Normal-thought biofeedback system based on virtual reality

Abstract

The invention discloses a virtual reality-based positive-feeling biofeedback system, which comprises a user evaluation module for acquiring psychological state information of a user through a psychological state evaluation questionnaire; the virtual reality equipment is used for providing a virtual reality scene for the user to carry out training; the guidance information is displayed in the virtual reality scene; the physiological signal detection device is used for collecting a physiological signal of the user in the process that the user executes the mind training by utilizing the virtual reality equipment; the physiological signals are synchronously displayed in the virtual reality scene; the electroencephalogram device is used for collecting electroencephalogram signals of the user in the process that the user executes the mind training through the virtual reality device; and the data analysis module is used for analyzing the psychological state cause of the user according to the psychological state information, the physiological signals and the electroencephalogram signals, generating an evaluation report according to an analysis result, and giving a mentality training suggestion according to the evaluation report, so that the intervention effect of mentality training on psychological diseases is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical devices, and particularly relates to a mindfulness biofeedback system based on virtual reality. Background Art

[0002] With the intensification of social competition and the acceleration of the pace of life, mental health problems have become increasingly serious, and more and more people have begun to pay attention to the effectiveness of psychological intervention methods. Traditional psychological intervention methods often have some limitations, such as lack of immersion, insufficient real-time feedback, and lack of personalized services. Many existing intervention programs rely on face-to-face consultations, making it difficult to adapt to the individual differences and diverse needs of users. In addition, traditional methods are also insufficient in terms of user participation and training effect evaluation, resulting in a decline in user enthusiasm and unclear effects.

[0003] In recent years, the rapid development of virtual reality technology has provided new possibilities for psychological intervention, which can create an immersive environment and enhance the user experience. At the same time, the application of biofeedback technology makes it possible to monitor the physiological state of users in real time, providing data support for personalized intervention. Therefore, a mindfulness training system combining virtual reality and biofeedback has emerged, aiming to overcome the deficiencies of traditional methods and provide a more comprehensive, personalized, and effective mental health management solution. This innovative technical background provides new ideas and solutions for improving the mental health status of users.

[0004] In related technologies, a patent application with the publication number CN113855052A proposed a neurofeedback intervention system based on mindfulness meditation. The system includes an electroencephalogram (EEG) signal acquisition module, an EEG signal preprocessing module, an EEG signal feature extraction module, a normalized neurofeedback index calculation module, and a normalized neurofeedback index and auditory neurofeedback mapping module. Among them, the EEG signal acquisition module includes a portable three-channel EEG signal sensor and an EEG signal receiving sub-module. The system collects EEG signals through the portable three-channel EEG signal sensor and calculates the first emotional state value, and uses a neurofeedback index normalization model to obtain the second emotional state value, thereby reducing the negative impact caused by individual differences in EEG signals. Finally, the normalized neurofeedback index is mapped to auditory neurofeedback based on natural sounds to achieve real-time feedback to improve the mindfulness meditation training effect. The system mainly provides auditory feedback through natural sounds. However, different users have different reactions to auditory feedback, so the intervention effects vary from person to person. Summary of the Invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a mindfulness biofeedback system based on virtual reality.

[0006] The technical problems to be solved by the present invention are realized through the following technical solutions:

[0007] A virtual reality-based mindfulness biofeedback system, comprising:

[0008] A user evaluation module for obtaining the psychological state information of a user through a psychological state assessment questionnaire;

[0009] A virtual reality device for providing a virtual reality scene for the user to perform mindfulness training; guidance information is displayed in the virtual reality scene; the guidance information is used to guide the user to perform mindfulness training;

[0010] A physiological signal detection device for collecting the physiological signals of the user during the process of the user performing mindfulness training using the virtual reality device; the physiological signals are synchronously displayed in the virtual reality scene;

[0011] An electroencephalogram device for collecting the electroencephalogram signals of the user during the process of the user performing mindfulness training using the virtual reality device;

[0012] A data analysis module for analyzing the causes of the user's psychological state based on the psychological state information, the physiological signals, and the electroencephalogram signals, generating an evaluation report according to the analysis results, and giving mindfulness training suggestions according to the evaluation report.

[0013] Optionally, the psychological state assessment questionnaire includes: a depression and anxiety assessment scale, a mindfulness level assessment scale, a stressor questionnaire, a psychological resilience assessment questionnaire, and cognitive flexibility test questions.

[0014] Optionally, the physiological signals include: heart rate, respiratory rate, galvanic skin response, and body temperature.

[0015] Optionally, mindfulness audio guiding the user to perform meditation and deep breathing and soft music for relaxing the user are played in the virtual reality scene.

[0016] Optionally, the data analysis module is further configured to adjust the mindfulness training plan according to the user's historical training data and the user state; the user state is determined according to the psychological state information, the physiological signals, and the electroencephalogram signals.

[0017] Optionally, the data analysis module analyzes the causes of the user's psychological state based on the psychological state information, the physiological signals, and the electroencephalogram signals, including:

[0018] Integrating the electroencephalogram signals into an electroencephalogram signal sequence, integrating the physiological signals into a physiological signal sequence, and encoding the psychological state information into a psychological state sequence;

[0019] Using a first convolutional neural network to extract features from the electroencephalogram signal sequence to obtain electroencephalogram features;

[0020] Feature extraction is performed on the physiological signal sequence by using a second convolutional neural network to obtain physiological features;

[0021] Feature extraction is performed on the mental state sequence by using a third convolutional neural network to obtain mental features;

[0022] Feature integration is performed on the EEG features, physiological features, and mental features by using a fully connected layer, and the cause of the user's mental state is output based on the integrated features.

[0023] Optionally, the data analysis module is further configured to analyze the physiological signals and / or EEG signals in real time, and according to the real-time analysis results, cooperate with the virtual reality device to prompt the user with an emotion regulation strategy.

[0024] Optionally, there are multiple virtual reality scenarios; any one of the virtual reality scenarios includes a scene interaction function.

[0025] Optionally, the multiple virtual reality scenarios at least include: a forest scene, a beach scene, a mountaintop scene, and a waterfall scene.

[0026] Optionally, both the user evaluation module and the data analysis module are deployed on a computer, the physiological signal detection device and the EEG device are both connected to the computer through a Bluetooth device, and the computer and the virtual reality device communicate through a serial port.

[0027] The virtual reality-based mindfulness biofeedback system provided by the present invention introduces virtual reality technology, adds visual elements, and on this basis, cooperates with physiological signal detection, EEG signal detection, and the mental state information of the user obtained through a mental state evaluation questionnaire, and can more comprehensively and accurately analyze the cause of the user's mental state, thereby giving targeted mindfulness training suggestions and improving the intervention effect of mindfulness training on mental diseases.

[0028] The following will further describe the present invention in detail with reference to the accompanying drawings. Brief Description of the Drawings

[0029] Figure 1 is a schematic structural diagram of a virtual reality-based mindfulness biofeedback system provided by an embodiment of the present invention;

[0030] Figure 2 Exemplarily shows a flowchart of performing mindfulness training by using the virtual reality-based mindfulness biofeedback system provided by an embodiment of the present invention;

[0031] Figure 3 Exemplarily shows a schematic diagram of a virtual reality mindfulness feedback interface. Detailed Description of the Embodiment

[0032] The present invention will be further described in detail below in conjunction with specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0033] Traditional psychological intervention methods, such as face-to-face psychotherapy and drug treatment, although effective to a certain extent, have many problems in terms of accessibility, personalization, and acceptance. Many students are unable to obtain timely psychological support due to factors such as time, economy, and privacy. In addition, self-help resources (such as books and online courses) although providing certain help, often lack real-time feedback and professional guidance, resulting in individuals having difficulty adhering to or achieving the expected effects during implementation.

[0034] Commonly used psychological treatment methods, such as cognitive behavioral therapy (CBT) and interpersonal therapy, rely on face-to-face interaction. Although these methods are highly effective, for some students, participating in these treatments may be hindered due to social anxiety or lack of time.

[0035] In recent years, mindfulness training, as an emotion regulation method, has received extensive attention in mental health intervention. Existing mindfulness training methods (such as Mindfulness-Based Stress Reduction MBSR) have shown positive effects on depression and anxiety. However, traditional mindfulness training often lacks immersion and personalized feedback, making it difficult to meet the diverse needs of individuals. Although using natural sounds as a feedback method in CN113855052A has affinity, the preferences and acceptance of different users vary, which may cause some users to feel dissatisfied with the experience, and there are differences in the responses of different users to auditory feedback, so the intervention effects vary from person to person.

[0036] To solve the problems existing in the prior art, the present invention provides a virtual reality-based mindfulness biofeedback system. Referring to Figure 1 as shown, the system includes: a user evaluation module, a virtual reality device, a physiological signal detection device, an electroencephalogram device, and a data analysis module.

[0037] Among them, both the user evaluation module and the data analysis module are software modules, which can be actually deployed on the same computer in practice. The physiological signal detection device, the electroencephalogram device, and the virtual reality device are all hardware modules. The physiological signal detection device and the electroencephalogram device are connected to the computer, and at the same time the computer also communicates with the virtual reality device. For example, both the physiological signal detection device and the electroencephalogram device can be connected to the computer through Bluetooth devices, and the computer and the virtual reality device can communicate through a serial port. Of course, it is not limited thereto.

[0038] The user evaluation module is used to obtain the psychological state information of the user through a psychological state assessment questionnaire.

[0039] Exemplarily, the psychological state assessment questionnaire includes: a depression and anxiety rating scale, a mindfulness level assessment scale, a stressor questionnaire, a psychological resilience assessment questionnaire and a cognitive flexibility test.

[0040] Here, in addition to the relevant scales that users need to fill out, the psychological state assessment questionnaire also adds detailed investigations on the user's living environment, daily stressors, etc. For example, asking users about the noise level of their living environment, whether they often face high-intensity learning or work tasks, and combining these data with the results of the psychological state assessment questionnaire and the mindfulness attention awareness questionnaire can provide a more comprehensive understanding of the user's psychological needs and stress background, and can provide a richer reference basis for the subsequent formulation of personalized training plans. In addition, the introduction of more professional and subdivided assessment dimensions such as psychological resilience and cognitive flexibility in the psychological state assessment questionnaire can more deeply explore the user's psychological characteristics, so as to have a more accurate grasp of the user's psychological state. Among them, psychological resilience is assessed by asking users about their coping methods and recovery time when facing setbacks; cognitive flexibility is measured through a series of cognitive test questions, including attention switching and thinking conversion ability.

[0041] A virtual reality device is used to provide a user with a virtual reality scene for mindfulness training; guidance information is displayed in the virtual reality scene; and the guidance information is used to guide the user to perform mindfulness training.

[0042] The virtual reality device includes a VR helmet and a handheld controller, through which users enter the real scene.

[0043] In the present invention, the virtual reality scenes may include multiple ones; illustratively, the multiple virtual reality scenes may include: forest scenes, beach scenes, mountain top scenes and waterfall scenes, but are certainly not limited thereto.

[0044] Taking the forest scene as an example, it not only contains a variety of real-scale trees, such as pine, oak, maple, etc., but also presents different colors and vegetation states according to seasonal changes. In spring, the trees are sprouting, and the ground is covered with tender green grass and colorful wildflowers; in autumn, the maple leaves are like fire, and the fallen leaves flutter in the breeze, creating an immersive natural atmosphere. At the same time, the light and shadow effects in the scene will change dynamically over time. In the early morning, the sun shines through the gaps in the leaves, casting mottled light and shadows, and at dusk it is shrouded in warm orange afterglow, combined with realistic bird calls, wind and other natural sound effects, to fully enhance the user's immersion and relaxation experience. Dynamic breathing elements are added to the forest scene, and users can better engage in breathing training through a combination of audio guidance and dynamic element guidance.

[0045] The virtual reality scene can also play mindfulness audio that guides users to meditate and breathe deeply, as well as light music that relaxes users, thereby helping users concentrate and creating a relaxing atmosphere.

[0046] In addition, any virtual reality scene can include a scene interaction function. For example, in a beach scene, virtual characters are added by the sea. In a mindful body scan exercise, according to the guidance of the audio, different body parts of the virtual characters are lit up in sequence, guiding the user to focus on the same parts of their own body and gradually relax. In a waterfall scene, the user adjusts the size of the waterfall water flow according to the size of their heart rate, and the change of the water flow will cause corresponding changes in the surrounding water vapor, sound and light, allowing the user to truly feel their impact on the environment and strengthening the subjective initiative during the training process. The user can choose according to personal preferences to enhance the relaxation effect and improve the experience.

[0047] A physiological signal detection device for collecting physiological signals of a user during the process of the user performing mindful training using a virtual reality device; the physiological signal is synchronously displayed in the virtual reality scene.

[0048] Exemplarily, the physiological signal detection device may include a device for monitoring heart rate, a device for monitoring respiratory rate, a high-precision galvanic skin sensor and a body temperature sensor. Correspondingly, the physiological signals collected in the present invention may include: heart rate, respiratory rate, galvanic skin response and body temperature.

[0049] In the present invention, on the basis of collecting heart rate and respiratory rate, the collection function of physiological indicators such as galvanic skin response and body temperature is added. High-precision galvanic skin sensors and body temperature sensors are used to ensure the accuracy and real-time nature of the data. The galvanic skin response can reflect the degree of emotional arousal of the human body, and the change in body temperature reflects the stress state of the body to a certain extent.

[0050] It can be understood that based on the collected physiological signals such as heart rate and respiratory frequency, it can help establish the baseline physiological state of the user, and thus determine whether there is an abnormality in the user's physiological state based on these baselines. The physiological signal detection device is connected to a computer, so through the computer, the collected physiological signals such as heart rate and respiratory frequency can be fed back to the user through a feedback interface, so that the user can view the real-time feedback physiological signal information, including heart rate, respiratory rate charts, emotional state indicators and guidance content, for self-emotional regulation and management. For example, the user can independently decide the start time of the training according to their own rhythm. Choose to pause the training when feeling unwell. Figure 3 Exemplarily shows a schematic diagram of a virtual reality mindful feedback interface.

[0051] In one implementation, an Android application based only on a mobile device can be developed, combined with biofeedback technology, to monitor the physiological signals (such as heart rate, respiration, etc.) of the user through a smart phone or a wearable device, and provide mindful training guidance.

[0052] An electroencephalogram (EEG) device is used to collect the EEG signals of a user during the process of the user performing mindfulness training using a virtual reality device.

[0053] In the present invention, the EEG device can focus on detecting alpha waves and beta waves, so as to analyze the brain activity state of the user, and monitor their concentration, relaxation level and mood fluctuations.

[0054] A data analysis module is used to analyze the causes of the user's mental state based on the mental state information, physiological signals and EEG signals, generate an evaluation report according to the analysis results, and give mindfulness training suggestions according to the evaluation report.

[0055] Specifically, the data analysis module analyzes the causes of the user's mental state based on the mental state information, physiological signals and EEG signals, including:

[0056] (1) Integrate the EEG signals into an EEG signal sequence, integrate the physiological signals into a physiological signal sequence, and encode the mental state information into a mental state sequence;

[0057] Here, the present invention introduces time series analysis technology to track the dynamic changes of various types of data during the mindfulness training process. Taking heart rate data as an example, heart rate data can be collected in real time, recorded every 5 seconds to form a heart rate sequence. In addition, a curve of heart rate changing with time can be drawn and displayed to the user in the virtual reality device;

[0058] (2) Use a first convolutional neural network to extract features from the EEG signal sequence to obtain EEG features;

[0059] (3) Use a second convolutional neural network to extract features from the physiological signal sequence to obtain physiological features;

[0060] (4) Use a third convolutional neural network to extract features from the mental state sequence to obtain mental features;

[0061] (5) Use a fully connected layer to integrate the EEG features, physiological features and mental features, and output the causes of the user's mental state based on the integrated features.

[0062] Among them, the first convolutional neural network, the second convolutional neural network, the third convolutional neural network and the fully connected layer all need to be obtained through pre-training. In actual training, a large number of samples of the mental state sequence, EEG signal sequence and physiological signal sequence of users with known mental state causes can be collected, so as to train the entire neural network model composed of the first convolutional neural network, the second convolutional neural network, the third convolutional neural network and the fully connected layer based on these samples. Regarding the model training method, reference can be made to relevant existing technologies, and the present invention will not elaborate.

[0063] In the present invention, by combining the fluctuation trends of alpha waves and beta waves in electroencephalogram (EEG) signals and the changes in physiological data such as respiration rate, the variation laws of the physical and mental states of users in different stages are analyzed. In this way, the instantaneous transitions of the user's state can be accurately captured, such as the transition nodes from relaxation to tension, providing an accurate basis for real-time feedback and scenario adjustment. At the same time, a deep neural network fusion model (i.e., the above neural network model) is constructed, taking physiological signals (heart rate, respiration rate, skin conductance response, body temperature), EEG signals (features of different frequency bands such as alpha waves and beta waves), and the results of the questionnaires filled in by users (covering multiple dimensions such as depression and anxiety assessment, mindfulness level evaluation, psychological resilience, and cognitive flexibility) as the multi-modal inputs of the model, and using the model to automatically mine the complex non-linear relationships between data and deeply analyze the causes of users' psychological states.

[0064] Preferably, the data analysis module can also be used to analyze physiological signals and / or EEG signals in real time, and according to the real-time analysis results, cooperate with virtual reality devices to prompt users with emotion regulation strategies.

[0065] Among them, the analysis of physiological signals can include heart rate variability (HRV), SDNN (total variability), RMSSD (parasympathetic activity), LF (low frequency, sympathetic related), HF (high frequency, parasympathetic related), skin conductance level (SCL), skin conductance response (SCR), respiration frequency (BR), and respiration depth, etc. In practice, indicators with a greater correlation with mental states can be selected for analysis. The analysis of EEG signals can include frequency domain analysis, time domain analysis (such as event-related potential (ERP)), and coherence, phase-locked value (PLV), etc.

[0066] Based on the real-time analysis results of physiological signals and / or EEG signals, further cooperate with virtual reality devices to prompt users with emotion regulation strategies. For example, when it is judged that the user's heart rate increases due to anxiety, a small window will pop up on the interface, introducing in detail several breathing exercise methods suitable for the current state, including the rhythm, depth, and duration of breathing, and cooperating with animation demonstrations of correct breathing actions. When it is detected that the user's skin conductance response increases, beta wave activity enhances, and heart rate accelerates, it is comprehensively judged that the user is in a highly tense or excited state, thereby providing a more comprehensive and accurate data basis for personalized feedback and scenario adjustment.

[0067] The data analysis module generates an evaluation report based on the analysis results, including: showing the causes of the user's mental state, relevant knowledge and suggestions in the evaluation report, statistically analyzing the analysis results of the physiological signals and EEG signals monitored during the training process, and presenting the statistical results in the evaluation report, as well as showing the user's mental state information obtained through the mental state evaluation questionnaire and the corresponding psychological analysis in the evaluation report, so as to give the user a comprehensive and comprehensive evaluation result, generate a detailed evaluation report, provide a visual display of emotional changes and training effects, and attach targeted improvement suggestions, thereby helping the user understand the relationship between training effects and physiological changes.

[0068] When generating the evaluation report, the evaluation indicators can be comprehensively refined. In addition to the traditional evaluation of relaxation level, concentration change and emotional fluctuation, the evaluation results of new dimensions such as mental toughness and cognitive flexibility can also be highlighted. For each evaluation indicator, not only quantitative data can be given, but also detailed text explanations and comparative analyses with groups of the same age and mental condition can be provided. For example, in the evaluation of mental toughness, it can be clearly pointed out the advantages and disadvantages of the user in coping with stress and setbacks, and compared with the average level, so that the user can clearly understand his position in this regard. At the same time, visual methods such as radar charts and line charts can be used to intuitively display the change trends of various evaluation indicators, help the user more intuitively understand his training effects, and provide a more comprehensive feedback mechanism.

[0069] It can be understood that the data analysis module gives mindfulness training suggestions according to the evaluation report, mainly using psychological knowledge to give the user training suggestions related to his mental state and its causes. In practice, the training suggestions related to different mental states and their causes can be pre-set in the data analysis module, so that after learning the user's mental state and its causes, the corresponding training suggestions can be output to the user.

[0070] For example, for users with low mental toughness, in addition to recommending increased deep breathing exercises and adjusting the training environment, a specialized mental toughness training plan is developed for them, including a series of challenge tasks with gradually increasing difficulty, such as setting short-term goals and overcoming difficulties to complete them, simulating stress scenarios for coping training, etc., and at the same time, corresponding mindfulness meditation exercises are paired to help users maintain calmness and focus during the process of enhancing mental toughness. For users with insufficient cognitive flexibility, the system recommends targeted cognitive training games, such as attention-switching games, graphic recognition and transformation games, etc., and combines more guiding meditation audio to guide users to exercise their thinking transformation ability during the training process and gradually improve cognitive flexibility. These personalized training suggestions are closely combined with the specific evaluation results of users, effectively meeting the personalized needs of users and enhancing the training effect. If the brain waves show that the user fails to concentrate during the training, the system recommends more guiding meditation audio or increases the meditation time.

[0071] Preferably, the data analysis module is further configured to adjust the mindfulness training plan according to the user's historical training data and user status; the user status is determined according to the psychological state information, physiological signals, and electroencephalogram signals.

[0072] Specifically, using psychological knowledge, a series of judgment conditions regarding psychological state information, physiological signals, and / or electroencephalogram signals are preset in advance, so as to know what state the user is in when the judgment conditions are met. Similarly, using psychological knowledge, the mindfulness training requirements corresponding to different user states are set. In this way, the mindfulness training plan can be adjusted for the user according to the user's historical training data and user status. For example, when it is determined according to the user's psychological state information, physiological signals, and / or electroencephalogram signals that the user is in a highly tense state, the originally colorful and element-rich scene in the scenario can be adjusted to a scene with a soft tone and simple elements to help the user quickly regain calmness.

[0073] The virtual reality-based mindfulness biofeedback system provided by the present invention, by introducing virtual reality technology, increases visual elements, and on this basis, cooperates with physiological signal detection, electroencephalogram signal detection, and the psychological state information of the user obtained through a psychological state assessment questionnaire, can more comprehensively and accurately analyze the causes of the user's psychological state, thereby giving targeted mindfulness training suggestions and improving the intervention effect of mindfulness training on mental diseases.

[0074] The following combines Figure 2 An exemplary description is given of the process of a user using the virtual reality-based mindfulness biofeedback system provided by the present invention for mindfulness training:

[0075] (1) The user browses the mindfulness psychological education and VR technology modules on a computer (or smartphone), understands the basic principles and techniques of mindfulness meditation, enhances the user's initiative and sense of participation, and prepares for subsequent regulation. Among them, the computer (or smartphone) is responsible for providing a browsing interface for the user.

[0076] (2) The user logs in to the Android system and fills out a psychological state scale (psychological state assessment questionnaire) on a computer (or smartphone). Among them, the computer (or smartphone) is responsible for providing a login interface and a question-answering interface for the user. For users who are undergoing mindfulness training for the first time, they can select their favorite virtual reality scene and training plan on a computer (or smartphone) during the first login. Then, through augmented reality technology, the mindfulness training content is superimposed on the virtual reality environment using a mobile phone or tablet.

[0077] (3) The user wears a virtual reality device and enters the selected scene. At the same time, the physiological signal detection device and the electroencephalogram device start to monitor the user's physiological signals and electroencephalogram signals in real time, and carry out virtual reality training (mindfulness training) according to the training plan. The data monitored during the training process will be fed back to the user in real time.

[0078] (4) After the user completes the training, the computer automatically saves the training data, allows the user to view the training review, and understand their improvement in relaxation and concentration. At this time, the data analysis module can judge whether the mindfulness training plan needs to be adjusted according to the user's historical training data and user status. If so, the computer will prompt the user that the current plan needs to be adjusted. After the user agrees, the next training can be carried out according to the new plan.

[0079] (5) The user logs in to the Android system again to fill out the psychological state assessment questionnaire, records the changes in the psychological state after training, collects the user's physiological signals and electroencephalogram signals, obtains subjective experience feedback, and generates a statistical analysis report.

[0080] (6) In addition, the user can also evaluate the training content, system feedback, and overall experience. In this way, the training plan and training plan can be continuously optimized according to the user's feedback, a personalized subsequent training plan can be formulated for the user, ensuring that the subsequent training better meets the user's needs and helps them gradually improve in mental health management.

[0081] It should be noted that the users of the system of the present invention are usually patients diagnosed and treated by psychiatrists. For doctors, after their patients use the system of the present invention for mindfulness training, doctors can use the system to compare the data performance of different users in similar training scenarios and the state differences of the same user at different training stages, so as to provide more highly customized training suggestions for their patients.

[0082] The mindfulness biofeedback system based on virtual reality provided by the present invention has the following beneficial effects:

[0083] (1) It provides a variety of virtual reality scenarios for users to choose from, emphasizing the in-depth design of virtual reality scenarios and rich interaction functions, including seasonal changes of the scenarios, dynamic light and shadow effects, diverse interaction elements, and intelligent adjustment according to users' physiological and behavioral data to enhance users' relaxation experience and sense of participation, and improve the flexibility and adaptability of the system.

[0084] (2) It collects physiological data such as heart rate and respiratory rate in real time to establish the user's baseline physiological state.

[0085] (3) Multi-dimensional data fusion and intelligent analysis: It emphasizes the fusion collection and in-depth analysis of multi-dimensional physiological data (heart rate, respiratory rate, galvanic skin response, body temperature, etc.) and electroencephalogram signals, as well as the real-time trend prediction and intelligent early warning functions based on this, providing more accurate data support for personalized feedback and training adjustment.

[0086] (4) According to the user's physiological reactions and psychological states, it provides personalized subsequent training suggestions to help users improve the training effect.

[0087] In summary, the system provided by the present invention provides a highly immersive virtual reality environment, enhancing the user's relaxation and concentration effects. At the same time, by real-time monitoring of physiological signals and electroencephalogram signals, it provides instant feedback to help users understand their own states and make adjustments. In addition, the system can generate personalized training plans and feedback suggestions according to users' physiological data and psychological evaluations to meet the specific needs of different users. Users can also choose diverse virtual scenarios, such as forests or beaches, to increase the fun and flexibility of training, thus enhancing the sense of participation. The system generates detailed evaluation reports by comprehensively analyzing physiological data and psychological states to help users clearly recognize their progress. At the same time, real-time monitoring and feedback enhance the user's self-regulation ability, enabling them to manage emotions more effectively. In terms of the user experience, the system simplifies the registration, login, and evaluation processes through an Android application. In addition, the system is continuously optimized according to user feedback to ensure that the training content meets user needs and improves overall satisfaction. The system also integrates a variety of psychological intervention methods, combining mindfulness meditation, psychological education, and biofeedback to provide a comprehensive psychological intervention plan. Finally, the system is based on psychological and biofeedback principles to ensure the scientificity and effectiveness of the methods. These advantages enable the present invention to have obvious competitive advantages in the field of mental health management and can provide more effective and personalized support for users.

[0088] It should be noted that the terms "first", "second", etc. are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention.

[0089] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification.

[0090] Although the present invention has been described in conjunction with various embodiments herein, however, in the process of implementing the claimed invention, those skilled in the art can understand and implement other variations of the disclosed embodiments by viewing the accompanying drawings and the disclosure. In the description of the present invention, the term "comprising" does not exclude other components or steps, the word "a" or "an" does not exclude a plurality of cases, and the meaning of "a plurality" is two or more unless otherwise specifically defined. In addition, certain measures are described in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0091] The above content is a further detailed description of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can still be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A virtual reality-based mindfulness biofeedback system, characterized in that, Including: A user evaluation module for obtaining the user's mental state information through a mental state assessment questionnaire; A virtual reality device for providing a virtual reality scenario for mindfulness training to the user; guiding information is displayed in the virtual reality scenario; the guiding information is used to guide the user to perform mindfulness training; A physiological signal detection device for collecting the user's physiological signals during the process of the user performing mindfulness training using the virtual reality device; the physiological signals are synchronously displayed in the virtual reality scenario; An electroencephalogram device for collecting the user's electroencephalogram signals during the process of the user performing mindfulness training using the virtual reality device; A data analysis module for analyzing the causes of the user's mental state based on the mental state information, the physiological signals, and the electroencephalogram signals, generating an evaluation report according to the analysis results, and giving mindfulness training suggestions according to the evaluation report.

2. The mindfulness biofeedback system based on virtual reality according to claim 1, wherein The mental state assessment questionnaire includes: a depression and anxiety assessment scale, a mindfulness level assessment scale, a stressor questionnaire, a mental toughness assessment questionnaire, and cognitive flexibility test questions.

3. The mindfulness biofeedback system based on virtual reality according to claim 1, wherein The physiological signals include: heart rate, respiratory rate, galvanic skin response, and body temperature.

4. The mindfulness biofeedback system based on virtual reality according to claim 1, characterized in that, Mindfulness audio guiding the user to meditate and take deep breaths and light music that relaxes the user are played in the virtual reality scenario.

5. The mindfulness biofeedback system based on virtual reality according to claim 1, characterized in that, The data analysis module is further configured to adjust the mindfulness training plan according to the user's historical training data and user status; the user status is determined based on the mental state information, the physiological signals, and the electroencephalogram signals.

6. The mindfulness biofeedback system based on virtual reality according to claim 1, wherein The data analysis module analyzes the causes of the user's mental state based on the mental state information, the physiological signals, and the electroencephalogram signals, including: Integrating the electroencephalogram signals into an electroencephalogram signal sequence, integrating the physiological signals into a physiological signal sequence, and encoding the mental state information into a mental state sequence; Using a first convolutional neural network to extract features from the electroencephalogram signal sequence to obtain electroencephalogram features; Using a second convolutional neural network to extract features from the physiological signal sequence to obtain physiological features; Using a third convolutional neural network to extract features from the mental state sequence to obtain mental features; Using a fully connected layer to integrate the electroencephalogram features, physiological features, and mental features, and outputting the causes of the user's mental state based on the integrated features.

7. The virtual reality-based mindfulness biofeedback system according to claim 1, wherein The data analysis module is further configured to analyze the physiological signals and / or electroencephalogram signals in real time, and according to the real-time analysis results, cooperate with the virtual reality device to prompt the user with emotion regulation strategies.

8. The mindfulness biofeedback system based on virtual reality according to claim 1, characterized in that, There are multiple virtual reality scenarios; any one of the virtual reality scenarios includes a scenario interaction function.

9. The mindfulness biofeedback system based on virtual reality according to claim 8, characterized in that, The multiple virtual reality scenarios at least include: a forest scenario, a beach scenario, a mountaintop scenario, and a waterfall scenario.

10. The mindfulness biofeedback system based on virtual reality according to claim 1, characterized in that The user evaluation module and the data analysis module are both deployed on a computer. The physiological signal detection device and the electroencephalogram device are both connected to the computer through a Bluetooth device, and the computer and the virtual reality device communicate through a serial port.

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