Bidirectional emotion interaction and intervention method based on electroencephalogram

Abstract

The invention provides a bidirectional emotion interaction and intervention method based on electroencephalogram. The two-way emotion interaction and intervention method based on the electroencephalogram comprises an electroencephalogram signal two-way emotion interaction system and an intervention system, according to the electroencephalogram bidirectional emotion interaction system, a closed-loop structure of'emotion recognition-bidirectional interaction-personalized intervention 'is constructed by adding a bidirectional emotion transmission module and a personalized intervention module on the basis of a traditional unidirectional emotion recognition structure. According to the electroencephalogram-based bidirectional emotion interaction and intervention method provided by the invention, by realizing real bidirectional emotion interaction, the limitation of unidirectional monitoring can be overcome, the emotion synchronization problem in a remote interaction scene can be effectively solved, emotion connection can be enhanced, and the practical value of application can be improved by constructing a recognition-feedback-regulation closed-loop system; and the interactivity and the care degree among the users can be enhanced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of brain-computer interface, and particularly relates to a two-way emotional interaction and intervention method based on electroencephalogram. BACKGROUND

[0002] As a non-invasive neural signal monitoring technology with high time resolution, electroencephalogram (EEG) has been widely used in the fields of neuroscience, clinical diagnosis and human-computer interaction. With the popularity of wearable EEG devices and the development of artificial intelligence algorithms, the application of EEG signals in emotion recognition has gradually become a research hotspot.

[0003] The prior art usually collects EEG signals through a portable EEG sensor, pre-processes and extracts features, and then classifies them using machine learning or deep learning models to identify user emotions (such as joy, sadness, anxiety, calmness, etc.), which shows certain potential in psychological state monitoring, human-computer interaction optimization and assisted medical treatment.

[0004] However, the existing system still has deficiencies, most of which only recognize and display single user emotions, with the user in a passive state, lacking two-way interaction, and it is difficult to pass emotions to others or obtain real-time feedback. In remote or remote scenarios, the system cannot realize real-time perception and synchronization of emotions between individuals, and emotional communication is limited. At the same time, these applications are mostly limited to scientific research or specific clinical environments, and it is difficult to expand to daily life or team collaboration scenarios, and there is also a lack of a closed-loop solution that combines emotion recognition and improving individual happiness and interpersonal relationship quality, so it is necessary to provide a new two-way emotional interaction and intervention method based on electroencephalogram to solve the above technical problems. SUMMARY

[0005] The technical problem solved by the application is to provide a two-way emotional interaction and intervention method based on electroencephalogram that can overcome the limitations of one-way monitoring, effectively solve the emotional synchronization problem in remote interaction scenarios, enhance emotional connection, and improve the practical value of the application by building a closed-loop system of "recognition-feedback-regulation", and also enhance the interactivity and caring degree between users.

[0006] To solve the above technical problems, the two-way emotional interaction and intervention method based on electroencephalogram provided by the application comprises: an electroencephalogram signal two-way emotional interaction system, which is constructed by adding a two-way emotional transmission module and a personalized intervention module to the traditional one-way emotion recognition structure to form a closed-loop structure of "emotion recognition-two-way interaction-personalized intervention". The brain electrical signal bidirectional emotion interaction system comprises a brain electrical signal acquisition module, a data processing and emotion recognition module, a bidirectional emotion interaction module and a personalized intervention module.

[0007] As a further scheme of the present application, the data processing and emotion recognition module is integrated in each user terminal device, and the module logically comprises a signal preprocessing unit, a frequency domain feature extraction unit and an emotion recognition unit, the signal preprocessing unit is used for performing preprocessing operations such as filtering, artifact removal and baseline correction.

[0008] As a further scheme of the present application, the frequency domain feature extraction unit is used for extracting frequency domain, time domain or time-frequency domain features such as alpha, beta, theta and gamma band powers and related emotional biomarkers, the emotion recognition unit maps the EEG features to emotion classification labels based on machine learning or deep learning algorithms, and the output end of the unit is connected with the bidirectional emotion interaction module and the personalized intervention module, which functions in real-time processing and analysis of the received signals to output quantitative scores or classification labels representing the user's emotional state.

[0009] As a further scheme of the present application, the bidirectional emotion interaction module is deployed on the user terminal device and realizes communication between users through a network (especially suitable for off-site scenarios).

[0010] As a further scheme of the present application, the bidirectional emotion interaction module comprises an emotion visualization unit and an emotion feedback unit, the input ends of which are connected with the data processing and emotion recognition module for receiving emotion recognition results, and the core function of the module is to transmit and display the emotional state data of the first user to the second user in real time, and transmit and display the emotional state data of the second user to the first user, thereby forming a closed-loop interaction and solving the one-way and fragmented problem of emotional communication in the prior art.

[0011] As a further scheme of the present application, the personalized intervention module is deployed on the user terminal device, the input end of which is connected with the data processing and emotion recognition module, and the control output end thereof can communicate with local software functions or external hardware control systems, the module is used for automatically triggering or recommending intervention schemes to the user according to the received emotion recognition results when preset conditions are met.

[0012] As a further scheme of the present application, the local software functions include but are not limited to breathing training guides in the APP, and the external hardware control systems include but are not limited to smart speakers and smart lights.

[0013] As a further aspect of the present invention, the personalized intervention module also includes a remote interactive intervention function, which allows a second user to send an intervention request to a first user through their terminal device. For example, when the first user is observed to be in a bad mood, the intervention operation is only executed by the first user's intervention module after the first user has given explicit consent and clicked to confirm. This can realize a closed-loop intervention of "identification-feedback-adjustment" while significantly enhancing the care and interaction between users.

[0014] As a further aspect of the present invention, the bidirectional emotion interaction system for EEG signals implements a bidirectional emotion interaction method, which specifically includes the following steps: Step 1: Signal Acquisition. The first and second users can be in the same location or in different locations, each wearing an EEG signal acquisition headband. The system will collect their EEG signals in real time. Step 2: Processing and Recognition. The collected raw EEG signals are transmitted to the data processing and emotion recognition module. The module performs preprocessing and feature extraction on each signal independently, and uses the emotion recognition unit to output data representing the user's current emotional state in real time. Step 3: Two-way interaction and synchronization. The two-way emotion interaction module is started and executed, sending the first user's emotional state data (generated in step 2) to the second user's terminal device and displaying it through the emotion visualization unit. At the same time, the second user's emotional state data is sent back to the first user's terminal device and displayed through the emotion visualization unit. This step realizes real-time sharing and two-way synchronization of emotional information. Step Four: Intervention and Adjustment, as detailed below: (1) The personalized intervention module continuously monitors the user's emotional state. When the preset conditions are met, the system automatically executes or recommends an intervention plan. (2). The second user can observe the emotional state of the first user through the two-way emotion interaction module and can actively trigger an intervention request. After the request is sent to the first user's terminal device and the user confirms and agrees, the first user's personalized intervention module starts the corresponding intervention plan to assist the user in emotional regulation.

[0015] As a further aspect of the present invention, the preset conditions include, but are not limited to, an emotion score below a threshold or being triggered by the user.

[0016] Compared with related technologies, the EEG-based bidirectional emotion interaction and intervention method provided by this invention has the following beneficial effects: 1. This invention, by setting up a "two-way emotion interaction module," enables the first user and the second user to send, receive, and visualize each other's emotional states simultaneously, fundamentally overcoming the problems of one-way emotional communication and fragmented feedback in traditional solutions, and upgrading the system from a "passive monitoring tool" to an "active emotion interaction medium." 2. The two-way interactive architecture of the present invention is based on network communication design, which can transmit emotional data in real time between terminals in different geographical locations. As a result, long-distance couples, parents and children or remote team members can instantly perceive each other's emotional fluctuations, achieve cross-regional emotional synchronization, and significantly improve the emotional resonance and interaction quality in remote communication. 3. By introducing a "personalized intervention module," this invention links emotion recognition results with multimodal intervention strategies such as music, breathing rhythm, and light regulation to form a complete closed-loop emotion regulation system. This enables the device not only to "discover problems" but also to proactively "solve problems," significantly expanding its application scenarios in health management, psychological assistance, and intimate relationship maintenance. 4. This invention, through its unique "remote interactive intervention function," allows one user to proactively trigger intervention measures for another user with the other's authorization. This enables the intervention behavior to not only be executed automatically by the system but also to serve as a means for users to convey care, comfort, or emotional support. This function can further enhance the system's humanistic care attributes and has positive social benefits in promoting the maintenance of close relationships, parent-child interaction, and remote companionship. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0018] Fig. 1 This is a structural block diagram of the two-way emotion interaction system for electrical signals of the present invention; Fig. 2 This is a schematic diagram of the operation process of the two-way emotion interaction system for EEG signals of the present invention; Fig. 3 This is a logical diagram of the data processing and emotion recognition module in this invention. Detailed Implementation

[0019] Please refer to the following: Figs. 1 to 3 ,in, Fig. 1 This is a structural block diagram of the two-way emotion interaction system for electrical signals of the present invention; Fig. 2 This is a schematic diagram of the operation process of the two-way emotion interaction system for EEG signals of the present invention; Fig. 3This is a logical diagram of the data processing and emotion recognition module in this invention. The EEG-based bidirectional emotion interaction and intervention method includes: an EEG signal bidirectional emotion interaction system, which constructs a closed-loop structure of "emotion recognition—bidirectional interaction—personalized intervention" by adding a bidirectional emotion transmission module and a personalized intervention module to the traditional unidirectional emotion recognition structure; The two-way emotion interaction system for EEG signals includes several parts: an EEG signal acquisition module, a data processing and emotion recognition module, a two-way emotion interaction module, and a personalized intervention module. The EEG signal acquisition module is set at user A and user B, each using a wearable EEG headband device. This module is used to acquire users' EEG signals in real time and send multi-channel raw EEG data to the corresponding user terminal through a wireless communication unit.

[0020] The data processing and emotion recognition module is integrated into each user terminal device, and the module logically includes a signal preprocessing unit, a frequency domain feature extraction unit, and an emotion recognition unit. The signal preprocessing unit is used to perform preprocessing operations such as filtering, artifact removal, and baseline correction.

[0021] The frequency domain feature extraction unit is used to extract frequency domain, time domain, or time-frequency domain features, such as α, β, θ, γ band power and related emotional biomarkers. The emotion recognition unit maps EEG features to emotion classification labels based on machine learning or deep learning algorithms. The output of this unit is connected to both the two-way emotion interaction module and the personalized intervention module. Its function is to process and analyze the received signals in real time to output a quantitative score or classification label that represents the user's emotional state.

[0022] The two-way emotion interaction module is deployed on the user terminal device and enables communication between users through the network (especially suitable for remote scenarios).

[0023] The two-way emotion interaction module includes an emotion visualization unit and an emotion feedback unit. Its input end is connected to the data processing and emotion recognition module to receive emotion recognition results. The core function of this module is to transmit and display the emotional state data of the first user to the second user in real time, and at the same time, transmit and display the emotional state data of the second user back to the first user, thereby forming a closed-loop interaction and solving the problem of one-way and fragmented emotion communication in the prior art.

[0024] The personalized intervention module is deployed on the user terminal device. Its input end is connected to the data processing and emotion recognition module, and its control output end can communicate with local software functions (such as the breathing training guide in the APP) or external hardware control system (such as smart speakers and smart lights). This module is used to automatically trigger or recommend intervention programs to the user when preset conditions are met based on the received emotion recognition results.

[0025] The personalized intervention module also includes a remote interactive intervention function, which allows a second user to send an intervention request to the first user through their terminal device. For example, if the first user is observed to be in a bad mood, the intervention operation will only be executed by the first user's intervention module after the first user has given explicit consent and clicked to confirm. This can realize a closed-loop intervention of "identification-feedback-adjustment" while significantly enhancing the care and interaction between users.

[0026] The bidirectional emotion interaction system based on electroencephalogram (EEG) signals implements a bidirectional emotion interaction method, which specifically includes the following steps: Step 1: Signal Acquisition. The first and second users can be in the same location or in different locations, each wearing an EEG signal acquisition headband. The system will collect their EEG signals in real time. Step 2: Processing and Recognition. The collected raw EEG signals are transmitted to the data processing and emotion recognition module. The module performs preprocessing and feature extraction on each signal independently, and uses the emotion recognition unit to output data representing the user's current emotional state in real time. Step 3: Two-way interaction and synchronization. The two-way emotion interaction module is started and executed, sending the first user's emotional state data (generated in step 2) to the second user's terminal device and displaying it through the emotion visualization unit. At the same time, the second user's emotional state data is sent back to the first user's terminal device and displayed through the emotion visualization unit. This step realizes real-time sharing and two-way synchronization of emotional information. Step Four: Intervention and Adjustment, as detailed below: (1) The personalized intervention module continuously monitors the user's emotional state. When the preset conditions are met (emotional score is below the threshold or triggered by the user), the system automatically executes or recommends an intervention plan. (2). The second user can observe the emotional state of the first user through the two-way emotion interaction module and can actively trigger an intervention request. After the request is sent to the first user's terminal device and the user confirms and agrees, the first user's personalized intervention module starts the corresponding intervention plan to assist the user in emotional regulation.

[0027] Compared with the prior art, the present invention, through its unique system structure and working method, achieves at least the following beneficial effects: This invention achieves true two-way emotion interaction, overcoming the limitations of one-way monitoring. Existing technologies can generally only identify and display user emotions in a one-way manner, leaving users in a passive monitoring state and unable to achieve real-time transmission of emotional information between different users. This invention, by setting up a "two-way emotion interaction module," enables the first user and the second user to send, receive, and visualize each other's emotional states simultaneously. This fundamentally overcomes the problems of one-way emotion communication and fragmented feedback in traditional solutions, upgrading the system from a "passive monitoring tool" to an "active emotion interaction medium."

[0028] This invention effectively solves the problem of emotion synchronization in remote interaction scenarios and enhances emotional connection. Addressing the shortcomings of existing technologies in supporting remote emotion perception, the bidirectional interactive architecture of this invention is based on network communication design, enabling real-time transmission of emotional data between terminals in different geographical locations. This allows couples, parents and children, or remote team members to instantly perceive each other's emotional fluctuations, achieving cross-regional emotion synchronization and significantly improving emotional resonance and interaction quality in remote communication.

[0029] A closed-loop system of "identification-feedback-regulation" has been constructed, enhancing the practical value of the application. Traditional emotion recognition technology often remains at the "detection" stage and lacks subsequent regulation measures. This invention introduces a "personalized intervention module" to link emotion recognition results with multimodal intervention strategies such as music, breathing rhythm, and light regulation, forming a complete closed-loop emotion regulation system. This enables the device not only to "detect problems" but also to proactively "solve problems," significantly expanding application scenarios such as health management, psychological assistance, and intimate relationship maintenance.

[0030] This invention enhances user interaction and care. Its unique "remote interactive intervention function" allows one user to proactively trigger intervention measures with the other's authorization. This makes the intervention not only automatically executed by the system, but also a means for users to convey care, comfort, or emotional support. This function further enhances the system's humanistic care attributes and has positive social benefits in promoting the maintenance of close relationships, parent-child interaction, and remote companionship.

[0031] The following are embodiments proposed by the present invention to address the above-mentioned technical effects: Researchers first induced three different levels of cognitive load using a "spot the difference" game with three difficulty levels (easy, medium, and hard). They then used the NASA-TLX subjective scale to verify that there were indeed statistically significant differences between the three levels. Subsequently, by analyzing EEG data, they identified features that changed significantly and consistently with the three load levels—such as increased theta wave power, decreased alpha wave power, and specific changes in functional connectivity and microstate parameters—as biomarkers of cognitive load. Finally, they fused these spatial, temporal, and spectral features together and fed them into a machine learning model for training. The model successfully predicted (classified) the corresponding cognitive load level with an accuracy of over 80% in cross-validation, real-time, and cross-time tests, thus confirming the effectiveness of the prediction method. (Liu, 2023#2)

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations can be made to these embodiments, or they can be used directly or indirectly, without departing from the principles and spirit of the invention. In other related technical fields, the scope of the invention is defined by the appended claims and their equivalents, and they are similarly included within the scope of patent protection of the invention.

Claims

1. A method for bidirectional emotion interaction and intervention based on electroencephalography (EEG), characterized in that, include: The EEG signal bidirectional emotion interaction system constructs a closed-loop structure of "emotion recognition - bidirectional interaction - personalized intervention" by adding a bidirectional emotion transmission module and a personalized intervention module to the traditional one-way emotion recognition structure. The two-way emotion interaction system for EEG signals includes several parts: an EEG signal acquisition module, a data processing and emotion recognition module, a two-way emotion interaction module, and a personalized intervention module. The EEG signal acquisition module is set at user A and user B, each using a wearable EEG headband device. This module is used to acquire users' EEG signals in real time and send multi-channel raw EEG data to the corresponding user terminal through a wireless communication unit.

2. The method for bidirectional emotion interaction and intervention based on EEG according to claim 1, characterized in that: The data processing and emotion recognition module is integrated into each user terminal device, and the module logically includes a signal preprocessing unit, a frequency domain feature extraction unit, and an emotion recognition unit. The signal preprocessing unit is used to perform preprocessing operations such as filtering, artifact removal, and baseline correction.

3. The method for bidirectional emotion interaction and intervention based on EEG according to claim 2, characterized in that: The frequency domain feature extraction unit is used to extract frequency domain, time domain, or time-frequency domain features, such as α, β, θ, γ band power and related emotional biomarkers. The emotion recognition unit maps EEG features to emotion classification labels based on machine learning or deep learning algorithms. The output of this unit is connected to both the two-way emotion interaction module and the personalized intervention module. Its function is to process and analyze the received signals in real time to output a quantitative score or classification label that represents the user's emotional state.

4. The method for bidirectional emotion interaction and intervention based on EEG according to claim 3, characterized in that: The two-way emotion interaction module is deployed on the user terminal device and enables communication between users through the network (especially suitable for remote scenarios).

5. The method for bidirectional emotion interaction and intervention based on EEG according to claim 3, characterized in that: The two-way emotion interaction module includes an emotion visualization unit and an emotion feedback unit. Its input end is connected to the data processing and emotion recognition module to receive emotion recognition results. The core function of this module is to transmit and display the first user's emotional state data to the second user in real time, and at the same time, transmit the second user's emotional state data back to the first user, thereby forming a closed-loop interaction.

6. The method for bidirectional emotion interaction and intervention based on EEG according to claim 5, characterized in that: The personalized intervention module is deployed on the user terminal device. Its input end is connected to the data processing and emotion recognition module, and its control output end can communicate with local software functions or external hardware control systems. This module is used to automatically trigger or recommend intervention plans to the user when preset conditions are met based on the received emotion recognition results.

7. The method for bidirectional emotion interaction and intervention based on EEG according to claim 6, characterized in that: The local software functions include, but are not limited to, the breathing training wizard within the APP, and the external hardware control system includes, but is not limited to, smart speakers and smart lights.

8. The method for bidirectional emotion interaction and intervention based on EEG according to claim 6, characterized in that: The personalized intervention module also includes a remote interactive intervention function, which allows a second user to send an intervention request to the first user through their terminal device. For example, if the first user is observed to be in a bad mood, the intervention operation will only be executed by the first user's intervention module after the first user has given explicit consent and clicked to confirm. This can realize a closed-loop intervention of "identification-feedback-adjustment" while significantly enhancing the care and interaction between users.

9. The method for bidirectional emotion interaction and intervention based on electroencephalography (EEG) according to claims 1 to 8, characterized in that: The bidirectional emotion interaction system based on electroencephalogram (EEG) signals implements a bidirectional emotion interaction method, which specifically includes the following steps: Step 1: Signal Acquisition. The first and second users can be in the same location or in different locations, each wearing an EEG signal acquisition headband. The system will collect their EEG signals in real time. Step 2: Processing and Recognition. The collected raw EEG signals are transmitted to the data processing and emotion recognition module. The module performs preprocessing and feature extraction on each signal independently, and uses the emotion recognition unit to output data representing the user's current emotional state in real time. Step 3: Two-way interaction and synchronization. The two-way emotion interaction module is started and executed, sending the first user's emotional state data (generated in step 2) to the second user's terminal device and displaying it through the emotion visualization unit. At the same time, the second user's emotional state data is sent back to the first user's terminal device and displayed through the emotion visualization unit. This step realizes real-time sharing and two-way synchronization of emotional information. Step Four: Intervention and Adjustment, as detailed below: (1) The personalized intervention module continuously monitors the user's emotional state. When the preset conditions are met, the system automatically executes or recommends an intervention plan. (2). The second user can observe the emotional state of the first user through the two-way emotion interaction module and can actively trigger an intervention request. After the request is sent to the first user's terminal device and the user confirms and agrees, the first user's personalized intervention module starts the corresponding intervention plan to assist the user in emotional regulation.

10. The method for bidirectional emotion interaction and intervention based on EEG according to claim 9, characterized in that: The preset conditions include, but are not limited to, an emotion score below a threshold or being triggered by the user.

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