Eye movement visual field testing method, system and storage medium

Abstract

The present invention belongs to the technical field of eye tracking, and specifically discloses an eye movement visual field test method, system and storage medium, the method comprising: S1. static eye tracking; S2. dynamic eye tracking; S3. pupil size measurement; S4. cognitive load assessment; S5. attention analysis. The present invention detects static and dynamic eye movement feature data of a subject when watching static text and dynamic video, and then analyzes to obtain the static and dynamic attention concentration of the subject, and obtains the cognitive load evaluation coefficient of the subject according to the pupil size of each static time period and each dynamic video clip of the subject, and then comprehensively analyzes to obtain the attention evaluation index of the subject, which can more comprehensively evaluate the concentration of the subject and take corresponding improvement measures, which is helpful to further explore the attention mechanism and the pathophysiological process of related diseases.

Description

Technical Field

[0001] The present invention belongs to the technical field of eye tracking, and relates to an eye movement visual field testing method, system and storage medium. Background Art

[0002] The eye movement visual field test is a test method used to evaluate an individual's attention and cognitive function. It tracks an individual's eye movements to understand how an individual allocates attention and processes information when observing visual stimuli. During the test, the subjects will be asked to watch specific visual stimuli, such as pictures, videos or texts, and their eye movements will be recorded and analyzed in real time. By analyzing the eye movement data, information about the subject's concentration level, attention allocation pattern, visual search strategy, etc. can be obtained.

[0003] This testing method has applications in many fields, such as psychology, neuroscience, medicine, etc. It can help researchers and clinicians understand the cognitive function status of individuals, evaluate the symptoms of diseases such as attention deficit hyperactivity disorder and autism spectrum disorder, and study the human visual cognitive process.

[0004] Prior art, such as an eye movement test calibration method and device disclosed in a Chinese invention patent application with application publication number 202410277644.9, plays a target calibration animation on a graphical user interface to guide child users to perform eye movement calibration before an eye movement test, and collects the subject's eye movement information during the playback of the target calibration animation, and determines the subject's completion results for each eye movement calibration task in the target calibration animation based on the collected eye movement information, and then displays the subject's completion results for the current eye movement calibration task in the target calibration animation in real time.

[0005] Obviously, although the above-mentioned existing technology can specifically guide child subjects to perform eye movement test calibration, which is beneficial to improving the efficiency of eye movement test calibration for child subjects, it still has the following deficiencies: First, this solution is used to guide child users to perform eye movement tests by playing on a graphical user interface, but it affects the length of time that children spontaneously stay at the gaze point to a certain extent, which is likely to affect the accuracy and reliability of the eye movement test, and it may require more time and resources to repeat the test to obtain more accurate results.

[0006] Second, the program is not designed to analyze the cognitive load of the subjects. High cognitive load may cause the subjects to feel negative emotions such as anxiety and fatigue, which will affect their learning and performance and lead to inaccurate test results. Summary of the invention

[0007] In view of this, in order to solve the problems raised in the above background technology, an eye movement visual field testing method, system and storage medium are now proposed.

[0008] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides an eye movement visual field test method, the method comprising: S1. Static eye movement tracking: detecting the static eye movement feature data of the subject when the subject is watching static text, and then analyzing to obtain the static attention concentration of the subject, the static eye movement feature data of the subject includes the dwell time of each static fixation point, the number of static eye saccades, the static blinking frequency, and the reading speed.

[0009] S2. Dynamic eye tracking: The dynamic eye movement feature data of the subjects are detected when the subjects watch dynamic videos, and then the dynamic attention concentration of the subjects is analyzed. The dynamic eye movement feature data of the subjects include the dwell time of each dynamic fixation point, the number of dynamic eye saccades, and the dynamic blinking frequency.

[0010] S3. Pupil size measurement: The pupil size of the subjects is tested in each static time period and each dynamic video clip.

[0011] S4. Cognitive load assessment: The cognitive load evaluation coefficient of the subject is obtained based on the pupil size analysis of the subject in each static time period and each dynamic video segment.

[0012] S5. Attention analysis: The subject’s attention evaluation index is obtained based on the static attention concentration, dynamic attention concentration, and cognitive load evaluation coefficient, and feedback is then provided.

[0013] Preferably, the specific analysis method of the static eye tracking is as follows: the first step is to track the eye movement trajectory of the subject when viewing the static text by an eye tracker to generate the subject's static eye movement trajectory, and record the number of eye movements of the subject during the whole process of viewing the static text, recorded as x, and at the same time, the static text is divided into a number of fixation points according to the set text structure, recorded as each static fixation point, and the dwell time of each static fixation point of the subject is read from the subject's static eye movement trajectory, recorded as t i , i represents the number of the i-th static fixation point, i = 1, 2, ..., n.

[0014] In the second step, the subject's eyes are captured by a camera while the subject is watching static text to obtain the subject's static eye movement video. The subject's static eye movement video is divided into a number of video segments of equal length according to the set duration, which are recorded as each video segment. The number of blinks of the subject in each video segment is counted, and the blink frequency of the subject in each video segment is obtained by dividing the number of blinks of the subject in each video segment by the duration of the video segment, which is recorded as δ l, l represents the number of the lth video clip, l = 1, 2, ..., d, and substitute it into the formula The static blink frequency δ of the subject is obtained, and d represents the number of video clips.

[0015] The third step is to record the time taken by the subject to finish viewing the static text, and read the number of words in the static text from the management database. The static reading speed of the subject is obtained by dividing the number of words in the static text by the time taken by the subject to finish viewing the static text, which is recorded as v.

[0016] Preferably, the specific analysis method of the subject's static attention concentration degree is: respectively reading the dwell time t of each static fixation point i , static eye saccade number x, static blink frequency δ, reading speed v, and the average dwell time of each dynamic fixation point is obtained by taking the average of the dwell time of each dynamic fixation point, which is recorded as Substituting this into the formula Get the subject's static concentration γ 静 , where x 0 ,δ 0 、v 0 Respectively represent the set eye saccade number, blink frequency, and reading speed reference value, φ 1 ,φ 2 ,φ 3 ,φ 4 They represent the weight factors of the set fixation point dwell time, number of eye saccades, blink frequency, and reading speed respectively, and n is the number of dynamic fixation points.

[0017] Preferably, the specific analysis method of the dynamic eye tracking is as follows: the first step is to track the eye movement trajectory of the subject when watching the dynamic video through an eye tracker to generate the subject's dynamic eye movement trajectory, and record the number of eye movements of the subject during the whole process of watching the dynamic video, which is recorded as x'; at the same time, the dynamic video screen is divided into several areas according to the set division method, and the intersection of the diagonals of each area is taken as the fixation point, which is recorded as each dynamic fixation point; the dwell time of each dynamic fixation point of the subject is read from the subject's dynamic eye movement trajectory, which is recorded as t' m , m represents the number of the mth dynamic gaze point, m = 1, 2, ..., q.

[0018] In the second step, the subject's eyes are captured by a camera while the subject is watching a dynamic video to obtain the subject's dynamic eye movement video. The subject's dynamic eye movement video is analyzed according to the method of analyzing the subject's static blinking frequency to obtain the subject's dynamic blinking frequency, which is recorded as δ'.

[0019] Preferably, the specific analysis method of the dynamic attention concentration of the subject is: reading the dwell time t' of each dynamic fixation point respectively. m , dynamic eye saccade number x', dynamic blink frequency δ', and the average dwell time of each dynamic gaze point is obtained by taking the average of the dwell time of each dynamic gaze point, which is recorded as Substituting this into the formula Get the subject's dynamic attention concentration γ 动 , where x' 0 ,δ' 0 They represent the reference values ​​of the set dynamic eye saccade times and dynamic blinking frequency respectively. They represent the weight factors of the set dynamic fixation point dwell time, dynamic eye saccade number, and dynamic blink frequency respectively, and q is the number of dynamic fixation points.

[0020] Preferably, the specific analysis method for measuring pupil size is as follows: the first step is to read the time taken by the subject to finish viewing the static text, divide it into a number of time periods of equal length, record it as each static time period, and take a number of time points in each static time period according to the set time interval, record it as each static time point in each static time period, obtain an image of the subject's pupil at each static time point in each static time period, and measure the pupil size therefrom, record it as the subject's pupil size at each static time point in each static time period. jk , j represents the number of the jth static time period, j = 1, 2, ..., u, k represents the number of the kth static time point, k = 1, 2, ..., f, and substitute it into the formula Get the pupil size of the subject in each static time period. j , f represents the number of static time points.

[0021] In the second step, the dynamic video is divided into a number of video segments according to the set length, which are recorded as each dynamic video segment, and a number of time points are taken in each dynamic video segment according to the set time interval, which are recorded as each dynamic time point of each dynamic video segment. Each dynamic video segment is analyzed according to the method of analyzing the pupil size of the subject at each static time point in each static time period of the subject to obtain the pupil size of the subject at each dynamic time point of each dynamic video segment of the subject, and the pupil size of each dynamic video segment of the subject is obtained by taking the average value, which is recorded as ο' h , h represents the number of the hth dynamic video segment, h = 1, 2, ..., g.

[0022] Preferably, the specific analysis method of the cognitive load assessment is: reading the pupil size of the subject in each static time period respectively. j , pupil size of each dynamic video clip h , substituting it into the formula The cognitive load evaluation coefficient χ of the subjects is obtained, where u represents the number of static time periods, g represents the number of dynamic video clips, and κ 1 represents the set environmental impact factor, and ω represents the proportional constant between the set pupil size and cognitive load.

[0023] Preferably, the specific analysis method of the attention analysis is: the first step is to read the static attention concentration degree γ of the subject respectively. 静 , dynamic attention concentration γ 动 , cognitive load evaluation coefficient χ, substitute it into the formula Get the subject's attention evaluation index ψ, where w 1 、w 2 They represent the set concentration level and the weight factor of cognitive load evaluation coefficient respectively, and e is a natural constant.

[0024] In the second step, the subject's attention evaluation index is compared with the preset attention evaluation index threshold. If the subject's attention evaluation index is greater than or equal to the preset attention evaluation index threshold, it means that the subject's attention evaluation index is qualified. If the subject's attention evaluation index is less than the preset attention evaluation index threshold, it means that the subject's attention evaluation index is unqualified and feedback is given.

[0025] The second aspect of the present invention provides an eye movement visual field testing system, which includes: a static eye movement tracking module, which is used to detect the static eye movement feature data of the subject when the subject is viewing static text, and then analyze the subject's static attention concentration level. The subject's static eye movement feature data includes the dwell time of each static gaze point, the number of static eye saccades, the static blinking frequency, and the reading speed.

[0026] The dynamic eye tracking module is used to detect the dynamic eye movement feature data of the subject when the subject is watching a dynamic video, and then analyze the subject's dynamic attention concentration. The subject's dynamic eye movement feature data includes the dwell time of each dynamic gaze point, the number of dynamic eye saccades, and the dynamic blinking frequency.

[0027] The eye movement analysis module is used to obtain the subject's static attention concentration level based on the subject's static eye movement feature data analysis, and to obtain the subject's dynamic attention concentration level based on the subject's dynamic eye movement feature data analysis.

[0028] The pupil size measurement module is used to detect the pupil size of the subject in each static time period and each dynamic video clip.

[0029] The cognitive load evaluation module is used to obtain the cognitive load evaluation coefficient of the subject based on the pupil size analysis of each static time period and each dynamic video segment of the subject.

[0030] The attention analysis module is used to obtain the subject's attention evaluation index based on the dwell time of each static fixation point and dynamic fixation point and the cognitive load evaluation coefficient, and feed it back to the system.

[0031] Management database, used to store the word count of static text.

[0032] The third aspect of the present invention further provides a storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in an eye movement visual field testing method.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention detects the static and dynamic eye movement feature data of the subjects when they watch static text and dynamic processes, and then analyzes the static and dynamic concentration levels of the subjects, which can help to discover attention-related problems at an early stage and provide opportunities for timely intervention.

[0034] 2. The present invention obtains the cognitive load evaluation coefficient of the subject based on the pupil size analysis of each static time period and each dynamic video clip of the subject, which can directly reflect the cognitive load level of the subject in different tasks or situations, and can promptly discover possible problems and take corresponding measures.

[0035] 3. The present invention obtains the subject's attention evaluation index based on the subject's static attention concentration, dynamic attention concentration, and cognitive load evaluation coefficient analysis, which can more comprehensively understand the subject's attention state and make the test results more reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0037] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method.

[0038] Figure 2 It is a schematic diagram of the connection of the system modules of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1 As shown, the first aspect of the present invention provides an eye movement visual field testing method, the method comprising: S1. static eye movement tracking: detecting the static eye movement feature data of the subject when the subject is viewing static text, and then analyzing to obtain the subject's static attention concentration level, the subject's static eye movement feature data includes the dwell time of each static fixation point, the number of static eye saccades, the static blinking frequency, and the reading speed.

[0041] The specific analysis method of the static eye tracking is as follows: the first step is to track the eye movement trajectory of the subject when viewing the static text by an eye tracker to generate the subject's static eye movement trajectory, and record the number of eye movements of the subject during the whole process of viewing the static text, which is recorded as x. At the same time, the static text is divided into a number of fixation points according to the set text structure, which are recorded as static fixation points. The dwell time of each static fixation point of the subject is read from the subject's static eye movement trajectory, which is recorded as t. i , i represents the number of the i-th static fixation point, i=1,2,...,n; the eye tracker can record the eye movement trajectory of the subject when viewing static text, which helps to gain a deeper understanding of the subject's attention and cognitive function.

[0042] In the second step, the subject's eyes are captured by a camera while the subject is watching static text to obtain the subject's static eye movement video. The subject's static eye movement video is divided into a number of video segments of equal length according to the set duration, which are recorded as each video segment. The number of blinks of the subject in each video segment is counted, and the blink frequency of the subject in each video segment is obtained by dividing the number of blinks of the subject in each video segment by the duration of the video segment, which is recorded as δ l , l represents the number of the lth video clip, l = 1, 2, ..., d, and substitute it into the formula The static blinking frequency δ of the subject is obtained, where d represents the number of video clips. By analyzing eye movement indicators such as blinking frequency, we can more objectively understand the attention state of the subject when watching static text, which is helpful for diagnosing attention-related diseases and providing a reference for the formulation of treatment plans.

[0043] The third step is to record the time taken by the subject to finish viewing the static text, and read the number of words in the static text from the management database. The static reading speed of the subject is obtained by dividing the number of words in the static text by the time taken by the subject to finish viewing the static text, which is denoted as v. This can intuitively understand the static reading speed of the subject, reflect his or her reading efficiency, and at the same time, reflect the subject's attention to a certain extent.

[0044] The specific analysis method of the subject's static attention concentration degree is: respectively read the dwell time t of each static fixation point i , static eye saccade number x, static blink frequency δ, reading speed v, and the average dwell time of each dynamic fixation point is obtained by taking the average of the dwell time of each dynamic fixation point, which is recorded as Substituting this into the formula Get the subject's static concentration γ 静 , where x 0 ,δ 0 、v 0 Respectively represent the set eye saccade number, blink frequency, and reading speed reference value, φ 1 ,φ 2 ,φ 3 ,φ 4 They represent the weight factors of the set fixation time, number of eye saccades, blinking frequency, and reading speed respectively, and n is the number of dynamic fixation points. It can more comprehensively evaluate the subject's static attention concentration and gain an in-depth understanding of the subject's attention formation and operation mechanism.

[0045] It should be noted that, in a specific embodiment, φ 1 Can be set to 0.4, φ 2 Can be set to 0.2, φ 3 Can be set to 0.2, φ 4 It can be set to 0.2. The duration of static fixation reflects the degree and duration of the subject's attention to a specific area during the reading of static text. It directly reflects the subject's attention to a specific object or task. A longer fixation duration may indicate a higher degree of concentration, so the weight corresponding to the static fixation duration is larger.

[0046] S2. Dynamic eye tracking: The dynamic eye movement feature data of the subjects are detected when the subjects watch dynamic videos, and then the dynamic attention concentration of the subjects is analyzed. The dynamic eye movement feature data of the subjects include the dwell time of each dynamic fixation point, the number of dynamic eye saccades, and the dynamic blinking frequency.

[0047] The specific analysis method of the dynamic eye tracking is as follows: the first step is to track the eye movement trajectory of the subject when watching the dynamic video through the eye tracker to generate the subject's dynamic eye movement trajectory, and record the number of eye movements of the subject during the whole process of watching the dynamic video, which is recorded as x'; at the same time, the dynamic video screen is divided into several areas according to the set division method, and the intersection of the diagonal lines of each area is taken as the fixation point, which is recorded as each dynamic fixation point; the dwell time of each dynamic fixation point of the subject is read from the subject's dynamic eye movement trajectory, which is recorded as t' m , m represents the number of the mth dynamic fixation point, m = 1, 2, ..., q; by recording the number of eye movements and the duration of each dynamic fixation point, a quantitative assessment of the subject's attention can be achieved, providing richer data for eye movement visual field testing, which is conducive to in-depth research and analysis.

[0048] In the second step, a video of the subject's eyes is captured by a camera while the subject is watching a dynamic video to obtain the subject's dynamic eye movement video. The subject's dynamic eye movement video is analyzed according to the method of analyzing the subject's static blinking frequency to obtain the subject's dynamic blinking frequency, which is recorded as δ'. The subject's eye movement can be recorded in real time to obtain more accurate data.

[0049] The specific analysis method of the dynamic attention concentration of the subject is: respectively read the dwell time t' of each dynamic fixation point m , dynamic eye saccade number x', dynamic blink frequency δ', and the average dwell time of each dynamic gaze point is obtained by taking the average of the dwell time of each dynamic gaze point, which is recorded as Substituting this into the formula Get the subject's dynamic attention concentration γ 动 , where x' 0 ,δ' 0 They represent the reference values ​​of the set dynamic eye saccade times and dynamic blinking frequency respectively. They respectively represent the weight factors of the set dynamic fixation point dwell time, dynamic eye saccade number, and dynamic blinking frequency, and q is the number of dynamic fixation points. It can monitor and analyze the changes in attention in real time, which is helpful to study the dynamic characteristics of attention.

[0050] It should be noted that, in a specific embodiment, It can be set to 0.4. It can be set to 0.3. It can be set to 0.3. The duration of the dynamic fixation point reflects the subject's attention to the dynamic target or task. A longer dynamic fixation point duration may indicate a higher level of concentration. Therefore, the weight corresponding to the dynamic fixation point duration is larger.

[0051] S3. Pupil size measurement: The pupil size of the subjects is tested in each static time period and each dynamic video clip.

[0052] The specific analysis method for pupil size measurement is as follows: the first step is to read the time taken by the subject to finish watching the static text, divide it into a number of equal-length time periods, record it as each static time period, and take a number of time points in each static time period according to the set time interval, record it as each static time point of each static time period, obtain images of the subject's pupil at each static time point of each static time period, and measure the pupil size therefrom, record it as the subject's pupil size at each static time point of each static time period. jk , j represents the number of the jth static time period, j = 1, 2, ..., u, k represents the number of the kth static time point, k = 1, 2, ..., f, and substitute it into the formula Get the pupil size of the subject in each static time period. j , f represents the number of static time points; it can be used to study the changing patterns of the subjects’ pupil size in different time periods and understand the dynamic changes of their attention and cognitive states.

[0053] In the second step, the dynamic video is divided into a number of video segments according to the set length, which are recorded as each dynamic video segment, and a number of time points are taken in each dynamic video segment according to the set time interval, which are recorded as each dynamic time point of each dynamic video segment. Each dynamic video segment is analyzed according to the method of analyzing the pupil size of the subject at each static time point in each static time period of the subject to obtain the pupil size of the subject at each dynamic time point of each dynamic video segment of the subject, and the pupil size of each dynamic video segment of the subject is obtained by taking the average value, which is recorded as ο' h , h represents the number of the h-th dynamic video segment, h=1,2,...,g; dividing the dynamic video into multiple segments and taking multiple time points therein can more comprehensively analyze the changes in the pupil size of the subjects, which is convenient for studying the distribution and concentration of the subjects' attention when watching dynamic videos.

[0054] S4. Cognitive load assessment: The cognitive load evaluation coefficient of the subject is obtained based on the pupil size analysis of the subject in each static time period and each dynamic video segment.

[0055] The specific analysis method of the cognitive load assessment is: reading the pupil size of the subject in each static time period respectively. j , pupil size of each dynamic video clip h , substituting it into the formula The cognitive load evaluation coefficient χ of the subjects is obtained, where u represents the number of static time periods, g represents the number of dynamic video clips, and κ 1represents the set environmental influencing factor, ω represents the proportional constant of the set pupil size to the cognitive load; combining the pupil size of static time periods and dynamic video clips more comprehensively considers cognitive activities in different situations, which is helpful for diagnosing diseases related to cognitive function and providing valuable information for clinicians.

[0056] It should be noted that the specific analysis method of the set environmental impact factors is: the monitoring time points are divided according to the set time intervals, and the light intensity at each monitoring time point when the subject performs static eye tracking and dynamic eye tracking is detected by a light sensor, which is recorded as the static eye movement light intensity at each monitoring time point and the dynamic eye movement light intensity at each monitoring time point, and the static eye movement light intensity and dynamic eye movement light intensity are obtained by taking the average value, which is recorded as θ 静 ,θ 动 , through the formula Get the environmental impact factor κ 1 , Indicates the proportional constant between the set light intensity and the environmental impact factor.

[0057] S5. Attention analysis: The subject’s attention evaluation index is obtained based on the static attention concentration, dynamic attention concentration, and cognitive load evaluation coefficient, and feedback is then provided.

[0058] The specific analysis method of the attention analysis is as follows: the first step is to read the static attention concentration degree γ of the subject respectively. 静 , dynamic attention concentration γ 动 , cognitive load evaluation coefficient χ, substitute it into the formula Get the subject's attention evaluation index ψ, where w 1 、w 2 They respectively represent the set concentration level and weight factors of cognitive load evaluation coefficient, and e is a natural constant. It helps to understand the subject's attention state and health status, and helps to understand the subject's attention characteristics.

[0059] It should be noted that, in a specific embodiment, w 1 Can be set to 0.5, w 2 It can be set to 0.5. The degree of concentration reflects a person's ability to focus in a specific task or situation. A higher degree of concentration usually means better attention performance, and the cognitive load evaluation coefficient can reflect the complexity of the task and the demand for cognitive resources. A higher cognitive load may challenge attention. Therefore, the corresponding weights of the degree of concentration and the cognitive load evaluation coefficient are equal.

[0060] In the second step, the subject's attention evaluation index is compared with the preset attention evaluation index threshold. If the subject's attention evaluation index is greater than or equal to the preset attention evaluation index threshold, it means that the subject's attention evaluation index is qualified. If the subject's attention evaluation index is less than the preset attention evaluation index threshold, it means that the subject's attention evaluation index is unqualified and feedback is given. For unqualified subjects, timely discovery and feedback can be given so that corresponding intervention measures can be taken, which is helpful to discover attention-related health problems and provide a basis for diagnosis.

[0061] The embodiment of the present invention detects the static and dynamic eye movement feature data of the subject when the subject watches static text and dynamic process, and then analyzes and obtains the static and dynamic attention concentration of the subject, and obtains the cognitive load evaluation coefficient of the subject according to the pupil size analysis of each static time period and each dynamic video clip of the subject, and obtains the attention evaluation index of the subject according to the static attention concentration degree, dynamic attention concentration degree and cognitive load evaluation coefficient of the subject, which can more comprehensively understand the attention state of the subject and take corresponding improvement measures, which is helpful to further explore the attention mechanism and the pathophysiological process of related diseases.

[0062] See also Figure 2 As shown, the second aspect of the present invention provides an eye movement visual field testing system, which includes: a static eye movement tracking module, a dynamic eye movement tracking module, an eye movement analysis module, a pupil size measurement module, a cognitive load assessment module, an attention analysis module, and a management database.

[0063] In the above, the management database is connected to the eye movement analysis module, the attention analysis module, and the cognitive load assessment module; the eye movement analysis module is connected to the static eye tracking module, the dynamic eye tracking module, and the attention analysis module; the cognitive load assessment module is connected to the pupil size measurement module and the attention analysis module.

[0064] The static eye movement tracking module is used to detect the static eye movement feature data of the subject when the subject is viewing static text, and then analyze the subject's static attention concentration. The subject's static eye movement feature data includes the dwell time of each static gaze point, the number of static eye saccades, the static blinking frequency, and the reading speed.

[0065] The dynamic eye tracking module is used to detect the dynamic eye movement feature data of the subject when the subject is watching a dynamic video, and then analyze the subject's dynamic attention concentration. The subject's dynamic eye movement feature data includes the dwell time of each dynamic gaze point, the number of dynamic eye saccades, and the dynamic blinking frequency.

[0066] The eye movement analysis module is used to obtain the subject's static attention concentration level based on the subject's static eye movement feature data analysis, and to obtain the subject's dynamic attention concentration level based on the subject's dynamic eye movement feature data analysis.

[0067] The pupil size measurement module is used to detect the pupil size of the subject in each static time period and each dynamic video clip.

[0068] The cognitive load evaluation module is used to obtain the cognitive load evaluation coefficient of the subject based on the pupil size analysis of each static time period and each dynamic video segment of the subject.

[0069] The attention analysis module is used to obtain the subject's attention evaluation index based on the dwell time of each static fixation point and dynamic fixation point and the cognitive load evaluation coefficient, and feed it back to the system.

[0070] Management database, used to store the word count of static text.

[0071] The third aspect of the present invention further provides a storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement an eye movement visual field testing method described in the present invention.

[0072] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for eye movement visual field testing, characterized in that: The method includes: S1. Static eye movement tracking: Detect the static eye movement feature data of the subject when the subject is watching static text, and then analyze the static attention concentration of the subject. The static eye movement feature data of the subject includes the dwell time of each static fixation point, the number of static eye saccades, the static blinking frequency, and the reading speed; S2. Dynamic eye tracking: Detect the dynamic eye movement feature data of the subject when the subject is watching the dynamic video, and then analyze the dynamic attention concentration of the subject. The dynamic eye movement feature data of the subject includes the dwell time of each dynamic fixation point, the number of dynamic eye saccades, and the dynamic blinking frequency; S3. Pupil size measurement: The pupil size of the subject is measured in each static time period and each dynamic video clip; S4. Cognitive load assessment: The cognitive load evaluation coefficient of the subject is obtained based on the pupil size analysis of the subject in each static time period and each dynamic video segment; S5. Attention analysis: According to the static attention concentration level, dynamic attention concentration level and cognitive load evaluation coefficient of the subject, the attention evaluation index of the subject is obtained, and feedback is then given; The specific analysis method of the static eye tracking is: In the first step, the eye movement trajectory of the subject when viewing the static text is tracked by an eye tracker to generate the subject's static eye movement trajectory, and the number of eye movements of the subject during the whole process of viewing the static text is recorded, recorded as x, and the static text is divided into several fixation points according to the set text structure, recorded as each static fixation point, and the duration of the subject's stay at each static fixation point is read from the subject's static eye movement trajectory, recorded as t i , i represents the number of the i-th static fixation point, i = 1, 2, ..., n; In the second step, the subject's eyes are captured by a camera while the subject is watching static text to obtain the subject's static eye movement video. The subject's static eye movement video is divided into a number of video segments of equal length according to the set duration, which are recorded as each video segment. The number of blinks of the subject in each video segment is counted, and the blink frequency of the subject in each video segment is obtained by dividing the number of blinks of the subject in each video segment by the duration of the video segment, which is recorded as δ l , l represents the number of the lth video clip, l = 1, 2, ..., d, and substitute it into the formula The static blinking frequency δ of the subject is obtained, where d represents the number of video clips; The third step is to record the time taken by the subject to finish viewing the static text, and read the number of words in the static text from the management database. The static reading speed of the subject is obtained by dividing the number of words in the static text by the time taken by the subject to finish viewing the static text, which is recorded as v. The specific analysis method of the subject's static attention concentration is: Read the dwell time t of each static gaze point respectively i , static eye saccade number x, static blink frequency δ, reading speed v, and the average duration of static fixation points is obtained by taking the average duration of each static fixation point, which is recorded as Substituting this into the formula Get the subject's static concentration γ 静 , where x0, δ0, v0 represent the set eye saccade number, blink frequency, and reading speed reference values, respectively; φ1, φ2, φ3, φ4 represent the set fixation point dwell time, eye saccade number, blink frequency, and reading speed weight factors, respectively; n is the number of static fixation points; The specific analysis method of the dynamic eye tracking is: In the first step, the eye movement trajectory of the subject when watching the dynamic video is tracked by an eye tracker to generate the subject's dynamic eye movement trajectory, and the number of eye movements of the subject during the whole process of watching the dynamic video is recorded, recorded as x'. At the same time, the dynamic video screen is divided into several areas according to the set division method, and the intersection of the diagonals of each area is taken as the fixation point, recorded as each dynamic fixation point, and the dwell time of each dynamic fixation point of the subject is read from the subject's dynamic eye movement trajectory, recorded as t' m , m represents the number of the mth dynamic fixation point, m = 1, 2, ..., q; The second step is to capture the subject's eyes through a camera while the subject is watching a dynamic video to obtain the subject's dynamic eye movement video, and analyze the subject's dynamic eye movement video according to the method of analyzing the subject's static blinking frequency to obtain the subject's dynamic blinking frequency, which is recorded as δ'; The specific analysis method of the dynamic attention concentration degree of the subject is: Read the dwell time t' of each dynamic gaze point respectively m , dynamic eye saccade number x', dynamic blink frequency δ', and the average dwell time of each dynamic gaze point is obtained by taking the average of the dwell time of each dynamic gaze point, which is recorded as Substituting this into the formula Get the subject's dynamic attention concentration γ 动 , where x'0 and δ'0 represent the reference values ​​of dynamic eye saccade times and dynamic blink frequency, respectively. They represent the weight factors of the set dynamic fixation point dwell time, dynamic eye saccade number, and dynamic blink frequency respectively, and q is the number of dynamic fixation points.

2. The eye movement visual field testing method according to claim 1, characterized in that: The specific analysis method of the pupil size measurement is: The first step is to read the time taken by the subject to finish watching the static text, divide it into several time periods of equal length, record it as each static time period, and take several time points in each static time period according to the set time, record it as each static time point of each static time period, obtain images of the subject's pupils at each static time point of each static time period, and measure the pupil size therefrom, record it as the pupil size of the subject at each static time point of each static time period of the subject. jk , j represents the number of the jth static time period, j = 1, 2, ..., u, k represents the number of the kth static time point, k = 1, 2, ..., f, and substitute it into the formula Get the pupil size of the subject in each static time period. j , f represents the number of static time points; In the second step, the dynamic video is divided into a number of video segments according to the set length, which are recorded as each dynamic video segment, and a number of time points are taken in each dynamic video segment according to the set time interval, which are recorded as each dynamic time point of each dynamic video segment. Each dynamic video segment is analyzed according to the method of analyzing the pupil size of the subject at each static time point in each static time period of the subject to obtain the pupil size of the subject at each dynamic time point of each dynamic video segment of the subject, and the pupil size of each dynamic video segment of the subject is obtained by taking the average value, which is recorded as ο' h , h represents the number of the hth dynamic video segment, h = 1, 2, ..., g.

3. The eye movement visual field testing method according to claim 2, characterized in that: The specific analysis method of the cognitive load assessment is: Read the pupil size of the subject in each static time period respectively. j , pupil size of each dynamic video clip h , substituting it into the formula The cognitive load evaluation coefficient χ of the subject is obtained, where u represents the number of static time periods, g represents the number of dynamic video clips, κ1 represents the set environmental impact factor, and ω represents the proportional constant between the set pupil size and cognitive load.

4. The eye movement visual field testing method according to claim 3, characterized in that: The specific analysis method of the attention analysis is: The first step is to read the static concentration level of the subjects γ 静 , dynamic attention concentration γ 动 , cognitive load evaluation coefficient χ, substitute it into the formula The subject's attention evaluation index ψ is obtained, where w1 and w2 represent the weight factors of the set attention concentration level and cognitive load evaluation coefficient, respectively, and e is a natural constant; In the second step, the subject's attention evaluation index is compared with the preset attention evaluation index threshold. If the subject's attention evaluation index is greater than or equal to the preset attention evaluation index threshold, it means that the subject's attention evaluation index is qualified. If the subject's attention evaluation index is less than the preset attention evaluation index threshold, it means that the subject's attention evaluation index is unqualified and feedback is given.

5. An eye movement visual field testing system, used to perform the steps in an eye movement visual field testing method as claimed in any one of claims 1 to 4, characterized in that: The system includes: The static eye movement tracking module is used to detect the static eye movement feature data of the subject when the subject is viewing static text, and then analyze the static concentration of the subject. The static eye movement feature data of the subject includes the dwell time of each static fixation point, the number of static eye saccades, the static blinking frequency, and the reading speed; The dynamic eye tracking module is used to detect the dynamic eye movement feature data of the subject when the subject is watching the dynamic video, and then analyze the dynamic attention concentration of the subject. The dynamic eye movement feature data of the subject includes the dwell time of each dynamic fixation point, the number of dynamic eye saccades, and the dynamic blinking frequency; An eye movement analysis module, used to obtain the subject's static attention concentration level based on the subject's static eye movement feature data analysis, and to obtain the subject's dynamic attention concentration level based on the subject's dynamic eye movement feature data analysis; The pupil size measurement module is used to detect the pupil size of the subject in each static time period and each dynamic video clip; A cognitive load evaluation module is used to obtain a cognitive load evaluation coefficient of a subject based on pupil size analysis of each static time period and each dynamic video segment of the subject; The attention analysis module is used to analyze the subject's attention evaluation index based on the dwell time of each static fixation point and dynamic fixation point and the cognitive load evaluation coefficient, and feed it back to the system; Management database, used to store the word count of static text.

6. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the eye movement visual field testing method as described in any one of claims 1-4.

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