data and second test data of multiple test persons are obtained, the first test data are physical sign monitoring data for characterizing the degree of visual fatigue when the multiple test persons watch standard equipment in a preset viewing time period, the second test data are physical sign monitoring data when the multiple test persons watch the test equipment in a preset viewing time period, the physical sign monitoring data include physical sign index monitoring values ​​of each test person at each viewing time in the preset viewing time period, the physical sign monitoring data indicated by the first test data are integrated within the preset viewing time period to obtain a first integrated index value corresponding to each viewing time, the integrated processing includes: integrating the physical sign monitoring data within the preset viewing time period, and calculating the ratio between the integrated result and the preset viewing time period; integrating the physical sign monitoring data indicated by the second test data within the preset viewing time period, A second accumulation height index value corresponding to each viewing time is obtained; a first accumulation height function corresponding to the first test data is constructed according to the first accumulation height index value corresponding to each viewing time, and a second accumulation height function corresponding to the second test data is constructed according to the second accumulation height index value corresponding to each viewing time. The accumulation height function is used to characterize the mapping relationship between the accumulation height index value and the viewing time. Based on the first ideal state function, a baseline vital sign indicator monitoring value at a baseline time is obtained. The first ideal state function is determined by the first accumulation height function. The ideal state function refers to a function that eliminates noise items and is used to characterize the cumulative changes of vital sign indicators with viewing time. Based on the second ideal state function, a comparison time corresponding to the baseline vital sign indicator monitoring value is obtained. The second ideal state function is determined by the second accumulation height function. Visual fatigue detection is performed according to the baseline time and the comparison time.

[0031] In a possible implementation, the vital sign monitoring data is determined in the following manner: if the vital sign indicator is a continuous measurement quantity, the vital sign indicator monitoring value generated by each subject within a preset viewing time period is collected at a preset collection frequency; the vital sign monitoring data is formed by multiple vital sign indicator monitoring values ​​corresponding to each subject within the preset viewing time period and the viewing time corresponding to each vital sign indicator monitoring value.

[0032] In a possible implementation, the vital sign monitoring data is determined in the following manner: if the vital sign indicator is a non-continuous measurement quantity, the preset viewing time period is divided into multiple viewing time periods according to the preset time intervals; according to the number of the multiple viewing time periods, the multiple test persons are divided into multiple test groups, and the multiple test groups are assigned one by one to multiple viewing time periods to test the viewing standard equipment or test equipment, and the number of people in each test group is equal; for each test person, the vital sign indicator monitoring value corresponding to the test person is collected during the viewing time period associated with the test group to which the test person belongs; the vital sign monitoring data is formed by the vital sign indicator monitoring value corresponding to each test person and the viewing time corresponding to the vital sign indicator monitoring value.

[0033] In a possible implementation, the first product-height function is determined in the following manner: for the first test data, for each viewing time, the corresponding physical sign index monitoring values ​​of all the test persons under the viewing time are weighted and averaged to obtain the corresponding comprehensive index value under the viewing time; a first mapping relationship curve between the viewing time and the comprehensive index value is established; within a preset viewing time period, the first mapping relationship curve is product-processed to obtain a second mapping relationship curve, and the second mapping relationship curve describes the mapping relationship between the viewing time and the first product-height index value; according to the second mapping relationship curve, the first product-height function is fitted.

[0034] In a possible implementation, the product height function is expressed by the following formula:

[0035]

[0036] In this formula, F(t) represents the product height index value corresponding to the viewing time t of the tested person, n represents the number of power function terms corresponding to the product height function, C K Represents the Kth power function term t that forms the product height function K The corresponding fitting coefficients.

[0037] In a possible implementation, the ideal state function is expressed by the following formula:

[0038]

[0039] In this formula, g(t) represents the ideal physical sign index monitoring value corresponding to the viewing time t of the tested person under the ideal state without noise interference, where A K Represents the Kth power term t that forms the ideal state function K The corresponding fitting coefficients, where A K =(K+1)×C K .

[0040] In a possible implementation, the step of performing visual fatigue detection according to the reference time and the comparison time includes:

[0041] Calculating a first ratio between a baseline vital sign index monitoring value and a baseline time, and determining the first ratio as a baseline visual fatigue speed corresponding to the standard equipment;

[0042] Calculate a second ratio of the baseline vital sign index monitoring value to the comparison time, determine the second ratio as the target visual fatigue speed corresponding to the device under test, compare the target visual fatigue speed with the baseline visual fatigue speed, and determine the degree of difficulty of the device under test in inducing visual fatigue relative to the standard device based on the comparison result;

[0043] Or, calculate a third ratio between the reference moment and the comparison moment, determine the third ratio as the target visual fatigue speed corresponding to the device under test, compare the target visual fatigue speed with 1, and determine the difficulty of the device under test to induce visual fatigue relative to the standard device based on the comparison result.

[0044] In a second aspect, an embodiment of the present application further provides a visual fatigue detection device, the device comprising:

[0045] The first acquisition module is used to acquire first test data and second test data of multiple test persons, the first test data is physical sign monitoring data for characterizing the degree of visual fatigue when multiple test persons watch standard equipment in a preset viewing time period, and the second test data is physical sign monitoring data when multiple test persons watch test equipment in a preset viewing time period, and the physical sign monitoring data includes physical sign index monitoring values ​​of each test person at each viewing time in the preset viewing time period; the first accumulation processing module is used to perform accumulation processing on the physical sign monitoring data indicated by the first test data in the preset viewing time period to obtain the first accumulation index value corresponding to each viewing time, and the accumulation processing includes: integrating the physical sign monitoring data in the preset viewing time period, and calculating the ratio between the integration result and the preset viewing time period; the second accumulation processing module is used to perform accumulation processing on the physical sign monitoring data indicated by the second test data in the preset viewing time period, A second accumulation height index value corresponding to each viewing time is obtained; a construction module is used to fit and construct a first accumulation height function corresponding to the first test data according to the first accumulation height index value corresponding to each viewing time, and to fit and construct a second accumulation height function corresponding to the second test data according to the second accumulation height index value corresponding to each viewing time, and the accumulation height function is used to characterize the mapping relationship between the accumulation height index value and the viewing time; a second acquisition module is used to obtain a baseline vital sign indicator monitoring value at a baseline time based on the first ideal state function, the first ideal state function is determined by the first accumulation height function, and the ideal state function refers to a function that eliminates noise items and is used to characterize the cumulative change of the vital sign indicator with viewing time; a third acquisition module is used to obtain a comparison time corresponding to the baseline vital sign indicator monitoring value based on the second ideal state function, and the second ideal state function is determined by the second accumulation height function; a detection module is used to perform visual fatigue detection according to the baseline time and the comparison time.

[0046] In the third aspect, an embodiment of the present application also provides an electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the visual fatigue detection method in the above-mentioned first aspect or any possible implementation scheme of the first aspect.

[0047] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the visual fatigue detection method in the above-mentioned first aspect or any possible implementation scheme of the first aspect are executed.

[0048] The embodiments of the present application provide a method, device, electronic device and storage medium for detecting visual fatigue, including: obtaining first test data and second test data corresponding to multiple test persons, and for the test data, performing product height processing on the test data within a preset viewing time period to obtain a corresponding product height function, the product height processing including: integrating the physical sign index monitoring data within the preset viewing time period, and calculating the ratio between the integral result and the preset viewing time period; performing an inverse transformation based on the product height function to obtain an ideal state function corresponding to the test data that excludes the influence of noise, and determining the visual fatigue detection speed based on the ideal state function corresponding to different test data. The present application determines the visual fatigue speed by creating a product height function based on fatigue test data that excludes noise interference, thereby eliminating non-systematic errors and improving the accuracy of the visual fatigue speed.

[0049] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 A flow chart of a method for detecting visual fatigue provided by an embodiment of the present application is shown;

[0052] Figure 2 A functional module diagram of a visual fatigue detection device provided in an embodiment of the present application is shown;

[0053] Figure 3 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art, under the guidance of the content of the present application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0055] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0056] In the actual visual fatigue speed test process, the differential method is often used to reduce the impact of environmental factors on signal accuracy. However, in a measurement process, if a more ideal test result with fewer interference factors is expected, this method cannot be used.

[0057] Systematic noise often has a certain bias. The differential method can reduce the impact of noise on the results. For non-systematic noise signals, since they always fluctuate around an ideal value, the differential method cannot effectively reduce the impact of noise on the test results, resulting in a certain deviation in the final result.

[0058] Based on this, the embodiments of the present application provide a method, device and electronic device for detecting visual fatigue, which determines the visual fatigue speed by creating a product height function based on fatigue test data and eliminating noise interference, eliminates non-systematic errors, and improves the accuracy of visual fatigue speed, as follows:

[0059] See also Figure 1 , Figure 1 FIG. 2 is a flow chart of a method for detecting visual fatigue provided by an embodiment of the present application. Figure 1 As shown, the method provided in the embodiment of the present application comprises the following steps:

[0060] S100: Acquire first test data and second test data of multiple test subjects.

[0061] Among them, the first test data is the physical sign monitoring data used to characterize the degree of visual fatigue when multiple subjects watch standard equipment in a preset viewing time period; the second test data is the physical sign monitoring data when multiple subjects watch the test equipment in a preset viewing time period. The physical sign monitoring data includes the physical sign indicator monitoring values ​​of each subject at each viewing time in the preset viewing time period.

[0062] S200: Perform accumulation processing on the vital sign monitoring data indicated by the first test data within a preset viewing time period to obtain a first accumulation index value corresponding to each viewing time.

[0063] S300: Perform accumulation processing on the vital sign monitoring data indicated by the second test data within a preset viewing time period to obtain a second accumulation index value corresponding to each viewing time.

[0064] S400, respectively constructing a first product height function corresponding to the first test data according to the first product height index value corresponding to each viewing time, and constructing a second product height function corresponding to the second test data according to the second product height index value corresponding to each viewing time.

[0065] The cumulative height function is used to characterize the mapping relationship between the cumulative height index value and the viewing time.

[0066] S500: Based on the first ideal state function, obtain a baseline vital sign index monitoring value at a baseline time.

[0067] The first ideal state function is determined by the first product height function. Specifically, the first ideal state function is determined by the first fitting coefficient corresponding to the first product height function. The ideal state function refers to a function that eliminates noise terms and is used to characterize the cumulative changes of vital sign indicators with viewing time. Specifically, the first ideal state function refers to a function that eliminates noise terms and is used to characterize the cumulative changes of vital sign indicators under the first test data with viewing time.

[0068] S600: Based on the second ideal state function, obtain a comparison time corresponding to the benchmark vital sign index monitoring value.

[0069] The second ideal state function is determined by the second product height function. Specifically, the second ideal state function is determined by the second fitting coefficient corresponding to the second product height function. The second ideal state function refers to a function that eliminates noise terms and is used to characterize the cumulative changes of physical sign indicators under the second test data with viewing time.

[0070] S700: Perform visual fatigue detection according to the reference time and the comparison time.

[0071] In step S100, different first viewing tests and second viewing tests are respectively performed on the same test population within a preset viewing time period to respectively determine first test data and second test data. The test population includes multiple test subjects. In the two viewing tests, the viewing targets are different. The viewing target corresponding to the test subjects in the first viewing test is the standard device, and the viewing target of the test subjects in the second viewing test is the test device. In the present application, the test data of the standard device is mainly used as a reference to determine the visual fatigue speed of the test device, wherein the standard device is a device whose visual fatigue speed meets the preset standard, and the standard device can also be a paper document.

[0072] During the viewing test, a target sign indicator can be selected from multiple sign indicators that reflect the user's visual fatigue state according to actual needs or test tasks. In the same viewing test, the sign indicator detection value corresponding to the target sign indicator generated by the test person within the preset viewing time period is monitored and collected to determine the sign monitoring data corresponding to the target sign indicator. In the present application, the data acquisition sensors corresponding to different sign indicators are different. After the target sign indicator is selected, the data acquisition sensor corresponding to the sign indicator is used to complete the collection of the indicator value corresponding to the target sign indicator. In the present application, the preset viewing time period is usually set to more than 30 minutes, so that the test results can have better stability, and it is generally set to 40 minutes.

[0073] Preferably, the physical sign indicators are divided into continuous measurement quantities and discontinuous measurement quantities. Continuous measurement quantities refer to physical sign indicators that can be continuously collected during the viewing time, including EEG (Electroencephalogram, brain waves), blinking frequency, etc. Discontinuous measurement quantities are indicators that cannot be continuously monitored and require interruption of the viewing process, such as flicker fusion.

[0074] In a preferred embodiment, if the vital sign indicator is a continuous measurement quantity, the vital sign indicator monitoring value generated by each subject during a preset viewing time period is collected at a preset collection frequency, and the vital sign monitoring data is formed by multiple vital sign indicator monitoring values ​​corresponding to each subject during the preset viewing time period and the viewing time corresponding to each vital sign indicator monitoring value.

[0075] Specifically, taking the first viewing test as an example, assuming that the preset time period is 40 minutes, and the target vital sign indicator set in the test process is the continuous measurement quantity EEG, then for EEG, through the preset EEG acquisition device, the preset acquisition frequency is continuously used to collect multiple vital sign indicator monitoring values ​​generated by each subject's continuous viewing of the standard device within 40 minutes of the first viewing test, as well as the viewing time corresponding to each vital sign indicator monitoring value. For each subject, the preset EEG acquisition device collects multiple monitoring values ​​corresponding to the EEG of each subject in 40 minutes and the viewing time corresponding to each monitoring value to form vital sign monitoring data.

[0076] The method for obtaining the vital sign monitoring data corresponding to the second viewing test is the same as that for the first viewing test, and will not be elaborated here.

[0077] In another preferred embodiment, if the physical sign indicator is a non-continuous measurement, the physical sign monitoring data is determined by:

[0078] A preset viewing time period is divided into multiple viewing time periods according to preset time intervals; multiple test persons are divided into multiple test groups according to the number of divided viewing time periods; the multiple test groups are assigned one by one to multiple viewing time periods to test the viewing standard equipment or test equipment; the number of persons in each test group is equal; for each test person, a vital sign indicator monitoring value corresponding to the test person is collected during the viewing time period associated with the test group to which the test person belongs; the vital sign monitoring data are formed by the vital sign indicator monitoring value corresponding to each test person and the viewing time corresponding to the vital sign indicator monitoring value.

[0079] Specifically, taking the first viewing test as an example, assuming that the preset time period is 10 minutes, the vital sign indicator set in the test process is CFF (critical fusion frequency), CFF is a non-continuous measurement, and the total number of subjects is 10. The 10 minutes are divided into multiple viewing periods of 0 to 5 minutes and 5 to 10 minutes at intervals. The 10 people are divided into 2 test groups (a first test group and a second test group), each with 5 people. The 2 test groups are associated with different viewing periods. The 10 subjects start a 20-minute viewing test. Within the viewing period of 0 to 5 minutes, the corresponding monitoring values ​​and the corresponding viewing time of each subject in the first test group under CFF are collected to form the corresponding monitoring data of each subject in the first test group. Within the viewing period of 5 to 10 minutes, the corresponding monitoring values ​​and the corresponding viewing time of each subject in the second test group under CFF are collected to form the corresponding monitoring data of each subject in the second test group. The monitoring data collected in each viewing period forms the vital sign monitoring data.

[0080] In the second viewing test, the method of obtaining the corresponding vital sign monitoring data of each test subject is the same as that of the first viewing test, which will not be repeated here.

[0081] During the viewing test, the viewing test may be affected by non-system noise such as the test environment, data acquisition sensors, and test subjects, which may cause different errors. In this application, a product height function is constructed to eliminate the noise influence during the viewing test, thereby obtaining an ideal state function without noise influence.

[0082] In a specific embodiment, visual fatigue is a gradually increasing process. Therefore, in the present application, for the test person, the physical sign index is a function that changes with the viewing time t. In an ideal case where noise disturbance is not considered during the test, the functional relationship between the physical sign index and the viewing time can be equivalent to the sum of at least one power function, and the ideal state function is obtained:

[0083]

[0084] Among them, t is the viewing time, which is the independent variable of the ideal state function. g(t) represents the ideal physical sign index monitoring value corresponding to the viewing time t of the tested person under the ideal state without noise interference. g(t) is the dependent variable of the ideal state function. Among them, A K represents the Kth power term t forming the ideal state function K The corresponding fitting coefficient, n represents the number of power functions that form the ideal state function.

[0085] However, in the actual testing process, it is necessary to consider the test fluctuations caused by different noises in the viewing test. Directly using the test data to fit the ideal state function g(t) will cause the final visual fatigue detection result to be inaccurate. Therefore, this application, inspired by the above-mentioned ideal state function, introduces noise disturbance and creates the corresponding noise function in the test process. On the basis of the ideal state function g(t), the noise function noise(t) is introduced to construct a test source function that represents the actual test situation.

[0086] In the specific implementation, after the above analysis and the introduction of the noise function, the test source function is expressed as:

[0087]

[0088] In formula (1), A K represents the fitting coefficient corresponding to the Kth power function term, t Krepresents the Kth power function term with viewing time as the base, noise(t) represents the noise value of the subject at viewing time t, wherein at least one test noise of different types may be generated during the viewing test (the first viewing test or the second viewing test). Therefore, the noise function noise(t) corresponding to the entire viewing test process is the sum of the noise functions corresponding to each test noise. Specifically, m represents the amount of test noise generated during the viewing test. i (t) represents the sub-noise function corresponding to the i-th test noise in the viewing test process, and y(t) represents the physical sign monitoring result obtained after the physical sign index monitoring value corresponding to the viewing time t of the subject is introduced into the noise value generated at the viewing time t.

[0089] In fact, formula (1) describes a mapping relationship between each viewing time in the viewing test process and the vital sign indicator monitoring value actually measured under the viewing time. That is to say, in this application, the mapping relationship between the viewing time and the vital sign monitoring indicator value described in the test data is actually the test source function. From formula (1), it can be seen that the test source function is related to the ideal state function g(t) and the noise function noise(t). That is to say, the mapping relationship between the viewing time and the vital sign monitoring indicator value described in the test data still retains the influence of the test noise.

[0090] However, in the process of visual fatigue detection in this application, in order to make the subsequent results more accurate, it is necessary to eliminate the influence of noise on the target visual fatigue during the test process. In this application, combined with the characteristics of the noise function, it is determined that as long as the collected test data is processed by product height, a product height function that eliminates the noise term can be obtained.

[0091] From the characteristics of the noise function, we can see that since the non-systematic noise itself always fluctuates around an ideal value, the final result is still a random value in a certain interval through the superposition of the noise signal itself. By utilizing the mutual cancellation characteristic of the non-systematic noise when it accumulates, by integrating the test source function and then calculating the ratio between it and the preset viewing time period T, the result obtained can more accurately determine the speed of visual fatigue.

[0092] In a specific embodiment, for the test source function In order to eliminate the influence of noise, using the second characteristic corresponding to the above noise function, if the test source function is transformed or processed by product height, it can be obtained:

[0093]

[0094] In this formula, T represents the preset viewing time period, and F(t) and y(t) can be inversely transformed, and the inverse transformation is recorded as: F(t) is called the product height function of the test source function y(t).

[0095] In the present application, y(t) can be represented by the corresponding mapping relationship between the viewing time described by the test data and the monitoring value of the physical sign index. Based on this, further transformation is performed in combination with formula (2):

[0096]

[0097] Among them, ΔT is the time interval between two adjacent collections (collection of vital sign index monitoring values). When Δt is small enough and T is large enough, Δt / T can be ignored. According to the property of the noise function ②, there exists:

[0098]

[0099] It can be seen that after the test source function is transformed by the product-height transformation, the product-height function F(t) obtained can eliminate the noise function term and is represented by the ideal state function. It shows that the product-height function obtained after the test source function is transformed by the product-height transformation and the ideal state function can be converted. Based on this, the present application can determine the corresponding ideal state function by calculating the product-height function, so as to facilitate subsequent visual fatigue detection.

[0100] It can be seen from the above formula that in the process of constructing the product height function, the characteristic of non-systematic noise canceling each other out when accumulated is utilized. By calculating the product height function, the non-systematic noise is accumulated and the fluctuation in the test source function is removed. This can effectively reduce the error of non-systematic noise on visual fatigue speed and improve the accuracy of subsequent visual fatigue speed.

[0101] In this formula, F(t) represents the product height index value corresponding to the viewing time t of the tested person, n represents the number of power function terms corresponding to the product height function, C K Represents the Kth power function term t that forms the product height function K The corresponding fitting coefficients.

[0102] In a preferred embodiment, in steps S200 to S400, the first product height function is determined in the following manner:

[0103] For each viewing time, the weighted average of the physical sign indicator monitoring values ​​corresponding to all the subjects under the viewing time is taken to obtain the comprehensive indicator value corresponding to the viewing time, and a first mapping relationship curve between the viewing time and the comprehensive indicator value is established. Within the preset viewing time period, the first mapping relationship curve is subjected to a product height processing to obtain a second mapping relationship curve. The second mapping relationship curve describes the mapping relationship between the viewing time and the first product height indicator value, and the first product height function is fitted according to the second mapping relationship curve.

[0104] Specifically, in the present application, taking the first test data as an example, within the preset viewing time period, for each viewing time, the corresponding physical sign index monitoring value of each tested person under the viewing time, the present application needs to process the average of multiple physical sign index monitoring values ​​under the viewing time, so as to obtain a comprehensive index value corresponding to the viewing time, and further, establish a first mapping relationship curve between the viewing time and its corresponding comprehensive index value, replace the above-mentioned test source function with the first mapping relationship curve, and combine with formula (2), perform the product height processing on the first mapping relationship curve within the preset viewing time period, so as to obtain the first product height index value corresponding to each viewing time, and then establish a second mapping relationship curve between the viewing time and the first product height index value, combined with formula:

[0105] Get the first product height function.

[0106] The second product height function is determined by the second test data, and the specific determination method is the same as the determination method of the first product height function, which will not be repeated here.

[0107] Furthermore, for the product height function, after determining the fitting coefficient corresponding to each power function term, we can use C K =A K / (K+1), we can get the fitting coefficient corresponding to the ideal state function, that is:

[0108] A K =(K+1)×C K .

[0109] In the method provided in the present application, based on the corresponding relationship A between the fitting coefficient corresponding to the power function term in the ideal state function and the fitting coefficient of the power function term in the product height function K =(K+1)×C K Therefore, before executing step S500, the first fitting value corresponding to each fitting coefficient in the first product height function and the second fitting value corresponding to each fitting coefficient in the second product height function can be respectively substituted into the following formula to obtain the first ideal state function g1(t) and the second ideal state function g2(t):

[0110]

[0111] There are two main methods for traditional noise elimination. One is the differential method, which uses the difference between adjacent signals in the same environment to remove noise. This method cannot be implemented without relevant conditions, and physically requires two signal paths.

[0112] Another method is to remove certain harmonic components through Fourier transform. If the noise component has a high frequency, this part of the influence can be removed, and then the inverse Fourier transform can be performed. However, low-frequency noise or noise with a frequency close to it cannot be removed, and a filtering circuit needs to be added to the hardware circuit, which increases the design cost.

[0113] The accuracy of the ideal state function obtained by inverse product transformation depends on Δt / T, that is, the number of samples and the sampling time. In fact, according to the fluctuation amplitude of the test waveform, we can determine the fluctuation range of {-Δ, +Δ}, and then determine the sampling frequency and duration according to the accuracy requirements, that is, the size of Δt / T, so as to obtain the required ideal state function in a more economical way.

[0114] In a preferred embodiment, in the process of determining the product-height function, different types of vital sign indicators are taken into consideration, and the expression forms of the product-height function obtained are different. Specifically, if the vital sign indicator is a continuous measurement quantity, the final product-height function is in a continuous form. If the vital sign indicator is a discontinuous measurement quantity, the final product-height function is in a piecewise function form, and the segmentation interval depends on the divided viewing time period.

[0115] In a preferred embodiment, in step S500, the corresponding first ideal state function g1(t) can be determined based on the above process, and the baseline vital sign index monitoring value A0 at the baseline time T0 is obtained after removing the noise influence during the first viewing test, and A0 / T0 is used as the standard visual fatigue speed Vs0 corresponding to the first viewing test.

[0116] In another preferred embodiment, in step S600, for the second viewing test, based on the second ideal state function g2(t) determined by the above process, the baseline vital sign index monitoring value A0 is substituted into the second ideal state function g2(t), and the comparison time T1 corresponding to the baseline vital sign index monitoring value A0 is determined.

[0117] In a preferred embodiment, step S700 includes:

[0118] A first ratio between the reference time T0 and the reference vital sign index monitoring value A0 is calculated, and the first ratio is determined as a reference visual fatigue speed Vs0 corresponding to the standard equipment.

[0119] Furthermore, a second ratio between the baseline vital sign index monitoring value A0 and the comparison time T1 is calculated, the second ratio is determined as the target visual fatigue speed corresponding to the device under test, the target visual fatigue speed is compared with the baseline visual fatigue speed Vs0, and based on the comparison result, the difficulty of the device under test to induce visual fatigue relative to the standard device is determined.

[0120] Specifically, if the target visual fatigue speed Vs1 is greater than the standard visual fatigue speed Vs0, it is determined that the tested device is more likely to cause visual fatigue than the standard device. If the target visual fatigue speed Vs1 is equal to the standard visual fatigue speed Vs0, it is determined that the tested device has an equivalent ability to cause visual fatigue as the standard device. If the target visual fatigue speed Vs1 is less than the standard visual fatigue speed Vs0, it is determined that the tested device is less likely to cause visual fatigue than the standard device.

[0121] In addition, the application can also determine the ease with which the tested device induces visual fatigue relative to the standard device by the following methods:

[0122] Calculate the third ratio between the reference time T0 and the comparison time T1, determine the third ratio as the target visual fatigue speed Vs1, compare the target visual fatigue speed Vs1 with 1, and determine the difficulty of the tested device in inducing visual fatigue relative to the standard device based on the comparison result.

[0123] Specifically, in this method, if the target visual fatigue speed Vs1 is greater than 1, it is determined that the tested device is more likely to cause visual fatigue than the standard device. If the target visual fatigue speed Vs1 is equal to 1, it is determined that the tested device has an equivalent ability to cause visual fatigue as the standard device. If the target visual fatigue speed Vs1 is less than 1, it is determined that the tested device is less likely to cause visual fatigue than the standard device.

[0124] See also Figure 2 , Figure 2 FIG. 2 shows a functional module diagram of a visual fatigue speed determination device provided by an embodiment of the present application. Figure 2 As shown, the device comprises:

[0125] The first acquisition module 800 is used to acquire first test data and second test data of multiple test persons, wherein the first test data is physical sign monitoring data for characterizing the degree of visual fatigue when multiple test persons watch standard equipment in a preset viewing time period, and the second test data is physical sign monitoring data when multiple test persons watch the test equipment in a preset viewing time period, and the physical sign monitoring data includes physical sign indicator monitoring values ​​of each test person at each viewing time in the preset viewing time period;

[0126] The first accumulation processing module 810 is used to perform accumulation processing on the vital sign monitoring data indicated by the first test data within the preset viewing time period to obtain a first accumulation index value corresponding to each viewing time, wherein the accumulation processing includes: integrating the vital sign monitoring data within the preset viewing time period and calculating the ratio between the integration result and the preset viewing time period;

[0127] The second accumulation processing module 820 is used to perform accumulation processing on the vital sign monitoring data indicated by the second test data within a preset viewing time period to obtain a second accumulation index value corresponding to each viewing time length;

[0128] A construction module 830 is used to construct a first product height function corresponding to the first test data according to the first product height index value corresponding to each viewing time, and to construct a second product height function corresponding to the second test data according to the second product height index value corresponding to each viewing time, wherein the product height function is used to characterize the mapping relationship between the product height index value and the viewing time;

[0129] A second acquisition module 840 is used to obtain a reference vital sign index monitoring value at a reference time based on a first ideal state function, where the first ideal state function is determined by a first product height function, and the ideal state function refers to a function that eliminates noise terms and is used to characterize the cumulative change of the vital sign index with viewing time;

[0130] A third acquisition module 850 is used to obtain a comparison time corresponding to the baseline vital sign index monitoring value based on a second ideal state function, where the second ideal state function is determined by a second product height function;

[0131] The detection module 860 is used to perform visual fatigue detection based on the reference time and the comparison time.

[0132] Based on the same application idea, please refer to Figure 3 , Figure 3 The structure diagram of an electronic device provided by an embodiment of the present application is shown. The electronic device 900 includes: a processor 910, a memory 920 and a bus 930, the memory 920 stores machine-readable instructions executable by the processor 910, when the electronic device 900 is running, the processor 910 and the memory 920 communicate through the bus 930, and the machine-readable instructions are executed by the processor 910 when running, as in the steps of the visual fatigue speed determination method provided in any of the above embodiments.

[0133] Based on the same application concept, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the visual fatigue speed determination method provided in the above embodiment are executed.

[0134] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0135] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0137] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0138] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for detecting visual fatigue, characterized in that: The method comprises: Acquire first test data and second test data of multiple test persons, wherein the first test data is physical sign monitoring data for characterizing the degree of visual fatigue when the multiple test persons watch a standard device in a preset viewing time period, and the second test data is physical sign monitoring data when the multiple test persons watch a test device in a preset viewing time period, and the physical sign monitoring data includes physical sign indicator monitoring values ​​of each test person at each viewing time in the preset viewing time period; Performing an integration process on the vital sign monitoring data indicated by the first test data within a preset viewing time period to obtain a first integration index value corresponding to each viewing time, wherein the integration process comprises: integrating the vital sign monitoring data within the preset viewing time period and calculating a ratio between the integration result and the viewing time used; Performing cumulative processing on the vital sign monitoring data indicated by the second test data within a preset viewing time period to obtain a second cumulative index value corresponding to each viewing time; A first product height function corresponding to the first test data is constructed according to the first product height index value corresponding to each viewing time, and a second product height function corresponding to the second test data is constructed according to the second product height index value corresponding to each viewing time, wherein the product height function is used to characterize the mapping relationship between the product height index value and the viewing time; Based on a first ideal state function, obtaining a reference vital sign index monitoring value at a reference time, wherein the first ideal state function is determined by the first product height function, and the ideal state function refers to a function that eliminates noise terms and is used to characterize the cumulative change of the vital sign index with viewing time; Based on a second ideal state function, obtaining a comparison time corresponding to the baseline vital sign index monitoring value, wherein the second ideal state function is determined by the second product height function; Visual fatigue detection is performed based on the reference time and the comparison time.

2. The method according to claim 1, characterized in that: Vital sign monitoring data is determined by: If the physical sign index is a continuous measurement, the physical sign index monitoring value generated by each tested person within the preset viewing time period is collected at a preset collection frequency; The physical sign monitoring data is formed by a plurality of physical sign indicator monitoring values ​​corresponding to each tested person within a preset viewing time period and the viewing time corresponding to each physical sign indicator monitoring value.

3. The method according to claim 1, characterized in that Vital sign monitoring data is determined by: If the physical sign indicator is a non-continuous measurement, the preset viewing time period is divided into a plurality of viewing time periods according to preset time intervals; According to the number of divided viewing time periods, the plurality of test subjects are divided into a plurality of test groups, and the plurality of test groups are assigned one by one to a plurality of viewing time periods to perform the test of the viewing standard device or the test device, and the number of persons in each test group is equal; For each tested person, during the viewing period associated with the test group to which the tested person belongs, the monitoring value of the physical sign index corresponding to the tested person is collected; The physical sign monitoring data is formed by the physical sign indicator monitoring value corresponding to each tested person and the viewing time corresponding to the physical sign indicator monitoring value.

4. The method according to claim 1, characterized in that: The first product height function is determined by: For the first test data, for each viewing time, weighted average of the physical sign index monitoring values ​​corresponding to all the tested persons for the viewing time is obtained to obtain the comprehensive index value corresponding to the viewing time; Establishing a first mapping relationship curve between viewing time and comprehensive index value; In a preset viewing time period, the first mapping relationship curve is subjected to accumulation processing to obtain a second mapping relationship curve, wherein the second mapping relationship curve describes a mapping relationship between the viewing time and the first accumulation index value; According to the second mapping relationship curve, a first product height function is obtained by fitting.

5. The method according to claim 1, characterized in that The product height function is expressed by the following formula: In this formula, F(t) represents the product height index value corresponding to the viewing time t of the tested person, n represents the number of power function terms corresponding to the product height function, C K represents the Kth power function term t forming the product height function K The corresponding fitting coefficients.

6. The method according to claim 5, characterized in that The ideal state function is expressed by the following formula: In this formula, g(t) represents the ideal physical sign index monitoring value corresponding to the viewing time t of the tested person under the ideal state without noise interference, where A K Represents the Kth power term t that forms the ideal state function K The corresponding fitting coefficients, where A K =(K+1)×C K .

7. The method according to claim 1, characterized in that The step of performing visual fatigue detection according to the reference time and the comparison time includes: Calculating a first ratio between a baseline vital sign index monitoring value and the baseline time, and determining the first ratio as a baseline visual fatigue speed corresponding to the standard equipment; Calculate a second ratio between the baseline vital sign index monitoring value and the comparison time, determine the second ratio as the target visual fatigue speed corresponding to the device under test, compare the target visual fatigue speed with the baseline visual fatigue speed, and determine the degree of difficulty of the device under test to induce visual fatigue relative to the standard device based on the comparison result; Or, calculate a third ratio between the reference moment and the comparison moment, determine the third ratio as the target visual fatigue speed corresponding to the device under test, compare the target visual fatigue speed with 1, and determine the difficulty of the device under test in inducing visual fatigue relative to the standard device based on the comparison result.

8. A visual fatigue detection device, characterized in that: The device comprises: A first acquisition module is used to acquire first test data and second test data of multiple test persons, wherein the first test data is physical sign monitoring data for characterizing the degree of visual fatigue when the multiple test persons watch the standard equipment in a preset viewing time period, and the second test data is physical sign monitoring data when the multiple test persons watch the test equipment in a preset viewing time period, and the physical sign monitoring data includes physical sign indicator monitoring values ​​of each test person at each viewing time in the preset viewing time period; A first accumulation processing module is used to perform accumulation processing on the vital sign monitoring data indicated by the first test data within a preset viewing time period to obtain a first accumulation index value corresponding to each viewing time, wherein the accumulation processing includes: integrating the vital sign monitoring data within the preset viewing time period, and calculating a ratio between the integration result and the preset viewing time period; A second accumulation processing module, used for performing accumulation processing on the vital sign monitoring data indicated by the second test data within a preset viewing time period to obtain a second accumulation index value corresponding to each viewing time; A construction module, configured to construct a first product height function corresponding to the first test data according to the first product height index value corresponding to each viewing time, and to construct a second product height function corresponding to the second test data according to the second product height index value corresponding to each viewing time, wherein the product height function is used to characterize the mapping relationship between the product height index value and the viewing time; A second acquisition module is used to obtain a reference vital sign index monitoring value at a reference time based on a first ideal state function, wherein the first ideal state function is determined by the first product height function, and the ideal state function refers to a function that eliminates noise items and is used to characterize the cumulative change of the vital sign index with viewing time; A third acquisition module, configured to obtain a comparison time corresponding to the reference vital sign index monitoring value based on a second ideal state function, wherein the second ideal state function is determined by the second product height function; The detection module is used to perform visual fatigue detection based on the reference time and the comparison time.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the visual fatigue detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the visual fatigue detection method according to any one of claims 1 to 7 are executed.

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