Attention training method, system and device based on brain-computer interface and storage medium

Abstract

The invention discloses an attention training method, system and device based on a brain-computer interface, and a storage medium, and belongs to the technical field of brain-computer interfaces. The attention method is carried out on the basis of electroencephalogram signal data, measured in real time through a brain-computer interface, of a trainee, movement of a training role is controlled on the basis of an attention numerical value by providing the training role, and multiple training modes such as an attention intensity training task, an execution training task, a suppression training task and a work memory training task are further provided. The method, the system, the equipment and the medium brain-computer training are high in interactivity, a multi-task training paradigm is adopted, the defects of singleness and boring in the prior art are overcome, so that the compliance of trainees is improved, the training frequency is increased, a better training effect is achieved, and ADHD patients can not only be trained in hospitals, but also can be trained in the hospitals. And training can be carried out in a home environment, so that the device is more convenient, economical and efficient. Especially for school-age children and adolescents, the training compliance of patients is greatly improved, and the falling rate in the training process is reduced.

Description

Technical Field

[0001] The present application relates to the field of brain-computer interface technology, and in particular to attention training methods, systems, devices and storage media based on brain-computer interfaces. Background Art

[0002] Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by inattention, hyperactivity and / or impulsivity. It is mainly divided into three types: inattention, hyperactivity-impulsivity and mixed manifestations.

[0003] Current mainstream treatments for ADHD include both pharmacotherapy and non-drug therapies. EEG biofeedback is a non-invasive brain-computer interface (BCI) technology that improves neural function by monitoring and modulating brain electrical activity in real time. It is a clinically accepted, low-risk, and low-side-effect non-drug treatment. Its core principles, based on biofeedback mechanisms and neuroplasticity theory, improve attention by training patients to autonomously regulate the frequency and intensity of specific brainwaves.

[0004] However, existing EEG biofeedback all adopts audio-visual feedback (such as animation and sound). This kind of feedback training is monotonous and boring, resulting in low patient compliance, which affects the training frequency and the final training effect. Summary of the Invention

[0005] The present application provides an attention training method, system, device and storage medium based on brain-computer interface to at least solve the above technical problems existing in the prior art.

[0006] The first aspect of the present application provides an attention training method based on a brain-computer interface, comprising the following steps:

[0007] Obtain the EEG signal data of the trainee measured in real time based on the brain-computer interface, perform 1Hz~35Hz filtering, and convert the EEG signal data into attention value.

[0008] Providing a training character and an observable scene, wherein the training character is at a certain position in the observable scene, and a movement speed of the training character is set according to the attention value, and the training character moves relatively in the observable scene along a movement route at the movement speed;

[0009] P obstacles are set on the movement route of the training character, where P≥1. When the distance between the training character and any one of the obstacles reaches a first preset distance threshold, continuous detection of whether a first instruction exists begins until the first instruction is detected or the training time ends.

[0010] If the first instruction is detected, the training character continues to move at the moving speed and is not affected by the obstacle; if the first instruction is not detected until the distance between the training character and the obstacle is a second preset distance threshold, the moving speed of the training character is set to 0 until the first instruction is detected, and the moving speed of the training character is set again using the current attention value, so that the training character is no longer affected by the obstacle and continues to move.

[0011] In some embodiments of the present application, during the entire training time, the presence of the second instruction is continuously detected, M target objects are displayed at intervals in the observable scene, M ≥ 1, and during the movement of the training character, each of the target objects first approaches relatively close to the training character and then moves relatively away from the training character;

[0012] If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0013] If the second instruction is detected one or more times during the period when the target object is displayed but the distance between the target object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected;

[0014] If the second instruction is detected once or multiple times while the target object is displayed and the distance between the target object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error.

[0015] In some possible implementation schemes of the present application, N non-target objects are displayed at intervals in the observable scene, where N ≥ 1. During the movement of the training character, each of the non-target objects is relatively close to and then relatively far away from the training character.

[0016] If the second instruction is detected one or more times during the period when the target object and the non-target object are not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0017] If the second instruction is detected one or more times during the display of the non-target object, a suppression error is recorded each time the second instruction is detected;

[0018] If the second instruction is not detected during the display of the non-target object, it is recorded that the suppression is correct.

[0019] In some possible implementation schemes of the present application, M ≥ 2, the M target objects are different, and the M target objects are first displayed sequentially in the observable scene for a period of time, wherein the period of time is 2 to 5 seconds, and then each target object is randomly displayed once or multiple times, wherein the target objects displayed in sequence are sequential objects, and the target objects displayed out of sequence are non-sequential objects.

[0020] If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0021] If the second instruction is detected one or more times when the sequential object is displayed but the distance between the sequential object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected;

[0022] If the second instruction is detected once or multiple times when the sequential object is displayed and the distance between the sequential object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error;

[0023] If the second instruction is detected one or more times during the display of the non-sequential object, a suppression error is recorded each time the second instruction is detected;

[0024] If the second instruction is not detected during the display of the non-sequential object, it is recorded that the suppression is correct.

[0025] In some possible implementation schemes of the present application, in step S2, the EEG signal data is spectrally analyzed by Fourier transform, and the power spectrum density of different frequency bands is calculated, and the attention value is further obtained based on the power spectrum density.

[0026] The second aspect of the present application provides an attention training system based on a brain-computer interface, comprising the following modules:

[0027] The EEG signal data receiving and processing module is used to receive the EEG signal data of the trainee measured in real time based on the brain-computer interface, and convert the EEG signal data into attention value after filtering at 1Hz~35Hz.

[0028] The visualization module is used to provide a training character and an observable scene, wherein the training character is at a certain position in the observable scene.

[0029] a training character control module, connected to the EEG signal data receiving and processing module and the visualization module, for setting a movement speed of the training character according to the attention value, wherein the training character moves relatively in the observable scene along a movement route at the movement speed;

[0030] The training function control module is used to set P obstacles in front of the moving direction of the training character, where P≥1.

[0031] A distance detection module is used to detect the distance between the training character and any of the obstacles.

[0032] An instruction recognition module, configured to recognize a first instruction;

[0033] a judgment module, connected to the distance detection module, the instruction detection module, and the training character control module, respectively, for starting to continuously detect whether a first instruction exists when the distance between the training character and any obstacle reaches a first preset distance threshold, until the first instruction is detected or the training time ends, and for:

[0034] If the first instruction is detected, the training character is controlled to continue moving at the moving speed without being affected by the obstacle; if the first instruction is not detected until the distance between the training character and the obstacle is a second preset distance threshold, the moving speed of the training character is set to 0 until the first instruction is detected, and the moving speed of the training character is set again using the current attention value, so that the training character is no longer affected by the obstacle and continues to move.

[0035] In some possible implementations of the present application, the instruction detection module is further configured to identify a second instruction; the training function control module is further configured to display M target objects at intervals in the observable scene, where M ≥ 1, and during the movement of the training character, each of the target objects first approaches relatively close to the training character and then moves relatively away from the training character;

[0036] The distance detection module is further used to detect the distance between the training character and any one of the target objects.

[0037] The judgment module is further configured to continuously detect whether the second instruction exists during the entire training time and complete the following recording operations:

[0038] If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0039] If the second instruction is detected one or more times during the period when the target object is displayed but the distance between the target object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected;

[0040] If the second instruction is detected once or multiple times while the target object is displayed and the distance between the target object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error.

[0041] In some possible implementation schemes of the present application, the training function control module is further configured to display N non-target objects at intervals in the observable scene, where N ≥ 1. During the movement of the training character, each of the non-target objects is relatively close to and then relatively far away from the training character.

[0042] The judgment module is also used to complete the following records:

[0043] If the second instruction is detected one or more times during the period when the target object and the non-target object are not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0044] If the second instruction is detected one or more times during the display of the non-target object, a suppression error is recorded each time the second instruction is detected;

[0045] If the second instruction is not detected during the display of the non-target object, it is recorded that the suppression is correct.

[0046] In some embodiments of the present application, M ≥ 2, the M target objects are different, and the training function control module is used to first display the sequence of the M target objects in the observable scene for a period of time, wherein the period of time is 2 to 5 seconds, and then randomly display each target object once or multiple times, wherein the target objects displayed in sequence are sequential objects, and the target objects displayed out of sequence are non-sequential objects.

[0047] The judgment module is used to complete the following records:

[0048] If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected;

[0049] If the second instruction is detected one or more times when the sequential object is displayed but the distance between the sequential object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected;

[0050] If the second instruction is detected once or multiple times while the sequential object is displayed and the distance between the sequential object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error;

[0051] If the second instruction is detected one or more times during the display of the non-sequential object, a suppression error is recorded each time the second instruction is detected;

[0052] If the second instruction is not detected during the display of the non-sequential object, it is recorded that the suppression is correct.

[0053] The third aspect of the present application provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any attention training method described in the first aspect of the present application.

[0054] The fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions, characterized in that the computer instructions are used to enable the computer to execute the attention training method according to any one of the first aspects of the present application.

[0055] Compared with the prior art, this application has the following beneficial effects:

[0056] The methods, systems, devices, and media of this application provide targeted neurofeedback training for the three core abilities that ADHD patients need to improve: attention intensity, executive inhibition, and working memory. This can comprehensively improve the symptoms of ADHD patients and enhance their cognitive abilities.

[0057] The method, system, device and medium of the present invention have strong interactivity in brain-computer training and adopt a multi-task training paradigm, which makes up for the shortcomings of the existing technology of being single and boring, thereby allowing trainees to improve their compliance and increase the frequency of training, thereby achieving better training results.

[0058] By utilizing the methods, systems, devices, or media of this application, ADHD patients can undergo training not only in hospitals but also at home, which is more convenient, economical, and efficient. This greatly improves patient compliance with training and reduces the dropout rate midway through training, especially for school-age children and adolescents.

[0059] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The above and other objects, features and advantages of the exemplary embodiments of the present application will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present application are shown in an illustrative and non-limiting manner, in which:

[0061] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

[0062] Figure 1 A schematic diagram of a training character encountering an obstacle according to an embodiment of the present application is shown;

[0063] Figure 2 A schematic diagram of a training character encountering a target object according to an embodiment of the present application is shown;

[0064] Figure 3 A schematic diagram of a target object / non-target object that a training character encounters when entering a blind box according to one embodiment of the present application is shown.

[0065] Figure 4 A schematic diagram of an implementation process of an embodiment of the present application is shown;

[0066] Figure 5 A schematic diagram of the structure of an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0067] In order to make the purpose, features, and advantages of this application more obvious and easy to understand, 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 those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0068] This application adopts closed-loop brain-computer interface technology for attention training.

[0069] First, by wearing a wearable EEG acquisition device, the trainee's frontal lobe is collected in real time. After the neural signal is decoded by the EEG data processing module, the real-time attention value is obtained. The specific EEG data processing steps include the following steps:

[0070] 1. Data preprocessing: 1Hz-35Hz filtering.

[0071] 2. Feature extraction: Spectral analysis of EEG data is performed using Fourier transform, and the power spectral density of different frequency bands, such as delta waves (0.5-4 Hz), theta waves (4-8 Hz), alpha waves (8-13 Hz), and beta waves (13-35 Hz), is calculated.

[0072] 3. Calculate attention value: Select attention-related EEG data features (e.g., power spectral density of beta and alpha waves) and perform calculations (e.g., beta power spectral density / alpha power spectral density) to obtain the specific value Yi(t) for participant i at time t. Based on the EEG datasets of N participants in the database (e.g., 1000), Yi(t) is normalized to a value between 0 and 1. This value is then multiplied by 100 to convert to an attention value Ai(t) within the range of 0 to 100.

[0073] The attention value reflects the state of brain activity, which is closely related to attentional cognitive activities. Trainees can adjust their attention state to increase or decrease the energy proportion of each frequency band in the brain, thereby increasing or decreasing the attention value.

[0074] In this embodiment, an observable scene is provided, and a training character (a cartoon character or a cartoon animal) is provided at a position in the observable scene. The observable scene can be a scene observable to the naked eye, such as a graphical interface, or a scene observable through a tool, such as VR glasses.

[0075] Furthermore, the movement speed of the training character is set according to the obtained attention value. Furthermore, the state of the training character (including actions and expressions) is set according to the obtained attention data. Furthermore, the background music is set according to the obtained attention data, as shown in Table 1.

[0076] Table 1 Relationship between attention value and training character parameters

[0077] In one embodiment, only attention intensity training (referred to as the beginner course) is included. In the beginner course, the parameters in Table 1 are used to control the movement of the training character based on the trainee's attention score, as measured in real time. The trainee can adjust their brain activity to alter their attention score, thereby varying the speed at which the training character moves within the provided scene. In the beginner course, the longer the distance traveled within a specified timeframe (e.g., 3 minutes), the higher the score awarded. This encourages the trainee to strive to improve their attention score, thereby achieving the training objectives.

[0078] Furthermore, P obstacles will appear at intervals in front of the training character's moving route, such as Figure 1As shown, when the training character moves to a distance from an obstacle (in this embodiment, the distance is the distance between the vertical centerline of the training character and the vertical centerline of the obstacle) no greater than L1 (i.e., a first preset distance threshold), the system detects whether the trainee has issued a command (a first command). This first command can be a body movement (such as nodding, shaking the head, raising a hand, waving, clapping, clicking, pressing a key, etc.), a designated sound, or an expression. This first command is collected by a corresponding signal collector. Upon detecting the first command, the training character is controlled to perform a first action, such as jumping, hitting, punching, knocking, pushing, pulling, or kicking, to overcome or remove the obstacle. Alternatively, the obstacle can be directly moved or eliminated. If the first command is not detected, the training character stops when the distance from the obstacle reaches L2 (i.e., a second preset distance threshold) until the trainee's first command is detected. The trainee is required to maintain attention and issue the first command at the appropriate time to avoid the obstacle and allow the character to continue moving. Similarly, since the goal is to achieve a higher score the longer the distance covered within the specified time, the trainee will be more focused and issue the first command correctly at the appropriate time, thereby completing the attention intensity training.

[0079] In this embodiment, the frequency of obstacles is increased or decreased according to the average attention of the trainee. For example, the average attention of 10 seconds is counted and the frequency of obstacles is increased or decreased accordingly.

[0080] In an embodiment, the following training indicator data is obtained based on the attention data during the training process:

[0081] (1) The average attention of the trainees during the training period;

[0082] (2) The average attention, highest attention, lowest attention and / or their ratio during the training time;

[0083] (3) The proportion of the trainee's concentration time during the training period;

[0084] (4) The trainee’s maximum reaction time, minimum reaction time and / or average reaction time to obstacles avoided during the training period.

[0085] Among them, the concentration time ratio refers to the ratio of the concentration time to the training time, and concentration means that the attention value is not less than the preset attention threshold (60 in this embodiment); the reaction time refers to the time interval from when the distance between the training character and the obstacle is the first preset threshold to when the first instruction is first detected.

[0086] Among them, attention can also be represented by the movement speed of the training character.

[0087] In this embodiment, the trainee's previous training scores are first obtained to appropriately set the number of obstacles. In this case, each training session requires obtaining the trainee's identifiable information (including but not limited to registration ID, ID card, student ID number, mobile phone number, etc.). After the training session is completed, the training results are stored in the trainee's name to form a training database.

[0088] In another embodiment, in addition to the attention intensity training task, it also includes an execution training task. Specifically, M (M≥1, for example, M=3) target objects (fruits in this embodiment) are displayed at intervals in an observable scene. During the movement of the training character, the target objects move relative to the trainer from an unrestricted direction, first approaching and then moving away.

[0089] In this embodiment, it is continuously detected whether the trainee has issued a second instruction, which can also be a body movement (such as nodding, shaking head, raising hand, waving, clapping, clicking, pressing keys, etc.) or making a specified sound or expression, and the second instruction is collected by the corresponding signal collector.

[0090] After detecting the second instruction, the training character is controlled to perform a second action, such as jumping, hitting, punching, knocking, pushing, pulling, kicking, catching, touching, waving, punching, etc. to contact the target object.

[0091] If the second instruction is detected once or multiple times while the target object is not displayed (ie, the target object does not exist in the observable scene), a hyperactivity error is recorded each time it is detected, indicating that the trainee has performed redundant operations.

[0092] If the second instruction is detected once or multiple times during the period when the target object is displayed but the distance between the target object and the training character is greater than the third preset distance threshold, a response error is recorded each time the second instruction is detected.

[0093] In this embodiment, if Figure 2 As shown, a circle is drawn with the center point of the training character as the center and the third preset distance threshold (L3) as the radius. If the target object is entirely outside the circle (indicating it is not approaching or has already moved away), it means that the distance between the target object and the training character is greater than the third preset distance threshold. If the second instruction is detected at this time, it means that the trainee reacted too early or too late. There is no limit on the direction and route of the target object approaching the training character. For example, it can be Figure 2 The movement path shown by the solid line in the figure can also be the dotted line, as long as it enters the circle and leaves it. (In an extreme case, the movement path is tangent to the circle, but in this case, the training character has very limited time to react in time.) In this embodiment, the time from the target object entering the circle to leaving the circle is 2-5 seconds. The trainee must fully concentrate and issue the second command in a timely manner.

[0094] If the second instruction is detected one or more times while the target object is displayed and the distance from the training character is not greater than the third predetermined distance threshold (i.e., when the target object is within the circle), only one correct response is recorded, and each additional detection is recorded as a hyperactivity error.

[0095] In this embodiment, after a correct response is recorded, the target object is controlled to disappear or be placed in a certain area of the observable scene.

[0096] For the target object, if a correct response is recorded, the response time is also recorded. The response time refers to the time from when the target object contacts the circle to when the second instruction is first detected.

[0097] In this embodiment, the second instruction is the same as or different from the first instruction. When the second instruction is the same as the first instruction, the presence of the instruction (the first instruction and the second instruction are collectively referred to as the instruction) is continuously detected throughout the training process. If there is an obstacle in the observable scene, a hyperactivity error is recorded only when the instruction is detected while the distance between the training character and the obstacle is greater than L1.

[0098] In this embodiment, the trainee is required to concentrate on observing the positions of the training character and the target object, and issue the second instruction at the appropriate time to try to get a correct response, and try to avoid response errors and hyperactivity errors, so as to achieve the training effect of improving attention.

[0099] At the end of the training, the number of correct responses, incorrect responses, and hyperactivity errors were counted, and the correct response rate was calculated: correct response rate = number of correct responses / (number of correct responses + number of incorrect responses) × 100%.

[0100] In another embodiment, in addition to the attention intensity training task and the execution training task, an inhibition training task (or intermediate course) is also included. In this embodiment, the three tasks are carried out simultaneously. The attention intensity training task and the execution training task are the same as described above. The inhibition training task is as follows:

[0101] N (N≥1, for example, N=3) non-target objects (in this embodiment, any object other than fruit, such as a folder, etc.) are also displayed at intervals in the observable scene. The non-target objects also move relative to the trainee from an unrestricted direction, first approaching and then moving away.

[0102] If the second instruction is detected one or more times during a period when the target object and the non-target object are not displayed (at this time, neither the first target object nor the non-target object exists in the observable scene), a hyperactivity error is recorded each time the second instruction is detected;

[0103] The command record during the target object display is the same as above. For non-target objects:

[0104] If the second instruction is detected one or more times during the display of the non-target object, a suppression error is recorded each time it is detected;

[0105] If the second instruction is not detected during the display of the non-target object, it is recorded that the suppression is correct.

[0106] At the end of the training, the number of correct inhibitions and the number of incorrect inhibitions were counted, and the correct inhibition rate was calculated, which was the correct inhibition rate = the number of correct inhibitions / (the number of correct inhibitions + the number of incorrect inhibitions) × 100%.

[0107] In this embodiment, if Figure 3 As shown, whether it is a target object or a non-target object, when its distance from the above circle on the movement path is greater than the fourth preset distance threshold (L4), it enters the observable scene in the form of a blind box. Only when the distance from the target object or non-target object on the movement path begins to be less than L4 from the above circle will it be displayed as a target object or non-target object. The fourth preset distance is calculated in real time based on the relative speed and path of the training character and / or (non-) target object. When the target object or non-target object moves on the movement path, the distance from the time it takes for it to leave the above circle at the real-time calculated relative speed is set to L4. In other words, the target object or non-target object is only displayed when it is only 1.5 seconds away from leaving the circle. In this case, the trainee needs to react quickly within a limited time, so he must concentrate, which can further improve the training effect.

[0108] In this embodiment, the correct response rate and / or correct inhibition rate of the trainee in previous training is first obtained, and during this training process, the number of target objects (for example, M+1) and / or the number of non-target objects (for example, N+1) are increased to achieve the goal of increasing the difficulty of training. This process is repeated to continuously improve the training effect.

[0109] In yet another embodiment, suppression training tasks are included or not included, and upgraded execution training tasks are also included.

[0110] In the upgraded execution training task, M (M≥2) target objects are different (for example, 3 different fruits, apple, banana and pineapple in order). First, 3 fruits arranged in order are displayed in the observable scene (the presentation time is limited, for example, 3 seconds), and then each target object is randomly displayed once or multiple times. The target objects displayed in order are called sequential objects, and the target objects displayed out of order are called non-sequential objects.

[0111] In this scenario, if there is no target object (either sequential or non-sequential) in the observable scene, and no non-target object (if an inhibition training task is also included), a hyperactivity error is recorded each time the second instruction is detected;

[0112] The command record during the display of sequential objects is the same as that of target objects, and the command record during the display of non-sequential objects is the same as that of non-target objects, that is:

[0113] If the second instruction is detected once or multiple times when the distance between the sequential object and the training character is greater than the third preset distance threshold, a response error is recorded each time the second instruction is detected;

[0114] If the second instruction is detected once or multiple times while the distance between the sequential object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error;

[0115] If the second instruction is detected one or more times during the display of the non-sequential object, a suppression error is recorded each time it is detected;

[0116] If the second instruction is not detected during the display of the non-sequential object, it is recorded that the suppression is correct.

[0117] In this scenario, the trainee needs to rely on working memory to remember the target objects and their order. For sequential objects, the trainee needs to send a second instruction at the appropriate time. For non-sequential objects and non-target objects, the trainee needs to control not to send a second instruction, thereby further improving the trainee's attention.

[0118] In this embodiment, regardless of whether the target object appears in sequence or not, when its distance from the circle on its movement path exceeds a fourth preset distance threshold (L4), it enters the observable scene as a blind box. Only when the distance from the circle on its movement path begins to fall below L4 does it appear in its true form. In this case, the trainee needs to react quickly within a limited time.

[0119] At the end of the training, the number of correct responses and the number of incorrect responses were counted and the correct response rate was calculated. Correct response rate = number of correct responses / (number of correct responses + number of incorrect responses) × 100%.

[0120] If the inhibition training task is included, the number of correct inhibitions and the number of incorrect inhibitions are also counted, and the correct inhibition rate is calculated, which is the correct inhibition rate = the number of correct inhibitions / (the number of correct inhibitions + the number of incorrect inhibitions) × 100%.

[0121] In one embodiment, the attention training task, the upgraded executive training task, and the inhibition training task are referred to as a working memory training task (or advanced course).

[0122] In this embodiment, the correct response rate and correct inhibition rate of the trainee in previous training are first obtained, and during this training process, the number of target objects (for example, M+1) and / or the number of non-target objects (for example, N+1) are increased to achieve the goal of increasing the difficulty of training. This process is repeated to continuously improve the training effect.

[0123] In one embodiment of the present application, only one object (blind box, target object, or non-target object) is displayed in the observable scene at a time. The subsequent object is displayed in the observable scene only after the previous object disappears from the observable scene. Furthermore, if the first instruction and the second instruction are the same, the obstacle is not displayed simultaneously with the blind box, target object, or non-target object.

[0124] In some embodiments of the present application, using Figure 4 The training process is as follows:

[0125] S1, real-time EEG data acquisition

[0126] The C / S system architecture that combines a wearable EEG data collector based on a brain-computer interface, a mobile terminal (tablet or smartphone), and a server is used to collect the trainee's EEG signal data in real time.

[0127] S2, EEG data processing

[0128] S21, data preprocessing: 1Hz-35Hz filtering;

[0129] S22, feature extraction: Spectral analysis of EEG data was performed using Fourier transform, and the power spectral density of different frequency bands of alpha waves (8-13 Hz) and beta waves (13-35 Hz) was calculated;

[0130] S23, Calculation of Attention Value: Select attention-related EEG data features (e.g., the power spectral density of beta and alpha waves) and calculate (beta power spectral density / alpha power spectral density) to obtain the specific value Y(t) for the trainee at time t. Based on the EEG datasets of N trainees in the database (e.g., 1000), Y(t) is normalized to a value between 0 and 1, then amplified by 100 times to convert it into an attention value A(t) within the range of [0, 100].

[0131] S3, EEG biofeedback therapy, includes three courses: beginner course, intermediate course and advanced course. All courses include attention intensity training tasks, including

[0132] The primary course consisted only of attention intensity training tasks;

[0133] In addition to attention intensity training tasks, the intermediate course also includes executive training tasks and further inhibition training tasks. The executive training tasks and inhibition training tasks are collectively referred to as executive inhibition training tasks.

[0134] In addition to attention intensity training tasks, advanced courses also include upgraded executive training tasks, further executive training tasks, and further inhibition training tasks. The upgraded executive training tasks and inhibition training tasks are collectively called working memory training tasks.

[0135] An embodiment of the present application also provides an electronic device and a readable storage medium.

[0136] Figure 5 A schematic block diagram of an example electronic device 800 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0137] like Figure 5 As shown, device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. RAM 803 may also store various programs and data required for the operation of device 800. Computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to bus 804.

[0138] Various components in device 800 are connected to I / O interface 805, including an input unit 806, such as a keyboard, mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0139] The computing unit 801 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the attention training method described above. For example, in some embodiments, the attention training method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the attention training method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the attention training method via any other suitable means (e.g., via firmware).

[0140] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow charts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0142] In the context of this application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0144] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0145] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0146] The system, device or medium of the present application is based on real-time EEG data and can be used in conjunction with a wearable EEG data collector.

[0147] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved. This is not a limitation herein.

[0148] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for attention training based on brain-computer interface, characterized in that: The following steps are involved: Obtain the EEG signal data of the trainee measured in real time based on the brain-computer interface, perform 1Hz~35Hz filtering, and convert the EEG signal data into attention value. Providing a training character and an observable scene, wherein the training character is at a certain position in the observable scene, and a movement speed of the training character is set according to the attention value, and the training character moves relatively in the observable scene along a movement route at the movement speed; P obstacles are set on the movement route of the training character, where P≥1. When the distance between the training character and any one of the obstacles reaches a first preset distance threshold, continuous detection of whether a first instruction exists begins until the first instruction is detected or the training time ends. If the first instruction is detected, the training character continues to move at the moving speed without being affected by the obstacle; If the first instruction is not detected until the distance between the training character and the obstacle reaches a second preset distance threshold, the movement speed of the training character is set to 0 until the first instruction is detected, and the movement speed of the training character is re-set using the current attention value so that the training character is no longer affected by the obstacle and continues to move.

2. The attention training method according to claim 1, characterized in that: During the entire training time, continuously detecting whether there is a second instruction, displaying M target objects at intervals in the observable scene, M ≥ 1, and during the movement of the training character, each of the target objects first relatively approaches the training character and then relatively moves away from the training character; If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected; If the second instruction is detected one or more times during the period when the target object is displayed but the distance between the target object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected; If the second instruction is detected once or multiple times while the target object is displayed and the distance between the target object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error.

3. The attention training method according to claim 2, characterized in that: N non-target objects are also displayed at intervals in the observable scene, where N≥1. During the movement of the training character, each of the non-target objects is relatively close to and then relatively far away from the training character. If the second instruction is detected one or more times during the period when the target object and the non-target object are not displayed, a hyperactivity error is recorded each time the second instruction is detected; If the second instruction is detected one or more times during the display of the non-target object, a suppression error is recorded each time the second instruction is detected; If the second instruction is not detected during the display of the non-target object, it is recorded that the suppression is correct.

4. The attention training method according to claim 2 or 3, characterized in that: M≥2, the M target objects are different, the M target objects are first displayed in sequence in the observable scene for a period of time, the period of time being 2-5 seconds, and then each target object is randomly displayed once or multiple times, wherein the target objects displayed in sequence are sequential objects, and the target objects displayed out of sequence are non-sequential objects, If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected; If the second instruction is detected one or more times when the sequential object is displayed but the distance between the sequential object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected; If the second instruction is detected once or multiple times while the sequential object is displayed and the distance between the sequential object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error; If the second instruction is detected one or more times during the display of the non-sequential object, a suppression error is recorded each time the second instruction is detected; If the second instruction is not detected during the display of the non-sequential object, it is recorded that the suppression is correct.

5. The attention training method according to any one of claims 1 to 3, characterized in that: In step S2, the EEG signal data is subjected to spectrum analysis by Fourier transform, and the power spectrum density of different frequency bands is calculated, and the attention value is further obtained based on the power spectrum density.

6. An attention training system based on brain-computer interface, characterized in that: Includes the following modules: The EEG signal data receiving and processing module is used to receive the EEG signal data of the trainee measured in real time based on the brain-computer interface, and convert the EEG signal data into attention value after filtering at 1Hz~35Hz. The visualization module is used to provide a training character and an observable scene, wherein the training character is at a certain position in the observable scene. a training character control module, connected to the EEG signal data receiving and processing module and the visualization module, for setting a movement speed of the training character according to the attention value, wherein the training character moves relatively in the observable scene along a movement route at the movement speed; The training function control module is used to set P obstacles in front of the moving direction of the training character, where P≥1. A distance detection module is used to detect the distance between the training character and any of the obstacles. An instruction recognition module, configured to recognize a first instruction; a judgment module, connected to the distance detection module, the training function control module, the instruction detection module, and the training character control module, respectively, for starting to continuously detect whether a first instruction exists when the distance between the training character and any obstacle reaches a first preset distance threshold, until the first instruction is detected or the training time ends, and for: If the first instruction is detected, the training character is controlled to continue moving at the moving speed without being affected by the obstacle; if the first instruction is not detected until the distance between the training character and the obstacle is a second preset distance threshold, the moving speed of the training character is set to 0 until the first instruction is detected, and the moving speed of the training character is set again using the current attention value, so that the training character is no longer affected by the obstacle and continues to move.

7. The attention training system according to claim 6, characterized in that: The instruction detection module is further configured to identify a second instruction; the training function control module is further configured to display M target objects at intervals in the observable scene, where M ≥ 1, and during the movement of the training character, each of the target objects first approaches the training character relatively and then moves away relatively; The distance detection module is further used to detect the distance between the training character and any one of the target objects. The judgment module is further configured to continuously detect whether the second instruction exists during the entire training time and complete the following recording operations: If the second instruction is detected one or more times during the period when the target object is not displayed, a hyperactivity error is recorded each time the second instruction is detected; If the second instruction is detected one or more times during the period when the target object is displayed but the distance between the target object and the training character is greater than a third preset distance threshold, a response error is recorded each time the second instruction is detected; If the second instruction is detected once or multiple times while the target object is displayed and the distance between the target object and the training character is not greater than the third preset distance threshold, only one correct response is recorded, and each additional detection is recorded as a hyperactivity error.

8. The attention training system according to claim 7, characterized in that: The training function control module is further configured to display N non-target objects at intervals in the observable scene, where N≥1. During the movement of the training character, each of the non-target objects is relatively close to and then relatively far away from the training character. The judgment module is also used to complete the following records: If the second instruction is detected one or more times during the period when the target object and the non-target object are not displayed, a hyperactivity error is recorded each time the second instruction is detected; If the second instruction is detected one or more times during the display of the non-target object, a suppression error is recorded each time the second instruction is detected; If the second instruction is not detected during the display of the non-target object, it is recorded that the suppression is correct.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the attention training method according to any one of claims 1 to 5.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable the computer to execute the attention training method according to any one of claims 1 to 5.

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