Headache relaxation training management system based on virtual reality

Abstract

The present invention relates to the technical field related to training management, and specifically includes a virtual reality-based headache relaxation training management system, comprising: a data collection module for constructing scenes and collecting physiological data; an adaptive control module for adjusting scenes according to indicators; a startup module for initiating training under specific conditions and enhancing feedback; an optimization management module for analyzing trends, strengthening prodromal characteristics, generating prediction maps, and optimizing training. The system solves the technical problem that headache relaxation training is insufficiently effective due to differences in users' headache types, inducements, pain levels, and accompanying symptoms, and achieves the technical effect of constructing a virtual reality environment based on the potential pain mechanism of headaches, adaptively controlling and adjusting the visual focus guidance path and sound field frequency distribution in the virtual environment scene, setting an attention mechanism to strengthen the prodromal characteristics of the attack, and generating a state prediction map within a time sliding window, thereby better adapting to individual differences among users and improving the pertinence and effectiveness of relaxation training.

Description

Technical Field

[0001] The present invention relates to the technical field related to training management, and in particular to a headache relaxation training management system based on virtual reality. Background Art

[0002] At present, the application of virtual reality technology in pain management has made certain progress and plays an important role as an auxiliary intervention in the treatment of acute and chronic pain. However, existing virtual reality-based pain treatment methods have some shortcomings. Common ones adopt a one-size-fits-all paradigm and ignore the potential of customizing virtual reality environments based on specific underlying pain mechanisms, resulting in reduced treatment efficacy and may even cause symptom worsening, lack of participation, safety issues (such as not tailored to specific physical limitations) and negative psychological effects, affecting the effectiveness of VR intervention for chronic pain. In addition, traditional pain management methods mainly include drug therapy and physical therapy, but these methods have limitations, such as drug dependence, large side effects, and unstable effects.

[0003] In summary, the existing technology has technical problems such as differences in users' headache types, causes, pain levels and accompanying symptoms, and insufficient effectiveness of headache relaxation training. Summary of the Invention

[0004] This application provides a virtual reality-based headache relaxation training management system to solve the technical problems in the existing technology that headache relaxation training is insufficiently effective due to differences in users' headache types, causes, pain levels, and accompanying symptoms.

[0005] In view of the above problems, the technical solution to implement this application is:

[0006] The present application provides a virtual reality-based headache relaxation training management system, wherein the system includes: a data collection module for constructing a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collecting eye movement data, facial muscle activity signals, and breathing rate parameters of a target user, and setting a physiological state indicator; an adaptive control module for adjusting the visual focus guidance path and sound field frequency distribution in the virtual environment scene through adaptive control based on the physiological state indicator, and inserting visual interference elements, wherein the generation frequency of the visual interference elements is associated with the user's real-time pupil contraction rate; a startup module for initiating a multi-stage headache relaxation training process and synchronously enhancing the vibration feedback intensity of a foot pressure pad after inserting the visual interference elements if it is detected that the facial muscle activity signal exceeds a preset threshold; and an optimization management module for matching abnormal physiological parameter fluctuation ranges through cosine similarity based on the physiological parameter change trend within the headache relaxation training cycle, setting an attention mechanism to strengthen the prodromal period characteristics of the attack, generating a state prediction map within a time sliding window, and performing training optimization management.

[0007] In summary, the one or more technical solutions provided in this application construct a virtual reality environment based on the potential pain mechanism of headache, adaptively control and adjust the visual focus guidance path and sound field frequency distribution in the virtual environment scene, set the attention mechanism to enhance the prodromal characteristics of the attack, and generate a state prediction map within the time sliding window, so as to better adapt to the individual differences of users and improve the targeted and effective technical effects of relaxation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A structural diagram of a headache relaxation training management system based on virtual reality is provided for this application;

[0009] Figure 2 This application provides a flow chart of configuring the resonance relaxation effect of the adaptive control module of the virtual reality-based headache relaxation training management system.

[0010] Description of reference numerals: data collection module M100, adaptive control module M200, startup module M300, optimization management module M400. DETAILED DESCRIPTION

[0011] Example

[0012] The present application is described in detail below with reference to the accompanying drawings. Figure 1 As shown, the present application provides a headache relaxation training management system based on virtual reality, wherein the system includes:

[0013] The data collection module M100 is used to build a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collect the target user's eye movement data, facial muscle activity signals and breathing rate parameters, and set physiological status indicators.

[0014] Specifically, a dynamic lighting unit refers to a lighting component that can change the light intensity, color temperature and distribution pattern according to real-time data or preset programs; a multi-frequency sound effect unit is an audio device that can produce sounds of different frequencies, rhythms and volumes; eye movement data is collected mainly through eye tracking technology to record eye movement trajectory, gaze point, scanning speed and other information; facial muscle activity signal detection generally uses surface electromyography sensors attached to relevant facial muscle areas to capture muscle electrical activity to reflect the activity state of the muscles; respiratory rate parameters are usually determined by measuring the frequency of chest or abdominal fluctuations through respiratory sensors (such as respiratory sensor belts, pressure sensors, etc.); physiological status indicators refer to a set of quantitative standards formed by comprehensive data such as eyes, facial muscles and breathing, which are used to measure the user's current physiological condition.

[0015] When constructing a virtual environment scene, the dynamic lighting unit can simulate a variety of lighting environments, from bright to dim, from cold light to warm light; the multi-frequency sound effect unit can play different styles of sound effects, from low frequency to high frequency, from soothing to tense, etc., to create an immersive multi-sensory experience environment for users. Specifically, collecting eye movement data can understand the user's visual attention distribution. For example, when a user looks at a specific area, the dwell time, scanning frequency and other data can reflect the degree of interest in the area; facial muscle activity signals can indirectly reflect the user's emotional state. For example, when the facial muscle tension increases, the user is in a state of tension or discomfort. The breathing rate parameter is one of the important indicators to measure the user's degree of relaxation. The normal breathing rate of an adult is generally between 12 times / minute and 20 times / minute.

[0016] Setting physiological state indicators is to integrate and quantify the collected data to form a comprehensive evaluation standard; in the entire headache relaxation training program, it provides basic data support for subsequent adaptive control adjustments, thereby fully understanding the user's physiological state and accurately constructing a virtual environment suitable for the individual user, thereby improving the targeted nature of relaxation training.

[0017] The adaptive control module M200 is used to adjust the visual focus guidance path and the sound field frequency distribution in the virtual environment scene through adaptive control based on the physiological state indicator, and insert visual interference elements, wherein the generation frequency of the visual interference elements is associated with the user's real-time pupil contraction rate.

[0018] Specifically, adaptive control is a control strategy that can automatically adjust system parameters or behaviors based on real-time feedback information; the visual focus guidance path refers to the trajectory that guides the user's visual attention to move along a specific route in the virtual environment; the sound field frequency distribution refers to the distribution of sound frequencies at different locations in the virtual environment space; visual interference elements are elements added to the visual scene to interfere with the user's visual attention, and their generation frequency is related to the user's real-time pupil contraction rate, which means that the frequency of these interference elements is controlled according to the speed of pupil contraction; the pupil contraction rate can be monitored by eye tracking equipment, which can reflect the user's concentration level to a certain extent.

[0019] When adaptive control is performed based on physiological state indicators, taking the visual focus guidance path as an example, the system will adjust the shape, speed and direction of the guidance path in real time according to the user's current physiological state (such as facial muscle tension, rapid breathing, etc.); if the user is in a nervous state (physiological indicators show increased facial muscle electrical activity and faster breathing rate), the user's visual focus can be guided along a more soothing and stable path, such as from a fast-flashing complex scene to a slow-moving simple graphic path.

[0020] Regarding the adjustment of the sound field frequency distribution, if the physiological status indicators show that the user is more sensitive to low-frequency sounds or low-frequency sounds can better help the user relax, the distribution density of low-frequency sound sources in the virtual environment can be increased, while the volume and frequency of high-frequency sound sources can be appropriately reduced; further, visual interference elements are inserted and their generation frequency is associated with the user's real-time pupil contraction rate. Specifically, when the user's pupil contraction rate accelerates, the generation frequency of visual interference elements increases. For example, when the pupil contraction rate exceeds 20 times per minute, 3 to 5 interference elements (such as suddenly appearing geometric figures, flashing light spots, etc.) are generated per minute, thereby guiding the user's attention to be distracted, relieving the tense visual attention state, and freeing the user from the tense state of concentration, which helps to relieve headache symptoms, dynamically optimize the way the virtual environment stimulates the user, enhances the user's immersion and relaxation effect, and improves the effectiveness of relaxation training.

[0021] The startup module M300 is used to start the multi-stage headache relaxation training process and simultaneously enhance the vibration feedback intensity of the foot pressure pad if it detects that the facial muscle activity signal exceeds the preset threshold after inserting visual interference elements.

[0022] Specifically, visual interference elements refer to elements inserted into the virtual environment to temporarily interrupt or interfere with the user's visual attention, such as suddenly appearing dynamic graphics, flashing light and shadow, etc.; facial muscle activity signals exceeding the preset threshold means that the intensity of facial muscle electrical activity detected by the electromyography sensor exceeds the preset standard value, which usually means that the user's facial muscles are in a tense state; the multi-stage headache relaxation training process refers to the training steps carried out in stages to relieve headaches; the vibration feedback intensity of the foot pressure pad refers to the intensity of the vibration stimulation applied to the foot through the vibration device. The vibration feedback can produce a massage effect and help relax the body.

[0023] In virtual reality headache relaxation training, when visual interference elements are inserted, the system monitors facial muscle activity signals in real time; once the signal exceeds the preset threshold, for example, the threshold is set to 20μV, when the facial muscle activity signal is detected to reach 30μV, it is judged that the user is in a tense state, and the multi-stage headache relaxation training process is initiated. The first stage is to guide the user to take a deep breath, while presenting a soothing natural scene in the virtual environment; the second stage will guide the user to perform simple head movements in coordination with breathing, etc.

[0024] Synchronously enhance the vibration feedback intensity of the foot pressure pad, for example, increase the vibration frequency from 20 times per second to 30 times per second, and the vibration intensity from 0.5N to 0.8N, so as to promote blood circulation and relieve body tension through foot vibration stimulation; these synergistic effects can help users relax through multiple sensory channels, relieve headaches, respond to users' tension in a timely manner, and improve the effectiveness of relaxation training through the synergistic effect of multi-sensory feedback.

[0025] The optimization management module M400 is used to match the abnormal physiological parameter fluctuation range through cosine similarity according to the changing trend of physiological parameters during the headache relaxation training cycle, set the attention mechanism to strengthen the prodromal characteristics of the attack, generate a state prediction map within the time sliding window, and perform training optimization management.

[0026] Specifically, the headache relaxation training cycle refers to the time period for headache relaxation training, including the start and end time of the training; the physiological parameter change trend refers to the change trend of various physiological parameters (such as heart rate, respiratory rate, skin conductance, etc.) over time during the training cycle; cosine similarity is used to compare whether the fluctuation patterns of physiological parameters in different time periods are similar; the abnormal physiological parameter fluctuation range refers to the time period range during the training cycle when abnormal changes occur in physiological parameters, such as the fluctuation range corresponding to a sudden increase in heart rate and a significant increase in skin conductance.

[0027] The attention mechanism refers to the mechanism used to highlight key features and ignore irrelevant features during data processing; prodromal characteristics refer to some changes in physiological or behavioral characteristics that may occur before a headache attack; the time sliding window refers to a continuous time period of a fixed length selected when analyzing data, which is used to dynamically observe data changes; the state prediction graph predicts the user's future state based on existing physiological parameter data and presents it in a graphical form; training optimization management refers to the process of adjusting and optimizing relaxation training methods, intensity, etc. based on the prediction results and analysis.

[0028] Furthermore, the visual focus guidance path and the sound field frequency distribution in the virtual environment scene are adjusted through adaptive control, and the adaptive control module M200 is further configured to execute the following method:

[0029] Set up the prefrontal cortex signal receiving electrodes to determine Wave and The power ratio of the wave; identify the characteristics of inattention, Wave and When the power ratio of the brainwave increases abnormally, the multi-frequency sound effect unit in the virtual environment scene is activated, and the multi-frequency sound effect unit is used to dynamically adjust the frequency distribution of the sound field until the brainwave synchronization index stabilizes in a preset target range.

[0030] Specifically, the prefrontal cortex signal receiving electrode is a sensor attached to the forehead area of ​​the scalp, used to capture weak electrical signals generated by the prefrontal cortex of the brain; theta wave is a brain wave with a frequency of 4Hz to 8Hz, which is usually associated with states such as relaxation and meditation; beta wave is a brain wave with a frequency of 13Hz to 30Hz, which is usually associated with states such as wakefulness, activity, and concentration; the power ratio refers to the relative relationship between the power of the two waves within a specific time period. By calculating the ratio of theta wave power to the beta wave power, the brain's state balance between relaxation and activity can be reflected.

[0031] When setting up the prefrontal cortex signal receiving electrodes in an application, first determine the electrode placement position. Usually, electrode positions related to the prefrontal region, such as Fp1 and Fp2, are selected to ensure good contact between the electrodes and the scalp to obtain high-quality EEG signals. In actual operation, these brain wave signals can be collected through electroencephalogram (EEG) equipment. For example, in the initial stage of the user's virtual reality headache relaxation training, the brain wave signals of the prefrontal cortex are continuously collected for 5 to 10 minutes, and the sampling frequency is set to 256Hz.

[0032] Through signal processing methods such as Fourier transform, the power of theta waves and beta waves is calculated, and then the power ratio between the two is determined. Data shows that in a relaxed state, the power ratio of theta waves to beta waves is usually between 0.5 and 1.0. When the ratio exceeds 1.2, it indicates that the user is in a state of distraction; when the distraction feature is identified, that is, the power ratio of theta waves to beta waves abnormally increases to 1.5, the system will activate the multi-frequency sound effect unit in the virtual environment scene.

[0033] The working principle of the multi-frequency sound effect unit is to stimulate the brain by generating sound waves of different frequencies to help users adjust their attention state. For example, you can first play soothing background music with a low frequency (40Hz to 60Hz) for 2 minutes, and then gradually increase the high-frequency (80Hz to 120Hz) components. By dynamically adjusting the frequency distribution of the sound field, the user's brain waveform is guided to shift to a more focused and relaxed state.

[0034] During the adjustment process, the EEG Synchrony Index is monitored in real time. This index reflects the degree of synchronization between brainwaves in different brain regions, with a normal range of 0.6 to 0.8. When the EEG Synchrony Index stabilizes within the preset target range, it indicates that the user's attention state has been optimized and the brain is in an ideal balance between relaxation and concentration. In these steps, the training environment is dynamically adjusted based on the real-time state of the brain, improving the effectiveness of relaxation training and making it easier for users to enter a state of relaxation that helps alleviate headaches.

[0035] Furthermore, the adaptive control module M200 is further configured to execute the following method:

[0036] An infrared eye tracker is embedded to capture pupil diameter changes and saccadic motion trajectories; the accumulated degree of visual fatigue is identified through the pupil diameter changes and saccadic motion trajectories, and a visual focus guidance path is generated in combination with the blinking frequency; a gradient color temperature light spot is projected in the virtual environment scene, and the visual focus guidance path is used to guide the eyeball for visual tracking training.

[0037] Specifically, an infrared eye tracker is a device that uses the principle of infrared light reflection to track eye movements; pupil diameter change refers to the change in pupil size under the influence of different lighting conditions, emotional state, degree of concentration and other factors; the saccadic motion trajectory refers to the path taken by the eye when moving rapidly, which can reflect the user's attention shift in the visual scene.

[0038] When using an infrared eye tracker, fix the device in a suitable position to ensure that the distance between the infrared transmitter and the user's eyes meets the usage specifications and the receiver can accurately capture the reflected infrared light signal. After the user enters the virtual environment, the infrared eye tracker starts working, capturing changes in pupil diameter and saccadic motion trajectories. By analyzing changes in pupil diameter, it is found that when the user is in a state of visual fatigue, the pupil diameter will be smaller than the initial state. Analysis of saccadic motion trajectories can reveal the user's visual exploration pattern in the virtual scene. If the amplitude and frequency of saccadic motion become smaller, it may indicate accumulated visual fatigue. The pupil diameter change and saccadic motion trajectory can accurately reflect the user's visual state, providing a key basis for the generation of subsequent visual focus guidance paths, ensuring that visual tracking training can be optimized for the user's actual visual condition.

[0039] The cumulative degree of visual fatigue refers to a quantitative indicator of the gradually increasing degree of visual fatigue of a user during continuous visual activity; the blinking frequency refers to the number of blinks per unit time. The blinking frequency of a normal adult in a quiet state is about 10 times / minute to 20 times / minute; the visual focus guidance path refers to the route set according to the user's visual state to guide the user's eye movement, which is used to help users relieve visual fatigue and optimize the allocation of visual attention.

[0040] Based on the captured data on pupil diameter changes and saccadic motion trajectories, a related visual fatigue assessment model is used to identify the cumulative degree of visual fatigue. For example, by analyzing pupil diameter, the average amplitude of saccadic motion, and blinking frequency, the user can be judged to be in a state of moderate visual fatigue. Based on this data, a visual focus guidance path is generated. In a virtual environment, the visual focus guidance path can be a route that moves along a soothing landscape image or a light spot that moves to the rhythm of soft music. The movement speed of the guidance path can be adjusted according to the user's level of visual fatigue, providing precise relaxation guidance from a visual perspective, improving the targeted training and enhancing the relaxation effect.

[0041] Gradient color temperature light spots refer to light spot areas projected in a virtual environment, where the color temperature gradually changes from warm to cool or from cool to warm. Visual tracking training refers to guiding the user's eyes to move along the visual focus guidance path to improve visual attention and relieve visual fatigue. In a virtual environment scene, gradient color temperature light spots are projected using projection technology or screen display technology, and the brightness of the light spots is controlled to ensure that the light spots are clearly visible but not too glaring. When the user's eyes move along the visual focus guidance path, passing through these gradient color temperature light spots, different color temperatures stimulate the eyes to different degrees. Warm light helps relax the eye muscles, and cool light can improve visual attention. Visual tracking training conducted in this way can not only exercise the user's eye movement ability during the entire headache relaxation training process, but also use color temperature changes to adjust the user's visual state, further enhance the effect of relaxation training, and help relieve headache symptoms caused by visual fatigue.

[0042] Furthermore, the accumulated degree of visual fatigue is identified and combined with the blinking frequency to generate a visual focus guidance path. The adaptive control module M200 is also used to execute the following method:

[0043] The coefficient of variation of the gaze point transfer speed and the coefficient of variation of the blink frequency are recorded to configure a visual fatigue feature vector; and visual focus guidance optimization is performed according to the visual fatigue feature vector to obtain the visual focus guidance path.

[0044] Specifically, the coefficient of variation of the gaze point transfer speed is an indicator that measures the degree of change in the user's gaze point movement speed, reflecting the stability of the user's attention transfer in the visual scene; the coefficient of variation of the blinking frequency is an indicator that measures the degree of change in the user's blinking frequency, which can reflect the change in the user's fatigue level during visual activities; the visual fatigue feature vector integrates multiple feature parameters related to visual fatigue into a vector, which is used to comprehensively evaluate the user's visual fatigue status.

[0045] When recording the coefficient of variation of gaze shift speed, the eye tracking device records the user's gaze position in the virtual environment at a high sampling frequency. The shift speed (the distance the gaze moves per unit time) is calculated, and then its coefficient of variation (the ratio of the standard deviation to the mean) is calculated. The coefficient of variation of gaze shift speed and blink rate are combined to form a visual fatigue feature vector. This quantifies the user's visual fatigue level and provides a basis for subsequent optimization of visual focus guidance. By accurately assessing visual fatigue, more targeted guidance paths can be designed to help users alleviate visual fatigue, thereby improving the effectiveness of relaxation training.

[0046] Visual focus guidance optimization refers to adjusting the path that guides the user's visual attention according to the user's visual fatigue status, so as to relieve visual fatigue and improve the relaxation effect; the visual focus guidance path refers to a route designed in a virtual environment to guide the user's eye movement, guiding the user's visual attention by controlling factors such as the shape, speed, and dwell time of the path.

[0047] The user's visual fatigue degree is judged based on the visual fatigue feature vector; the visual focus guidance path is optimized based on the user's visual fatigue degree; the optimization process includes adjusting the speed of the guidance path, adding appropriate stopping points, changing the complexity of the path, etc. Furthermore, in a virtual environment, the visual focus guidance path can be achieved by displaying a moving cursor, dynamic graphics, or following the guided visual target; the optimized guidance path can be adjusted according to the user's visual fatigue degree, making the user's eye movement more comfortable, reducing the accumulation of visual fatigue, and improving the pertinence and effectiveness of relaxation training.

[0048] Furthermore, the coefficient of variation of the gaze point transfer speed and the coefficient of variation of the blink frequency are recorded to configure a visual fatigue feature vector. The adaptive control module M200 is further used to execute the following method:

[0049] Based on the dynamic lighting unit, a retinal stimulation index is obtained and mapped to a virtual depth of field adjustment grid; and according to the light transmittance of the curtain, a negative feedback association mechanism between the ambient illumination gradient change and the virtual depth of field adjustment grid is established.

[0050] Specifically, a dynamic lighting unit refers to a device that can change the light intensity, color temperature and lighting mode in real time; the retinal stimulation index is a quantitative indicator used to measure the degree of stimulation of the retina by light, which is usually related to factors such as light intensity, wavelength and duration; the virtual depth of field adjustment grid is used to divide the virtual environment space into different depth of field levels, thereby simulating the visual depth changes in the real world.

[0051] In the application, the dynamic lighting unit affects the retinal stimulation index by changing the light intensity and color temperature; by mapping the retinal stimulation index to the virtual depth of field adjustment grid, the depth of field effect of the virtual environment can be dynamically adjusted according to the degree of retinal stimulation. For example, when the retinal stimulation index is high, the depth of field grid levels at long distances will be clearer, and the depth of field grid levels at close distances will be appropriately blurred to reduce visual fatigue; this mapping relationship can adjust the visual effects of the virtual environment in real time according to the user's visual stimulation level in the entire solution, thereby improving the user's visual comfort, especially in long-term virtual reality headache relaxation training, which helps to relieve fatigue and discomfort caused by improper visual stimulation.

[0052] Curtain transmittance refers to the proportion of light that the curtain allows to pass through, usually expressed as a percentage; the ambient illumination gradient change refers to the law of change of light intensity in the environment with spatial position; the negative feedback association mechanism refers to the mechanism that when a certain parameter changes, feedback adjustment is used to make another parameter change in the opposite direction to maintain the balance of the system.

[0053] By measuring the transmittance of the curtains, the gradient change of ambient illumination can be determined; based on this transmittance, a negative feedback association mechanism is established between the gradient change of ambient illumination and the virtual depth of field adjustment grid; when the ambient illumination increases, the dynamic lighting unit automatically reduces the light intensity, reduces the retinal stimulation index, and at the same time adjusts the virtual depth of field adjustment grid to make the distant depth of field grid levels more blurred and the close depth of field grid levels clearer; conversely, when the ambient illumination decreases, the dynamic lighting unit appropriately increases the light intensity, improves the retinal stimulation index, and adjusts the virtual depth of field adjustment grid to make the distant depth of field grid levels clearer and the close depth of field grid levels more blurred; this negative feedback mechanism can dynamically adjust the visual effects of the virtual environment according to the ambient lighting conditions, ensuring that users can obtain a comfortable visual experience in different lighting environments and ensuring the effectiveness of headache relaxation training.

[0054] Furthermore, if Figure 2 As shown, the adaptive control module M200 is also used to execute the following method:

[0055] Connect to the neck massager via Bluetooth. When it detects that the trapezius muscle hardness index exceeds the standard, the thermal magnetic pulse and breathing guidance animation are synchronously started. At the same time, according to the heart rate variability data, the neck massage intensity and frequency are dynamically adjusted to match the massage rhythm with the user's breathing rate, configuring a resonant relaxation effect.

[0056] Specifically, the trapezius muscle hardness index measures the hardness of the trapezius muscle through the bioelectrical impedance principle or pressure sensor, and is used to evaluate the tension of the neck muscles; thermal magnetic pulse is a physical therapy method that combines heat therapy and magnetic therapy, which promotes blood circulation and relieves muscle tension by generating thermal and magnetic effects; breathing guidance animation refers to an animation displayed in a virtual environment that guides users to perform specific breathing patterns, such as deep breathing, abdominal breathing, etc.

[0057] The neck massager is connected to the virtual reality device via Bluetooth to ensure the real-time and stable data transmission; when the trapezius muscle hardness index detection device (such as the pressure sensor embedded in the massager) detects that the trapezius muscle hardness index exceeds the standard, the system automatically triggers the thermal magnetic pulse device and the breathing guidance animation; the thermal magnetic pulse device generates pulses, and at the same time, the breathing guidance animation is displayed in the virtual environment to guide the user to perform deep breathing exercises; through the combination of physical therapy and breathing regulation, the neck muscle tension is effectively relieved, the headache symptoms caused by muscle tension are alleviated, and the comprehensiveness and effectiveness of relaxation training are improved.

[0058] Heart rate variability refers to the changes in the differences between successive heartbeats, reflecting the regulatory function of the autonomic nervous system on the heart; massage intensity refers to the force applied by the neck massager to the neck; massage frequency refers to the number of times the massage action is repeated per minute; and the resonance relaxation effect refers to the phenomenon of enhanced relaxation effect produced when the massage rhythm matches the user's breathing rate.

[0059] During the massage, heart rate variability data is collected in real time using a heart rate variability monitoring device (such as a pulse sensor worn on a finger or earlobe). If heart rate variability analysis indicates a state of tension (e.g., decreased high-frequency components and increased low-frequency components), the system dynamically adjusts the intensity and frequency of the neck massage. This adjustment synchronizes the massage movements with the user's breathing rhythm, creating a resonant relaxation effect. In this process, massage parameters are dynamically adjusted based on the user's physiological state, enhancing the relaxation effect, optimizing the training experience, and increasing the success rate of headache relief.

[0060] Furthermore, the adaptive control module M200 is further configured to execute the following method:

[0061] An IMU array is set up to track the neck rotation angle and scapula displacement trajectory in real time to identify abnormal muscle compensation patterns. If the sternocleidomastoid muscle activation exceeds the standard, a virtual mirror correction instruction is generated to guide the muscle group force using the abnormal muscle compensation pattern.

[0062] Specifically, an IMU (Inertial Measurement Unit) array typically includes accelerometers, gyroscopes, and magnetometers, which are used to measure the motion state of an object in real time. The IMU array is attached to the user's neck and shoulders to track the neck rotation angle and scapula displacement trajectory. The neck rotation angle refers to the degree of rotation of the neck in different directions (such as left and right rotation, forward and backward flexion and extension), usually expressed in degrees. The scapula displacement trajectory refers to the path of position changes of the scapula during movement, reflecting the activity of the shoulder muscles. Abnormal muscle compensation pattern refers to the abnormal compensatory activity pattern of other muscles due to excessive tension or fatigue of certain muscles, which may aggravate muscle tension and pain.

[0063] Data is collected in real time using each unit of the IMU array, and acceleration, angular velocity, and magnetic field data are converted into neck rotation angles and scapula displacement trajectories. By analyzing these data and combining them with pre-set normal muscle activity patterns, abnormal muscle compensation patterns are identified. For example, when one trapezius muscle is overly tense, it causes excessive displacement of the contralateral scapula. This abnormal pattern can be identified through the changing characteristics of the IMU data. The user's neck and shoulder muscle activity status is monitored in real time to provide an accurate basis for subsequent muscle correction and relaxation training. By identifying abnormal muscle compensation patterns, targeted corrective training is designed to help users restore normal muscle activity patterns, relieve muscle tension, and thus alleviate headache symptoms.

[0064] The sternocleidomastoid muscle is a neck muscle whose activation degree can be measured by surface electromyography sensors, reflecting the tension of the muscle; virtual mirror correction instructions refer to instructions generated in a virtual environment to guide users in muscle correction, usually presented in the form of mirror feedback, allowing users to intuitively see their muscle activity and make adjustments; muscle group force guidance refers to helping users use relevant muscle groups correctly through guidance to avoid abnormal muscle compensation patterns.

[0065] When the activation degree of the sternocleidomastoid muscle exceeds the set threshold, it is determined that the sternocleidomastoid muscle is in an over-tense state. At this time, a virtual mirror correction instruction is generated, and a mirror image of the user's neck and shoulders is displayed in a virtual environment. At the same time, the activation status of the sternocleidomastoid muscle and other related muscles is highlighted with different colors or graphics. For example, over-tense muscles are displayed in yellow, and muscles in normal state are displayed in green.

[0066] Based on the identified abnormal muscle compensation pattern, muscle group force guidance is provided, such as instructing users to perform specific neck stretching and relaxation movements, while the correct muscle force sequence and degree are displayed on the mirror image; the guidance process can be combined with voice prompts and animation demonstrations. For example, the voice prompts the user to "slowly tilt your head to the left and feel the stretch of the right sternocleidomastoid muscle", while the mirror image shows the corresponding action demonstration; helping users to intuitively understand their muscle status, correct abnormal muscle compensation patterns through virtual mirror feedback and muscle group force guidance, and promote muscle balance and relaxation. This not only helps to relieve current headache symptoms, but also prevents chronic headache problems caused by long-term muscle tension, and improves the targetedness and effectiveness of training.

[0067] Furthermore, the adaptive control module M200 is further configured to execute the following method:

[0068] The electromagnetic damping coefficient of the training resistor will be adjusted in real time according to the correction needs, and the sample distribution characteristics of the headache attack period and the headache remission period will be analyzed; based on the sample distribution characteristics of the headache attack period and the headache remission period, the difference factors of the muscle movement state between the headache attack period and the headache remission period are extracted; through the physiological state indicators, the difference factors of the human physiological parameters between the headache attack period and the headache remission period are extracted; based on the muscle movement state difference factors and the human physiological parameter difference factors, a multi-task learning framework is configured, and the multi-task learning framework uses risk classification and attack duration prediction as joint optimization goals for optimization training.

[0069] Specifically, the electromagnetic damping coefficient refers to the parameter that affects the size of the electromagnetic damping, which determines the resistance generated by the training resistor to muscle movement; by real-time monitoring of the user's muscle state and dynamically adjusting the coefficient according to correction needs, it can provide users with more accurate muscle training, help alleviate and correct headaches caused by muscle tension or abnormal movement patterns; analyze data samples during headache attacks and relief periods, and extract differences in muscle movement states between headache attacks and relief periods, as well as differences in human physiological parameters between headache attacks and relief periods. Differences in muscle movement states and human physiological parameters help to understand the mechanism of headache occurrence, thereby providing a basis for formulating more effective headache management and rehabilitation strategies.

[0070] Based on the extracted differential factors, a multi-task learning framework is configured to simultaneously achieve risk stratification and attack duration prediction; through optimized training, the model's prediction accuracy is improved to provide support for personalized treatment and management of headaches; through real-time monitoring of the user's muscle state and physiological parameters, combined with data analysis and machine learning technology, personalized training plan optimization is achieved, the targetedness and effectiveness of relaxation training are improved, and help alleviate headache symptoms.

[0071] In summary, the beneficial effects of the embodiments of the present application are:

[0072] The data collection module is used to construct a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collect the target user's eye movement data, facial muscle activity signals and breathing rate parameters, and set physiological state indicators; the adaptive control module is used to adjust the visual focus guidance path and sound field frequency distribution in the virtual environment scene through adaptive control based on the physiological state indicators, and insert visual interference elements, wherein the generation frequency of the visual interference elements is associated with the user's real-time pupil contraction rate; the startup module is used to start the multi-stage headache relaxation training process after inserting the visual interference elements, if the facial muscle activity signal is detected to exceed the preset threshold, and simultaneously enhance the vibration feedback intensity of the foot pressure pad; The optimization management module is used to match the abnormal physiological parameter fluctuation range through cosine similarity according to the changing trend of physiological parameters during the headache relaxation training cycle, set the attention mechanism to strengthen the prodromal period characteristics of the attack, generate a state prediction map within the time sliding window, and perform training optimization management. This application provides a headache relaxation training management system based on virtual reality, constructs a virtual reality environment according to the potential pain mechanism of headache, adaptively controls and adjusts the visual focus guidance path and sound field frequency distribution in the virtual environment scene, sets the attention mechanism to strengthen the prodromal period characteristics of the attack, and generates a state prediction map within the time sliding window, thereby better adapting to individual differences of users and improving the technical effect of the targetedness and effectiveness of relaxation training.

[0073] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory and can be called and recognized by an unlimited computer processor, without any unnecessary restrictions.

[0074] Furthermore, the above technical solution only reflects the preferred technical solution of the technical solution of the embodiment of the present application. Some changes that may be made to certain parts thereof by technical personnel in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technical personnel in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. Headache relaxation training management system based on virtual reality, characterized by: include: The data collection module is used to build a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collect the target user's eye movement data, facial muscle activity signals and breathing rate parameters, and set physiological status indicators; an adaptive control module, configured to adaptively adjust the visual focus guidance path and the sound field frequency distribution in the virtual environment scene based on the physiological state indicator, and insert visual interference elements, wherein the generation frequency of the visual interference elements is associated with the user's real-time pupil contraction rate; The activation module is used to start the multi-stage headache relaxation training process and simultaneously increase the vibration feedback intensity of the foot pressure pad if the facial muscle activity signal detected exceeds the preset threshold after the visual interference element is inserted; The optimization management module is used to match abnormal physiological parameter fluctuation ranges based on the changing trends of physiological parameters during the headache relaxation training cycle through cosine similarity, set an attention mechanism to strengthen the prodromal characteristics of the attack, generate a state prediction map within the time sliding window, and perform training optimization management; The step of adjusting the visual focus guidance path and the sound field frequency distribution in the virtual environment scene through adaptive control includes: Set up the prefrontal cortex signal receiving electrodes to determine Wave and The power ratio of the waves; Identify the characteristics of inattention. Wave and When the power ratio of the brainwave increases abnormally, a multi-frequency sound effect unit in the virtual environment scene is activated, and the multi-frequency sound effect unit is used to dynamically adjust the frequency distribution of the sound field until the brainwave synchronization index stabilizes in a preset target range; The system is used to perform the following method: Embedded infrared eye tracker to capture pupil diameter changes and saccadic movement trajectories; The accumulated degree of visual fatigue is identified through the pupil diameter change and the scanning motion trajectory, and the visual focus guidance path is generated in combination with the blinking frequency; A light spot with a gradually changing color temperature is projected in the virtual environment scene, and the eyeball is guided to perform visual tracking training using the visual focus guide path.

2. The virtual reality-based headache relaxation training management system according to claim 1, characterized in that: Identify the accumulated degree of visual fatigue, combine it with the blink frequency, and generate a visual focus guidance path, including: Record the coefficient of variation of gaze point transfer speed and blink frequency, and configure the visual fatigue feature vector; Visual focus guidance optimization is performed according to the visual fatigue feature vector to obtain the visual focus guidance path.

3. The virtual reality-based headache relaxation training management system according to claim 2, characterized in that: Record the coefficient of variation of gaze point transfer speed and blink frequency, and configure the visual fatigue feature vector, including: Based on the dynamic illumination unit, a retinal stimulation index is obtained, and the retinal stimulation index is mapped to a virtual depth of field adjustment grid; According to the light transmittance of the curtain, a negative feedback association mechanism is established between the ambient illumination gradient change and the virtual depth of field adjustment grid.

4. The virtual reality-based headache relaxation training management system according to claim 3, characterized in that: Also includes: Connect to the neck massager via Bluetooth, and when it detects that the trapezius muscle hardness index exceeds the standard, it will simultaneously start the thermal magnetic pulse and breathing guidance animation; At the same time, based on the heart rate variability data, the neck massage intensity and frequency are dynamically adjusted, the massage rhythm is matched with the user's breathing rate, and a resonant relaxation effect is configured.

5. The virtual reality-based headache relaxation training management system according to claim 4, characterized in that: include: Set up an IMU array to track neck rotation angle and scapula displacement trajectory in real time to identify abnormal muscle compensation patterns; If the activation degree of the sternocleidomastoid muscle exceeds the standard, a virtual mirror correction instruction is generated to guide the muscle group to exert force using the abnormal muscle compensation mode.

6. The virtual reality-based headache relaxation training management system according to claim 5, characterized in that: Also includes: The electromagnetic damping coefficient of the training resistor will be adjusted in real time according to the correction needs, and the distribution characteristics of samples during the headache attack period and the headache relief period will be analyzed; Extracting the difference factors of muscle movement state between the headache attack period and the headache relief period based on the distribution characteristics of the samples during the headache attack period and the distribution characteristics of the samples during the headache relief period; Extracting the difference factors of human physiological parameters between the headache attack period and the headache relief period through the physiological state indicators; A multi-task learning framework is configured based on the differences in muscle movement states and human physiological parameters. The multi-task learning framework performs optimization training with risk classification and seizure duration prediction as joint optimization objectives.

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