Attention training method and device based on eye movement detection and electronic equipment

Abstract

The invention discloses an attention training method and device based on eye movement detection and electronic equipment. A target object is generated on display equipment; acquiring a sight moving track when the sight of the user moves along with the target object, synchronously acquiring electroencephalogram data of the user, and determining real-time attention of the user according to the electroencephalogram data; judging whether a sight line locking condition is met or not according to the sight line moving track, the current moving track of the target object and the real-time attention; when the preset sight line locking condition is met, the target object is controlled to move according to a preset moving mode; otherwise, regenerating the target object. According to the method and the device, the sight line moving track of the user is tracked in real time, and the real-time attention of the user is evaluated in combination with the electroencephalogram data, so that the attention concentration degree of the user when the target object is tracked can be more accurately known, the method and the device are more accurate and personalized, and the attention level of the user can be more effectively improved.

Description

Technical Field

[0001] The present application belongs to the field of brain-computer interface technology, and specifically relates to an attention training method, device and electronic equipment based on eye movement detection. Background Art

[0002] In today's era of information explosion, it is increasingly difficult for people to concentrate. Whether it is work, study or entertainment, they are faced with interference from all aspects, which leads to distraction and inability to complete tasks effectively. For patients with ADHD, their eyes are mostly erratic, their concentration time is short, their attention is easily distracted, and they are often distracted by the movement in the surrounding environment, looking around or interrupting the conversation. Therefore, eye and head tracking is particularly important. However, simply improving attention is not entirely feasible, and excessive concentration can also bring a series of hazards.

[0003] When we over-focus, our brains will continue to consume energy, causing us to feel tired and stressed. Long-term over-focusing can also increase psychological stress, leading to psychological problems such as anxiety and depression. Secondly, over-focusing can also affect creativity and problem-solving skills. In addition, over-focusing can also affect interpersonal relationships and social skills. When we over-focus, we tend to ignore the people around us and the surrounding environment. This makes it difficult for us to establish good communication and relationships with others, affecting our social skills.

[0004] Therefore, finding an attention training method that can provide visual tracking while effectively improving the effect of attention training is an urgent problem to be solved. Summary of the invention

[0005] The technical purpose of the present application is to provide an attention training method, device, and electronic device based on eye movement detection, which can effectively improve the attention training effect.

[0006] In order to achieve the above technical objectives, the embodiments of the present application adopt the following technical solutions.

[0007] In a first aspect, an embodiment of the present application provides an attention training method based on eye movement detection, the attention training method comprising: generating a target object on a display device; Acquire the eye movement trajectory of the user when the eye follows the target object, synchronously collect the user's electroencephalogram data, and determine the user's real-time attention according to the electroencephalogram data; Determining whether a sight locking condition is met according to the sight movement trajectory, the current movement trajectory of the target object, and the real-time attention; When the preset sight locking condition is met, the target object is controlled to move according to the preset movement mode; otherwise, the target object is regenerated.

[0008] In some embodiments, judging whether a sight locking condition is met according to the sight movement trajectory, the current movement trajectory of the target object, and the real-time attention includes: Determining whether the sight line movement trajectory and the current movement trajectory form a mapping relationship; When the sight line movement trajectory forms a mapping relationship with the current movement trajectory, and the real-time attention is greater than or equal to the attention threshold, it is determined that the sight line locking condition has been met.

[0009] In some embodiments, determining whether the movement trajectory forms a mapping relationship with the current movement trajectory includes: When the sight line movement trajectory coincides with the current movement trajectory, it is determined that a mapping relationship is formed between the sight line movement trajectory and the current movement trajectory.

[0010] In some embodiments, controlling the target object to move in a preset movement manner includes: Determine the user's critical attention based on the user's EEG data after the target object moves to the critical contact area; determine the reflex force that the target object will obtain based on the critical attention; and make the target object move with the reflex force after reaching the target end point; wherein the critical contact area is a set range centered on the target end point.

[0011] In some embodiments, the method further comprises: The rotation direction and rotation angle of the user's head are obtained, and the reflection angle of the target object is determined based on the direction opposite to the rotation direction and the angle equal to the rotation angle, so that after the target object reaches the target end point, it is reflected and moved according to the reflection force and the reflection angle.

[0012] In some embodiments, determining the user's critical attention according to the user's EEG data after the target object moves to the critical contact area includes: The average value of the EEG data of all the EEG data points in the critical contact area is calculated, and the critical attention corresponding to the average value of the EEG data is determined.

[0013] In a second aspect, the present application provides an attention training device based on eye movement detection, the device comprising: A target display module, used for generating a target object on a display device; A sight line trajectory determination module, used to obtain a sight line movement trajectory when the user's sight follows the target object; The attention assessment module is used to synchronously collect the user's EEG data and determine the real-time attention based on the EEG data; A sight locking judgment module, used to judge whether a sight locking condition is met according to the sight movement trajectory and the current movement trajectory of the target object and the real-time attention; The movement control module is used to control the target object to move in a preset movement mode when a preset line of sight locking condition is met; otherwise, the target object is regenerated.

[0014] In some embodiments, the mobile control module is also used to determine the user's critical attention based on the user's EEG data after the target object moves to the critical contact area when a preset line of sight locking condition is met; determine the reflection force that the target object will obtain based on the critical attention; and make the target object move with the reflection force after reaching the target end point; wherein the critical contact area is a set range centered on the target end point.

[0015] In some embodiments, the attention training device further includes a head detection unit and a head analysis unit; The head detection unit is used to obtain the rotation direction and rotation angle of the user's head; The head analysis unit is used to determine the reflection angle of the target object based on the direction opposite to the rotation direction and the angle the same as the rotation angle; the movement control module is also used to make the target object perform reflection movement according to the reflection force and the reflection angle after reaching the target end point.

[0016] In a third aspect, an embodiment of the present application provides a terminal device, comprising a memory, a processor, and a program for an attention training method based on eye movement detection stored in the memory and capable of running on the processor, wherein when the processor executes the attention training program based on eye movement detection, the steps of the attention training method based on eye movement detection provided in any possible implementation manner of the first aspect are implemented.

[0017] Compared with the prior art, the attention training method based on eye movement detection provided in the embodiment of the present application can more accurately understand the user's concentration level when tracking the target object by tracking the user's line of sight movement trajectory in real time and combining EEG data to evaluate the user's real-time attention. It is more accurate and personalized than traditional attention training methods, and can more effectively improve the user's attention level.

[0018] The attention training device based on eye movement detection provided in the embodiment of the present application has the same technical effect as the attention training method based on eye movement detection provided in the embodiment of the present application, and will not be elaborated herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are for explanation purposes only and are not intended to limit the scope of the present application in any way. In addition, the shapes and proportional dimensions of the components in the drawings are only for illustration purposes and are used to help understand the present application. They do not specifically limit the shapes and proportional dimensions of the components of the present application. Under the guidance of the present application, those skilled in the art can select various possible shapes and proportional dimensions to implement the present application according to specific circumstances. In the drawings: Figure 1 A flowchart of an attention training method based on eye movement detection provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of an attention training device based on eye movement detection provided in an embodiment of the present application; Figure 3 A schematic diagram of the terminal device structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0021] In the prior art, attention training of ADHD patients is performed by eye tracking, but the training method is not targeted, the training effect is poor, and attention cannot be improved evenly. The embodiment of the present application provides an attention training method based on eye movement detection, which is more accurate and personalized than the traditional attention training method, and can more effectively improve the user's attention level.

[0022] The present application is further described below in conjunction with the accompanying drawings and specific implementations of the specification.

[0023] See also Figure 1 The present application embodiment provides an attention training method based on eye movement detection, comprising the following steps: Step S1: generating a target object on a display device; Step S2: obtaining the user's line of sight movement trajectory when the line of sight follows the target object, synchronously collecting the user's EEG data, and determining the user's real-time attention according to the EEG data; Step S3: judging whether the sight locking condition is met according to the sight movement trajectory and the current movement trajectory of the target object and the real-time attention; Step S4: When the preset sight locking condition is met, the target object is controlled to move according to the preset movement mode; otherwise, the target object is regenerated.

[0024] The attention training method based on eye movement detection provided by the embodiment of the present application can capture and record the user's line of sight movement trajectory in real time through eye movement tracking technology, so that the user can focus more on the movement trajectory of the ball during the movement of the target object (such as simulating hitting the ball), thereby improving the concentration ability of attention. By simulating the hitting process of the ball, the user needs to constantly adjust the line of sight to match the moving trajectory of the ball, so as to train the user's ability to maintain attention for a long time, thereby enhancing the persistence of attention. In addition, in the process of simulating hitting the ball, the user needs to react quickly and lock the target, which helps to improve the user's acuity and reaction speed to the target object. Through the ball movement process and the process of simulating hitting the ball in the display device (such as a screen), the training process is made more interesting and challenging, which can attract users to continue to participate. According to the analysis and evaluation of the user's training process data, personalized training suggestions and feedback can be provided to the user, helping the user to better understand their training progress and conduct targeted training.

[0025] In a specific implementation, the display device in step S1 may include but is not limited to a liquid crystal display (LCD), an organic light emitting diode display (OLED), an electronic ink screen (such as a screen used in an e-book reader), a projection screen, etc.

[0026] Optionally, in step S1, the target object may move randomly or according to a preset target trajectory.

[0027] In some embodiments, step S2 obtains the line of sight movement trajectory of the user as the line of sight follows the movement of the target object, including: obtaining the user's facial image, and determining the user's pupil position based on the facial image; determining the viewpoint position corresponding to the user on the display device based on the pupil position, and determining the line of sight movement trajectory based on the viewpoint position.

[0028] Optionally, an eye tracker is used to capture and record the user's line of sight movement trajectory in real time.

[0029] As an example, step S2 can use an EEG headband to collect real-time EEG data and process the acquired real-time EEG data; match the intensity information of the processed real-time EEG data with a preset attention table, which records the correspondence between the attention value and the intensity information of the EEG signal data, thereby determining the user's real-time attention.

[0030] In some embodiments, step S3 determines whether the line of sight locking condition is met based on the line of sight movement trajectory, the current movement trajectory of the target object, and the real-time attention, including: determining whether the line of sight movement trajectory and the current movement trajectory form a mapping relationship; when the line of sight movement trajectory and the current movement trajectory form a mapping relationship, and the real-time attention is greater than or equal to the attention threshold, it is determined that the line of sight locking condition is met.

[0031] Meeting the sight locking condition indicates that the target user is currently at a high level of concentration. Step S4 can move the target object according to a preset movement method, such as a linear movement that is completely launched along a preset movement trajectory, or a trajectory change according to a trajectory setting method; if the sight locking condition is not met, the target object can be regenerated.

[0032] As an example, the user's current viewpoint position can be compared with the current position of the target object. If the current viewpoint position and the current position of the target object are at the same position, that is, when the line of sight movement trajectory coincides with the current movement trajectory, it is determined that the line of sight movement trajectory and the current movement trajectory form a mapping relationship.

[0033] In some embodiments, in step S4, the target object is controlled to move according to a preset trajectory, including: determining the user's critical attention based on the user's EEG data after the target object moves to the critical contact area; determining the reflex force that the target object will obtain based on the critical attention; and moving the target object with the reflex force after reaching the target end point; wherein the critical contact area is a set range centered on the target end point. For example, the critical contact area can be a circle centered on the target end point (i.e., the target landing point) with a radius value of the target object; or a circle centered on the target landing point with a radius value of a preset parameter value.

[0034] As an example, the target end point may be a preset boundary point, or the target end point may also be a preset landing point of the target movement trajectory.

[0035] Optionally, the user's critical attention is determined based on the user's EEG data in the critical contact area, including: taking the time point when the boundary of the target object touches the boundary of the critical contact area as point A, and the time point when the center point of the target object coincides with the boundary of the critical contact area as point B, extracting all EEG data points in the time period between point A and point B, dividing the sum of all EEG data in the time period by the number of data points to obtain the mean of the corresponding EEG signal in the time period, and determining the critical attention size based on the mean.

[0036] In an embodiment, the time from the center point of the target object to the center point of the critical contact area after it coincides with the boundary of the critical contact area can provide analysis time for determining the critical attention size based on the mean, thereby ensuring the timeliness of feedback.

[0037] In the embodiment, critical attention is used as the reflection force of the target object's launching motion. The moving distance generated by the reflection of the target object at the target end point can be controlled through the user's critical attention, which can make the training process more interesting and challenging, attract users to continue to participate, and make users more engaged and focused during the participation process.

[0038] In some embodiments, the attention training method based on eye movement detection also includes: obtaining the rotation direction and angle of the user's head, determining the reflection angle of the target object based on the direction opposite to the rotation direction and the angle the same as the rotation angle, so that after the target object reaches the target end point, it performs a reflective movement according to the reflection force and the reflection angle.

[0039] As an example, obtaining the rotation direction and angle of the user's head may include: facial image acquisition, obtaining the user's facial image in real time through an image acquisition device such as a camera; using a facial feature point detection algorithm to identify key points in the facial image, which usually include the corners of the eyes, the corners of the mouth, the tip of the nose, etc.; based on the detected feature points, using a head posture estimation algorithm to estimate the posture of the head in three-dimensional space. This usually involves mapping two-dimensional feature points to three-dimensional space and calculating the corresponding rotation matrix or Euler angle. Based on the calculated Euler angle, the rotation direction and angle of the head can be determined.

[0040] The following is an application example of an attention training method based on eye movement detection: The scene is a badminton sport. First, badminton is displayed on the display device. The badminton net divides the screen into two halves, and the four sides are grid lines. At the beginning of the game, the badminton will first make random linear movements outside the grid lines. The user needs to observe the movement trajectory of the badminton. When the user's line of sight movement trajectory and the current movement trajectory of the badminton form a mapping relationship, and the attention reaches the preset attention threshold (greater than or equal to) the attention threshold, the badminton will make a complete launch linear movement. After the badminton crosses the net and is in the critical contact area, the critical attention value and direction trajectory at this time are detected, and the badminton makes a reflective linear movement. Its launch distance is determined according to the critical attention value. Finally, according to the launch distance and launch direction at this time, the user needs to adjust the reflection direction in time to make the badminton stay stably on the grid line. At the end, the training effect is evaluated according to the badminton's stop position. Based on the training results, users can clearly judge the current level of concentration by whether the badminton goes out of the grid line or stays within the grid line (going out of the grid line means that the concentration is too high, and staying too far within the grid line means that the concentration is too low), and adjust the current concentration in time to reach a balanced state, so that the badminton can stay on the grid line in the next training.

[0041] The embodiment of the present application can balance concentration and provide attention training effects. Through eye tracking and real-time EEG conversion of concentration analysis, only the concentration within the appropriate range can continuously and stably complete the back and forth movement of badminton. Too low or too high can interrupt the continuous badminton training in advance. In the embodiment, the continuous exercise duration and number within the specified time can be scored to evaluate the current trainee's concentration ability and help them achieve concentration training.

[0042] In some embodiments, the reflection movement trajectory at this time can be determined according to the user's head rotation direction and head rotation angle. According to the reflection movement trajectory and reflection distance at this time, the user needs to adjust the head rotation direction and rotation angle to make the target object stop within the set stop range. The training effect is judged according to whether the target object finally stops within the range and the distance from the finish line.

[0043] In the embodiment, only when the reflex force determined according to the user's critical attention is appropriate and the sight line movement trajectory forms a mapping relationship with the current movement trajectory, can the target object fall into the opposite target area; if the reflex force or sight line movement trajectory is too large, it will exceed the opposite target area, and if it is too small, it will not reach the target area. According to the final training results, the user can evaluate the current stage of attention, so as to judge the degree of concentration in the next training process, constantly adjust their own attention, and achieve precise adjustment of attention.

[0044] Based on the same inventive concept as the attention training method based on eye movement detection provided in the above embodiment, the present application also provides an attention training device based on eye movement detection, such as Figure 2 As shown in , the device includes a target display module, a sight track determination module, an attention assessment module, a sight lock judgment module and a movement control module; The target display module is used to generate a target object on a display device; The sight track determination module is used to obtain the sight track of the user when the sight follows the target object; The attention assessment module is used to synchronously collect the user's EEG data and determine the real-time attention based on the EEG data; The sight lock judgment module is used to judge whether the sight lock condition is met according to the sight movement trajectory and the current movement trajectory of the target object and the real-time attention; The movement control module is used to control the target object to move according to a preset movement mode when the preset sight locking condition is met; otherwise, the target object is regenerated.

[0045] In some embodiments, the mobile control module is also used to determine the user's critical attention based on the user's EEG data after the target object moves to the critical contact area when a preset line of sight locking condition is met; determine the reflex force that the target object will obtain based on the critical attention; and make the target object move with the reflex force after reaching the target end point; wherein the critical contact area is a set range centered on the target end point.

[0046] In some embodiments, the eye gaze trajectory determination module includes a pupil positioning unit, a pupil analysis unit and a viewpoint comparison unit; the pupil positioning unit is used to obtain a facial image of the user and determine the pupil position of the user based on the facial image; the pupil analysis unit is used to determine the viewpoint position corresponding to the user on the display device based on the pupil position, and determine the eye gaze movement trajectory based on the viewpoint position.

[0047] In some embodiments, the device also includes a head detection unit and a head analysis unit. The head detection unit is used to obtain the rotation direction and rotation angle of the user's head; the head analysis unit is used to determine the reflection angle of the target object based on the direction opposite to the rotation direction and the angle the same as the rotation angle; the movement control module is also used to make the target object reach the target end point and then perform a reflection movement according to the reflection force and the reflection angle.

[0048] Based on the above embodiments, the present application also provides a terminal device, the principle block diagram of the terminal device can be as follows: Figure 3 The terminal device may include one or more processors ( Figure 3 Only one is shown in the figure), a memory and a computer program stored in the memory and executable on one or more processors, for example, a program for attention training based on eye movement detection. When one or more processors execute the computer program, the various steps in the method embodiment for attention training based on eye movement detection can be implemented. Alternatively, when one or more processors execute the computer program, the functions of the various modules / units in the device embodiment for attention training based on eye movement detection can be implemented, which is not limited here.

[0049] In one embodiment, the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0050] In one embodiment, the memory may be an internal storage unit of an electronic device, such as a hard disk or memory of the electronic device. The memory may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Furthermore, the memory may also include both an internal storage unit of the electronic device and an external storage device. The memory is used to store computer programs and other programs and data required by the terminal device. The memory may also be used to temporarily store data that has been output or is to be output.

[0051] The above is a detailed introduction to the attention training method, device, electronic device and medium based on eye movement detection provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the concept of the present application and should not be understood as limiting the scope of protection of the present application.

Claims

1. A method for attention training based on eye movement detection, characterized in that: The attention training method comprises: generating a target object on a display device; Acquire the eye movement trajectory of the user when the eye follows the target object, synchronously collect the user's electroencephalogram data, and determine the user's real-time attention according to the electroencephalogram data; Determining whether a sight locking condition is met according to the sight movement trajectory, the current movement trajectory of the target object, and the real-time attention; When the preset sight locking condition is met, the target object is controlled to move according to the preset movement mode; otherwise, the target object is regenerated.

2. The attention training method based on eye movement detection according to claim 1, characterized in that: Judging whether a sight locking condition is met according to the sight movement trajectory, the current movement trajectory of the target object, and the real-time attention includes: Determining whether the sight line movement trajectory and the current movement trajectory form a mapping relationship; When the sight line movement trajectory forms a mapping relationship with the current movement trajectory, and the real-time attention is greater than or equal to the attention threshold, it is determined that the sight line locking condition has been met.

3. The attention training method based on eye movement detection according to claim 1, characterized in that: Determining whether the sight line movement trajectory and the current movement trajectory form a mapping relationship includes: When the sight line movement trajectory coincides with the current movement trajectory, it is determined that a mapping relationship is formed between the sight line movement trajectory and the current movement trajectory.

4. The attention training method based on eye movement detection according to claim 1, characterized in that: Controlling the target object to move in a preset moving manner includes: Determining the user's critical attention according to the user's EEG data after the target object moves to the critical contact area; determining the reflex force that the target object will acquire according to the critical attention; After the target object reaches the target end point, the target object is reflected and moved by the reflection force; wherein the critical contact area is a set range centered on the target end point.

5. The attention training method based on eye movement detection according to claim 4, characterized in that: The method further comprises: The rotation direction and rotation angle of the user's head are obtained, and the reflection angle of the target object is determined based on the direction opposite to the rotation direction and the angle equal to the rotation angle, so that after the target object reaches the target end point, it is reflected and moved according to the reflection force and the reflection angle.

6. The attention training method based on eye movement detection according to claim 4, characterized in that: Determining the user's critical attention according to the user's EEG data after the target object moves to the critical contact area includes: The average value of the EEG data of all the EEG data points in the critical contact area is calculated, and the critical attention corresponding to the average value of the EEG data is determined.

7. An attention training device based on eye movement detection, characterized in that: The device comprises: A target display module, used for generating a target object on a display device; A sight line trajectory determination module, used to obtain a sight line movement trajectory when the user's sight follows the target object; The attention assessment module is used to synchronously collect the user's EEG data and determine the real-time attention based on the EEG data; A sight locking judgment module, used to judge whether a sight locking condition is met according to the sight movement trajectory and the current movement trajectory of the target object and the real-time attention; The movement control module is used to control the target object to move in a preset movement mode when a preset line of sight locking condition is met; otherwise, the target object is regenerated.

8. The attention training device based on eye movement detection according to claim 7, characterized in that: The movement control module is further configured to determine the user's critical attention according to the user's EEG data after the target object moves to the critical contact area when a preset sight locking condition is met; determining a reflection force to be acquired by the target object according to the critical attention; After the target object reaches the target end point, the target object is reflected and moved by the reflection force; wherein the critical contact area is a set range centered on the target end point.

9. The attention training device based on eye movement detection according to claim 8, characterized in that: The attention training device also includes a head detection unit and a head analysis unit; The head detection unit is used to obtain the rotation direction and rotation angle of the user's head; The head analysis unit is used to determine the reflection angle of the target object based on a direction opposite to the rotation direction and an angle the same as the rotation angle; The movement control module is also used to make the target object perform a reflection movement according to the reflection force and the reflection angle after reaching the target end point.

10. A terminal device, characterized in that: The terminal device includes a memory, a processor, and a program of the attention training method based on eye movement detection stored in the memory and capable of running on the processor. When the processor executes the attention training program based on eye movement detection, the steps of the attention training method based on eye movement detection as described in any one of claims 1 to 6 are implemented.

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