Visual cognitive ability assessment method based on electroencephalogram signals

Abstract

The invention belongs to the technical field of visual cognition assessment, and discloses a visual cognition ability assessment method based on electroencephalogram signals. The method comprises the steps that a user executes a series of visual cognition evaluation tasks on a computer, the visual cognition evaluation tasks are visual target identification tasks, and the task targets of the user are that under the influence of numerous interference points, a correct target is found in the as short as possible, and a mouse is operated to select the target; meanwhile, the electroencephalogram signal collecting device worn by the user synchronously collects electroencephalogram signals of the user; after the user completes all the visual cognition tasks, all the collected electroencephalogram signals are stored in a file of a specific format; and reading the original electroencephalogram signals and behavioral signals in the file, and decoding the electroencephalogram signal concentration level and behavioral characteristics of the user, thereby realizing evaluation of the visual cognition ability of the user from two dimensions of brain waves and behavioral.

Description

Technical Field

[0001] The present invention relates to the technical field of visual cognitive assessment, and particularly to a method for assessing visual cognitive ability based on electroencephalogram (EEG) signals. Background Art

[0002] Employees in many industries not only have extraordinary physical abilities and professional skills, but also need to reach a relatively high level in terms of perception and cognition. Cognition ability refers to the ability of the human brain to process, store, and extract information, and is the most important psychological condition for people to successfully complete activities. How to conduct effective assessment of cognitive ability is one of the hot topics that cognitive researchers are concerned about.

[0003] During the cognitive process, communication and cooperation occur between different regions of the brain, and these processes generate brain waves of different frequencies, such as delta waves (1 - 4 Hz), theta waves (4 - 8 Hz), alpha waves (8 - 13 Hz), beta waves (13 - 30 Hz), etc. Brain waves of different frequencies reflect different brain activities and cognitive states. The cognitive assessment technology combining EEG is to synchronously record the user's brain waves when the user performs a computerized task, and decode the user's brain state based on the EEG signal to achieve the assessment of the user's cognitive ability level.

[0004] Currently, the assessment methods for visual cognitive ability mainly focus on performing computerized tasks, and still take the behavioral indicators generated during the task as the only standard for evaluating the level of visual cognitive ability, lacking a more objective and broader - dimensional assessment method with physiological indicators as a reference; in addition, the current assessment tasks mainly focus on computerized simulation of real - world situations, lacking a visual cognitive assessment means that starts from psychology and can be widely applied to various scenarios. Summary of the Invention

[0005] The present invention provides a method for assessing visual cognitive ability based on EEG signals, which assesses the user's visual cognitive ability through computerized visual cognitive tasks, and simultaneously detects the brain state of the user when performing visual cognitive tasks by combining EEG signals.

[0006] The technical solution adopted by the present invention is as follows: A method for assessing visual cognitive ability based on EEG signals, comprising:

[0007] The user performs a series of visual cognitive assessment tasks on the computer, and the accuracy of task judgment and the time of task completion are recorded as the user's behavioral data. At the same time, the user wears an EEG signal acquisition device to synchronously acquire the user's EEG signals; after the user completes all visual cognitive assessment tasks, all acquired EEG signals are saved in a file of a specific format; the original EEG signals and behavioral data in the file are read, and decoded to obtain the user's EEG signal concentration index and behavioral index, so as to evaluate the visual cognitive ability.

[0008] If both the concentration index and the behavioral index are higher than the population average, the visual cognitive ability is considered to meet the standard; if the concentration index is lower than the population average, it is considered that the user has not completed this assessment in the optimal brain state and needs to be re-assessed; if the behavioral index is lower than the population average, it is considered that the visual cognitive ability is not up to standard.

[0009] The visual cognition assessment task is a visual target recognition task, and the task goal is to find the correct target with a different motion pattern from the interfering targets in the shortest possible time under the influence of many interfering targets, and operate the mouse to click on the correct target.

[0010] The visual cognition assessment task has a total of no less than 40 task modules, of which low-difficulty task modules and high-difficulty task modules each account for half, and high-difficulty task modules and low-difficulty task modules appear alternately; each task module contains 5 consecutive visual cognition assessment task trials of the same difficulty.

[0011] At the beginning of the visual cognition assessment task, a cross fixation point appears in the center of the computer screen and lasts for two seconds, assisting the user to return the visual field to the center of the screen and at the same time assisting the user to restore the brain state from the actively mobilized task state to the resting state; after the cross fixation point disappears, the computer screen presents a visual target search task, and a number of white dots of the same shape, size, and moving speed appear simultaneously against a black background, all of which move in a uniform straight line. Among them, one and only one white dot is the correct target point, which moves in a fixed direction; the remaining white dots are interference points, and the movement directions of these dots change at a specific frequency; when the user completes the selection of the target with the mouse, the selected dot changes from white to orange, and all dots on the screen maintain the original movement mode and continue to move for one second; then the correct target point changes to green, and all dots on the screen maintain the original movement mode and continue to move for one second, at which point the visual cognition assessment task trial ends.

[0012] The decoding process of the user's EEG signal concentration index is as follows: The computer reads the original EEG signal data from a file and preprocesses the original EEG signal data; the preprocessing includes 50Hz notch filtering and 1-30Hz band-pass filtering; the computer intercepts the EEG signal data segments corresponding to each visual cognitive task trial of the user according to the time stamp, and calculates the power density spectrum of the EEG data corresponding to the electrode channels in the parietal lobe area; calculates the power in the beta frequency band of 13-30Hz and the power in the 1-30Hz frequency band; calculates the ratio of the power in the beta frequency band to the power in the 1-30Hz frequency band to obtain the key EEG signal feature: the relative power of the beta frequency band; the average value of the key EEG signal feature in all task trials is used as the concentration index for measuring the user's visual cognitive task execution.

[0013] The behavioral indicators include accuracy and task time.

[0014] The decoding process of the behavioral indicators is as follows: The computer reads the original behavioral data from a file, and calculates the average values of the task accuracy and the task completion time in all task trials respectively, as the behavioral indicators for measuring the user's visual cognitive ability level.

[0015] Advantages of the present invention:

[0016] First, by integrating EEG technology, the present invention can simultaneously decode the behavioral indicators and brain feature indicators of the user during the execution of the target recognition task, and realize the evaluation of the user's visual cognitive level in two dimensions of behavioral performance and brain response mode.

[0017] Second, the present invention uses the visual target recognition task to provide a two-dimensional target search scenario for the user, enabling the user to be in an immersive state of performing target search during the cognitive ability evaluation process, and thus making the collected EEG signals of the user the physiological characteristics induced by the target search task, which is more conducive to the representation of visual cognitive ability by EEG features.

[0018] Third, using EEG technology, the present invention decodes the EEG signals to obtain a physiological feature index that has a high correlation with the concentration of the user during task execution, that is, the relative power of the beta frequency band. This feature index can reflect the user's visual cognitive level to a certain extent as a representation of the user's brain state.

[0019] Fourth, the present invention can be applied to the evaluation of the visual cognitive ability of ball game players and e-sports players. Since this type of population has higher requirements for visual cognitive ability, using the method described in this article can more objectively and scientifically evaluate the visual ability and potential of athletes from the perspective of the brain. Description of the Drawings

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 This is the overall flowchart of a visual cognitive ability assessment method based on electroencephalogram (EEG) signals provided by the embodiments of the present invention, including the general presentation process of visual cognitive tasks and the general processes of collecting, storing, and feature extracting synchronized EEG data and behavioral data.

[0022] Figure 2 This is the single-trial flowchart of the visual cognitive assessment task described in the present invention.

[0023] Figure 3 This is a schematic diagram showing the alternating presentation of high- and low-difficulty tasks in the visual cognitive assessment task described in the present invention. Detailed implementation manners

[0024] The following will describe in detail the implementation manners of the present invention. Examples of the implementation manners are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The implementation manners described below by referring to the drawings are exemplary and are only used to explain the present invention, and cannot be construed as a limitation of the present invention.

[0025] For the convenience of understanding the embodiments of the present invention, the following will describe the embodiments of the present invention in detail in conjunction with the drawings.

[0026] It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other; and, based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present disclosure.

[0027] The user performs a series of visual cognitive assessment tasks on a computer, records the correct rate of task judgment and the task completion time as the user's behavioral data. At the same time, the EEG signal acquisition device worn by the user synchronously acquires the user's EEG signals. After the user completes all visual cognitive assessment tasks, all the acquired EEG signals are saved in a file in a specific format; the original EEG signals and behavioral data in the file are read, and the EEG signal concentration index and behavioral index of the user are decoded to perform visual cognitive ability assessment.

[0028] The computer obtains the original synchronous EEG signals of the user during the execution of the visual cognitive task from the EEG signal file, intercepts the task-state EEG signal data segment corresponding to the time when the user performs the visual cognitive assessment task from the EEG signals, preprocesses the EEG signal data segment, and extracts the required EEG signal features from the preprocessed EEG data, that is, the relative beta-band power of the electrode channels in the parietal region. The EEG signal features are the indicators for measuring the concentration of the user in performing the visual cognitive task;

[0029] The visual cognitive assessment task performed by the user is a target recognition task. The task goal of the user is to find the correct target in the shortest possible time under the influence of numerous interfering targets and operate the mouse to click on the target;

[0030] The visual cognitive assessment task has no less than 40 task modules, among which the low-difficulty task and the high-difficulty task modules each account for half, and the high-difficulty task modules and the low-difficulty task modules appear alternately; each task module contains 5 consecutive visual cognitive assessment task trials with the same difficulty.

[0031] As a specific embodiment, the visual cognitive assessment task has a total of forty task modules, including twenty low-difficulty task modules and twenty high-difficulty task modules, and the high- and low-difficulty task modules appear alternately; each task module contains five consecutive visual cognitive task trials with the same difficulty;

[0032] Specifically, at the beginning of each visual cognitive task trial, a cross fixation point will appear at the center of the computer screen and last for two seconds, assisting the user to return the field of view to the center of the screen and at the same time assisting the user to restore the brain state from the actively mobilized task state to the resting state;

[0033] Further, a visual target search task will be presented on the computer screen. Specifically, several white dots with the same shape, the same size, the same moving speed and all moving in a uniform straight line will appear simultaneously on a black background. Among them, there is only one white dot that is the correct target point, and this point moves in a uniform straight line along a certain fixed direction; the remaining white dots are all interference points, and the interference points move in a uniform straight line with randomly changing moving directions;

[0034] The user needs to confirm the correct target in the shortest possible time, control the mouse of the computer to select the target, and click the mouse to select it;

[0035] Further, when the user completes the selection with the mouse, the selected dot will change from white to orange, and all the dots on the screen will continue to move in the original moving mode for one second;

[0036] Furthermore, the correct target point will change from white (not selected) or orange (selected) to green, and all dots on the screen will continue to move in the original mode for one second. At this point, the visual cognition task trial ends;

[0037] After completing all visual cognition tasks, the user's behavioral data in each visual cognition task trial will be saved in a file of a specific format; through analysis of the behavioral data, important indicators such as the user's average task accuracy and average task time when performing visual cognition tasks can be obtained. These indicators are regarded as important considerations of the user's visual cognition ability.

[0038] The overall flow chart of a visual cognition training method based on EEG signal neural feedback provided by an embodiment of the present invention is as follows: Figure 1 As shown, the following steps are included:

[0039] In the first step, the user needs to wear the EEG signal acquisition device, correctly connect the EEG signal acquisition device to the computer, and correctly set up the EEG signal acquisition software, which specifically includes the following steps:

[0040] 1.1) The user wears an EEG signal collection cap and ensures that each electrode channel on the EEG signal collection cap is in the correct position;

[0041] 1.2) Correctly connect the EEG signal acquisition cap to the EEG signal amplifier, and the EEG signal amplifier to the computer;

[0042] 1.3) Use a syringe to inject conductive gel into the electrode pores of the EEG signal collection cap, and ensure that the impedance of each electrode channel is less than 30 kΩ;

[0043] 1.4) Open the EEG signal acquisition software in the computer, correctly set the EEG signal acquisition parameters, and ensure that the EEG signal acquisition software acquires EEG signals with reliable data quality.

[0044] In the second step, the user starts to perform the visual cognition assessment task, and the EEG signal acquisition device synchronously acquires the EEG signal of the user when performing the task, which specifically includes the following steps:

[0045] 2.1) After the user reads the text instructions of the visual cognition assessment presented on the computer screen and ensures that the experimental content and experimental requirements are correctly understood, the experiment officially begins;

[0046] 2.2) In general, the visual cognition assessment task has a total of 40 task modules, including 20 low-difficulty task modules and 20 high-difficulty task modules, and the high-difficulty and low-difficulty task modules appear alternately, such as Figure 2As shown; each task module contains five consecutive visual cognitive task trials of the same difficulty;

[0047] 2.3) The process of any trial of the visual cognition task is as follows Figure 3 Specifically, in the first two seconds of the task, a white cross-shaped fixation point appears in the center of the screen, which can not only help the user to refocus the visual field on the center of the screen, but also help the user to restore the brain state from the task state to the resting state; then, the computer screen will present a visual target search task. Specifically, a number of white dots of the same shape, size, and speed will appear simultaneously against a black background, and all of them are moving in a uniform linear motion. Among them, only one white dot moves in a uniform linear motion in a fixed direction, which is called the correct target point; the rest of the white dots move in a uniform linear motion with randomly changing directions. The white dots move in a straight line, and the direction of movement changes every 0.3 seconds. These white dots are called interference dots. The user needs to confirm the correct target in the shortest possible time, control the computer mouse to select the target, and click the mouse to select it. When the user completes the selection with the mouse, the selected dot will change from white to orange, and all the dots on the screen will continue to move in the original movement mode for one second. Subsequently, the correct target dot will change from white (not selected) or orange (selected) to green, and all the dots on the screen will continue to move in the original movement mode for one second. At this point, the visual cognition task trial ends.

[0048] The third step is that after the user completes all visual cognitive assessment tasks, the computer saves the synchronized EEG signals and behavioral signals of the user when performing the visual cognitive assessment tasks in a file of a specific format for subsequent processing and analysis, which specifically includes the following steps:

[0049] 3.1) The EEG signal acquisition software saves the synchronized EEG signals of the user during the task execution in a file in BDF format;

[0050] 3.2) The visual cognition assessment program saves the behavioral data of the user during the task execution in a MAT format file, and the behavioral data includes the accuracy rate of the user in any task trial and the task completion time.

[0051] The fourth step is to analyze the EEG signal data and behavioral data of the user when performing the visual cognition assessment task, and obtain the concentration index of the user during the task execution and the behavioral index for evaluating the visual cognition ability level of the user, which specifically includes the following steps:

[0052] 4.1) The computer reads the original EEG signal data from the BDF format file and preprocesses each data segment, including 50 Hz notch filtering and 1 - 30 Hz band - pass filtering; the computer intercepts the EEG signal data segments corresponding to each task trial executed by the user according to the time stamp, and calculates the power density spectrum of the EEG data corresponding to the electrode channels in the parietal lobe area; calculates the power in the β (13 - 30 Hz) frequency band and the power in the 1 - 30 Hz frequency band; calculates the ratio of the β - band power to the 1 - 30 Hz - band power to obtain the key EEG signal feature: the relative power of the β - band; the average value of the EEG signal features in all task trials is the concentration index for measuring the user's performance of the visual cognitive task.

[0053] 4.2) The computer reads the original behavioral data from the MAT format file, and respectively calculates the average values of the task accuracy rate and the task completion time in all task trials, which are the behavioral indexes for measuring the user's visual cognitive ability level.

[0054] As described above, it is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for evaluating visual cognitive ability based on electroencephalogram signals, characterized in that: include: The user performs a series of visual cognitive assessment tasks on the computer, and the accuracy of task judgment and task completion time are recorded as the user's behavioral data. At the same time, the user wears an electroencephalogram signal acquisition device to synchronously acquire the user's electroencephalogram signals; after the user completes all visual cognitive assessment tasks, all acquired electroencephalogram signals are saved in a file of a specific format; The original EEG signals and behavioral data in the file are read, and the EEG signal concentration index and behavioral index of the user are obtained by decoding to evaluate the visual cognitive ability.

2. The visual cognitive ability assessment method based on concentration index and behavioral index according to claim 1 is characterized in that: If both the concentration index and the behavioral index are higher than the population average, the visual cognitive ability is considered to meet the standard; if the concentration index is lower than the population average, it is considered that the user has not completed this assessment in the optimal brain state and needs to be re-assessed; if the behavioral index is lower than the population average, it is considered that the visual cognitive ability is not up to standard.

3. The method for evaluating visual cognitive ability based on EEG signals according to claim 1, characterized in that: The visual cognition assessment task is a visual target recognition task, and the task goal is to find the correct target with a different motion pattern from the interfering targets in the shortest possible time under the influence of many interfering targets, and operate the mouse to click on the correct target.

4. The method for evaluating visual cognitive ability based on EEG signals according to claim 3, characterized in that: The visual cognition assessment task has a total of no less than 40 task modules, of which low-difficulty task modules and high-difficulty task modules each account for half, and high-difficulty task modules and low-difficulty task modules appear alternately; each task module contains 5 consecutive visual cognition assessment task trials of the same difficulty.

5. The method for evaluating visual cognitive ability based on EEG signals according to claim 4, characterized in that: The low-difficulty task includes 6 interference targets, and the high-difficulty task includes 14 interference targets.

6. The method for evaluating visual cognitive ability based on EEG signals according to claim 4, characterized in that: At the beginning of the visual cognition assessment task, a cross fixation point appears in the center of the computer screen and lasts for two seconds, assisting the user to return the visual field to the center of the screen and at the same time assisting the user to restore the brain state from the actively mobilized task state to the resting state; after the cross fixation point disappears, the computer screen presents a visual target search task, and a number of white dots of the same shape, size, and moving speed appear simultaneously against a black background, all of which move in a uniform linear motion, of which one and only one white dot is the correct target point, which moves in a fixed direction; the remaining white dots are interference points, and the movement directions of these dots change at a specific frequency; when the user completes the selection of the target with the mouse, the selected dot changes from white to orange, and all dots on the screen maintain the original movement mode and continue to move for one second; then the correct target dot changes to green, and all dots on the screen maintain the original movement mode and continue to move for one second, at which point the visual cognition assessment task trial ends.

7. The method for evaluating visual cognitive ability based on EEG signals according to claim 1, characterized in that: The decoding process of the user's EEG signal concentration index is as follows: the computer reads the original EEG signal data from the file and preprocesses the original EEG signal data; the preprocessing includes 50Hz notch filtering and 1-30Hz bandpass filtering; the computer intercepts the EEG signal data segments corresponding to the user's visual cognitive task trials according to the timestamp, and calculates the power density spectrum of the EEG data corresponding to the electrode channel of the parietal lobe area; calculates the β band power 13-30Hz and 1-30Hz band power; calculates the ratio of the β band power to the 1-30Hz band power to obtain the key EEG signal feature: the relative power of the β band; the average value of the key EEG signal feature in all task trials is used as an indicator to measure the user's concentration when performing visual cognitive tasks.

8. The method for evaluating visual cognitive ability based on EEG signals according to claim 1, characterized in that: The behavioral indicators include accuracy and task time.

9. The method for evaluating visual cognitive ability based on EEG signals according to claim 8, characterized in that: The decoding process of the behavioral index is as follows: the computer reads the original behavioral data from the file, and calculates the average values ​​of the task accuracy and the task completion time in all task trials as behavioral indicators to measure the visual cognitive ability level of the user.

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