Method and device for monitoring concentration linkage corresponding training game based on electroencephalogram

Abstract

The invention discloses a method and device for linkage of corresponding training games based on electroencephalogram monitoring concentration, and the method comprises the following steps: S1, a user wears a wearable brain wave collection device with a plurality of electrodes to ensure that the electrodes are in close contact with the scalp so as to reduce signal noise; the wearable brain wave acquisition device acquires brain wave signals of a user in real time; s2, performing amplification and filtering preprocessing operation on the brain wave signals acquired in the S1 so as to improve the signal quality. According to the method, the brain wave data of the user is collected and analyzed in real time, the corresponding training game is combined, a customized personalized concentration training scheme is provided for the user, the interest of children is improved through a personalized training mode and game participation, then the participation degree and the training effect of the children are improved, and therefore the concentration level of the user is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of concentration training, and particularly to a method and device for a concentration-linked corresponding training game based on electroencephalogram monitoring. Background Art

[0002] In modern society, the problem of concentration has become an important factor affecting people's study and life. Especially for children with attention deficit hyperactivity disorder (ADHD) or ordinary children with low concentration, in order to improve children's concentration, it is necessary to train their concentration. However, traditional concentration training methods have the defects of slow training effect, low training personalization, and boring training content, and children are not willing to participate in the training. Therefore, we propose a method and device for a concentration-linked corresponding training game based on electroencephalogram monitoring. Summary of the Invention

[0003] Based on the technical problems existing in the background art, the present invention proposes a method and device for a concentration-linked corresponding training game based on electroencephalogram monitoring.

[0004] A method for a concentration-linked corresponding training game based on electroencephalogram monitoring proposed by the present invention includes the following steps:

[0005] S1: The user wears a wearable electroencephalogram acquisition device with multiple electrodes, ensuring that the electrodes are in close contact with the scalp to reduce signal noise, and the wearable electroencephalogram acquisition device continuously acquires the user's electroencephalogram signals;

[0006] S2: Perform amplification and filtering preprocessing operations on the electroencephalogram signals acquired in S1 to improve the signal quality;

[0007] S3: Divide the preprocessed signals into different frequency bands, such as Delta (0.5 - 4 Hz), Theta (4 - 8 Hz), Alpha (8 - 12 Hz), and Beta (12 - 35 Hz), etc., and extract key features within each frequency band, such as power spectral density, peak frequency, etc., to evaluate the user's attention level;

[0008] S4: According to the extracted electroencephalogram features, use a preset evaluation algorithm to calculate the user's concentration level, and display the evaluation result to the user in the form of a numerical value, chart, or grade, providing an intuitive feedback on the concentration state;

[0009] S5: According to the user's concentration evaluation result, combine a preset training algorithm and model to generate a personalized training plan. The plan includes specific training tasks and parameters of the training duration, set training goals, and display the generated training plan to the user through a display screen to ensure that the user clearly understands the training content and requirements;

[0010] S6: The user trains according to the training plan, and the user's brain wave signals are monitored in real time during training. According to the changes in brain waves during training, the training plan can be adjusted or additional guidance can be provided;

[0011] S7: During the training process, the corresponding training feedback is given instantly according to the user's brain wave data. According to the user's feedback and training effect, the training plan is personalized and optimized to improve the training effect and user experience.

[0012] Preferably, in S1, the electrodes on the wearable brainwave acquisition device are 8-lead, 20-lead or more, and the wearable brainwave acquisition device supports Bluetooth or Wi-Fi connection, the sampling rate of the wearable brainwave acquisition device is 256Hz, 512Hz or higher, and shielding technology is used or non-metallic electrodes are contained during the sampling process to reduce external interference.

[0013] Preferably, in S2, when pre-processing the brain wave signal, ICA (independent component analysis) or other algorithms are used to remove artifacts in the signal, such as eye movements, muscle activities, etc.

[0014] Preferably, in S5, the training task is game training, and the games are sorted from low to high according to the concentration level, such as games with a concentration level of 70 to 70, and concentration is trained through games.

[0015] Preferably, in S5, the training objectives include improving the user's concentration, reducing the number of distractions, etc.

[0016] Preferably, in S7, the feedback form includes sound prompts, vibration alerts or reward signals, and the feedback content may involve key information about the user's concentration and number of distractions.

[0017] The present invention also proposes a device for linking corresponding training games based on EEG monitoring of concentration, including an EEG acquisition module, a signal processing module, a concentration evaluation module, a training program generation module, a user feedback module, a program adjustment module and a game matching module;

[0018] The training program generation module is connected to the user feedback module, the concentration evaluation module, the program adjustment module and the game matching module, and the signal processing module is connected to the brain wave acquisition module and the concentration evaluation module.

[0019] Preferably, the brain wave acquisition module acquires the user's brain wave signals in real time through a wearable brain wave acquisition device, and the wearable brain wave acquisition device includes multiple electrodes that can cover different areas of the brain to obtain comprehensive brain wave data;

[0020] The signal processing module is used to preprocess, extract features and classify and identify the collected electroencephalogram (EEG) signals. It improves the clarity and accuracy of the signals through amplification and filtering steps, and extracts key information related to concentration, such as the EEG activity in different frequency bands.

[0021] The concentration assessment module is used to evaluate the user's concentration level according to the key information extracted by the signal processing module. The evaluation results are presented in the form of numerical values, charts or grades, providing the user with an intuitive feedback on the concentration state.

[0022] The training plan generation module generates a personalized concentration training plan according to the user's attention evaluation results, in combination with preset training algorithms and models, and also in combination with the game matching module. The training plan may include parameters such as specific training tasks and training durations, and its training tasks are game-based trainings.

[0023] The plan adjustment module can adjust the training plan or provide additional guidance according to the changes in the EEG during the training process.

[0024] The user feedback module is used to give corresponding training feedback immediately according to the user's EEG data, and optimize the training plan personalized according to the user's feedback and training effects.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0026] 1. By collecting and analyzing the user's EEG data in real time, a personalized concentration training plan is provided for the user. And according to the EEG characteristics of different people, the training content and difficulty can be adjusted to improve the degree of training personalization, and the training effect is improved through the personalized training method.

[0027] 2. By linking corresponding training games as the training plan, the interest of children is increased, and children are more willing to participate in the training, thereby further improving the training effect.

[0028] The present invention provides a personalized concentration training plan for the user by collecting and analyzing the user's EEG data in real time and combining corresponding training games. Through the personalized training method and the participation in games, the interest of children is increased, and then the participation degree and training effect of children are improved, thereby effectively improving the user's concentration level. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a flowchart of a method for monitoring concentration based on EEG and linking corresponding training games proposed by the present invention;

[0030] Figure 2 is a system block diagram of a device for monitoring concentration based on EEG and linking corresponding training games proposed by the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further explained below in conjunction with specific embodiments.

[0032] Example

[0033] Reference Figure 1-2 This embodiment proposes a method for linking a corresponding training game based on EEG monitoring of concentration, including the following steps:

[0034] S1: The user wears a wearable EEG acquisition device with multiple electrodes to ensure that the electrodes are in close contact with the scalp to reduce signal noise. The wearable EEG acquisition device collects the user's EEG signals in real time;

[0035] The electrodes on the wearable EEG collection device are 8-lead, 20-lead or more, and the wearable EEG collection device supports Bluetooth or Wi-Fi connection. The sampling rate of the wearable EEG collection device is 256 Hz, 512 Hz or higher, and shielding technology is used or non-metallic electrodes are contained during the sampling process to reduce external interference;

[0036] S2: amplify and filter the EEG signals collected in S1 to improve signal quality. When preprocessing the EEG signals, ICA (independent component analysis) or other algorithms are used to remove artifacts in the signals, such as eye movements, muscle activities, etc.;

[0037] S3: Divide the preprocessed signal into different frequency bands, such as Delta (0.5-4Hz), Theta (4-8Hz), Alpha (8-12Hz) and Beta (12-35Hz), and extract key features in each frequency band, such as power spectrum density and peak frequency, to evaluate the user's attention level;

[0038] S4: Calculate the user's concentration level based on the extracted brain wave features using a preset evaluation algorithm, and present the evaluation results to the user in the form of numerical values, charts or levels, providing intuitive feedback on the concentration status;

[0039] S5: Generate a personalized training plan based on the user's concentration evaluation results, combined with the preset training algorithm and model. The plan includes specific training tasks and training duration parameters. The training task is game training, and the games are sorted from low to high according to the concentration level, such as games with a concentration level of 70 and a match level of 70. Concentration is trained through games.

[0040] Set training goals, including improving user concentration, reducing distraction, etc. The generated training plan is displayed to the user through the display screen to ensure that the user is clear about the training content and requirements;

[0041] S6: The user conducts training according to the training plan. During the training, the user's electroencephalogram (EEG) signals are monitored in real time. Based on the changes in the EEG during the training, the training plan can be adjusted or additional guidance can be provided.

[0042] S7: During the training process, corresponding training feedback is given immediately according to the user's EEG data. The feedback forms include sound prompts, vibration alerts, or reward signals. The feedback content can involve key information such as the user's concentration level and the number of distractions. According to the user's feedback and training effect, the training plan is optimized personalized to improve the training effect and user experience.

[0043] This embodiment also proposes a device for a concentration-linked corresponding training game based on EEG monitoring, including an EEG acquisition module, a signal processing module, a concentration assessment module, a training plan generation module, a user feedback module, a plan adjustment module, and a game matching module.

[0044] Among them, the EEG acquisition module collects the user's EEG signals in real time through a wearable EEG acquisition device. The wearable EEG acquisition device contains multiple electrodes that can cover different regions of the brain to obtain comprehensive EEG data.

[0045] The signal processing module is used to preprocess, extract features, and classify and identify the collected EEG signals. Through amplification and filtering steps, the clarity and accuracy of the signals are improved, and key information related to concentration, such as the EEG activity in different frequency bands, is extracted.

[0046] The concentration assessment module is used to evaluate the user's concentration level based on the key information extracted by the signal processing module. The evaluation results are presented in the form of numerical values, charts, or grades, providing the user with an intuitive feedback on the concentration state.

[0047] The training plan generation module is connected to the user feedback module, the concentration assessment module, the plan adjustment module, and the game matching module. The signal processing module is connected to the EEG acquisition module and the concentration assessment module.

[0048] The training plan generation module generates a personalized concentration training plan according to the user's attention assessment results, in combination with a preset training algorithm and model, and at the same time in combination with the game matching module. The training plan may include parameters such as specific training tasks and training durations. The training task is game training. The plan adjustment module can adjust the training plan or provide additional guidance based on the changes in the EEG during the training process.

[0049] The user feedback module is used to give corresponding training feedback immediately according to the user's EEG data, and optimize the training plan personalized according to the user's feedback and training effect.

[0050] This embodiment provides a customized and personalized concentration training plan for users by collecting and analyzing the user's brain wave data in real time and combining corresponding training games. Through personalized training methods and participation in games, it can improve children's interest, and then enhance children's participation and training effects, thereby effectively improving the user's concentration level.

[0051] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention should cover equivalent substitutions or changes made according to the technical solution and inventive concept of the present invention within the protection scope of the present invention.

Claims

1. A method for linking a corresponding training game based on EEG monitoring of concentration, characterized in that: The following steps are involved: S1: The user wears a wearable EEG acquisition device with multiple electrodes to ensure that the electrodes are in close contact with the scalp to reduce signal noise. The wearable EEG acquisition device collects the user's EEG signals in real time; S2: amplify and filter the brain wave signals collected in S1 to improve signal quality; S3: Divide the preprocessed signal into different frequency bands and extract key features in each frequency band to evaluate the user's attention level; S4: Calculate the user's concentration level based on the extracted brain wave features using a preset evaluation algorithm, and present the evaluation results to the user in the form of numerical values, charts or levels, providing intuitive feedback on the concentration status; S5: Generate a personalized training plan based on the user's concentration assessment results, combined with the preset training algorithm and model. The plan includes specific training tasks and training duration parameters, sets training goals, and displays the generated training plan to the user through the display screen to ensure that the user is clear about the training content and requirements; S6: The user trains according to the training plan, and the user's brain wave signals are monitored in real time during training. According to the changes in brain waves during training, the training plan can be adjusted or additional guidance can be provided; S7: During the training process, the corresponding training feedback is given instantly according to the user's brain wave data. According to the user's feedback and training effect, the training plan is personalized and optimized to improve the training effect and user experience.

2. The method of claim 1, characterized in that: In S1, the electrodes on the wearable brainwave acquisition device are 8-lead, 20-lead or more, and the wearable brainwave acquisition device supports Bluetooth or Wi-Fi connection. The sampling rate of the wearable brainwave acquisition device is 256 Hz, 512 Hz or higher, and shielding technology is used or non-metallic electrodes are contained during the sampling process to reduce external interference.

3. The method of claim 1, wherein: In S2, when preprocessing the brain wave signal, ICA or other algorithms are used to remove artifacts in the signal.

4. The method of claim 1, wherein: In S5, the training task is game training, and the games are sorted from low to high according to the concentration level.

5. The method of claim 1, wherein: In the S5, the training objectives include improving the user's concentration and reducing the number of distractions.

6. The method of claim 1, wherein: In the S7, the feedback form includes sound prompts, vibration alerts or reward signals, and the feedback content may involve key information about the user's concentration and the number of distractions.

7. A device based on EEG monitoring of concentration linked to corresponding training games, used to implement the method described in any one of claims 1 to 6, characterized in that: It includes brain wave acquisition module, signal processing module, concentration assessment module, training program generation module, user feedback module, program adjustment module and game matching module; The training program generation module is connected to the user feedback module, the concentration evaluation module, the program adjustment module and the game matching module, and the signal processing module is connected to the brain wave acquisition module and the concentration evaluation module.

8. The device according to claim 7, characterized in that: The brain wave acquisition module collects the user's brain wave signals in real time through a wearable brain wave acquisition device. The wearable brain wave acquisition device includes multiple electrodes that can cover different areas of the brain to obtain comprehensive brain wave data; The signal processing module is used to pre-process, extract features and classify the collected brain wave signals, improve the clarity and accuracy of the signals through amplification and filtering steps, and extract key information related to concentration; The concentration evaluation module is used to evaluate the user's concentration level based on the key information extracted by the signal processing module, and the evaluation result is displayed in the form of numerical values, charts or levels to provide the user with intuitive concentration status feedback; The training program generation module generates a personalized concentration training program based on the user's attention evaluation results, combined with a preset training algorithm and model, and combined with a game matching module. The training program may include specific training tasks and training duration parameters, and the training task is game training; The program adjustment module can adjust the training program or provide additional guidance according to the changes in brain waves during the training process; The user feedback module is used to give corresponding training feedback in real time according to the user's brain wave data, and to perform personalized optimization on the training program according to the user's feedback and training effect.

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