User subjective brightness adjustment system and method based on visual ERP

Abstract

This application discloses a user-subjective brightness adjustment system and method based on visual ERP. An EEG signal acquisition device acquires EEG signals from a user when they are visually stimulated. A paradigm control module controls a display device to generate at least one visual stimulation group consisting of multiple rounds, each of which includes target stimulation and non-target stimulation, presented at fixed time intervals. An EEG data processing module filters and removes interference from the acquired EEG signals, and calculates the ERP amplitudes of the target stimulation and non-target stimulation based on baseline EEG data. A brightness sensitivity index calculation module calculates the brightness sensitivity index corresponding to each brightness level. A brightness adjustment module determines the display device brightness corresponding to the optimal ERP quality based on the brightness sensitivity index corresponding to each brightness level, and automatically adjusts the brightness or grayscale of the display device. This application avoids the blindness and individual bias of traditional subjective brightness adjustment.

Description

Technical Field

[0001] The present application belongs to the technical field of digital product brightness adjustment, and in particular relates to methods and devices for wearable devices based on bioelectric signals. Background Art

[0002] Electroencephalography (EEG) is a noninvasive diagnostic method that uses scalp electrodes to capture subtle changes in the electrical activity of brain neurons, thereby reflecting brain function. It is widely used in the diagnosis of diseases such as epilepsy, dementia, and encephalitis. Among them, event-related potentials (ERPs) evoked by visual stimulation, as a type of EEG signal, can accurately reflect a person's cognitive processing of visual stimuli. Therefore, it is widely used in cognitive tasks such as rehabilitation therapy and cognitive testing.

[0003] However, in practice, the quality of ERPs induced by visual stimulation can be affected by a variety of factors, including a user's mental state and external environment. Studies have found that the brightness of visual stimulation significantly impacts ERP quality. Inappropriate brightness can lead to a decrease in ERP signal quality, thereby affecting the accuracy and effectiveness of cognitive tasks. Therefore, determining an appropriate stimulus brightness before performing cognitive tasks is crucial.

[0004] While display device brightness adjustment is now a common technology, meeting user needs for both ambient light and personalized brightness, manual adjustment is often required. Furthermore, subjective user-determined brightness is often not optimal for cognitive tasks. Automatically and accurately determining the optimal display brightness for cognitive tasks has become a key issue in improving the effectiveness of ERP-based cognitive tasks. Summary of the Invention

[0005] The technical purpose of this application is to provide a user subjective brightness adjustment system based on visual ERP to address the technical problem that the current display device brightness adjustment method requires manual adjustment and the brightness determined subjectively by the user is not necessarily the most suitable for cognitive tasks and cannot meet the user's personalized brightness adjustment.

[0006] In order to achieve the above technical objectives, this application adopts the following technical solutions.

[0007] In a first aspect, an embodiment of the present application provides a user subjective brightness adjustment system based on visual ERP, comprising:

[0008] An electroencephalogram (EEG) signal acquisition device for acquiring EEG signals from a selected brain region on the user's scalp when the user is visually stimulated;

[0009] a paradigm control module, configured to control the display device to generate at least one visual stimulus group comprising a plurality of rounds, wherein each visual stimulus in the round comprises a target stimulus and a non-target stimulus, each visual stimulus is presented at a set time interval, and the brightness levels of the visual stimuli in different rounds are different, while the brightness levels of the visual stimuli in the same round are the same;

[0010] an EEG data processing module, configured to filter and remove interference from the collected EEG signals, and calculate the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus based on the reference EEG data;

[0011] The brightness sensitivity index calculation module is used to calculate the brightness sensitivity index corresponding to each brightness based on the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus in each round;

[0012] The brightness adjustment module is used to determine the brightness of the display device corresponding to the optimal ERP quality according to the brightness sensitivity index corresponding to each brightness, and automatically adjust the brightness or grayscale of the display device.

[0013] Furthermore, the target stimulus and the non-target stimulus are different in shape and / or color.

[0014] Furthermore, the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus are calculated based on the baseline EEG data, including:

[0015] Select the EEG signal of the user at a specific electrode in a resting state as the reference EEG signal, and determine the average value of the absolute value of the amplitude of the reference EEG signal , the average value of the absolute value of the EEG signal amplitude within the set time after the visual stimulus appears is selected as the mean absolute value of the EEG signal , calculate the ERP amplitude of visual stimulation, the formula is as follows: , V erp is the ERP amplitude of visual stimulation.

[0016] Furthermore, the calculation formula of the brightness sensitivity index is:

[0017] ;

[0018] Among them, Index tar is the brightness sensitivity index, is the ERP amplitude of the target stimulus, is the mean ERP amplitude of all non-target stimuli with the same brightness level as the target stimulus, is the standard deviation of the ERP amplitude of all target stimuli with the same brightness level as the target stimulus, is the standard deviation of the ERP amplitude of all non-target stimuli with the same luminance level as the target stimulus.

[0019] Furthermore, the method for the brightness adjustment module to automatically adjust the brightness or grayscale of the display device includes:

[0020] A one-way ANOVA was performed on the brightness sensitivity index of different brightness levels, and the F value of the difference between the visual stimulation groups was calculated. If the F value exceeded the threshold, the brightness level with no significant difference from the maximum mean brightness group was selected as the candidate group. The maximum mean brightness group was the brightness group corresponding to the maximum mean of the brightness sensitivity index of each brightness level in all visual stimulation groups.

[0021] Select the brightness that the user is subjectively comfortable with from the candidate group or take the average brightness as the optimal brightness.

[0022] Furthermore, the brightness adjustment module supports brightness adjustment by adjusting the RGB component ratio or grayscale value of the display device. The specific formula is:

[0023] V rgb =int(R0×255); where V rgb is the adjusted RGB component value, R0 is the brightness adjustment ratio, int is the rounding calculation, and the mapping relationship between the brightness adjustment ratio and the actual brightness of different display devices is determined by pre-calibration.

[0024] In a second aspect, an embodiment of the present application provides a brightness adjustment method for a user subjective brightness adjustment system based on visual ERP provided by any possible implementation method of the first aspect, comprising the following steps:

[0025] The user wears an EEG signal acquisition device to collect EEG signals from selected brain areas on the user's scalp surface when the user is visually stimulated;

[0026] Presenting at least one visual stimulus group including a plurality of rounds through a display device, wherein each round of visual stimulation includes a target stimulus and a non-target stimulus, each visual stimulus is presented at a fixed time interval, and the brightness of the visual stimuli in different rounds is different, while the brightness of the visual stimuli in the same round is the same;

[0027] The collected EEG signals are filtered and interference removed, and the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus are calculated based on the baseline EEG data;

[0028] According to the ERP amplitude of target stimulation and non-target stimulation in each round, the brightness sensitivity index corresponding to each brightness was calculated respectively;

[0029] According to the brightness sensitivity index corresponding to each brightness, the brightness of the display device corresponding to the optimal ERP quality is determined, and the brightness or grayscale of the display device is automatically adjusted.

[0030] Furthermore, the method also includes: if the brightness sensitivity index of all rounds in a single stimulation group is less than a set brightness sensitivity index threshold, then determining that the stimulation group is invalid.

[0031] Furthermore, when the number of ineffective stimulation groups exceeds a preset threshold, the measurement is terminated and a prompt is given to adjust the task parameters, wherein the adjustment of the task parameters includes extending the stimulation interval and / or enhancing the visual characteristics of the target stimulation.

[0032] Furthermore, the brightness levels of each round in each visual stimulation group were randomly arranged.

[0033] The user-subjective brightness adjustment system and method based on visual ERP provided in the embodiments of this application have the following beneficial technical effects: By determining ERP signals based on EEG signals, the EEG response induced by visual stimulation is directly quantified, avoiding the blindness and individual bias of traditional subjective brightness adjustment (such as manual adjustment by the user). The system automatically completes everything from EEG acquisition and stimulus presentation to brightness calculation and adjustment, eliminating the need for human intervention. This system is suitable for scenarios requiring rapid initialization, such as medical rehabilitation and cognitive testing. It can automatically adjust screen brightness before the user begins a corresponding cognitive task, ensuring optimal task performance in a variety of environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are for illustrative 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 schematic 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. Those skilled in the art can select various possible shapes and proportional dimensions to implement the present application according to the specific circumstances under the guidance of the present application. In the drawings:

[0035] Figure 1 A schematic diagram of the structure of a user's subjective brightness adjustment system based on visual ERP provided in an embodiment;

[0036] Figure 2 A schematic flow chart of a brightness adjustment method of a user subjective brightness adjustment system based on visual ERP provided in an embodiment;

[0037] Figure 3 Schematic diagram of the stimulation paradigm in the embodiment, wherein (a) is a schematic diagram of the time axis of target stimulation and non-target stimulation in a round of stimulation; (b) is a schematic diagram of the presentation sequence of a stimulation group;

[0038] Figure 4Schematic diagram of brightness adaptation process in an embodiment. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0040] This application aims to provide a display device brightness adjustment system based on EEG and visual ERP, which can automatically adjust the screen brightness according to the user's subjective feelings, ensuring that the user can get a comfortable visual experience in various environments.

[0041] The present application is further described below with reference to the accompanying drawings and specific embodiments.

[0042] like Figure 1 As shown, the embodiment provides a user subjective brightness adjustment system based on visual ERP, including an EEG signal acquisition device, a paradigm control module, an EEG data processing module, a brightness sensitivity index calculation module and a brightness adjustment module.

[0043] The electroencephalogram (EEG) signal acquisition device is used to acquire EEG signals from selected brain areas on the scalp surface when the user is visually stimulated.

[0044] The paradigm control module is used to control the display device to generate at least one visual stimulus group including multiple rounds, each round of visual stimulation includes target stimulation and non-target stimulation, each visual stimulation group includes multiple rounds, each visual stimulation is presented at a set time interval, and the brightness levels of the visual stimulations in different rounds are different, while the brightness levels of the visual stimulations in the same round are the same.

[0045] The EEG data processing module is used to filter and remove interference from the collected EEG signals, and calculate the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus based on the baseline EEG data.

[0046] The brightness sensitivity index calculation module is used to calculate the brightness sensitivity index corresponding to each brightness according to the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus in each round.

[0047] The brightness adjustment module is used to determine the brightness of the display device corresponding to the optimal ERP quality according to the brightness sensitivity index corresponding to each brightness, and automatically adjust the brightness or grayscale of the display device.

[0048] In one embodiment, the user-subjective brightness adjustment system based on visual ERP implements a brightness adjustment phase before a specific EEG task. The specific cognitive task can be ERP-based cognitive testing, visual stimulation-based cognitive training, etc. The cognitive task is similar to the visual stimulation in the brightness adjustment phase to ensure that the optimal brightness is suitable for the subsequent cognitive task.

[0049] Ideally, both target and non-target stimuli generate visually evoked signals, but cognitively relevant ERPs are only induced by target stimuli. Screen brightness that is too low or too high can affect the user's ability to distinguish visual stimuli, resulting in the target stimulus failing to induce ERPs. The brightness adjustment system provided in the embodiments of the present application automatically finds the appropriate brightness based on the user's subjective perception by observing ERP induction.

[0050] In the embodiment, the brightness adjustment process of the system is as follows: Figure 2 As shown, the user wears an EEG signal acquisition device, and the range of EEG signal acquisition includes at least Cz and Pz of the temporal lobe and parietal lobe brain regions, avoiding the occipital lobe region to reduce the influence of visual evoked potential on the results.

[0051] The paradigm control module controls the display device to present visual stimuli, and the user is instructed to focus on the visual stimuli. In one embodiment, at the beginning of a stimulus set, the display device presents a series of visual stimuli, including target stimuli and non-target stimuli. The visual stimuli are presented at set time intervals (e.g., fixed or variable time intervals). The user is only required to focus on the target stimulus and silently count the number of times the target stimulus appears.

[0052] In an embodiment, the number of target stimuli may be less than the number of non-target stimuli, and all target stimuli and non-target stimuli appear in one round. The brightness of the stimuli in each round is the same, and the brightness of the visual stimuli varies between rounds. Different brightness levels appear randomly, and each brightness level appears once, constituting a stimulation group. The number of rounds within a stimulation group is consistent with the number of brightness levels. After each stimulation group ends, the next stimulation group follows.

[0053] For example, there are N0 brightness levels of the stimulus, and N1 stimulus groups. After the visual stimulation is completed, there are N0 Rounds of stimulation.

[0054] In some embodiments, the display paradigm controlled by the paradigm control module is based on an oddball ERP paradigm, where both target stimuli and non-target stimuli appear in the user's field of view.

[0055] As an example, in each round of stimulation, the number of target stimuli is much smaller than that of non-target stimuli. Figure 3 As shown in the figure, (a) is a schematic diagram of the timeline of target stimulation and non-target stimulation in a round of stimulation; (b) is a schematic diagram of the presentation sequence of a stimulation group.

[0056] In some embodiments, the display device is a liquid crystal display, and a round of stimulation includes 1 target stimulus and 6 non-target stimuli. The brightness of the round of stimulation is the same. In the embodiment, the shape and / or color of the target stimulus and the non-target stimulus are different. As an example, Figure 3 As shown, the target stimulus is a square and the non-target stimulus is a triangle. The interval between each visual stimulus is 300 milliseconds, and the stimulus presentation time is 100 milliseconds. The target and non-target stimuli appear randomly, and the interval between different rounds should be greater than 1 second to avoid too little interval between target stimuli and affecting the quality of ERP signals. Optionally, there are 10 levels of brightness, evenly divided from 90% to 10% of the maximum brightness of the display device. Each stimulus group contains 10 rounds of stimulation, and each round of stimulation corresponds to 1 brightness level. If there are 10 stimulus groups, a total of 100 visual stimuli will appear.

[0057] In the embodiment, the EEG data processing module processes the collected EEG signals in the following manner: performing 3Hz-30Hz bandpass filtering on the EEG signals; and removing EEG signal interference from the filtered EEG signals.

[0058] In this embodiment, the brightness sensitivity index calculation module calculates the ERP brightness amplitude of the target stimulus and the non-target stimulus after the visual stimulus appears. The 1-second EEG signal of the main electrodes (such as Cz, Pz) with eyes open in the resting state is taken as the baseline EEG data, and the average value of the absolute value of the baseline EEG data is determined. , the average absolute value of the EEG signal 1 second after the visual stimulus appears As the stimulation EEG data, the ERP amplitude of visual stimulation is calculated as follows:

[0059] ;

[0060] in is the ERP amplitude of visual stimulation (target stimulation or non-target stimulation), It is the average absolute value of the EEG signal amplitude within a set time (such as 200-400 milliseconds) after the visual stimulus appears. It is the average absolute value of the EEG signal amplitude of the user in the resting state with eyes open for 1 second. This indicates EEG signals induced by visual stimulation. The 200-400 millisecond timeframe contains a large number of ERP signals related to cognition, while avoiding some visually evoked signals, making it more representative of the impact of brightness on cognition.

[0061] Because the brightness of a round is the same, a round corresponds to a brightness sensitivity index. As an example, when a round of stimulation includes one target stimulus and multiple non-target stimuli, the calculation formula of the brightness sensitivity index is:

[0062] ;

[0063] in, is the ERP amplitude of the target stimulus, is the mean ERP amplitude of all non-target stimuli with the same brightness level as the target stimulus, is the standard deviation of the ERP amplitude of all target stimuli with the same brightness level as the target stimulus, is the standard deviation of the ERP amplitude of all non-target stimuli with the same luminance level as the target stimulus.

[0064] If there are multiple target stimuli and multiple non-target stimuli in a round of stimulation, the calculation formula of the brightness sensitivity index is as follows:

[0065] ;

[0066] in, is the mean ERP amplitude of all target stimuli.

[0067] It can more intuitively evaluate the ERP quality caused by target stimulation. The bigger it is, the better the ERP quality is. There is no direct linear relationship between the index and brightness. When the stimulus brightness is high, both target and non-target stimuli can induce stronger EEG signals. The index can help users find the appropriate brightness to perform cognitive detection tasks.

[0068] After completing the above steps, you will have Different groups .

[0069] In an embodiment, the method for automatically adjusting the brightness or grayscale of a display device by a brightness adjustment module includes:

[0070] A one-way ANOVA was performed on the brightness sensitivity index of different brightness levels, and the F value of the difference between the visual stimulation groups was calculated. If the F value exceeded the threshold, the brightness level with no significant difference from the maximum mean brightness group was selected as the candidate group. The maximum mean brightness group was the brightness group corresponding to the maximum mean of the brightness sensitivity index of each brightness level in all visual stimulation groups.

[0071] Select the brightness that the user is subjectively comfortable with from the candidate group or take the average brightness as the optimal brightness.

[0072] As an example, all Divide the data into N0 groups, with the same stimulus brightness within each group, and each group has N1 samples. Calculate the correlation F value between each visual stimulus group. The formula used in this method is as follows:

[0073] ;

[0074] in All for group n The mean of For all The mean of All for group n The variance of .

[0075] The larger the F value, the brighter the stimulus. If the F value is less than the threshold, it means that the brightness induced If there is no significant difference, there is no need to further determine the optimal brightness. If the F value exceeds the threshold, it means that the brightness induced There is a significant difference, and the optimal brightness needs to be further determined.

[0076] In some embodiments, the F-value threshold is determined as follows: a random data set S0 with a sample size of 10,000 is generated, and the random data has a mean of , the standard deviation is The normal distribution of . and For all The mean and standard deviation of .

[0077] Randomly select N0 groups of data from S0, each group of data contains N1 samples, and calculate F according to the above formula.

[0078] Repeat the above process 1000 times and record the value of F each time.

[0079] All calculated F values ​​are sorted from high to low, with the set ratio (such as 10%) being the F value threshold.

[0080] If the F value is less than the threshold, it means that the brightness induced There is no significant difference. Each brightness level has no significant effect on the cognitive experiment. All brightness levels are included in the brightness candidate group. If the F value is greater than the threshold, it means that the brightness level has a substantial effect on the cognitive experiment. As a group, record , whose mean is . Find the brightness level group corresponding to the maximum mean value, recorded as . Then, With each brightness group A significance test was performed to check whether there was a significant difference.

[0081] If each stimulus set covers all N0 brightness levels, each brightness level will appear only once within the set (i.e., one round). For example, if N0 = 10, then a single stimulus set will contain 10 rounds, corresponding to brightness levels 1 to 10, with each level appearing once. In the embodiments, the repeatability of multiple stimulus sets is employed. For example, if N1 stimulus sets are performed, the same brightness level (e.g., the nth) will appear N1 times in each stimulus set (once in each stimulus set). For example, if N1 = 5, then brightness level n will appear once in each of the five stimulus sets, for a total of five appearances.

[0082] Specifically, the significance detection method used in the embodiment may be t-test or other detection methods.

[0083] Finally, all The brightness levels without significant differences were included in the brightness candidate group.

[0084] In the embodiment, any of the following methods may be used to find the optimal brightness group from the candidate brightness groups:

[0085] 1. Please find the most comfortable brightness for the user;

[0086] 2. Take the average of all brightness of the brightness candidate group as the optimal brightness.

[0087] Other embodiments, such as Figure 4 As shown, according to the brightness sensitivity index corresponding to each brightness, the brightness of the display device corresponding to the optimal ERP quality is determined, including:

[0088] Set a counter for each brightness level, initially set to 0;

[0089] After each round of stimulation, the brightness sensitivity index of the current round is calculated. If the index is greater than the threshold (e.g. > 1), the corresponding brightness counter is + 1;

[0090] When N3 stimulation groups are completed or the counter reaches the preset value N4, the brightness with the largest counter value is selected as the optimal brightness, or the average value is taken as the optimal brightness.

[0091] As an example, the brightness sensitivity index calculation module calculates the brightness sensitivity index of each round using the following formula:

[0092] ;

[0093] is the ERP amplitude of the target stimulus in the current round, is the mean ERP amplitude induced by non-target stimulation in the current round, is the standard deviation of the mean ERP amplitude evoked by non-target stimulation in the current round.

[0094] is calculated as follows:

[0095] ;

[0096] It is the average absolute value of the EEG signal 1 second after the appearance of the visual stimulus in the current round.

[0097] The larger the value of this indicator, the better the ERP amplitude induced by the target stimulation.

[0098] The brightness adjustment module determines the display device brightness corresponding to the optimal ERP quality based on the brightness sensitivity index corresponding to each brightness, and automatically adjusts the brightness or grayscale of the display device, including:

[0099] Statistical analysis of the optimal brightness level in each stimulus group: Calculate the optimal brightness level in each stimulus group for each round. , find the largest N2 values ​​and increase the corresponding brightness level counter by 1. Repeat the above process. After the stimulation group ends, determine whether the stopping condition is met. If so, find the brightness level with the largest counter value as the optimal brightness.

[0100] The stopping conditions are as follows, and the system can stop if any of the conditions are met:

[0101] 1) Complete N3 stimulation groups;

[0102] 2) The counter of a certain brightness reaches N4;

[0103] in, If, after stopping, multiple brightness level counters are equal to the maximum value, they are all included in the brightness candidate group. The method in the above embodiment can be used to find the optimal brightness group from the candidate brightness groups.

[0104] For example, before stimulation, all brightness level counters are set to 0. The thresholds N2, N3, and N4 are adjusted based on site conditions. In a preferred embodiment, N2 is 3, N3 is 8, and N4 is 5, with the number of brightness levels N0 being 10, for a total of 10 levels. The condition is met as soon as the fifth stimulus group is presented, and stimulation is discontinued. If no brightness level counter reaches 5, stimulation is discontinued after the eighth stimulus group is presented.

[0105] If the counter values ​​for brightness 6 and 7 are the largest after the stimulation stops, the average brightness of the candidate group is 6.5. The average lumens corresponding to brightness 7 and brightness 6 is taken as the optimal brightness.

[0106] This application uses the brightness sensitivity index (Indextar) to comprehensively evaluate signal strength (mean difference) and stability (standard deviation) to screen out the brightness that satisfies subjective comfort (such as user selection within the candidate group) and maximizes ERP quality, avoiding the problems of "too bright causing fatigue and discomfort" or "too dark affecting recognition".

[0107] To ensure test quality, some embodiments provide a user subjective brightness adjustment system based on visual ERP, further comprising an ERP signal quality detection module for performing the following steps:

[0108] After one stimulation group, If all the values ​​of the stimulus group are less than the set brightness sensitivity index threshold (e.g., set to 1), the stimulus group is invalid. If the number of invalid stimulus groups is greater than N5, the measurement fails and the process is terminated.

[0109] There are many reasons why measurements fail, such as poor EEG acquisition quality or the user not performing the task. In some cases, a test fails simply because the user has difficulty completing the task. Parameters can be adjusted to make the task less difficult.

[0110] Specifically, the adjustable parameters are as follows:

[0111] 1. Increase the interval between visual stimuli by 100 milliseconds. For example, if the original test interval between visual stimuli was 300 milliseconds, then increase it to 400 milliseconds. This method can increase user reaction time and reduce ERP interference.

[0112] 2. Change the shape of target and non-target stimuli. Enhance the visual intensity of target stimuli and weaken the visual intensity of non-target stimuli, such as reducing the image area of ​​non-target stimuli.

[0113] After the appropriate brightness is selected, the brightness adjustment module obtains the appropriate display device brightness by looking up the table, adjusts the display device brightness, and completes the adjustment process.

[0114] In a specific embodiment, in an environment where the screen brightness can be adjusted, the system automatically controls the display device to adjust the stimulus brightness. In display conditions where the brightness cannot be automatically adjusted, the stimulus brightness is adjusted by adjusting the grayscale.

[0115] For example: Before the test, the user manually adjusts the brightness of the display device to a given initial brightness value. The system adjusts the grayscale of the stimulus based on the relationship between the set brightness and grayscale to achieve the purpose of automatic brightness adjustment.

[0116] When the visual stimulus is a pure white square, the RGB components of the stimulus color are adjusted proportionally at the same time:

[0117] ;

[0118] Where V rgb is the adjusted RGB component value, The brightness adjustment ratio, int, is rounded to an integer. For example, when the brightness adjustment ratio is 100%, the RGB components of the stimulus color are (255, 255, 255). When the brightness adjustment ratio is 50%, the RGB components of the stimulus color are (127, 127, 127).

[0119] In the embodiment, the relationship between different color visual stimuli, brightness adjustment ratio and actual display brightness is calibrated for a specific model of display device by a professional brightness testing tool.

[0120] This invention uses visual stimulation to automatically determine the optimal stimulation brightness, improving the effectiveness of cognitive testing and rehabilitation equipment. It supports brightness control through both physical brightness adjustment (e.g., LCD displays) and grayscale simulation (e.g., fixed-brightness devices), making it compatible with different display devices and reducing hardware dependencies.

[0121] Based on the same inventive concept as the user subjective brightness adjustment system based on visual ERP provided in the above embodiment, the embodiment of the present application further provides a brightness adjustment method of the user subjective brightness adjustment system based on visual ERP, including:

[0122] The user wears an EEG signal acquisition device to collect EEG signals from selected brain areas on the user's scalp surface when the user is visually stimulated;

[0123] Presenting at least one visual stimulus group including a plurality of rounds through a display device, wherein each round of visual stimulation includes a target stimulus and a non-target stimulus, each visual stimulus is presented at a set time interval, and the brightness of the visual stimuli in different rounds is different, while the brightness of the visual stimuli in the same round is the same;

[0124] The collected EEG signals are filtered and interference removed, and the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus are calculated based on the baseline EEG data;

[0125] According to the ERP amplitude of target stimulation and non-target stimulation in each round, the brightness sensitivity index corresponding to each brightness was calculated respectively;

[0126] According to the brightness sensitivity index corresponding to each brightness, the brightness of the display device corresponding to the optimal ERP quality is determined, and the brightness or grayscale of the display device is automatically adjusted.

[0127] In some embodiments, if the brightness sensitivity index of all rounds in a single stimulation group is less than a set brightness sensitivity index threshold, the stimulation group is determined to be invalid.

[0128] In some embodiments, when the number of ineffective stimulation groups exceeds a preset threshold, the measurement is terminated and a prompt is given to adjust the task parameters, where adjusting the task parameters includes extending the stimulation interval or enhancing the visual features of the target stimulation.

[0129] In some embodiments, the brightness levels of each round of each visual stimulus group are randomly arranged.

[0130] The above is a detailed introduction to the user subjective brightness adjustment system and method based on visual ERP provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the concept of this application and should not be understood as limiting the scope of protection of this application.

Claims

1. A user subjective brightness adjustment system based on visual ERP, characterized by: The system comprises: An electroencephalogram (EEG) signal acquisition device for acquiring EEG signals from a selected brain region on the user's scalp when the user is visually stimulated; a paradigm control module, configured to control the display device to generate at least one visual stimulus group comprising a plurality of rounds, wherein each visual stimulus in the round comprises a target stimulus and a non-target stimulus, each visual stimulus is presented at a set time interval, and the brightness levels of the visual stimuli in different rounds are different, while the brightness levels of the visual stimuli in the same round are the same; The EEG data processing module is used to filter and remove interference from the collected EEG signals, and calculate the ERP amplitude of the target stimulation and the ERP amplitude of the non-target stimulation based on the reference EEG data, including: selecting the EEG signal of the user's specific electrode in the resting state as the reference EEG signal, and determining the average value V of the absolute value of the amplitude of the reference EEG signal. base , the average value of the absolute value of the EEG signal amplitude within the set time after the visual stimulus appears is selected as the stimulation EEG signal V t , calculate the ERP amplitude of visual stimulation, the formula is as follows: Verp=V t -V base , Verp is the ERP amplitude of visual stimulation; A brightness sensitivity index calculation module is used to calculate the brightness sensitivity index corresponding to each brightness level based on the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus in each round; a brightness adjustment module, configured to determine the brightness of the display device corresponding to the optimal ERP quality based on the brightness sensitivity index corresponding to each brightness level, and automatically adjust the brightness or grayscale of the display device; The calculation formula of the brightness sensitivity index is: ； Among them, Index tar is the brightness sensitivity index, V erp-tar is the ERP amplitude of the target stimulus, V mean-notar is the mean ERP amplitude of all non-target stimuli with the same brightness level as the target stimulus, V std-tar is the standard deviation of the ERP amplitude of all target stimuli with the same brightness level as the target stimulus, V std-notar is the standard deviation of the ERP amplitude of all non-target stimuli with the same brightness level as the target stimulus; The method for automatically adjusting the brightness or grayscale of a display device by the brightness adjustment module includes: performing a one-way analysis of variance on the brightness sensitivity index of different brightness levels and calculating the difference F value between visual stimulation groups; if the F value exceeds a threshold, screening out brightness levels that are not significantly different from the maximum mean brightness group as a candidate group, wherein the maximum mean brightness group is the brightness group corresponding to the maximum mean value of the brightness sensitivity index of each brightness level in all visual stimulation groups; and selecting the brightness that is subjectively comfortable to the user from the candidate group or taking the average brightness value as the optimal brightness.

2. The user subjective brightness adjustment system based on visual ERP according to claim 1, characterized in that: The target stimulus is different from the non-target stimulus in shape and / or color.

3. The user subjective brightness adjustment system based on visual ERP according to claim 1, characterized in that: The brightness adjustment module supports brightness adjustment by adjusting the RGB component ratio or grayscale value of the display device. The specific formula is: V rgb = int (R0×255)； in, V rgb is the adjusted RGB component value, R 0 is the brightness adjustment ratio, int For rounding calculations, the mapping relationship between the brightness adjustment ratios of different display devices and the actual brightness is determined through pre-calibration.

4. A brightness adjustment method based on the system according to any one of claims 1 to 3, characterized in that: The following steps are involved: The user wears an EEG signal acquisition device to collect EEG signals from selected brain areas on the user's scalp surface when the user is visually stimulated; Presenting at least one visual stimulus group including a plurality of rounds through a display device, wherein each round of visual stimulation includes a target stimulus and a non-target stimulus, each visual stimulus is presented at a set time interval, and the brightness of the visual stimuli in different rounds is different, while the brightness of the visual stimuli in the same round is the same; Filter and remove interference from the collected EEG signals, and calculate the ERP amplitude of the target stimulus and the ERP amplitude of the non-target stimulus based on the baseline EEG data; According to the ERP amplitude of target stimulation and non-target stimulation in each round, the brightness sensitivity index corresponding to each brightness was calculated respectively; According to the brightness sensitivity index corresponding to each brightness, the brightness of the display device corresponding to the optimal ERP quality is determined, and the brightness or grayscale of the display device is automatically adjusted.

5. The brightness adjustment method according to claim 4, wherein: The method further includes: if the brightness sensitivity index of all rounds in a single stimulation group is less than a set brightness sensitivity index threshold, then determining that the stimulation group is invalid.

6. The brightness adjustment method according to claim 5, characterized in that: When the number of invalid stimulation groups exceeds a preset threshold, the measurement is terminated and a prompt is given to adjust the task parameters, which includes extending the stimulation interval and / or enhancing the visual features of the target stimulation.

7. The brightness adjustment method according to claim 4, wherein: The brightness levels of each round in each visual stimulation group were randomly arranged.

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