A quantitative evaluation system for eye movement function based on eye tracker

Abstract

The present invention relates to an eye movement function quantitative evaluation system based on an eye tracker, which can realize automatic quantitative evaluation of three eye functions: fixation, saccade and smooth pursuit, and provide support for eye disease diagnosis and eye rehabilitation effect evaluation. The system includes an eye tracker, an evaluation interface generation module, a data processing module, a motor function evaluation module and an evaluation result display interface. The computer processes the acquired eye movement data, calculates the eye movement data characteristics, designs the eye movement function quantitative rating index, and automatically gives the quantitative rating result, so that the diagnosis result is more accurate, intuitive and convenient, reduces the workload of doctors, provides doctors with more accurate eye movement diagnosis information, and helps doctors understand the patient's eye movement function status, so as to better diagnose and treat. Starting from the clinical needs of ophthalmology, this system realizes automatic quantitative evaluation and grading of eye movement function, provides reference for eye disease diagnosis and eye rehabilitation effect evaluation, and is of great significance.

Description

Technical Field

[0001] The invention relates to the field of eye movement function assessment, and in particular to an eye movement function quantitative assessment system based on an eye tracker. Background Art

[0002] According to a survey in my country, among the five types of disabilities, visually impaired children account for 5%. Among the new disabilities each year, visually impaired children increase by about 16,000, of which eye movement dysfunction accounts for a large part. Some of them can be restored through surgery or non-surgical means, so it is particularly important to detect the problem as early as possible and carry out corresponding treatment. However, most eye movement dysfunctions are now diagnosed by doctors, which depends on the doctor's experience and is very subjective. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides an eye movement function quantitative evaluation system based on an eye tracker.

[0004] The present invention adopts the following technical solutions:

[0005] An eye movement function quantitative evaluation system based on an eye tracker, comprising:

[0006] Eye tracker, used to collect eye movement data;

[0007] An evaluation interface generation module is used to generate a corresponding dynamic display interface according to the eye movement function to be evaluated, so as to guide the subject's eye movement;

[0008] A data processing module, used for processing the eye movement data collected by the eye tracker according to the eye movement function to be evaluated, and generating corresponding feature data;

[0009] A motor function evaluation module, used to evaluate eye movement ability and give a motor function grade based on the characteristic data generated by the data processing module; and

[0010] The evaluation result display interface is used to display the evaluation and grading results of the subject's eyes.

[0011] Optionally, the eye movement data includes the eye gaze focus position, the collection time corresponding to each focus data and the spatial position of the eyeball.

[0012] Optionally, the dynamic display interface generated by the evaluation interface generation module includes a gaze function evaluation interface, a scan function evaluation interface and a smooth pursuit function evaluation interface.

[0013] Optionally, the data processing module includes: a gaze data processing unit, a scan data processing unit and a smooth pursuit data processing unit.

[0014] Optionally, the data processing module further includes: a data preprocessing unit, and the data preprocessing unit is used to complete the eye movement data using a linear interpolation method.

[0015] Optionally, the gaze data processing unit comprises: first analyzing the eye movement data to determine the gaze start point and the saccade start point, then extracting the gaze data, the gaze data being the data from the start of gaze to the start of saccade, and calculating the following from the extracted gaze data: focus radius, maximum saccade distance, total gaze time, maximum gaze duration and saccade latency;

[0016] The scanning data processing unit comprises: performing scanning data processing on the eye movement data to calculate the scanning peak speed and the scanning average speed;

[0017] The smooth tracking data processing unit includes: smoothly moving the fixation target point from the starting position to the ending position, and calculating the average phase lag and the average tracking gain.

[0018] Optionally, the motor function assessment module includes a gaze function assessment unit, a saccade function assessment unit and a smooth pursuit function assessment unit;

[0019] The gaze function evaluation unit comprises: normalizing the focus radius, maximum saccade distance, total gaze time, maximum continuous gaze time and saccade latency obtained by the gaze data processing unit, and grading each data according to the interval in which it is located; and calculating the mean of each normalized data as an overall evaluation of the gaze function;

[0020] The scanning function evaluation unit includes: normalizing the scanning peak speed and the scanning average speed obtained by the scanning data processing unit, and classifying each data according to the interval in which each data is located; and calculating the mean value of each normalized data as an overall evaluation of the scanning function;

[0021] The smooth tracking function evaluation unit includes: normalizing the average phase lag and average tracking gain obtained by the smooth tracking data processing unit, grading each data according to the interval in which it is located; and calculating the mean of each normalized data as an overall evaluation of the smooth tracking function.

[0022] The present invention provides an eye movement function quantitative evaluation system based on an eye tracker. The eye tracker is used to create a system for automatic quantitative evaluation of eye movement function. The computer processes the acquired eye movement data, calculates the eye movement data features, designs eye movement function quantitative rating indicators, and automatically gives quantitative rating results, thereby making the diagnosis results more accurate, intuitive, and convenient, reducing the workload of doctors, providing doctors with more accurate eye movement diagnostic information, and helping doctors understand the patient's eye movement function status for better diagnosis and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the following is a brief introduction to the drawings required for use in the embodiment:

[0024] Figure 1 It is a structural principle diagram of a quantitative evaluation system for eye movement function based on an eye tracker provided in an embodiment of the present application;

[0025] Figure 2 It is a schematic diagram of the human-computer interaction interface of the eye movement function quantitative evaluation system based on an eye tracker;

[0026] Figure 3-a and Figure 3-b is a schematic diagram of the gaze data collection interface;

[0027] Figure 4-a and Figure 4-b is a schematic diagram of the scanning data collection interface;

[0028] Figure 5-a and Figure 5-b It is a schematic diagram of the smooth tracking data acquisition interface;

[0029] Figure 6 This is a radar diagram. DETAILED DESCRIPTION

[0030] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0031] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0032] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0033] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0034] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0035] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0036] In order to illustrate the technical solution described in this application, a specific implementation method is provided below.

[0037] like Figure 1 As shown, this embodiment provides an eye movement function quantitative evaluation system based on an eye tracker, including an eye tracker, an evaluation interface generation module, a data processing module, a motor function evaluation module, and an evaluation result display interface. In this embodiment, the evaluation interface generation module, the data processing module, the motor function evaluation module, and the evaluation result display interface are all implemented by a host computer. This evaluation system will provide patients with a portable, easy-to-use quantitative evaluation device.

[0038] The eye tracker may be a Tobii5 eye tracker, which is used to collect eye movement data. In this embodiment, the eye tracker is used to calibrate and capture eye movement data in real time, including the eye focus position, the collection time corresponding to each focus data, and the spatial position of the eyeball. The position of the eye focus is (x ki ,yki ), i is the order of gaze point collection, k is the target point (specifically represents the order of target points), and the collection time (i.e. sampling time) corresponding to each data (i.e. the position of the eye's gaze focus) is t ki .

[0039] In this embodiment, Figure 2 The figure is a schematic diagram of the human-computer interaction interface of the eye movement function quantitative evaluation system based on the eye tracker. Figure 2 As shown, the human-computer interaction interface of the eye movement function quantitative evaluation system of the present invention includes eye tracker calibration, nine-point method test, tracking test, glance check, and result evaluation. The module shown in the eye tracker calibration will calibrate the patient's eye tracker to ensure the accuracy of the eye movement data. Each patient needs to be calibrated before collecting eye movement data, and if the patient's head moves too much during the test, it is necessary to recalibrate before collecting eye movement data. The calibration process uses the calibration program that comes with EyeTracker5 for calibration. The module shown in the nine-point method test can collect gaze data from patients, the module shown in the tracking test can collect smooth tracking data from patients, the module shown in the glance check can collect glance data from patients, and the module shown in the result evaluation will perform quantitative evaluation on the collected data.

[0040] The evaluation interface generation module is used to generate a corresponding dynamic display interface according to the eye movement function to be evaluated, and guide the subject's eye movement. In this embodiment, the dynamic display interface generated by the evaluation interface generation module includes a gaze function evaluation interface, a saccade function evaluation interface, and a smooth pursuit function evaluation interface.

[0041] As a specific implementation, in the gaze function evaluation interface, the tracked target is a circular ring, the inner circle radius of which is 15 pixels and the outer circle radius is 30 pixels.

[0042] like Figure 3-a As shown, the first target point in the upper left corner is located at (0.1x s , 0.1y s ), before starting, you can set the duration of the target point, Figure 3-a As shown in the figure, the duration of each target point is 10 seconds. After setting the desired target point duration, the patient is required to stare at the target while keeping his head still. Then click Start to start collecting the patient's gaze data. Figure 3-b shows the order in which the various targets appear when collecting the patient's gaze data. Figure 3-b As shown, at the first target point (0.1x s , 0.1y s ) disappears, and after the second dot appears, the patient is asked to focus on the newly appeared target as quickly as possible. The targets appear in the following order: Figure 3-bAs shown by the arrow in the middle. At the last target (0.5x s , 0.5y s ) disappears, data collection stops.

[0043] The display interface contains nine tracking targets. The target position is related to the display range. The generation algorithm is: if the display range is (x s ,y s ), then the nine fixation targets are: (0.1x s , 0.1y s )、(0.1x s , 0.5y s )、(0.1x s , 0.9y s )、(0.5x s , 0.1y s )、(0.5x s , 0.5y s )、(0.5x s , 0.9y s )、(0.9x s , 0.1y s )、(0.9x s , 0.5y s )、(0.9x s , 0.9y s ), the target position is defined as (x tk ,y tk ).

[0044] In the scanning function evaluation interface, if the display range is (x s ,y s ), then in: (0.1x s , 0.1y s ), (0.1x s , 0.2y s ), (0.1x s , 0.3y s ),......,(0.1x s , 0.9y s ), (0.2x s , 0.1y s ), (0.2x s , 0.2y s ), (0.2x s , 0.3y s ), ..., (0.2x s , 0.9y s ),......,(0.3x s , 0.9y s ), ..., (0.5xs , 0.9y s ),......,(0.9x s , 0.9y s ) and 81 other positions each display a randomly generated number between 1 and 99, with a number size of 30 pixels. A number is randomly selected from each row as the target, with a total of 9 targets. In this embodiment, the target number and the non-target number are represented differently, for example, the target number is surrounded by a circle, while other non-target numbers do not have a circle. The target position is defined as (x tk ,y tk ).

[0045] like Figure 4-a and Figure 4-b As shown in the figure, there are 81 digital targets in the scanning task, among which the circled numbers are the targets that the patient needs to search for. During the data collection process, the patient needs to search for the circled targets in each column as quickly as possible. After the patient completes the search task, press the space bar to end the task. During this process, the patient's scanning data is collected through an eye tracker. Figure 4-a and Figure 4-b It also shows that after the click starts, the position of the target will change and is not constant.

[0046] The smooth pursuit function evaluation interface simulates the paper-based scanning function training book used in clinical practice. There is a target in the display interface, and the target passes through 6 set positions in sequence at a set speed. Figure 5-a and Figure 5-b As shown, before starting to collect data, the target movement time can be set to change the target movement speed to meet different data collection requirements. Figure 5-a and Figure 5-b The target motion time shown in the figure is 10 seconds. Before starting, the patient is required to keep his head still and stare at the center of the target point circle, then click Start to start collecting smooth pursuit data. Figure 5-a and Figure 5-b The order in which the targets appear when the patient's smooth pursuit data is collected is also shown in Figure . Figure 5-a and Figure 5-b As shown, the target point is from (0.3x s , 0.1y s ) and arrive at (0.7x s , 0.3y s ) and then to (0.3x s , 0.5y s ), then reach (0.7x s , 0.5y s ), and finally arrive at (0.3x s , 0.9y s) position, during which the patient is required to track the target as much as possible and focus on the center of the target. The algorithm for generating these positions is: if the display range is (x s ,y s ), then the tracking target position changes over time: (0.3x s , 0.1y s ), (0.7x s , 0.3y s ), (0.3x s , 0.5y s ), (0.7x s , 0.5y s ), (0.5x s ,0,5y s ), (0.3x s , 0.9y s ), and can be adjusted from (0.3x s , 0.1y s ) to (0.3x s , 0.9y s ) is the time taken to change the target's speed. The target position is defined as (x tk ,y tk ).

[0047] The data processing module is used to process the eye movement data collected by the eye tracker according to the eye movement function to be evaluated, and generate corresponding feature data. In this embodiment, the data processing module includes: a data preprocessing unit, a gaze data processing unit, a saccade data processing unit and a smooth pursuit data processing unit.

[0048] The data preprocessing unit is used to supplement the missing eye movement data using the linear interpolation method. Specifically: the amount of missing data is calculated using the timestamps provided by the eye tracker: First, the time difference ti between all collected target points is calculated i =t i+1 -t i , where i represents the order of eye gaze points. If there is ti i >T, T is the sampling period, T = 1 / f, f is the sampling frequency, then N = ti i / T, N is the amount of data required to interpolate between points i and i+1.

[0049] The gaze data processing unit includes: first analyzing the eye movement data to determine the start point of gaze and the start point of saccade, then extracting the gaze data, which is the data from the start of gaze to the start of saccade, and calculating the following from the extracted gaze data: focus radius, maximum saccade distance, total gaze time, maximum gaze duration and saccade latency. Specifically:

[0050] The start point of the scan was defined as the change speed of three consecutive focal points (≥22° / s), acceleration (≥3800° / s 2 ) and amplitude (≥1°), the search range for the start point of the scan is (n-1)fT t -200 to (n-1)fT t , where n is the order of the target points, n = 2, 3....9, T t The duration of the target; the fixation start point, defined as the time when the velocity (=0° / s), acceleration (=0° / s 2 ) and amplitude (=0°), and the search range is the first focus that reaches the requirement within 50 points from the start point of the sweep to the start point of the sweep.

[0051] Calculate the extracted gaze data:

[0052] Focus radius RM C , whose value is the mean of the distribution radius of the eye gaze point when gazing at nine targets. It is defined as:

[0053]

[0054] Among them, RM Ck is the eye focus radius when gazing at each target point. First, calculate the distance from each visual fixation point to the corresponding target point:

[0055] x cmki =ti ki *x ki ,y cmki =ti ki *y ki

[0056] Among them ki is the acquisition time corresponding to the time stamp at position i, x ki and ki is the gaze point position corresponding to the timestamp at position i.

[0057]

[0058]

[0059]

[0060] The range of ki is defined as the sequence from the start point of fixation to the start point of saccade to target k.

[0061] Maximum scanning distance:

[0062]

[0063] Where (x tk ,y tk ) is the target point position, (x ki ,y ki ) is the gaze point position (the range of i is from the start point of fixation to the start point of saccade).

[0064] The total fixation time is defined as the total time spent during the fixation period. mki The total time corresponding to the target point of ≤30.

[0065]

[0066] The maximum duration of fixation, defined as the longest continuous d mki The time and corresponding to the points ≤30.

[0067]

[0068] Saccadic latency, Where i represents the scanning starting point corresponding to point n, n is the target point number (n=1, 2...8), T L The duration of the target point.

[0069] The scanning data processing unit includes: performing scanning data processing on the eye movement data to calculate the scanning peak speed and the scanning average speed. In this embodiment, after the missing data is supplemented by linear interpolation according to the timestamp provided by the eye tracker, the scanning data after linear interpolation is calculated:

[0070] Peak scanning velocity:

[0071] V smax =max v si

[0072]

[0073]

[0074] where y i is the coordinate corresponding to the i-th scanning point, z i is the mean of the left and right eye spatial positions corresponding to the i-th point (z i =(left eye spatial position + right eye spatial position) / 2).

[0075] Average scanning speed:

[0076]

[0077] The smooth tracking data processing unit includes: moving the gaze target point smoothly from the starting position to the ending position, calculating the average phase lag and the average tracking gain. In this embodiment, the position of the target point is calculated according to the timestamp provided by the eye tracker: when the total test time is set to T, the target position (x t(i+1) ,y t(i+1) ) changes with time as follows:

[0078] When 0≤t≤T / 4s, the target point position is x t(i+1) =x ti +1.6 / T*ti i ,y t(i+1) =y ti +0.8 / T*ti i ;

[0079] When T / 4<t≤T / 2s, the target point position is x t(i+1) =x ti -1.6 / T*ti i ,y t(i+1) =y ti +0.8 / T*ti i ;

[0080] When T / 2<t≤3T / 4s, the target point position is x t(i+1) =x ti +1.6 / T*ti i ,y t(i+1) =0.5);

[0081] When 3T / 4<t≤Ts, the target point position is x t(i+1) =x ti -1.6 / T*ti i ,y t(i+1) =y ti +1.6 / T*ti i ;

[0082] where x ti and ti The initial position, x t0 =0.3,y t0 =0.1. ti is the calculated target point position.

[0083] When t = T, the target point position is (0.3x s , 0.9y s ).

[0084] For the collected data, calculate:

[0085] Average phase lag:

[0086]

[0087]

[0088] Average tracking gain:

[0089]

[0090]

[0091] The motor function evaluation module is used to evaluate the eye movement ability and give a motor function grade according to the characteristic data generated by the data processing module. In this embodiment, the motor function evaluation module includes a gaze function evaluation unit, a saccade function evaluation unit and a smooth pursuit function evaluation unit.

[0092] The gaze function evaluation unit includes: normalizing the focus radius, maximum saccade distance, total gaze time, longest continuous gaze time and saccade latency obtained by the gaze data processing unit, and grading each data according to the interval in which each is located. As a specific implementation, three range intervals are provided, wherein 1-0.8 represents an excellent interval, 0.8-0.6 represents a good interval, and below 0.6 represents an unqualified interval. Then, for each data after normalization, the value in the range of 1-0.8 is classified as excellent, 0.8-0.6 is classified as good, and the data below 0.6 is classified as unqualified, so that each data is classified into three categories. And the mean is calculated for each normalized data, and the mean is used as an overall evaluation of the gaze function. In this embodiment, if the mean is a value in the range of 1-0.8, it is classified as excellent, a value in the range of 0.8-0.6 is classified as good, and a data below 0.6 is classified as unqualified.

[0093] The scanning function evaluation unit comprises: the scanning peak velocity and the scanning average velocity that the scanning data processing unit obtains are normalized, and each data is classified according to the interval in which they are located. As a specific embodiment, three range intervals are provided, wherein, 1-0.8 represents an excellent interval, and 0.8-0.6 represents a good interval, and 0.6 represents an unqualified interval below. So, each data after the normalization process, the value of the scope between 1-0.8 is classified as excellent, and 0.8-0.6 is classified as good, and the data below 0.6 are classified as unqualified, so each data is classified into three categories. And each data after the normalization is calculated mean, as the overall assessment for scanning function. If this mean is that the value of the scope between 1-0.8 is classified as excellent, the value between 0.8-0.6 is classified as good, and the data below 0.6 is classified as unqualified.

[0094] The smooth tracking function evaluation unit normalizes the average phase lag and average tracking gain obtained by the smooth tracking data processing unit, and classifies each data according to the interval in which it is located. As a specific implementation, three range intervals are set, wherein 1-0.8 represents an excellent interval, 0.8-0.6 represents a good interval, and below 0.6 represents an unqualified interval. Then, for each data after normalization, the value in the range of 1-0.8 is classified as excellent, 0.8-0.6 is classified as good, and the data below 0.6 is classified as unqualified, so that each data is classified into three categories. And the mean of each normalized data is calculated as an overall evaluation of the smooth tracking function. For the overall evaluation of the smooth tracking function, if the mean is a value in the range of 1-0.8, it is classified as excellent, a value in the range of 0.8-0.6 is classified as good, and a data below 0.6 is classified as unqualified.

[0095] The evaluation result display interface is used to display the evaluation and grading results of the subject's eyes. The displayed data includes: the data obtained by the above-mentioned data processing units and the data obtained by each evaluation unit. Finally, a comprehensive evaluation is made and displayed by combining gaze, saccade and smooth pursuit. As a specific implementation method, it is displayed as a radar chart, such as Figure 6 shown.

[0096] The working process of the present invention is as follows: When patients with eye diseases use this system to evaluate their eye movement function, medical staff need to fix the eye tracker directly below the display, and use the adjustment program of Eye Tracker5 to fix the eye tracker at the center position below the screen. After the eye tracker is fixed. Let the patient sit on a chair in front of the screen, open the Eye Experience software that comes with Eye Tracker5 to calibrate the eye tracker for the patient. The calibration method used is the seven-point method. Target points appear at the center of the screen, upper left, upper right, lower left, lower right, upper, and lower positions. The patient needs to stare at the target point until the target point explodes. Before that, the patient's eye position needs to be kept in the center of the screen (before the seven-point method calibration, the position of the patient's eye will be displayed on the screen). After calibration, the patient should keep his head still, and then start the nine-point method test module to perform a gaze test. First, the screen (0.1x s , 0.1y s ) will appear at the first target point. At this time, data collection has not started. In this interface, you can set the duration of each target point. After setting the required time, let the patient look at the inner circle of the target point and ask the patient if he can start. Click the Start button to start collecting gaze data. At every set time, the target point disappears and a new target point appears. The order in which the target points appear is as follows: Figure 3-b, until the last target point disappears, and the gaze data collection is completed. During this process, if the patient's head moves significantly, the patient needs to be recalibrated and the data needs to be remeasured. After the gaze data measurement is completed, continue to measure the patient's smooth tracking data. Similarly, click the tracking test button to enter the smooth tracking test interface. This interface can set the movement time of the target point to change the movement speed of the target point to meet different test requirements. After setting the required target movement time, let the patient look at the screen (0.3x s , 0.1y s ) position, and ask the patient to keep his / her gaze on the inner circle of the target point as much as possible. After confirming that it is OK to start, click the start button to start the test, and the program will start recording the patient's eye movement data. During this process, the target moves at a constant speed, and the patient is asked to keep his / her gaze on the inner circle of the target point as much as possible. s , 0.9y s ) position, the smooth tracking test is completed, such as Figure 4-a and 4-b Click the scan test button to enter the scan test interface. Figure 5-a and 5-b As shown in the figure, there are 81 target points in total, of which the red target points are the targets that the patient needs to scan, one in each column, and a total of 9 targets. In order to prevent the patient from scanning other targets instead of the set targets during this process. The patient is required to read the number displayed by the target after scanning to the target. In this process, the patient needs to find the target point in each column as quickly as possible. When the patient completes the scanning of the nine target points, press the space bar to end the data recording, and the scanning data collection is completed. After the collection is completed, click the result evaluation button, and the collected data will be processed by the pre-written program, and the processing results will be presented in the form of a radar chart.

[0097] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A quantitative evaluation system for eye movement function based on an eye tracker, characterized in that: include: Eye tracker, used to collect eye movement data; An evaluation interface generation module is used to generate a corresponding dynamic display interface according to the eye movement function to be evaluated, so as to guide the subject's eye movement; A data processing module, used for processing the eye movement data collected by the eye tracker according to the eye movement function to be evaluated, and generating corresponding feature data; A motor function evaluation module, used to evaluate eye movement ability and give a motor function grade based on the characteristic data generated by the data processing module; as well as Evaluation result display interface, used to display the evaluation and grading results of the subject's eyes; The data processing module includes: a gaze data processing unit, a scan data processing unit and a smooth pursuit data processing unit; The gaze data processing unit comprises: firstly analyzing the eye movement data to determine the gaze start point and the saccade start point, then extracting the gaze data, the gaze data is the data from the start of gaze to the start of saccade, and calculating the following from the extracted gaze data: focus radius, maximum saccade distance, total gaze time, maximum gaze duration and saccade latency; The scanning data processing unit comprises: performing scanning data processing on the eye movement data to calculate the scanning peak speed and the scanning average speed; The smooth tracking data processing unit comprises: smoothly moving the fixation target point from the starting position to the ending position, calculating the average phase lag and the average tracking gain; The motor function assessment module includes a gaze function assessment unit, a saccade function assessment unit and a smooth pursuit function assessment unit; The gaze function evaluation unit comprises: normalizing the focus radius, maximum saccade distance, total gaze time, maximum continuous gaze time and saccade latency obtained by the gaze data processing unit, and grading each data according to the interval in which it is located; and calculating the mean of each normalized data as an overall evaluation of the gaze function; The scanning function evaluation unit includes: normalizing the scanning peak speed and the scanning average speed obtained by the scanning data processing unit, and classifying each data according to the interval in which each data is located; and calculating the mean value of each normalized data as an overall evaluation of the scanning function; The smooth tracking function evaluation unit includes: normalizing the average phase lag and average tracking gain obtained by the smooth tracking data processing unit, grading each data according to the interval in which it is located; and calculating the mean of each normalized data as an overall evaluation of the smooth tracking function.

2. The eye movement function quantitative evaluation system based on an eye tracker according to claim 1, characterized in that: The eye movement data includes the eye gaze focus position, the collection time corresponding to each focus data and the spatial position of the eyeball.

3. The eye movement function quantitative evaluation system based on an eye tracker according to claim 1, characterized in that: The dynamic display interface generated by the evaluation interface generation module includes a gaze function evaluation interface, a scan function evaluation interface and a smooth pursuit function evaluation interface.

4. The eye movement function quantitative evaluation system based on an eye tracker according to claim 1, characterized in that: The data processing module also includes: a data preprocessing unit, which is used to complete the eye movement data using a linear interpolation method.

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