A dynamic best field of view measurement method based on eye movement indicators

Abstract

The application discloses a kind of dynamic best visual field measurement methods based on eye movement index, belong to visual field measurement technical field, including step one, obtain standard dynamic visual field range figure;Step two, based on standard dynamic visual field range figure, divide several equal lines of sight;Step three, build software and hardware platform, including display module, storage module, processing module, input module and eye movement acquisition module;Step four, display module sequentially displays standard dynamic visual field range figure and the optotype on equal line of sight, and eye movement acquisition module collects the eye movement data of gazing corresponding optotype;Step five, processing module processes the eye movement data obtained, obtains best visual field curve, and is displayed by display module;The application adopts the above method, can be widely applied to intelligent terminal equipment software interface design, provides data support for task optimization, process optimization, interface optimization etc., improves operator operation efficiency, optimizes terminal man-machine interface design.

Description

Technical Field

[0001] This invention relates to the field of visual field measurement technology, and in particular to a dynamic optimal visual field measurement method based on eye movement indices. Background Technology

[0002] In fields such as electronic information equipment and smart terminals, where user interfaces are dense and human-computer interaction is frequent, especially interfaces that require operators to respond instantly to displayed information, dynamic optimal field-of-view detection is crucial. Refined field-of-view segmentation can not only optimize interface layout rationality but also evaluate the operability of electronic information equipment. This, in turn, optimizes terminal functional layout, operation processes, and icon design, improving user operating efficiency, reducing accidental touch rates, and enhancing user experience.

[0003] In existing technologies, the core of dynamic visual field measurement methods is to "draw a map" using a moving cursor. The operator slowly moves a target of fixed brightness from the periphery (the invisible area) of the subject's visual field towards the center (the visible area). The subject reacts immediately when they can just see the moving target. The boundary between just being unable to see and just being able to see represents a "shoreline" point of the "visual island" in that direction. Connecting these points in multiple directions forms a closed curve called an "isotropy." All points on the isopter have the same sensitivity to a target of that specific brightness. The Goldmann perimeter is a classic example of dynamic measurement. However, the above-mentioned dynamic visual field measurement methods mainly address the distinction between "visible" and "invisible" areas and cannot further determine the optimal visual field area.

[0004] Therefore, it is necessary to provide a dynamic optimal visual field measurement method based on eye movement indices, which further divides the visual field range based on eye movement indices, thereby solving the problems of existing visual field measurement methods. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic optimal visual field measurement method based on eye movement indices, which solves the problem that existing dynamic visual field measurement methods can only measure the "visible" or "unvisible" areas.

[0006] To achieve the above objectives, the present invention provides a method for measuring dynamic optimal visual field based on eye movement indices, comprising the following steps: Step 1: Obtain a standard dynamic field of view graphic; Step 2: Based on the standard dynamic field of view map, divide the field of view into several equal lines of sight; Step 3: Build the hardware and software platform, including the display module, storage module, processing module, input module, and eye-tracking acquisition module; Step 4: The display module sequentially displays the standard dynamic field of view graphic and the optotypes on the isolinear line of sight, while the eye movement acquisition module acquires eye movement data of the person fixating on the corresponding optotype. Step 5: The processing module processes the acquired eye-tracking data to obtain the optimal visual field curve, which is then displayed through the display module.

[0007] Preferably, in step two, the coordinates of the standard dynamic field of view curve are extracted, and the curve is translated from the outside towards the origin by a certain number of degrees to form several isolines. Several optotypes are then evenly distributed along each isoline. The first line of sight The coordinates of each target are expressed in polar coordinates as follows: ,in, The polar radius of the target is 0° to 90°. The polar angle of the target is 0° to 360°.

[0008] Preferably, in step four, the display module displays the standard dynamic field of view graphic and the visual targets on the isolinear curves sequentially from the outside to the inside. The visual targets on each curve appear randomly, and after traversing each curve, it moves on to the next curve.

[0009] Preferably, in step four, the eye-tracking acquisition module records the eye-tracking data of the eye target at the time of each visual target's appearance and fixation.

[0010] Preferably, in step four, the eye-tracking data includes the initial fixation time.

[0011] Preferably, in step five, a first fixation time threshold is set based on the range of first fixation time of the collected visual targets.

[0012] Preferably, in step five, the processing module performs the following steps: Define the target The first fixation time is Therefore, the coordinates and first fixation time of each target are expressed as follows: ; The initial gaze time threshold range set by the processing module is: ,in, This is the lower limit of the first fixation time threshold, in milliseconds. This represents the upper limit of the first fixation time threshold, in milliseconds (ms). After setting the first fixation time threshold, the target lines at the same polar angle for each curve are compared to determine whether they fall within the first fixation time threshold. Within the range: If no optotype exists within the first fixation time threshold range, proceed to the next optotype comparison for each curve. After traversing all optotype comparisons, find optotypes that meet the first fixation time threshold range and connect them sequentially. If there are more than one target at the same polar corner within the first fixation time threshold, then the target with the longest first fixation time is selected. Connect; Finally, the curve formed after connection is displayed on the display module.

[0013] Therefore, the present invention adopts the above-mentioned dynamic optimal visual field measurement method based on eye movement index, which further divides the visual field range based on eye movement index, solves the shortcomings of existing visual field measurement methods, and also has the advantages of simple operation and minimal impact on subjects. It can be used for interface layout optimization and has significant implications for further optimizing and improving the human-computer interaction interface of electronic information equipment.

[0014] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0015] Figure 1 This is a flowchart of a dynamic optimal visual field measurement method based on eye movement indices according to the present invention; Figure 2 This is a schematic diagram of the standard dynamic field of view in an embodiment of the present invention, wherein (a) is the left eye and (b) is the right eye; Figure 3 The coordinates of the standard dynamic visual field range curve and the isoline of sight for the left eye in this embodiment of the invention are shown, where (a) is the standard dynamic visual field range curve and (b) is the isoline of sight. Detailed Implementation

[0016] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0017] Please see Figure 1 A dynamic optimal visual field measurement method based on eye-tracking indices includes the following steps: Step 1: Obtain a standard dynamic field of view graphic, such as... Figure 2 As shown; Step 2: Based on the standard dynamic field of view diagram, divide the field of view into several equal lines of sight; such as... Figure 3As shown, in this embodiment, taking the left eye as an example, the coordinates of the standard dynamic visual field range curve are extracted, and shifted 10° from the outside towards the origin to form 5 isolinear lines. Several optotypes are then evenly distributed (one point every 15°) along each isolinear line. The first line of sight The coordinates of each target are expressed in polar coordinates as follows: ,in, The polar radius of the target is expressed in degrees (°) and ranges from 0° to 90°. The polar angle of the target is expressed in degrees, ranging from 0° to 360°.

[0018] Step 3: Build a hardware and software platform, including a display module, storage module, processing module, input module, and eye-tracking acquisition module. The display module, eye-tracking acquisition module, and input module are all electrically connected to the processing module. The display module is used to alternately present visual targets, and the eye-tracking acquisition module (such as an eye tracker) is used to collect eye movement information generated by the subject during the measurement process.

[0019] Conduct dynamic optimal field of view measurement experiment: (a) Test conditions: (1) Environmental conditions: The experiment was conducted in a quiet, undisturbed laboratory with a room temperature controlled at 22±2℃ and uniform lighting (illuminance 500±50lx). Strong light was avoided from shining directly on the eye tracker lens and the subject's eyes to reduce the interference of environmental factors on the eye movement data.

[0020] (2) Equipment conditions: Each participant wore an eye tracker in turn to complete the experiment. It is recommended that the eye tracker have a sampling rate of ≥100Hz and a fixation point accuracy of ≤0.5° to ensure accurate data collection. A high-resolution monitor should be provided, with the screen distance from the participant's eyes and the size of the display module matched. The monitor's brightness and contrast should be adjusted to standard values ​​(brightness 50%, contrast 70%) to avoid screen glare.

[0021] (3) Subject conditions: At least 6 participants (visual or corrected visual acuity ≥1.0, no eye disease, no cognitive impairment) were selected. Participants were required to rest for 10 minutes before the test to avoid fatigue. Before the test, participants were informed of the task process and precautions and signed an informed consent form to ensure that they understood the task and cooperated actively.

[0022] (b) Pre-test preparation and debugging: (1) Subject training: When the subject enters the test site, adjust the seat height and monitor position to ensure that the subject is comfortable and that the eyes are aligned with the center of the display module's visual area. Subsequently, the evaluator needs to explain the purpose of the test, the task process, operating procedures and precautions to the subject (such as not turning the head during the test, maintaining a normal blinking frequency, and not ending the task prematurely).

[0023] (2) Eye tracker calibration: Turn on the eye tracker, monitor and other equipment, and perform equipment self-test and calibration. Have the subject look at the calibration points that appear on the screen in sequence to ensure that the calibration error is ≤0.3°; if the calibration fails, readjust the subject's sitting posture and calibrate again until the calibration is qualified.

[0024] (3) Pre-test: The subjects were asked to perform a simplified version of the test task once to familiarize themselves with the task operation and eye tracker data collection requirements, and their questions were answered in a timely manner; the pre-test data was not included in the final analysis, but was only used to help the subjects adapt to the test procedure.

[0025] Step 4: Start the test. The display module sequentially displays the standard dynamic visual field graph and the optotypes on the isolinear curves from the outside in. The optotypes on each curve appear randomly. After traversing each curve, the module moves to the next curve. During the time each optotype appears and is fixated on, the eye-tracking acquisition module records the eye movement data for that optotype. The eye movement data includes the initial fixation time.

[0026] Step 5: Based on the collected first fixation time range of the target, set the first fixation time threshold. The processing module processes the data based on the first fixation time and displays the optimal visual field curve in the display module. The processing procedure is as follows: Define the target The first fixation time is Therefore, the coordinates and first fixation time of each target are expressed as follows: ; The initial gaze time threshold range set by the processing module is: ,in, This is the lower limit of the first fixation time threshold, in milliseconds. This represents the upper limit of the first fixation time threshold, in milliseconds (ms). After setting the first fixation time threshold, the target lines at the same polar angle for each curve are compared to determine whether they fall within the first fixation time threshold. Within the range: If no optotype exists within the first fixation time threshold range, proceed to the next optotype comparison for each curve. After traversing all optotype comparisons, find optotypes that meet the first fixation time threshold range and connect them sequentially. If there are more than one target at the same polar corner within the first fixation time threshold, then the target with the longest first fixation time is selected. Connect; Finally, the curve formed after connection is displayed on the display module.

[0027] Therefore, the present invention adopts the above-mentioned dynamic optimal visual field measurement method based on eye movement index, which further divides the visual field range based on eye movement index, solves the shortcomings of existing visual field measurement methods, and also has the advantages of simple operation and minimal impact on subjects. It can be used for interface layout optimization and has significant implications for further optimizing and improving the human-computer interaction interface of electronic information equipment.

[0028] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for measuring dynamic optimal visual field based on eye-tracking indices, characterized in that, Includes the following steps: Step 1: Obtain a standard dynamic field of view graphic; Step 2: Based on the standard dynamic field of view map, divide the field of view into several equal lines of sight; Step 3: Build the hardware and software platform, including the display module, storage module, processing module, input module, and eye-tracking acquisition module; Step 4: The display module sequentially displays the standard dynamic field of view graphic and the optotypes on the isolinear line of sight, while the eye movement acquisition module acquires eye movement data of the person fixating on the corresponding optotype. Step 5: The processing module processes the acquired eye-tracking data to obtain the optimal visual field curve, which is then displayed through the display module.

2. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 1, characterized in that: In step two, the coordinates of the standard dynamic field of view curve are extracted, and the curve is translated from the outside towards the origin by a certain number of degrees to form several isolines. Several optotypes are then evenly distributed along each isoline. The first line of sight The coordinates of each target are expressed in polar coordinates as follows: ,in, The polar radius of the target is 0° to 90°. The polar angle of the target is 0° to 360°.

3. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 1, characterized in that: In step four, the display module displays the standard dynamic field of view graphic and the visual targets on the isolinear curves from the outside to the inside. The visual targets on each curve appear randomly. After traversing the visual targets on each curve, the module moves on to the next curve.

4. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 1, characterized in that: In step four, the eye-tracking module records the eye movement data of the person looking at the corresponding visual target during the time each target appears and is viewed.

5. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 2, characterized in that: In step four, eye-tracking data includes the time to first fixation.

6. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 5, characterized in that: In step five, the first fixation time threshold is set based on the range of first fixation time of the collected visual targets.

7. The method for measuring dynamic optimal visual field based on eye movement indices according to claim 6, characterized in that, In step five, the processing module's procedure is as follows: Define the target The first fixation time is Therefore, the coordinates and first fixation time of each target are expressed as follows: ; The initial gaze time threshold range set by the processing module is: ,in, This is the lower limit of the first fixation time threshold, in milliseconds. This represents the upper limit of the first fixation time threshold, in milliseconds (ms). After setting the first fixation time threshold, the target lines at the same polar angle for each curve are compared to determine whether they fall within the first fixation time threshold. Within the range: If no optotype exists within the first fixation time threshold range, proceed to the next optotype comparison for each curve. After traversing all optotype comparisons, find optotypes that meet the first fixation time threshold range and connect them sequentially. If there are more than one target at the same polar corner within the first fixation time threshold, then the target with the longest first fixation time is selected. Connect; Finally, the curve formed after connection is displayed on the display module.

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