Headache relaxation training management system based on virtual reality

Abstract

The invention relates to the related technical field of training management, in particular to a headache relaxation training management system based on virtual reality, which comprises a data collection module for constructing a scene and collecting physiological data; the self-adaptive control module adjusts the scene according to indexes; the starting module starts training and enhances feedback under specific conditions; and the optimization management module analyzes the trend, strengthens the characteristics of the forward driving period, generates a prediction map and optimizes training, so that the technical problems that headache types, inducements, pain degrees and accompanying symptoms of users are different and the effectiveness of headache relaxation training is insufficient are solved, a virtual reality environment is constructed according to a potential pain mechanism of headache, and the user experience is improved. The technical effects of adaptively controlling and adjusting a visual focus guide path and sound field frequency distribution in a virtual environment scene, setting an attention mechanism to strengthen the characteristics of the attack proactive period, and generating a state prediction map in a time sliding window, so as to better adapt to the individual difference of users, and improve the pertinence and effectiveness of relaxation training are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of training management, and particularly 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 means in the treatment of acute and chronic pain. However, there are some deficiencies in the existing virtual reality-based pain treatment methods. Commonly, a one-size-fits-all paradigm is adopted, ignoring the potential of customizing virtual reality environments based on specific underlying pain mechanisms, resulting in reduced treatment effects, and may even lead to symptom exacerbation, lack of participation, safety issues (such as not being tailored to specific physical limitations), and negative psychological impacts, affecting the effectiveness of VR interventions for chronic pain. In addition, traditional pain management methods mainly include drug treatment and physical therapy, but these methods have limitations such as drug dependence, large side effects, and unstable effects.

[0003] In summary, there are technical problems in the prior art that the headache types, causes, pain degrees, and accompanying symptoms of users vary, and the effectiveness of headache relaxation training is insufficient. Summary of the Invention

[0004] This application provides a headache relaxation training management system based on virtual reality, aiming to solve the technical problems in the prior art that the headache types, causes, pain degrees, and accompanying symptoms of users vary, and the effectiveness of headache relaxation training is insufficient.

[0005] In view of the above problems, the technical solution of this application is as follows: This application provides a headache relaxation training management system based on virtual reality. Among them, 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 the eye movement data, facial muscle activity signals, and respiratory frequency parameters of the target user, and setting physiological state indicators; an adaptive control module for, based on the physiological state indicators, adjusting the visual focus guidance path and sound field frequency distribution in the virtual environment scene through adaptive control, and inserting visual interference elements, wherein the generation frequency of the visual interference elements is associated with the real-time pupil contraction rate of the user; a start module for, after inserting the visual interference elements, if it detects that the facial muscle activity signal exceeds a preset threshold, starting a multi-stage headache relaxation training process and synchronously enhancing the vibration feedback intensity of the foot pressure pad; an optimization management module for, according to the change trend of physiological parameters during the headache relaxation training cycle, setting an attention mechanism to strengthen the prodromal period characteristics by matching abnormal physiological parameter fluctuation intervals through cosine similarity, generating a state prediction map within a time sliding window, and performing training optimization management.

[0006] In summary, for one or more technical solutions provided in this application, a virtual reality environment is constructed according to the potential pain mechanism of headache, the visual focus guiding path and the sound field frequency distribution in the virtual environment scene are adaptively controlled and adjusted, an attention mechanism is set to strengthen the characteristics of the prodromal period, and a state prediction map within a time sliding window is generated, so as to better adapt to individual differences of users and improve the pertinence and effectiveness of relaxation training. Description of the Drawings

[0007] Figure 1 This application provides a schematic structural diagram of a headache relaxation training management system based on virtual reality; Figure 2 This application provides a schematic flowchart of configuring resonance relaxation effect for an adaptive control module of a headache relaxation training management system based on virtual reality.

[0008] Description of the reference numerals: data collection module M100, adaptive control module M200, start module M300, optimization management module M400. Detailed Embodiments Embodiment

[0009] The following specifically describes this application with reference to the drawings. As Figure 1 shown, this application provides a headache relaxation training management system based on virtual reality, wherein the system includes: A data collection module M100, configured to construct a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collect eye movement data, facial muscle activity signals and breathing frequency parameters of a target user, and set physiological state indicators.

[0010] Specifically, the dynamic lighting unit refers to a lighting component that can change the lighting intensity, color temperature and distribution mode according to real-time data or a preset program; the multi-frequency sound effect unit is an audio device that can generate sounds with different frequencies, rhythms and volumes; collecting eye movement data mainly records information such as the movement trajectory, fixation points, and saccade speed of the eyeballs through eye tracking technology; the detection of facial muscle activity signals generally uses surface electromyography sensors attached to relevant facial muscle areas to capture muscle electrical activity to reflect the activity state of the muscles; the breathing frequency parameter is usually determined by measuring the chest or abdominal undulation frequency through a breathing sensor (such as a respiratory inductance plethysmograph, a pressure sensor, etc.); the physiological state indicator refers to a set of quantitative criteria formed by integrating multi-faceted data such as eyes, facial muscles and breathing to measure the current physiological condition of the user.

[0011] When constructing a virtual environment scene, the dynamic lighting unit can simulate various lighting environments, such as from bright to dim, from cold light to warm light, etc.; the multi-frequency sound effect unit can play sound effects of different styles, from low frequency to high frequency, from soothing to intense, creating an immersive multi-sensory experience environment for users. Specifically, collecting eye movement data can understand the distribution of users' visual attention. For example, when a user gazes at a specific area, data such as dwell time and scan frequency can reflect their degree of interest in that area; facial muscle activity signals can indirectly reflect the user's emotional state. For example, when the facial muscle tension increases, correspondingly, the user is in a tense or uncomfortable state; the breathing frequency parameter is one of the important indicators to measure the user's relaxation level. The breathing frequency of a normal adult is generally between 12 and 20 breaths per minute.

[0012] Setting physiological state indicators is to integrate and quantify these 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 comprehensively understanding the user's physiological state and accurately constructing a virtual environment suitable for the user's individual, so as to improve the pertinence of relaxation training.

[0013] The adaptive control module M200 is used to, based on the physiological state indicators, adjust the visual focus guiding path and sound field frequency distribution in the virtual environment scene through adaptive control, and insert visual interference elements, where the generation frequency of the visual interference elements is associated with the user's real-time pupil constriction rate.

[0014] Specifically, adaptive control is a control strategy that can automatically adjust system parameters or behaviors according to real-time feedback information; the visual focus guiding 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 positions in the virtual environment space; the visual interference elements are elements added to the visual scene to interfere with the user's visual attention, and their generation frequency is associated with the user's real-time pupil constriction rate, which means controlling the frequency of appearance of these interference elements according to the speed of pupil constriction; the pupil constriction rate can be monitored by an eye movement tracking device and can reflect the user's attention concentration to a certain extent.

[0015] When performing adaptive control based on physiological state indicators, taking the visual focus guiding path as an example, the system will adjust the shape, speed, and direction of the guiding 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 tense state (physiological indicators show increased facial muscle electrical activity and increased breathing frequency), the user's visual focus can be guided to move along a more soothing and stable path, such as guiding from a rapidly flashing complex scene to a slowly moving simple graphic path.

[0016] For the adjustment of the sound field frequency distribution, if the physiological state index shows 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, and at the same time, the volume and appearance 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 the 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 points, etc.) are generated per minute, thereby guiding the user's attention to disperse, relieving the tense visual attention state, enabling the user to break free from the tense state of concentrated attention, helping to relieve headache symptoms, dynamically optimizing the stimulation method of the virtual environment on the user, enhancing the user's immersion and relaxation effect, and improving the effectiveness of relaxation training.

[0017] The activation module M300 is used to, after inserting the visual interference elements, if it detects that the facial muscle activity signal exceeds the preset threshold, activate the multi-stage headache relaxation training process and synchronously enhance the vibration feedback intensity of the foot pressure pad.

[0018] Specifically, the visual interference elements refer to the elements inserted in 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.; the facial muscle activity signal exceeding the preset threshold means that the intensity of the facial muscle electrical activity detected by the electromyography sensor exceeds the pre-set standard value, usually indicating 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 headache; the vibration feedback intensity of the foot pressure pad refers to the intensity of the vibration stimulation applied to the foot by the vibration device, and the vibration feedback can produce a massage effect, which helps to relax the body.

[0019] In the virtual reality headache relaxation training, after the visual interference elements are inserted, the system monitors the facial muscle activity signal in real time; once this signal exceeds the preset threshold, for example, the threshold is set at 20 μV, when the facial muscle activity signal is detected to reach 30 μV, it is determined that the user is in a tense state. At this time, the multi-stage headache relaxation training process is activated. The first stage is to guide the user to take a deep breath, and at the same time present 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.

[0020] Synchronously enhance the vibration feedback intensity of the foot pressure pad, such as increasing the vibration frequency from 20 times per second to 30 times per second and the vibration intensity from 0.5 N to 0.8 N, promoting blood circulation through foot vibration stimulation and relieving body tension; these synergistic effects can help the user relax from multiple sensory channels, relieve headache, respond to the user's tense state in a timely manner, and improve the effectiveness of relaxation training through the synergistic effect of multi-sensory feedback.

[0021] The optimization management module M400 is used to, according to the variation trend of physiological parameters within the headache relaxation training cycle, match the abnormal physiological parameter fluctuation range through cosine similarity, set an attention mechanism to strengthen the features in the pre-ictal period, generate a state prediction graph within a time sliding window, and perform training optimization management.

[0022] Specifically, the headache relaxation training cycle refers to the time interval during which headache relaxation training is carried out, including the start time and end time of the training; the variation trend of physiological parameters refers to the change direction of various physiological parameters (such as heart rate, respiratory rate, skin conductance, etc.) over time within the training cycle; cosine similarity is used to compare whether the physiological parameter fluctuation patterns in different time periods are similar; the abnormal physiological parameter fluctuation range refers to the time period range in which physiological parameters show abnormal changes within the training cycle, such as the fluctuation range corresponding to a sudden increase in heart rate or a significant increase in skin conductance.

[0023] The attention mechanism refers to a mechanism used to highlight key features and ignore irrelevant features during data processing; the features in the pre-ictal period refer to some physiological or behavioral feature changes that may occur before a headache attack; the time sliding window refers to a continuous time period of a fixed duration selected when analyzing data, used to dynamically observe data changes; the state prediction graph is to predict the user's future state based on the existing physiological parameter data and present it in a graphical manner; the training optimization management refers to the process of adjusting and optimizing the relaxation training method, intensity, etc. according to the prediction results and analysis situation.

[0024] Furthermore, the visual focus guiding path and sound field frequency distribution in the virtual environment scene are adjusted through adaptive control. The adaptive control module M200 is also used to execute the following method: Set the signal receiving electrodes in the prefrontal cortex and determine the power ratio of wave and wave; identify the feature of distracted attention. When the power ratio of wave and wave abnormally increases, start the multi-frequency sound effect unit in the virtual environment scene. The multi-frequency sound effect unit is used to dynamically adjust the sound field frequency distribution until the brain wave synchronization index stabilizes within a preset target range. wave abnormally increases, start the multi-frequency sound effect unit in the virtual environment scene. The multi-frequency sound effect unit is used to dynamically adjust the sound field frequency distribution until the brain wave synchronization index stabilizes within a preset target range.

[0025] Specifically, the prefrontal cortex signal receiving electrode is a sensor attached to the forehead area of the scalp for capturing weak electrical signals generated by the prefrontal cortex of the brain; theta wave is an electroencephalogram with a frequency of 4 Hz to 8 Hz, usually associated with states such as relaxation and meditation; beta wave is an electroencephalogram with a frequency of 13 Hz to 30 Hz, usually associated with states such as wakefulness, activity, and concentration; the power ratio refers to the relative relationship between the power magnitudes of two waves within a specific time period. By calculating the ratio of the theta wave power to the beta wave power, the state balance between relaxation and activity of the brain can be reflected.

[0026] When applying and setting the prefrontal cortex signal receiving electrode, first determine the electrode placement position. Usually, electrode positions related to the prefrontal areas such as Fp1 and Fp2 are selected to ensure good contact between the electrode and the scalp to obtain high-quality electroencephalogram signals. In actual operation, these electroencephalogram signals can be collected through an electroencephalogram (EEG) device. Exemplarily, in the initial stage of the user's virtual reality headache relaxation training, continuously collect the electroencephalogram signals of the prefrontal cortex for a duration of 5 to 10 minutes, and set the sampling frequency to 256 Hz.

[0027] Through signal processing methods such as Fourier transform, calculate the power magnitudes of the theta wave and the beta wave, and then determine the power ratio between the two. Data shows that the power ratio of the theta wave to the beta wave is usually between 0.5 and 1.0 in the relaxed state. When the ratio exceeds 1.2, it indicates that the user is in a state of distracted attention. When the feature of distracted attention is recognized, that is, when the power ratio of the theta wave to the beta wave abnormally increases to 1.5, the system will activate the multi-frequency sound effect unit in the virtual environment scene.

[0028] The working principle of the multi-frequency sound effect unit is to stimulate the brain by generating sound waves of different frequencies to help the user adjust the attention state. For example, first play soothing background music with a low frequency (40 Hz to 60 Hz) for 2 minutes, and then gradually increase the high-frequency (80 Hz to 120 Hz) component. By dynamically adjusting the frequency distribution of the sound field, guide the brain waveform of the user to a more concentrated and relaxed state.

[0029] During the adjustment process, the electroencephalogram synchronization index is monitored in real time. The electroencephalogram synchronization index reflects the synchronization degree of electroencephalograms in different regions of the brain, and the normal value range is between 0.6 and 0.8. When the electroencephalogram synchronization index stabilizes within the preset target range, it indicates that the user's attention state has been optimized, and the brain is in a relatively ideal state of balance between relaxation and concentration. In the above steps, accurately adjust the training environment according to the real-time state of the brain to improve the effect of relaxation training and make it easier for the user to enter a relaxed state that helps relieve headaches.

[0030] Furthermore, the adaptive control module M200 is also used to execute the following method: Embed an infrared eye tracker to capture the changes in pupil diameter and saccade movement trajectories; identify the cumulative degree of visual fatigue based on the changes in pupil diameter and saccade movement trajectories, and combine with the blink frequency to generate a visual focus guidance path; project a gradually changing color temperature light spot in the virtual environment scene, and use the visual focus guidance path to guide the eyeball for visual tracking training.

[0031] Specifically, an infrared eye tracker is a device that uses the principle of infrared light reflection to track eye movements; the change in pupil diameter refers to the change in pupil size under the influence of factors such as different lighting conditions, emotional states, and attention levels; the saccade movement trajectory refers to the path that the eyeball passes through during rapid movement, which can reflect the user's attention transfer in the visual scene.

[0032] When applying the infrared eye tracker, fix the device in a suitable position to ensure that the distance between the infrared emitter 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 scene, the infrared eye tracker starts to work, capturing the changes in pupil diameter and saccade movement trajectories; by analyzing the changes in pupil diameter, it is found that when the user is in a state of visual fatigue, the pupil diameter will shrink compared to the initial state; the analysis of the saccade movement trajectory can reveal the user's visual exploration pattern in the virtual scene. If the amplitude and frequency of saccade movements decrease, it may indicate the accumulation of visual fatigue; the changes in pupil diameter and saccade movement trajectories can accurately reflect the user's visual state, providing a key basis for the subsequent generation of the visual focus guidance path, ensuring that the visual tracking training can be optimized according to the user's actual visual condition.

[0033] The cumulative degree of visual fatigue is a quantitative index that reflects the gradual increase in the degree of visual fatigue during the user's continuous visual activity; the blink frequency refers to the number of blinks per unit time. The blink frequency of normal adults is about 10 to 20 times per minute in a quiet state; the visual focus guidance path is a route set according to the user's visual state to guide the movement of the user's eyeball, which is used to help the user relieve visual fatigue and optimize visual attention allocation.

[0034] Based on the captured data of changes in pupil diameter and saccade movement trajectories, use relevant visual fatigue assessment models to identify the cumulative degree of visual fatigue. For example, by analyzing and finding the pupil diameter and the average amplitude of saccade movements, combined with the blink frequency, it is determined that the user is in a state of moderate visual fatigue. Generate a visual focus guidance path based on these data. In the virtual environment, the visual focus guidance path can be a route that moves along a soothing landscape picture, or a trajectory of light points that changes with the rhythm of gentle music; the moving speed of the guidance path can be adjusted according to the user's degree of visual fatigue, providing precise relaxation guidance to the user from a visual perspective, improving the pertinence of training and enhancing the relaxation effect.

[0035] A gradient color temperature light spot refers to a light spot area in a virtual environment where the color temperature of the projected light gradually changes from warm color to cold color or from cold color to warm color; visual tracking training refers to guiding the user's eyes to move along the visual focus guiding path to improve visual attention and relieve visual fatigue; in a virtual environment scene, projection technology or screen display technology is used to project gradient color temperature light spots and control the light spot brightness to ensure that the light spots are clearly visible but not too dazzling; when the user's eyes move along the visual focus guiding path and pass through these gradient color temperature light spots, different color temperatures have different degrees of stimulation to the eyes. Warm light helps relax the eye muscles, and cold light can improve visual attention; through this method of visual tracking training, during the entire headache relaxation training process, not only can the user's eye movement ability be exercised, but also the user's visual state can be adjusted using the color temperature change, further enhancing the effect of the relaxation training and helping to relieve headache symptoms caused by visual fatigue.

[0036] Furthermore, to identify the cumulative degree of visual fatigue and combine it with the blink frequency to generate a visual focus guiding path, the adaptive control module M200 is further configured to execute the following method: Record the coefficient of variation of the fixation point transfer speed and the coefficient of variation of the blink frequency, and configure a visual fatigue feature vector; optimize the visual focus guidance based on the visual fatigue feature vector to obtain the visual focus guiding path.

[0037] Specifically, the coefficient of variation of the fixation point transfer speed is an index to measure the degree of change in the movement speed of the user's fixation point, reflecting the stability of the user's attention transfer in the visual scene; the coefficient of variation of the blink frequency is an index to measure the degree of change in the user's blink frequency, which can reflect the change in the fatigue degree of the user during visual activities; the visual fatigue feature vector is to integrate multiple feature parameters related to visual fatigue into a vector for comprehensively evaluating the user's visual fatigue state.

[0038] When recording the coefficient of variation of the fixation point transfer speed, the eye movement tracking device is used to record the position of the user's fixation point in the virtual environment at a high sampling frequency, calculate the transfer speed (the distance that the fixation point moves per unit time), and then calculate its coefficient of variation (the ratio of the standard deviation to the average value); combine the coefficient of variation of the fixation point transfer speed and the coefficient of variation of the blink frequency to form a visual fatigue feature vector; quantify the user's visual fatigue degree to provide a basis for subsequent optimization of the visual focus guidance. By accurately evaluating visual fatigue, the guiding path can be designed more targeted to help the user relieve visual fatigue, thereby improving the effect of the relaxation training.

[0039] Visual focus guidance optimization refers to adjusting the path that guides the movement of the user's visual attention according to the user's visual fatigue state, 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 movement of the user's eyeballs, and by controlling factors such as the shape, speed, and dwell time of the path, the user's visual attention is guided.

[0040] According to the visual fatigue feature vector, judge the degree of the user's visual fatigue; according to the degree of the user's visual fatigue, optimize the visual focus guidance path; the optimization process includes adjusting the speed of the guidance path, adding appropriate stop points, changing the complexity of the path, etc. Further, in the virtual environment, the visual focus guidance path can be realized by displaying a moving cursor, a dynamic graphic, or a visual target following the guidance, etc.; the optimized guidance path can be adjusted according to the degree of the user's visual fatigue, making the user's eye movement more comfortable, reducing the accumulation of visual fatigue, and improving the pertinence and effectiveness of relaxation training.

[0041] Further, record the coefficient of variation of the fixation point transfer speed and the coefficient of variation of the blink frequency, configure the visual fatigue feature vector, and the adaptive control module M200 is also used to execute the following method: Based on the dynamic lighting unit, obtain the retinal stimulation index and map the retinal stimulation index to the virtual depth-of-field adjustment grid; establish a negative feedback correlation mechanism between the environmental illuminance gradient change and the virtual depth-of-field adjustment grid according to the curtain light transmittance.

[0042] Specifically, the 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 index used to measure the degree of stimulation of light on the retina, 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, so as to simulate the visual depth change in the real world.

[0043] In the application, the dynamic lighting unit affects the retinal stimulation index by changing the light intensity and color temperature; mapping the retinal stimulation index to the virtual depth-of-field adjustment grid can realize dynamically adjusting the depth-of-field effect of the virtual environment according to the degree of retinal stimulation. For example, when the retinal stimulation index is relatively high, the depth-of-field grid levels in the distance become clearer, and the depth-of-field grid levels in the near distance are appropriately blurred to relieve visual fatigue; this mapping relationship can adjust the visual effect of the virtual environment in real time according to the degree of visual stimulation of the user in the whole scheme, improving the visual comfort of the user. Especially in the long-term virtual reality headache relaxation training, it helps to relieve the fatigue and discomfort caused by improper visual stimulation.

[0044] The light transmittance of the curtain refers to the proportion of light that the curtain allows to pass through, usually expressed as a percentage; the environmental illuminance gradient change refers to the law of the change of light intensity in the environment with the change of spatial position; the negative feedback correlation mechanism refers to the mechanism that when a certain parameter changes, through feedback regulation, another parameter changes in the opposite direction to maintain the balance of the system.

[0045] By measuring the light transmittance of the curtain, the environmental illuminance gradient change can be determined; based on this light transmittance, a negative feedback correlation mechanism between the environmental illuminance gradient change and the virtual depth-of-field adjustment grid is established; when the environmental illuminance 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 long-distance depth-of-field grid levels become more blurred and the short-distance depth-of-field grid levels become clearer; conversely, when the environmental illuminance decreases, the dynamic lighting unit appropriately increases the light intensity, increases the retinal stimulation index, and adjusts the virtual depth-of-field adjustment grid to make the long-distance depth-of-field grid levels become clearer and the short-distance depth-of-field grid levels become more blurred; this negative feedback mechanism can dynamically adjust the visual effect of the virtual environment according to the environmental lighting conditions, ensuring that users can obtain a comfortable visual experience in different lighting environments and guaranteeing the effect of headache relaxation training.

[0046] Furthermore, as Figure 2 shown, the adaptive control module M200 is also used to execute the following method: Connect the neck massager through Bluetooth. When it detects that the trapezius muscle hardness index exceeds the standard, it synchronously activates the thermomagnetic pulse and the breathing guidance animation; at the same time, according to the heart rate variability data, it dynamically adjusts the neck massage intensity and massage frequency, matches the massage rhythm with the user's breathing frequency, and configures the resonance relaxation effect.

[0047] Specifically, the trapezius muscle hardness index measures the hardness degree of the trapezius muscle through the principle of bioelectrical impedance or a pressure sensor, and is used to evaluate the tension state of the neck muscles; the thermomagnetic pulse is a physical therapy method that combines heat therapy and magnetic therapy, and promotes blood circulation and relieves muscle tension by generating heat effects and magnetic effects; the breathing guidance animation refers to the animation displayed in the virtual environment to guide the user to perform specific breathing patterns, such as deep breathing, abdominal breathing, etc.

[0048] Connect the neck massager to the virtual reality device through Bluetooth to ensure the real-time and stability of data transmission; when the trapezius muscle hardness index detection device (such as a pressure sensor embedded in the massager) detects that the trapezius muscle hardness index exceeds the standard, the system automatically triggers the thermomagnetic pulse device and the breathing guidance animation; the thermomagnetic 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, it effectively relieves the tension of the neck muscles, reduces the headache symptoms caused by muscle tension, and improves the comprehensiveness and effectiveness of relaxation training.

[0049] Heart rate variability refers to the variation of successive heartbeat intervals, reflecting the regulatory function of the autonomic nervous system on the heart; massage intensity refers to the magnitude of the force exerted by the neck massager on the neck; massage frequency refers to the number of times the massage action is repeated per minute; the resonance relaxation effect refers to the phenomenon of enhanced relaxation effect when the massage rhythm matches the user's breathing frequency.

[0050] During the massage process, heart rate variability data is collected in real time through a heart rate variability monitoring device (such as a pulse sensor worn on the finger or earlobe). When the heart rate variability analysis shows that the user is in a tense state (such as a decrease in high-frequency components and an increase in low-frequency components), the system dynamically adjusts the neck massage intensity and frequency; through this adjustment, the massage action synchronizes with the user's breathing rhythm, generating a resonance relaxation effect; in the above steps, the massage parameters are dynamically adjusted according to the user's physiological state, enhancing the relaxation effect, optimizing the training experience, and increasing the success rate of headache relief.

[0051] Furthermore, the adaptive control module M200 is also used to execute the following method: Set up an IMU array to track the neck rotation angle and scapular displacement trajectory in real time, and identify abnormal muscle compensation patterns; when the activation degree of the sternocleidomastoid muscle exceeds the standard, generate a virtual mirror correction instruction to guide the muscle group to exert force in the abnormal muscle compensation pattern.

[0052] Specifically, an IMU (Inertial Measurement Unit) array usually includes an accelerometer, a gyroscope, and a magnetometer, 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 shoulder to track the neck rotation angle and scapular 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 scapular displacement trajectory refers to the path of the position change of the scapula during movement, reflecting the activity of the shoulder muscles; the abnormal muscle compensation pattern refers to the abnormal compensatory activity pattern of other muscles caused by excessive tension or fatigue of some muscles, which may exacerbate muscle tension and pain.

[0053] Data is collected in real time by each unit of the IMU array, and acceleration, angular velocity, and magnetic field data are converted into neck rotation angles and scapular displacement trajectories. By analyzing this data and combining it with a pre-set normal muscle activity pattern, abnormal muscle compensation patterns are identified. For example, when one side of the trapezius muscle is overly tense, it causes excessive displacement of the contralateral scapula, and this abnormal pattern can be identified through the change characteristics of the IMU data. The neck and shoulder muscle activity status of the user is monitored in real time to provide accurate basis for subsequent muscle correction and relaxation training. By identifying abnormal muscle compensation patterns, corrective training is designed specifically to help the user restore the normal muscle activity pattern, relieve muscle tension, and thus alleviate headache symptoms.

[0054] The sternocleidomastoid muscle belongs to the neck muscles, and its activation degree can be measured by a surface electromyography sensor, which reflects the tension degree of this muscle. The virtual mirror correction instruction refers to the instruction generated in the virtual environment for guiding the user to perform muscle correction, usually presented in the form of mirror feedback, enabling the user to intuitively see their own muscle activity and make adjustments. Muscle group force guidance refers to guiding the user to correctly use the relevant muscle groups through guidance to avoid abnormal muscle compensation patterns.

[0055] When the activation degree of the sternocleidomastoid muscle exceeds the set threshold, it is determined that the sternocleidomastoid muscle is in an overly tense state. At this time, a virtual mirror correction instruction is generated, and the mirror images of the user's neck and shoulders are displayed in the virtual environment. At the same time, the activation status of the sternocleidomastoid muscle and other relevant muscles is highlighted with different colors or graphics. For example, overly tense muscles are displayed in yellow, and muscles in a normal state are displayed in green.

[0056] According to the identified abnormal muscle compensation pattern, muscle group force guidance is provided, such as guiding the user to perform specific neck stretching and relaxation actions, and at the same time, 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 user is prompted by voice "Slowly tilt your head to the left and feel the stretch of the right sternocleidomastoid muscle", and at the same time, the corresponding action demonstration is shown on the mirror image. Help the user 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 alleviate the current headache symptoms but also prevents chronic headache problems caused by long-term muscle tension, improving the pertinence and effectiveness of training.

[0057] Furthermore, the adaptive control module M200 is also used to execute the following method: The electromagnetic damping coefficient of the training resistance device will be adjusted in real time according to the correction requirements, and the sample distribution characteristics in the headache attack period and the headache remission period will be analyzed; based on the sample distribution characteristics in the headache attack period and the headache remission period, the differential factors of the muscle movement state in the headache attack period and the headache remission period will be extracted; through the physiological state indicators, the differential factors of the human physiological parameters in the headache attack period and the headache remission period will be extracted; according to the differential factors of the muscle movement state and the differential factors of the human physiological parameters, a multi-task learning framework will be configured, and the multi-task learning framework will be optimized and trained with risk grading and attack duration prediction as the joint optimization objectives.

[0058] Specifically, the electromagnetic damping coefficient refers to the parameter that affects the magnitude of electromagnetic damping and determines the resistance generated by the training resistance device to muscle movement; by real-time monitoring the muscle state of the user and dynamically adjusting this coefficient according to the correction requirements, more accurate muscle training can be provided for the user, helping to relieve and correct headaches caused by muscle tension or abnormal movement patterns; analyzing the data samples in the headache attack period and the remission period, extracting the differences in muscle movement state and human physiological parameters between the headache attack period and the headache remission period, and the differences in muscle movement state and human physiological parameters contribute to understanding the mechanism of headache occurrence, thus providing a basis for formulating more effective headache management and rehabilitation strategies.

[0059] Based on the extracted differential factors, a multi-task learning framework is configured to simultaneously achieve risk grading and attack duration prediction; through optimization training, the prediction accuracy of the model is improved to provide support for the personalized treatment and management of headaches; by real-time monitoring the muscle state and physiological parameters of the user, combined with data analysis and machine learning techniques, the optimization of the personalized training plan is realized, the pertinence and effectiveness of relaxation training are improved, and the headache symptoms are helped to be relieved.

[0060] In summary, the beneficial effects of the embodiments of the present application are: Due to the adoption of a data collection module for constructing a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound effect unit, collecting the eye movement data, facial muscle activity signals, and respiratory frequency parameters of the target user, and setting physiological state indicators; an adaptive control module for adjusting the visual focus guiding path and sound field frequency distribution in the virtual environment scene through adaptive control based on the physiological state indicators, and inserting visual interference elements, wherein the generation frequency of the visual interference elements is associated with the real-time pupil contraction rate of the user; a start module for starting a multi-stage headache relaxation training process and synchronously enhancing the vibration feedback intensity of the foot pressure pad if it detects that the facial muscle activity signal exceeds a preset threshold after inserting the visual interference elements; an optimization management module for setting an attention mechanism to strengthen the prodromal period characteristics by matching abnormal physiological parameter fluctuation intervals through cosine similarity according to the change trend of physiological parameters during the headache relaxation training period, generating a state prediction map within a time sliding window, and performing training optimization management. The present 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 guiding path and sound field frequency distribution in the virtual environment scene, sets an attention mechanism to strengthen the prodromal period characteristics, generates a state prediction map within a time sliding window, and thus better adapts to the individual differences of users, and improves the pertinence and effectiveness of relaxation training.

[0061] In summary, any step can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor, and no redundant restrictions are imposed here.

[0062] Furthermore, the above technical solutions only reflect the preferred technical solutions of the technical solutions of the embodiments of the present application. Some changes that those skilled in the art may make to some parts thereof all reflect the principles of the novel embodiments of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A headache relaxation training management system based on virtual reality, characterized in that, Comprising: A data collection module, configured to construct a virtual environment scene equipped with a dynamic lighting unit and a multi-frequency sound unit, collect eye movement data, facial muscle activity signals, and respiratory frequency parameters of a target user, and set physiological state indicators; An adaptive control module, configured to, based on the physiological state indicators, adjust the visual focus guiding path and the sound field frequency distribution in the virtual environment scene through adaptive control, and insert visual interference elements, wherein the generation frequency of the visual interference elements is associated with the real-time pupil constriction rate of the user; A start module, configured to, after inserting the visual interference elements, if it is detected that the facial muscle activity signal exceeds a preset threshold, start a multi-stage headache relaxation training process, and synchronously enhance the vibration feedback intensity of the foot pressure pad; An optimization management module, configured to, according to the change trend of physiological parameters during the headache relaxation training period, set an attention mechanism to strengthen the premonitory seizure characteristics by matching abnormal physiological parameter fluctuation intervals through cosine similarity, generate a state prediction map within a time sliding window, and perform training optimization management.

2. The virtual reality-based headache relaxation training management system according to claim 1, wherein Adjusting the visual focus guiding path and the sound field frequency distribution in the virtual environment scene through adaptive control includes: Set up a signal receiving electrode in the prefrontal cortex and determine the ratio of the power of the wave to the power of the wave; Identify the feature of distracted attention. When the wave and the power ratio of the wave abnormally increases, start the multi-frequency sound effect unit in the virtual environment scene. The multi-frequency sound effect unit is used to dynamically adjust the sound field frequency distribution until the brain wave synchronization index stabilizes in a preset target range.

3. The virtual reality-based headache relaxation training management system according to claim 2, characterized in that, Comprising: Embedding an infrared eye tracker to capture pupil diameter changes and saccade movement trajectories; Identifying the cumulative degree of visual fatigue based on the pupil diameter changes and saccade movement trajectories, and combining with the blink frequency to generate a visual focus guiding path; Projecting a gradient color temperature light spot in the virtual environment scene, and guiding the eyeball to perform visual tracking training along the visual focus guiding path.

4. The virtual reality-based headache relaxation training management system according to claim 3, characterized in that Identifying the cumulative degree of visual fatigue, and combining with the blink frequency to generate a visual focus guiding path includes: Recording the coefficient of variation of the transfer speed of the fixation point and the coefficient of variation of the blink frequency, and configuring a visual fatigue feature vector; Performing visual focus guiding optimization according to the visual fatigue feature vector to obtain the visual focus guiding path.

5. The virtual reality-based headache relaxation training management system according to claim 4, wherein, Recording the coefficient of variation of the transfer speed of the fixation point and the coefficient of variation of the blink frequency, and configuring a visual fatigue feature vector includes: Based on the dynamic lighting unit, obtaining a retinal stimulation index, and mapping the retinal stimulation index to a virtual depth of field adjustment grid; Establishing a negative feedback association mechanism between the ambient illuminance gradient change and the virtual depth of field adjustment grid according to the curtain light transmittance.

6. The virtual reality-based headache relaxation training management system according to claim 5, wherein Further comprising: Connecting a neck massager via Bluetooth, and when it is detected that the trapezius muscle hardness index exceeds the standard, synchronously starting a thermomagnetic pulse and a breathing guidance animation; Meanwhile, according to the heart rate variability data, dynamically adjusting the neck massage intensity and massage frequency, matching the massage rhythm with the user's respiratory frequency, and configuring a resonance relaxation effect.

7. The virtual reality-based headache relaxation training management system according to claim 6, characterized in that, Comprising: Setting an IMU array to real-time track the neck rotation angle and the scapula displacement trajectory, and identify abnormal muscle compensation patterns; If the activation degree of the sternocleidomastoid muscle exceeds the standard, generating a virtual mirror correction instruction, and guiding the muscle group to exert force in the abnormal muscle compensation pattern.

8. The virtual reality-based headache relaxation training management system according to claim 7, wherein Further comprising: The electromagnetic damping coefficient of the training resistance device will be adjusted in real time according to the correction requirements, and analyze the sample distribution characteristics during the headache attack period and the sample distribution characteristics during the headache remission period; Based on the sample distribution characteristics in the headache attack period and the headache remission period, extract the differential factors of muscle movement states in the headache attack period and the headache remission period; Through the physiological state indicators, extract the differential factors of human physiological parameters in the headache attack period and the headache remission period; According to the differential factors of muscle movement states and the differential factors of human physiological parameters, configure a multi-task learning framework, and optimize and train the multi-task learning framework with risk grading and attack duration prediction as the joint optimization objectives.

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