Multi-parameter group biofeedback training method, apparatus and system, and storage medium

Abstract

Provided are a multi-parameter group biofeedback training method, apparatus and system, and a storage medium. The method comprises the following steps: receiving a training scheme and a training prescription preset in a training management module, wherein the training scheme and the training prescription are configured in training management, the configuration of the training management module comprises a training scenario, the training scheme is a combination of single training, and the training prescription is a combination of phased training or training schemes over an extended time period (S110); and displaying the training scenario to a participant according to the training or the training prescription so as to perform training, and collecting physiological data and / or target index data selected for the training in real time (S120). The training prescription comprises preset multiple stages of training schemes and a jump rule between the training schemes of the stages, and the training scheme comprises training tasks in a preset execution sequence, and each training task has a corresponding training scenario. The method can achieve standardized multi-parameter group biological training.

Description

Multi-parameter group biofeedback training method, device, system and storage medium

[0001] Related applications

[0002] This invention claims priority to the Chinese invention patent with application number 2023118526330, application date December 28, 2023, and invention name “Multi-parameter group biofeedback training method, device, system and storage medium”. Technical Field

[0003] The present invention relates to the field of group biofeedback training medical health technology, and in particular to a multi-parameter group biofeedback training method, device, system and storage medium. Background Art

[0004] Biofeedback training is a method of monitoring and measuring physiological indicators and providing feedback to individuals, enabling them to self-regulate and train to control their physiological state. Commonly used physiological indicators in biofeedback training include heart rate, electrocardiogram (ECG), skin conductance response, respiratory rate, and muscle electrical activity. These indicators can be collected and measured in real time using sensors or devices. By providing real-time feedback and generating test reports, and tailoring training methods based on individual test results, individuals can monitor their physical condition and, through adjustment and training, alter these physiological indicators to improve their health and control their body's responses.

[0005] Group biofeedback training is a training method that applies biofeedback training to a multi-person group setting. In group biofeedback training, multiple individuals simultaneously receive feedback on their physical condition and achieve their goals through interaction and collaboration. In multi-person biofeedback training, individuals can encourage and improve each other, promptly identify gaps, and achieve better training objectives. However, existing biofeedback systems only support single-user use and lack the ability for multi-user real-time communication. There are no group collaborative training strategies or interactive modes, and even no objective evaluation standards. Instead, feedback training results are generated through subjective assessments by relevant medical practitioners. The specific effectiveness of the training and its rationale cannot be quantified. Training is then repeated multiple times based on these assessments, lacking a standardized training process.

[0006] Summary of the Invention

[0007] In view of this, embodiments of the present invention provide a multi-parameter group biofeedback training method, system, and storage medium to eliminate or improve one or more deficiencies in the prior art.

[0008] One aspect of the present invention provides a multi-parameter group biofeedback training method, which is implemented based on a multi-parameter group biofeedback training system. The multi-parameter group biofeedback training system includes a training management module. The method includes the following steps:

[0009] Obtaining preset training plans and training prescriptions; wherein the training plans and prescriptions are configured in the training management module, the training management module configuration includes training scenarios, the training plan is a combination of single trainings, and the prescription is a phased training or combination of training plans over a long period of time;

[0010] Showing the training scene to the subject according to the training or the training direction to perform the training, and collecting physiological data and / or target indicator data selected for the training in real time;

[0011] The training prescription includes preset training plans for multiple stages and jump rules between the training plans for each stage. The training plan includes preset training tasks to be executed, and each training task has a corresponding training scenario.

[0012] In some embodiments of the present invention, before receiving the pre-set training configuration set in the training management module, the method also includes: obtaining the evaluation report and / or training tools configured in the training management; and configuring a corresponding training plan based on the evaluation report and / or training tools of the subject.

[0013] In some embodiments of the present invention, the system includes a user management module for managing the training configurations and training records of different subjects. The user management module supports operations including adding, deleting, modifying, importing and exporting, batch importing and batch deleting the training configurations and training records of the subjects.

[0014] In some embodiments of the present invention, the system further includes a group management module for group management of different subjects according to set requirements. The group management module also supports operations including addition, deletion, modification, import and export, batch import and batch deletion of the subjects' training configurations and training records.

[0015] In some embodiments of the present invention, the training management module supports custom configuration of the training configuration, and the steps of custom configuration of the training configuration include: selecting target indicator data based on multi-parameter group biofeedback training; selecting a training scene suitable for the multi-parameter group biofeedback training, and the types of the training scenes include any one or a combination of VR virtual scenes, audio and video scenes, virtual multi-person interactive animation scenes and virtual multi-person interactive game scenes, multi-person interactive virtual and real fusion scenes, screen-based 3D scenes, visualization chart components and audio and video game resource scenes; according to the jump rules between different training schemes in the pre-acquired training prescription, the interaction settings between different scenes are performed; wherein, the interaction settings include the end method settings for ending the training prescription, and the jump rules include the jump condition settings and jump relationship network for jumping between training schemes.

[0016] In some embodiments of the present invention, the training scene is presented to the subjects according to the training or the training direction to perform multi-parameter group biofeedback training, and the physiological data and / or target indicator data selected for the training are collected in real time, including: in the physiological feedback training scene, the target indicator data is selected by freely combining physiological channels.

[0017] In some embodiments of the present invention, the method further includes: generating a group biofeedback training report according to the target indicator data display method pre-configured by the training management module; wherein the target indicator data display method includes target indicator data to be presented and visual charts; wherein the target indicator data display method includes target indicator data to be presented and visual charts; the step of customizing the training configuration further includes: configuring the target indicator data display method, wherein the visual charts include but are not limited to one or more of pie charts, bar charts and Venn diagrams.

[0018] In some embodiments of the present invention, the training management module also includes a pre-built-in calculation formula, a classification algorithm model and a recommendation algorithm model, and the step of customizing the training configuration also includes: using the built-in calculation formula to calculate the group biofeedback training results based on the target indicator data; using the classification algorithm model to classify the subjects based on the group biofeedback training results according to preset classification rules; and using the recommendation algorithm model to recommend the next stage of training plan to the subjects based on the group biofeedback training results according to preset recommendation rules.

[0019] In some embodiments of the present invention, the different stages of the training prescription include multiple stages of evaluation, training, verification and application, different training stages include corresponding training schemes, and the training prescription includes pre-set jump rules and recommendation rules between different training schemes.

[0020] In some embodiments of the present invention, the multi-parameter group biofeedback training system performs multi-parameter group biofeedback training through process management.

[0021] In some embodiments of the present invention, the method further includes: after obtaining the target indicator data, performing data analysis and data profiling based on the obtained target indicator data, customizing the construction of a user ability assessment and training model, and agilely establishing a data model and data profiling system through dragging and dropping, thereby building an ability model and / or data profiling, obtaining the target indicator data after the subject completes the group biofeedback training, and obtaining the subject's ability model and / or data profiling based on the data model and data profiling system.

[0022] Another aspect of the present invention provides a multi-parameter group biofeedback training device, which is used to implement the steps of the method described in any one of the above embodiments.

[0023] Another aspect of the present invention provides a multi-parameter group biofeedback training system, comprising a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method described in any one of the above embodiments.

[0024] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any one of the above embodiments.

[0025] The multi-parameter group biofeedback training method, system and storage medium proposed in the present invention can train subjects according to a pre-selected training configuration, and the training prescription includes jump rules between training schemes to realize multi-modal training of subjects, thereby realizing standardized multi-parameter group biological training.

[0026] Additional advantages, objects, and features of the present invention will be set forth in part in the following description and will become apparent to those skilled in the art upon examination of the following or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained by the structures particularly pointed out in the description and drawings.

[0027] Those skilled in the art will understand that the purposes and advantages that can be achieved by the present invention are not limited to the above specific descriptions, and the above and other purposes that can be achieved by the present invention will be more clearly understood based on the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. In the drawings:

[0029] FIG1 is a flow chart of a multi-parameter group biofeedback training method according to an embodiment of the present invention.

[0030] FIG2 is a flowchart of the training configuration described in the custom configuration in one embodiment of the present invention.

[0031] FIG3 is an example of jumping between training schemes in one embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0033] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, the accompanying drawings only show structures and / or processing steps closely related to the solutions according to the present invention, while other details that are not closely related to the present invention are omitted.

[0034] It should be emphasized that the term "include / comprises" when used herein refers to the existence of features, elements, steps or components, but does not exclude the existence or addition of one or more other features, elements, steps or components.

[0035] It should also be noted that, unless otherwise specified, the term "connection" herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0036] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0037] In order to solve the problems existing in the existing human factors testing and training methods, the present invention provides a multi-parameter group biofeedback training method, system and storage medium.

[0038] FIG1 is a flow chart of a multi-parameter group biofeedback training method according to an embodiment of the present invention. The method is implemented based on a multi-parameter group biofeedback training system, which includes a training management module. The method includes the following steps:

[0039] Step S110: Obtain preset training plans and training prescriptions; wherein, the training plans and prescriptions are configured in the training management, the training management module configuration includes training scenarios, the training plan is a combination of single trainings, and the prescription is a combination of phased training or training plans in a long-term sequence.

[0040] Step S120: showing the training scene to the subject according to the training or the training direction to perform the training, and collecting the physiological data and / or target indicator data selected for the training in real time.

[0041] The training prescription includes preset training plans for multiple stages and jump rules between the training plans for each stage. The training plan includes preset training tasks to be executed, and each training task has a corresponding training scenario.

[0042] By adopting this embodiment of the invention, the subjects can be trained according to a pre-selected training configuration, and the training prescription includes jump rules between training schemes to realize multi-modal training of the subjects, thereby realizing standardized multi-parameter group biological training and high-freedom multi-channel biofeedback training.

[0043] In some embodiments of the present invention, prior to receiving the pre-set training configuration in the training management module, the method further includes: obtaining an assessment report and / or training tool configured in the training management module; and configuring a corresponding training plan based on the subject's assessment report and / or training tool. Using this embodiment of the invention, a corresponding training plan can be configured based on the subject's test report, thereby achieving targeted training for subjects in different situations.

[0044] In the training management module, there are three entity objects configured: training, plan, and prescription. Training is a configured tool for evaluation or training, like a scale; plan is a combination of training, the concept of training package; prescription is a phased, timeline-based combination of training + plan, which can be configured into a complete training course for a period of time.

[0045] In one embodiment of the present invention, the multi-parameter group biofeedback training system includes a user management module for managing the training configurations and training records of different subjects. The user management module supports operations including addition, deletion, modification, import and export, batch import and batch deletion of the training configurations and training records of the subjects.

[0046] By adopting the embodiment of the invention, it is possible to manage personnel who are performing group biofeedback training, thereby avoiding confusion when there are many users participating in the training.

[0047] Furthermore, in some other embodiments of the present invention, the multi-parameter group biofeedback training system also includes a group management module for group management of different subjects according to set requirements. The group management module also supports operations including addition, deletion, modification, import and export, batch import and batch deletion of the training configurations and training records of the subjects.

[0048] By adopting the embodiment of the invention, subjects (users) can be managed in groups, and subjects participating in group biofeedback training can be managed in an orderly manner.

[0049] FIG2 is a flowchart of customizing the training configuration in an embodiment of the present invention. In some embodiments of the present invention, the training management module supports customizing the training configuration. The steps of customizing the training configuration include:

[0050] Step S210: Select target indicator data based on multi-parameter group biofeedback training.

[0051] Step S220: Select a training scene that is suitable for the multi-parameter group biofeedback training. The types of the training scenes include any one or a combination of VR virtual scenes, audio and video scenes, virtual multi-person interactive animation scenes and virtual multi-person interactive game scenes, multi-person interactive virtual and real fusion scenes, screen-based 3D scenes, visualization chart components and audio and video game resource scenes.

[0052] Step S230: According to the jump rules between different training schemes contained in the pre-acquired training prescription, interaction settings between different scenarios are performed; wherein the interaction settings include the end method settings for ending the training prescription, and the jump rules include the jump condition settings and jump relationship network for jumping between training schemes.

[0053] By adopting the embodiment of the invention, the training configuration to be selected in the training management module can be set, thereby realizing multi-mode and flexible group biofeedback training. The embodiment of the present application can also meet the needs of patients with different needs, and can reduce the repeated configuration time of medical workers, and can also ensure the standardization and normalization of the evaluation and treatment system. For example, for patients who need rapid recovery, they may be able to go directly to the training center to choose 1-2 training; if the patient needs long-term treatment, they can first be evaluated, then prescribed, and conduct complete follow-up treatment; they can also combine the plan to comprehensively evaluate the patient's physical and mental state, such as using neurofeedback to evaluate the patient's nervous system, HRV training to evaluate the patient's autonomic nervous system, etc.

[0054] Biofeedback training is widely used in healthcare. It's a therapeutic approach based on physiological data collection instruments. Through biofeedback technology, it collects and amplifies information about physiological changes that are difficult for individuals to perceive, presenting it in easily discernible visual and auditory forms. Once individuals become aware of these physiological or pathological changes, they engage in conscious control and psychological training to manage and regulate abnormal physiological reactions, ultimately adjusting body functions and preventing and treating illnesses.

[0055] The feedback information collected in this application obtains biological signals of the human body through a biological collection device, including but not limited to EEG information, brain imaging information, heart rate, electrocardiogram, electrodermal conductivity, electromyography (muscle electrical signals), blood pressure, blood oxygen, eye movements and other physiological signals and perception signals. The collected signals of different dimensions are analyzed and a feedback report corresponding to each individual is generated. Individuals conduct symptomatic training based on the feedback reports, and group training can also be formed by combining feedback reports from the same or different fields.

[0056] Biofeedback technology can also be applied to various stress-related physical and mental illnesses, such as tension headaches, gastric ulcers, and chronic anxiety. Furthermore, biofeedback technology is also widely used in neurorehabilitation, exercise rehabilitation, and psychological rehabilitation. For example, neurofeedback technology helps regulate and improve brain function by monitoring and training an individual's brain electrical activity, and is widely used in neurorehabilitation fields such as stroke rehabilitation, attention deficit hyperactivity disorder treatment, and motor control disorders. Heart rate variability feedback technology, on the other hand, helps improve cardiovascular function and regulate the autonomic nervous system by monitoring an individual's heart rate variability, and is widely used in stress management, anxiety treatment, and mental health improvement.

[0057] Neurofeedback technology can also help regulate and improve brain function and is widely used in neurorehabilitation fields such as stroke rehabilitation, attention deficit hyperactivity disorder treatment, and motor control disorders. By observing EEG patterns and receiving specific visual feedback, individuals enhance their understanding of their own brain state, enabling self-regulation and recovery of brain function.

[0058] In addition, heart rate variability feedback technology is widely used in areas such as stress management, anxiety treatment, and mental health improvement. Individuals can improve their awareness of their cardiovascular state by observing heart rate variability graphs and conducting specific breathing exercises. They can also improve heart rate variability by adjusting their breathing rate and depth, thereby achieving self-regulation and improvement of heart health.

[0059] Muscle electrical signal feedback technology helps improve muscle control and motor function by monitoring an individual's muscle electrical activity. It is widely used in areas such as muscle denervation injury rehabilitation, pain management, and motor skill improvement.

[0060] Corresponding to the biofeedback training system's treatment plan based on EEG signal collection, when people with anxiety disorders experience symptoms such as excessive tension, worry, and fear, the system collects and analyzes EEG biosignals to determine the degree of tension, worry, or fear, and provides feedback on their status to assist in training and improvement. Generally, there are standard testing specifications to determine the parameter range, which is then adjusted through multiple training sessions. Timely testing and comparison with previous status parameters allow patients to promptly understand the improvement of their symptoms. This allows for real-time dynamic monitoring and early warning of EEG changes, thereby achieving the effect of treating anxiety disorders.

[0061] In addition, the EEG biofeedback training system can also upload EEG waveforms and signals to a computer or cloud platform through EEG biofeedback technology, and then conduct a series of dynamic EEG changes monitoring to judge the type, degree and specific disease of insomnia, so as to conduct repeated training according to the doctor's instructions to alleviate symptoms. It can also form a group biofeedback training model with patients with the same experience to supervise each other, share methods to promote each other, and improve treatment plans.

[0062] In some embodiments of the present invention, the training scene is presented to the subjects according to the training or the training direction to perform multi-parameter group biofeedback training, and the physiological data and / or target indicator data selected for the training are collected in real time, including: in the physiological feedback training scene, the target indicator data is selected by freely combining physiological channels.

[0063] By adopting this embodiment of the invention, physiological feedback training can be performed in a physiological feedback training scenario, and the group biofeedback training includes physiological feedback training.

[0064] In some embodiments of the present invention, after acquiring the target indicator data in real time, the method further includes: generating a group biofeedback training report according to the target indicator data display method pre-configured in the training management module; wherein the target indicator data display method includes the target indicator data to be presented and a visual chart. At the same time, correspondingly, the step of customizing the training configuration further includes: configuring the target indicator data display method, wherein the visual chart includes but is not limited to one or more of a pie chart, a bar chart, and a Venn diagram. The present invention is not limited to this, and the display methods for the target indicator data are not limited to those listed, and technicians can freely expand them.

[0065] By adopting the embodiment of the invention, a group biofeedback training report can be generated based on the obtained target indicator data, thereby visually presenting the training results to the subjects or third parties.

[0066] In some embodiments of the present invention, the training management module further includes a pre-built-in calculation formula, a classification algorithm model, and a recommendation algorithm model, and the step of customizing the training configuration further includes:

[0067] (1) calculating the group biofeedback training results based on the target indicator data using a built-in calculation formula;

[0068] (2) using the classification algorithm model to classify the subjects according to preset classification rules based on the group biofeedback training results;

[0069] (3) Using the recommendation algorithm model to recommend the next stage of training plan to the subjects based on the group biofeedback training results in accordance with preset recommendation rules.

[0070] By adopting the embodiment of the invention, the jump rules between different training programs in the training prescription are enriched, and group biofeedback training can be carried out more flexibly.

[0071] In some embodiments of the present invention, different stages of a training prescription include multiple stages of an evaluation stage, a training stage, a verification stage, and an application stage. Different training stages include corresponding training schemes, and the training prescription includes jump rules and recommendation rules pre-set between different training schemes.

[0072] Figure 3 illustrates an example of transitioning between training programs in one embodiment of the present invention. First, group biofeedback training results are calculated. Based on these results, a training program for the corresponding phase is arranged. The training program includes multiple training tasks. As shown in Figure 3, a training program includes two consecutive training sessions 1, two training sessions 2, or two training sessions 3. Based on result 1, an evaluation result can be calculated to proceed to the next phase of training.

[0073] In a specific embodiment of the present invention, the training plan supports custom combinations of multiple training tasks (see Training 1, Training 2, and Training 3 in Figure 3). It also supports the selection of system-built-in scales, questionnaires, cognitive assessments, cognitive training, or behavioral experiments to form a complete multi-dimensional and multi-type training plan. The advanced mode of the plan supports the construction of a complete training plan model based on training results, that is, adding a conditional jump function to the training plan to jump between training tasks. As shown in Figure 3, the jump logic between training tasks can be configured, and jump rules and jump training can be configured based on training results, which is conducive to the generation of personalized training plans for users of different levels.

[0074] In some embodiments of the present invention, the multi-parameter group biofeedback training system utilizes process management to conduct multi-parameter group biofeedback training. Users can directly select the aforementioned training prescriptions for training, or administrators can assign them to specific groups, individuals, or multiple users. Administrators can create processes, freely combine the aforementioned training programs, and assign them to specific groups, individuals, or multiple users. Once a process is successfully created, users' progress can be tracked and monitored, and the overall group training status can be controlled. Administrators can adjust training plans or progress at any time based on user results and feedback.

[0075] In some embodiments of the present invention, the method further includes: after obtaining the target indicator data, performing data analysis and data profiling based on the obtained target indicator data, customizing the construction of a user capability assessment and training model, and agilely establishing a data model and a data profiling system by dragging and dropping, thereby constructing a capability model and / or a data profiling system, obtaining the target indicator data after the subject completes the group biofeedback training, and obtaining the subject's capability model and / or data profiling based on the data model and data profiling system. After the training is completed, the subject is profiled according to the pre-stored algorithms and classification rules configured in the training, and the assessment report of the subject after the training is updated in real time, wherein the assessment report at least includes the subject's physiological data and / or target indicator data.

[0076] By adopting the embodiment of the invention, the results of group biofeedback training of subjects (users) can be analyzed through data analysis and data profiling, thereby generating a capability model and / or data profiling personalized for the subjects.

[0077] Furthermore, in a specific embodiment of the present invention, data analysis and data mining are performed at the granularity of each data field and data indicator result through data analysis technology: support is provided for custom construction of user capability assessment and training models, and data models and data portrait systems are agilely established through dragging and dropping. For example, a user's physical and mental assessment model is built, the data source, primary indicators and secondary indicators of the model are selected, and the calculation formula for each level is configured. The formula supports basic operations, function operations, standard score calculations, normalization processing and / or deep learning algorithms and other calculation methods, so as to build user portraits or capability models. In this way, after the user generates data after training or evaluation, he can view his own capability model and data portrait; in addition, the system also provides a variety of physical and mental state warning and state recognition algorithms, which can calculate the user's physical and mental state in real time based on the user's physical and mental data, training data and basic data, and perform classification or warning. The system also provides custom algorithm expansion functions, and users can upload open source algorithms or self-developed algorithms for training or modeling as needed.

[0078] Among them, data profiling refers to the process of abstracting, processing, and integrating the attributes, characteristics, behaviors, and other information of users or things through the analysis of massive data to form a three-dimensional, multi-dimensional user or thing model. The purpose of data profiling is to better understand users or things, so as to provide them with better services or products. Data profiling can be applied to a variety of scenarios, such as: (1) User profiling: used to understand the attributes, interests, needs, etc. of users, so as to provide users with personalized recommendations, precision marketing and other services. (2) Product profiling: used to understand product usage, user feedback, etc., so as to improve product design and enhance product experience. (3) Enterprise profiling: used to understand the scale, industry, customers, etc. of the enterprise, so as to formulate a strategy that is more suitable for the development of the enterprise.

[0079] For example, some industries require personnel to be selected based on specific competencies. This requires continuous testing, feedback, and training within a group to achieve the desired results. For example, pilots must possess excellent vision and hearing to accurately discern and assess various flight situations. Vision and hearing test results can serve as important indicators for assessing a candidate's physical fitness. Therefore, EEG and brain imaging data representing vision and hearing, as part of a pilot's physiological parameters, can be collected and identified to determine the optimal standard range. Based on a paradigm for enhancing specific competencies, such as vision and hearing, continuous training is then conducted to achieve the desired level of qualified pilots.

[0080] It can also be used to target pilots who need to possess high strength and endurance, enabling them to maintain sufficient stamina and endurance during long, high-intensity flights. Group biofeedback training can also provide feedback training on strength and endurance, including muscle strength testing, grip strength testing, and aerobic endurance testing.

[0081] Of course, the biofeedback system provided by this application is not limited to the field of pilots, and other fields or personnel can also use it.

[0082] In a specific embodiment of the present invention, the training management module is used to manage a single training resource. The training resource includes a training prescription, including categories such as assessment, training, and group training, and supports category customization. The process of customizing the training management module includes the following steps:

[0083] (1) During biofeedback training, training based on the biofeedback system allows users to freely combine physiological channels and select physiological indicators and visual charts that need to be fed back to users. ① The indicator results are presented in numerical form, dashboard, and score bar. ② Visual charts include line charts, bar charts, spectrum charts, and fan charts. ③ The system will perform intelligent layout based on the selected indicators and charts. The intelligent layout engine can calculate the optimal layout method based on the indicators, chart size, and number, which is conducive to feedback on physiological and physical and mental states during training.

[0084] (2) Freely select training scenarios for human factors testing training

[0085] ① Scene types include VR scenes, audio and video, multi-person interactive animations or multi-person interactive game scenes, etc. The system can have built-in scene resources of the above types, and the training scenes also include dynamic multi-person interactive virtual-reality fusion scenes, screen-based 3D scenes, visualization chart components and audio and video game resources. It also supports the development of the above scene resources through extensibility. The above scene resources are used to configure training. Users can select the above types of scenes as needed, or customize and upload audio, video, animation and other files, and conduct biofeedback training, relaxation training and other human factors testing training by displaying the above scenes.

[0086] ②The above-mentioned system development scenarios are all dynamic scenarios. After selecting the scenario, you can interact with the scenario. For example, the VR scenario developed by the system can set input indicators, and the scene's picture, color, animation and other elements will change according to the numerical changes of the input indicators; the multi-person interaction scenario supports intelligent grouping of multiple people. During training, you can cooperate or play PK games based on the changes in the numerical values ​​of physiological indicators within and between groups. The game scene will display dynamic results in real time and provide feedback to users and groups.

[0087] (3) Other configurations (including built-in formulas, classification algorithm models, and recommendation algorithm models)

[0088] ① The system provides a default training report and also supports customized configuration in advanced mode. The report content includes basic training information, basic personnel information, visual indicator results and process record charts, result explanations, guidance suggestions and intelligent recommendations. In advanced configuration mode, you can configure the indicator results and visual charts presented in the report. The charts can switch presentation formats, such as pie charts, bar charts, etc. The result explanation supports customized configuration calculation rules. You can choose the system's built-in calculation formula or enter it manually. It supports calculations based on formulas of algorithms such as mean and standard scores, and supports adding result explanations for different results. For example, classification is performed using a classification algorithm, and the classification results are medium, high and low. Result explanations and guidance suggestions can be customized for each level of users, which is conducive to users viewing personalized report results and recommendations after the training is completed. At the same time, it supports the extraction, matching and training of user characteristics and features in combination with recommendation algorithms, and intelligently recommending other training to users. Recommendation rules can be customized or automatically generated based on training results, user characteristics, training characteristics, etc.

[0089] In a specific embodiment of the present invention, the reporting center saves all reports and generates reports according to the granularity of each user and each training session. It supports the generation of completion plans, prescription reports, etc. based on multi-modal training such as training plans and training prescriptions, and also supports the generation of personal training files or group training files according to users and groups; it also supports the generation of trend analysis reports for longitudinal tracking and comparison reports for horizontal comparison.

[0090] The built-in formula, classification algorithm model and recommendation algorithm model proposed in the above-mentioned embodiments of the invention can more flexibly provide multi-modal human factors test training prescriptions, thereby training the subjects in a targeted manner to achieve the expected results.

[0091] ②Ending method settings: You can choose to end at the default time or stop at the end of the game, or you can customize the interaction to end the training, such as selecting key or mouse operations.

[0092] Corresponding to the above method, the present invention also provides a multi-parameter group biofeedback training system, which includes a computer device, the computer device includes a processor and a memory, the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method described above.

[0093] Specifically, the multi-parameter group biofeedback training system includes a user management module, a group management module, a training management module, a program management module, a prescription management module, a process management module, a report management module, a data analysis and data profiling module, etc.

[0094] The user management module supports operations such as adding, deleting, modifying, and querying, importing and exporting, and batch importing and deleting. The group management module can be used to organize groups based on group therapy needs. A group is a collection of users with the same treatment, testing, or training process or purpose. The group management module is functionally identical to the user management module.

[0095] The prescription management module is used to manage training plans at different stages. The prescription contains different stages. Each stage can customize the selection and combination of the above-mentioned training tasks or training plans to form a systematic and periodic complete training plan. This prescription is not equivalent to the clinical prescription. It is a general concept of the above-mentioned periodic and complete training cycle and plan. (1) The prescription can customize the bed creation stage. Common stages include: evaluation stage, training stage, verification stage and application stage, etc. The above stages can be combined as needed. (2) The training and plan of each stage can also be configured with jump logic and recommendation rules to form a training prescription. Different users can generate personalized training paths and plans.

[0096] It's important to note that, in practice, training tasks, plans, and prescriptions are three entities. A training configuration involves configuring a single training task. A training task is a configured assessment or training tool, documented as a "training resource," similar to a "scale." A training plan is a combination of training tasks, similar to a training package. A training prescription is a phased, time-based combination of training and plans, which can be configured to form a complete training course over a specific period of time. Taking group biofeedback training in the medical field as an example, this approach offers the following advantages: it can meet the diverse needs of patients, reduce the time required for healthcare professionals to repeatedly configure training, and ensure standardized and regularized assessment and treatment systems. For example, patients requiring rapid recovery may simply visit a training center and select one or two training sessions. For patients requiring long-term treatment, an assessment can be performed first, followed by a prescription, and comprehensive follow-up treatment can be provided. Alternatively, a comprehensive assessment of the patient's physical and mental state can be integrated into the plan, such as using neurofeedback to assess the patient's nervous system or HRV training to assess the patient's autonomic nervous system. Correspondingly, in step S110: a pre-set training plan and training prescription training configuration set in the training management module is received; wherein, the training plan includes a combination of one or more training tasks, the training management module includes a training scene adapted to the training task, and the training prescription includes a combination of long-term phased training tasks and training plans. The training configuration includes training scenes, training prescriptions and target indicator data, and the training prescription includes training plans for multiple stages.

[0097] An embodiment of the present invention further provides a multi-parameter group biofeedback training device, which is used to implement the steps of the method described in any one of the above embodiments.

[0098] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above. The computer-readable storage medium may be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the art.

[0099] The multi-parameter group biofeedback training method, system and storage medium proposed in the present invention can train subjects according to a pre-selected training configuration, and the training prescription includes jump rules between training schemes to realize multi-modal training of subjects, thereby realizing standardized multi-parameter group biological training.

[0100] It should be understood by those skilled in the art that the various exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is specifically performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0101] It should be understood that the present invention is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted. In the above embodiments, several specific steps are described and illustrated as examples. However, the method of the present invention is not limited to the specific steps described and illustrated. Those skilled in the art may make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present invention.

[0102] In the present invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or replace features of other embodiments.

[0103] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations to the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A multi-parameter group biofeedback training method, characterized in that The method is implemented based on a multi-parameter group biofeedback training system, which includes a training management module. The method comprises the following steps: Obtain a preset training plan and training prescription; wherein, the training plan and prescription are configured in the training management, the training management module is configured to include a training scenario, the training plan is a combination of individual trainings, and the prescription is a combination of phased trainings or training plans in a long-term time series; Display the training scenario to the subjects according to the training or the training prescription to execute the training, and collect the physiological data and / or target index data selected during the training in real time; Wherein, the training prescription includes training plans for multiple preset stages and jump rules between the training plans of each stage, the training plan includes preset training tasks to be executed, and each training task has a corresponding training scenario.

2. The method according to claim 1, characterized in that, Before receiving the training configuration preset in the training management module, the method further includes: Obtain the evaluation report and / or training tools configured in the training management; Configure the corresponding training plan according to the evaluation report and / or training tools of the subjects.

3. The method according to claim 1, wherein The system includes a user management module for managing the training configurations and training records of different subjects. The user management module supports operations on the training configurations and training records of the subjects, including addition, deletion, modification, query, import, export, batch import, and batch deletion.

4. The method according to claim 3, wherein The system further includes a group management module for combining and managing different subjects according to the set requirements. The group management module also supports operations on the training configurations and training records of the subjects, including addition, deletion, modification, query, import, export, batch import, and batch deletion.

5. The method according to claim 1, wherein The training management module supports customizing the training configuration. The steps for customizing the training configuration include: Select the target index data according to the multi-parameter group biofeedback training; Select a training scenario suitable for the multi-parameter group biofeedback training. The types of the training scenario include any one or combination of VR virtual scenarios, audio-visual scenarios, virtual multi-person interactive animation scenarios, virtual multi-person interactive game scenarios, virtual-real fusion scenarios with multi-person interaction, screen-based 3D scenarios, visualization chart components, and audio-visual game resource scenarios; Perform interaction settings between different scenarios according to the jump rules between different training plans in the pre-obtained training prescription; wherein, the interaction settings include end mode settings for ending the training prescription, and the jump rules include jump condition settings and jump relationship networks for jumping between training plans.

6. The method according to claim 5, characterized in that, The step of displaying the training scenario to the subjects according to the training or the training prescription to execute the multi-parameter group biofeedback training and collecting the physiological data and / or target index data selected during the training in real time includes: in the physiological feedback training scenario, select the target index data by freely combining physiological channels.

7. The method according to claim 5, wherein The method further includes: generating a group biofeedback training report according to the target index data display mode pre-configured by the training management module; wherein, the target index data display mode includes target index data to be presented and visualization charts; The step of customizing the training configuration further includes: Configuring the target index data display mode, wherein the visualization charts include, but are not limited to, one or more of a pie chart, a bar chart, and a Venn diagram.

8. The method according to claim 5, characterized in that, The training management module further includes pre-built calculation formulas, classification algorithm models, and recommendation algorithm models. The step of customizing the training configuration further includes: Calculating the group biofeedback training result based on the target index data by using the built-in calculation formula; Classifying the subjects according to the preset classification rules based on the group biofeedback training result by using the classification algorithm model; Recommending the training plan for the next stage to the subjects according to the preset recommendation rules based on the group biofeedback training result by using the recommendation algorithm model.

9. The method according to claim 1, wherein The method further includes: after the training is completed, performing data profiling on the subjects according to the pre-stored algorithms and classification rules of the training configuration, and updating the evaluation report of the subjects after training in real time. The evaluation report at least includes the physiological data and / or target index data of the subjects.

10. The method according to claim 1, wherein The different stages of the training prescription include multiple of an evaluation stage, a training stage, a verification stage, and an application stage. Different training stages include corresponding training plans. The training prescription includes jump rules and recommendation rules preset between different training plans.

11. The method according to claim 1, characterized in that, The multi-parameter group biofeedback training system performs multi-parameter group biofeedback training in a process management manner.

12. The method according to claim 1, wherein The method further includes: After obtaining the target index data, performing data analysis and data profiling based on the obtained target index data, customizing and building a user ability evaluation and training model, and agilely establishing a data model and a data profiling system in a drag-and-drop form, Thereby building an ability model and / or a data profile. After the subjects complete the group biofeedback training, target index data is obtained, and the ability model and / or data profile of the subjects are obtained based on the data model and the data profiling system.

13. A multi-parameter group biofeedback training device, characterized in that, The device is used to implement the steps of the method according to any one of claims 1 to 12.

14. A multi-parameter group biofeedback training system, comprising a processor and a memory, characterized in that, Computer instructions are stored in the memory, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method according to any one of claims 1 to 12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 12.

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