82 results about "Physiological Feedbacks" patented technology

The invention relates to the technical field of nervous system dysfunction, in particular to a nerve regulation and control system for degenerative disease treatment based on multi-modal physiological feedback, which comprises a central processing unit, an optical radiation applicator, a mechanical vibration applicator, an integrated biological signal sensing array and a man-machine interaction module, cooperative stimulation is applied by using a multispectral light source and a broadband vibrator, and multi-dimensional physiological signals such as heart rate variability, myoelectricity, galvanic skin and the like are monitored in real time through a sensor array. A multi-parameter adaptive control algorithm built in the central processing unit can dynamically and intelligently adjust stimulation parameters based on the feedback signals to form an accurate personalized treatment closed loop. Meanwhile, the safety monitoring module based on the biological thermal model ensures the safety boundary of the treatment process. According to the invention, intelligent, self-adaptive and non-invasive treatment of nerve dysfunction is realized.

The invention relates to the technical field of monitoring and alarming, in particular to an intelligent orthopedic rehabilitation training monitoring system based on multi-modal sensing, which comprises a basic data synchronous acquisition module, a dynamic stiffness differential analysis module, a defensive contraction judgment module and a load boundary dynamic reconstruction module. According to the method, a time sequence is constructed by synchronously collecting joint angle and moment data, an instantaneous dynamic stiffness change trend is analyzed by combining a moment and angle difference value, a Savitz-golay filter is used for carrying out second-order differential processing on dynamic stiffness to capture a stiffness second-order derivative mutation point, and the critical moment when defensive contraction pain occurs to the joint of a patient is recognized. The maximum activity angle upper limit is dynamically reconstructed based on the critical angle and the safety buffering difference value, a control instruction is directly fed back to a driving end to execute reverse braking, crossing from single-position monitoring to multi-dimensional mechanical state sensing is achieved, it is ensured that the activity boundary is automatically adjusted according to real-time physiological feedback of a patient, and the safety performance of the patient is improved. And secondary injury caused by forcibly breaking through a pain threshold value is prevented.

The invention discloses a closed-loop percutaneous spinal cord electrical stimulation analgesia system and method based on physiological feedback, and belongs to the field of noninvasive electrical stimulation analgesia technologies and stimulation control systems thereof. The system comprises an electrode patch, a flexible substrate of which is provided with at least one pair of electrode units in an integrated manner, and the electrode patch is used for being attached to a corresponding spinal cord segment area of the body surface of a subject; the physiological signal acquisition module is used for acquiring a multi-modal physiological signal of a subject in real time; the stimulator is electrically connected with the electrode patch and used for generating and outputting electrical stimulation signals to at least one pair of electrode units of the electrode patch; the control module is connected with the physiological signal acquisition module and the stimulator and is used for evaluating the pain state of the subject based on the physiological signals acquired by the physiological signal acquisition module; and according to the evaluation result, generating a control instruction to perform closed-loop adjustment on the output state of the stimulator. According to the system, objective feedback is introduced, adaptability is improved, noninvasive individualization is achieved, operation is easy and convenient, and closed-loop automatic control over monitoring, analysis and adjustment is achieved.

The invention relates to a digital non-abandoned rural culture display and interaction method and device based on a virtual reality technology, and a medium, and the method comprises the steps: obtaining multi-modal data, carrying out the time-space alignment and feature extraction, and obtaining an action track feature and a time-space correlation feature; generating a fusion feature matrix and constructing a virtual display scene; integrating a dynamic narrative engine in the virtual display scene, and constructing a non-abandoned knowledge graph; interactive behavior information and physiological feedback information are obtained in real time, semantic retrieval and path reasoning are carried out, and a response strategy set is obtained; executing the response strategy set; in conclusion, by obtaining the multi-modal data, carrying out space-time alignment and feature extraction, constructing the virtual scene and the knowledge graph and responding to the user information in real time, an organic association network of non-perpetual cultural elements can be constructed, user interaction behaviors can be responded in real time, technical support is provided for display, interaction and inheritance of non-perpetual cultural, and user experience is improved. And the intelligence and the reliability are improved.

The invention provides an intelligent pillow sleep monitoring and personalized improvement method based on digital twinning, relates to the technical field of medical health information, and aims to quickly judge a reflection condition and make emergency intervention through hard-wired logic, generate a personalized intervention strategy for execution by establishing a dynamic digital twinning body, and improve the sleep monitoring and personalized improvement of an intelligent pillow after each intervention. The method comprises the following steps: acquiring implicit physiological feedback data of a user to calculate an intervention consensus score, executing differentiated parameter updating based on the intervention consensus score, performing structural self-evolution when new feature data appears, removing and creating an internal characterization component, and through a dual mechanism of parameter updating and structural self-evolution, establishing an internal characterization component. According to the method, the dynamic change sleep portrait of the user can be accurately described by the digital twinborn body all the time, so that continuous, effective and more intimate personalized services are provided, the technical problem that the suitability of a static model is attenuated is fundamentally solved, the suitability with the user is improved, and a good intervention effect is ensured.

The present application relates to the technical field of healthcare information processing, and discloses a rehabilitation nursing plan method and system, comprising: obtaining a physiological feedback sequence of a subject through a state perception module, and generating a real-time state vector representing a physiological load state by an attribute mapping unit; a logic arbitration module calculates a plan load index of a current path based on a logic migration matrix, and when a limit threshold of the vector is triggered, a target primitive is selected from an alternative task pool to replace a conflict task according to a dimensional orthogonal relationship and a migration cost, the present application realizes the protection of the logical continuity of the rehabilitation path by topological potential constraint, avoids the phase jump of neural remodeling caused by plan switching, and independently maintains the constant total flux of rehabilitation tasks on the premise of guaranteeing the physiological safety envelope of the subject, thereby improving the consistency and evolution resilience of home rehabilitation decision.

The invention relates to the technical field of tourism management, and discloses a cultural heritage travel scene immersion adaptation design method and system, and the method comprises the steps: collecting the multi-dimensional state data of tourists in a cultural heritage travel scene, and the multi-dimensional state data comprise real-time behavior data, physiological feedback data and environment interaction data; performing personalized fusion analysis on the multi-dimensional state data to obtain emotional state analysis data; performing multi-dimensional feature matching on the emotional state analysis data to obtain a personalized culture experience scheme; performing effect simulation on the personalized culture experience scheme in the cultural heritage travel scene, and monitoring behavior state feedback data of tourists in real time; performing adaptive adjustment on the personalized culture experience scheme to obtain an optimized culture experience scheme; performing immersion effect verification on the optimization experience scheme to obtain a target immersion adaptation design scheme; according to the invention, the efficiency of the immersion adaptation design of the cultural heritage travel scene can be improved.

The invention discloses a fitness intensity self-adaptive adjusting method and system based on physiological data feedback, and relates to the technical field of medical rehabilitation. The method comprises the following steps: acquiring historical physiological limit data of a target rehabilitation user and an initial physiological state baseline of a current training period; calculating a dynamic safety intensity interval of the user individual; collecting physiological feedback data in real time in training, inputting the physiological feedback data into the stimulation efficiency evaluation network, and outputting an actual physiological load value and an effective stimulation coefficient of current training; calculating the recommendation intensity of the next training unit in the safety interval according to the effective stimulation coefficient and the rehabilitation progress function; and executing the recommendation intensity, updating the evaluation value based on a new round of physiological feedback data, and carrying out loop iteration until a training cycle target is reached. According to the invention, through dynamic safety boundary and intelligent closed-loop regulation and control, personalized and adaptive optimization of medical rehabilitation training intensity under safety guarantee is realized, and the safety and efficiency of training are improved.

The invention relates to a trajectory type shock wave noninvasive acupuncture system based on manipulation parameterization, and the system comprises a user interaction terminal which is used for receiving a traditional Chinese medicine manipulation operation instruction inputted by an operator; the central processing and control unit is used for converting the traditional Chinese medicine manipulation operation instruction into a corresponding shock wave parameter set through a pre-constructed parameter mapping model; the ballistic shock wave generation module is connected with the central processing and control unit and used for generating ballistic shock waves according to the shock wave parameter set; the treatment head is connected with the ballistic shock wave generation module and used for outputting the ballistic shock waves to human body acupuncture points; the physiological signal acquisition module is used for acquiring physiological parameters of a human body acupuncture point area in real time; the central processing and control unit is further configured to adjust the shock wave output parameters according to the comparison result of the physiological parameters and a preset physiological response model. According to the application, parameterized simulation and dynamic adjustment of traditional Chinese medicine manipulation are realized through real-time physiological feedback, and the treatment accuracy is improved.

This invention discloses an essential oil-based intervention system for the simultaneous treatment of heart and brain function based on dual feedback of eye movement and heart rate variability, belonging to the field of rehabilitation medicine technology. The system includes: a data synchronization acquisition module, which acquires heart rate variability data and eye movement characteristic data and generates a synchronized physiological data stream; a dual feedback joint assessment module, which assesses the patient's real-time physical and mental state level based on the synchronized physiological data stream; a synchronized intervention decision module, which generates essential oil atomization control instructions and eye movement training control instructions in parallel according to the physical and mental state level; and a synchronized intervention execution module, which drives the essential oil atomization unit and the eye movement training unit to execute corresponding intervention actions synchronously at the hardware level on the time axis. This invention achieves integrated and precise intervention of heart and brain function through dual-modal physiological feedback closed loop and synchronized control, effectively solving the problems of brain separation, delayed intervention, and poor coordination in traditional rehabilitation centers, and improving the synchronous rehabilitation effect of cognitive function and autonomic nervous function in stroke patients.

This invention relates to a self-learning method and system for home environment regulation based on multimodal feedback and scene awareness. The method collects the user's physiological characteristics and body movement signals through non-contact sensing devices to identify the user's current activity scene. The system integrates the user's explicit intervention operations with implicit comfort feedback based on physiological stability, dynamically assigning fusion weights for explicit and implicit feedback according to the activity scene to generate target feedback labels. An online incremental learning algorithm is used to update the local environmental control model, and a privacy-preserving model aggregation is performed in the cloud through a federated learning mechanism. This invention solves the problems of traditional home control relying on single commands and lacking physiological feedback mechanisms, achieving intelligent closed-loop control that balances user privacy and personalized comfort.

This invention relates to the field of art education technology and discloses a method for evaluating the effectiveness of overseas art education based on multi-source data fusion, comprising the following steps: collecting images of artworks, time sequences of learning behaviors, teacher comments, and physiological feedback data; preprocessing the multi-source data to generate standardized image tensors, text word sequences, smoothed behavioral features, and physiological attention scalars; extracting multimodal features to obtain deep image features, text sentiment features, behavioral time sequence features, and physiological scalars; using an adversarial decoupling network to decouple image features into three parts: content semantics, source cultural style, and target cultural style, and outputting corresponding feature vectors; calculating the cultural fusion coefficient, fusion entropy, and innovation potential based on the decoupled style features; concatenating multidimensional features, weighting and summing them through an adaptive attention network to obtain a comprehensive score and classifying them into levels; generating a visual evaluation report, including a radar chart, comprehensive score, and sub-dimensional numerical interpretations, and archiving the data.

Embodiments of the present application provide an air conditioner control method, a vehicle and electronic equipment, which comprises the following steps: obtaining an initial physiological characteristic sequence and an initial environment temperature characteristic sequence according to a preset time cycle; constructing an individual dynamic thermal comfort evaluation model based on the initial physiological characteristic sequence and the initial environment temperature characteristic sequence which are synchronized by a time stamp; calculating a real-time thermal comfort index of a target user by the individual dynamic thermal comfort evaluation model; determining a target control parameter for the air conditioner based on the real-time thermal comfort index, an instant physiological characteristic sequence and an instant environment temperature characteristic sequence which are synchronized by the time stamp; generating a control command for the air conditioner by using the target control parameter, and controlling the air conditioner based on the control command. Thus, by time sequence synchronization modeling of physiological and environmental characteristics, the hysteresis effect of human physiological feedback can be effectively eliminated, and precise dynamic matching of the air conditioner control parameter and the passenger transient thermal perception demand can be realized.

The invention discloses a scraping therapy parameter adaptive optimization method and system combined with multi-source data, and relates to the technical field of parameter optimization, and the method comprises the steps: generating a preliminary scraping therapy parameter scheme; a staged scraping therapy target effect is set for each scraping therapy stage; executing the scraping operation in the current scraping stage, and collecting operation dynamic physiological feedback data and user subjective feedback data; evaluating to obtain an effect achievement degree score of the current stage; based on the effect achievement degree score, multi-target self-adaptive optimization is conducted on the scraping therapy parameters of the next scraping therapy stage, the optimal scraping therapy parameters of the next scraping therapy stage are generated, and the scraping therapy instruction is executed. The technical problems that the subjectivity is high and the effect is unstable due to the fact that existing scraping therapy parameters depend on artificial experience judgment, and the personalized adaptability and the intelligent degree are low due to the lack of a dynamic monitoring and real-time feedback mechanism are solved.

The application discloses a pre-hospital emergency intelligent tourniquet individualized pressure determination and closed-loop pressure control system and method. The system comprises an intelligent tourniquet execution terminal, a limb mode recognition, a thin clothing condition confirmation, a parameter collection, a typing KTP prediction, an initial target pressure calculation, a feedback correction, a target pressure locking and a closed-loop pressure control module, and is also equipped with a safety protection, a time sequence control, a voice interaction and a data recording module. The method first recognizes the upper limb or lower limb hemostasis mode, determines the thin clothing condition through low pressure exploration and pressurization, collects the limb girth, systolic pressure, physiological feedback and real-time pressure parameters, calculates the tissue filling coefficient KTP and the initial target pressure, and locks the final target pressure after the physiological feedback correction. The application can realize the upper and lower limb typing individualized precise pressure control, adapt to the thin clothing emergency scene, is simple and easy to operate, safe and stable in hemostasis, and is suitable for pre-hospital trauma emergency rapid hemostasis.

The invention discloses a thermoelectric synergistic excitation signal generation system suitable for electrotherapy, and the system comprises a time sequence control central module which is used for building a mapping relation between an electrotherapy main parameter and a thermal therapy auxiliary parameter, so as to generate a time sequence control instruction; the thermal therapy auxiliary module is used for regulating and controlling the activity of a temperature sensitive channel on an electrotherapy target region of the target object in a thermal therapy synergistic pretreatment stage based on the time sequence control instruction so as to construct an electrotherapy synergistic microenvironment, and maintaining a temperature environment adaptive to the target object in an electrotherapy leading implementation stage; generating a gradient cooling signal along with the electrotherapy end of the target object in the gradient termination stage; the electrotherapy main module is used for outputting a first treatment electric signal in an electrotherapy leading implementation stage based on the time sequence control instruction and generating a second treatment electric signal in a gradient termination stage; and the mapping optimization unit is used for monitoring the physiological feedback characteristics of the target object on the first treatment electric signal or the second treatment electric signal so as to optimize the mapping relationship between the electrotherapy main parameter and the thermal therapy auxiliary parameter.

The invention discloses a virtual resource processing method and device, a storage medium, equipment and a program product. The method comprises the following steps: acquiring physiological data of a user; the physiological data are preprocessed to obtain feature change data, and the feature change data can represent physiological changes of the user; material control parameters and / or physical control parameters of the virtual resources are / is calculated based on the feature change data; and adjusting visual attributes of the virtual resources according to the material control parameters and / or adjusting physical attributes of the virtual resources according to the physical control parameters. According to the method, the physiological data can be effectively converted into real-time parameters in the game through data analysis and quantification, reliable technical support is provided for development of physiological feedback games, and therefore better game experience can be provided for users.

The invention relates to a diver stress state and attitude simulation method and device, equipment and a medium. According to the method, a physical entity with accurate direction and speed is constructed, so that real environment driving is provided for stress calculation of the diver; by establishing a refined hydrodynamic model based on multiple rigid body segments, the influence of attitude change on motion stability, resistance and energy consumption is accurately simulated; a physiological feedback mechanism in which the pressure, the visual range and the fluid environment are linked is established, and diver operation training conforming to the fluid mechanics law and human kinematics is achieved.

The invention provides a lower limb blood circulation promoting system and method based on physiological feedback self-adaption, and relates to the technical field of intelligent wearable. According to the scheme, a plurality of detachable independent flexible air bag units are integrated through a flexible wearable sleeve, and segmented sequential inflation and deflation in the axial direction of a leg are achieved in cooperation with a circulation air pressure module; the muscle pump effect is effectively simulated to push venous blood to flow back; meanwhile, the micro-current stimulation module outputs low-frequency pulse current to directly activate muscular tissues of the lower limbs and enhance the vasomotor function, and the warm physical therapy module provides partitioned controllable warm stimulation; a sensing monitoring module arranged in the system collects PPG blood flow signals before and after pressurization, the internal pressure of each air bag and the skin temperature in real time, and a control module calculates a venous return index based on pulse wave amplitude changes, so that the air pressure intensity and rhythm, the micro-current frequency and amplitude and the heating temperature are dynamically adjusted; cooperative self-adaptive regulation and control of three modes of air pressure, electrical stimulation and warming are achieved, and blood circulation of the lower limbs is promoted.

The invention relates to the technical field of virtual reality medical training, and discloses a cardio-pulmonary resuscitation simulation training system based on virtual reality. The system comprises a situation configuration module, an operation driving module, a physiological feedback module, an operation guidance evaluation module and a data integration and tracing module. The system receives a situation selected by a user and loads a corresponding anatomical model and pathological data to generate a virtual patient; collecting a user gesture and a force application vector through VR equipment, and driving the model to deform; deducing a vital sign sequence in real time by combining deformation and pathological data, and dynamically adjusting the physiological characterization and sound effect of the patient; performing frame-by-frame space-time alignment and difference measurement on the user operation and the standard regulation, rendering a guide mark at a corresponding position of the VR view field, and judging whether the operation generates expected physiological intervention or not based on the vital sign sequence; and various types of data are integrated to form a traceable training timeline. According to the system, high-simulation training of dynamic physiological response and immersive space guidance is realized.

The application relates to the field of artificial intelligence technology and discloses a non-sensing user identification and self-adaptive training method and system based on an AI display screen, which comprises the following steps: collecting a front face image and a human body posture video of a user by a visual sensor of an AI display screen of a sports device in a non-sensing mode; after extracting a part-related descriptor of a human face contour region in the front face image, generating face texture features corresponding to the user, and determining a user identity corresponding to the user; extracting skeleton key point data in the human body posture video to determine a joint position and a limb angle of the user, and analyzing action standardization of the user; collecting physiological feedback signals and behavior performance data of the user in real time by using an auxiliary sensor in the AI display screen, analyzing physiological fatigue of the user, and performing self-adaptive training and adjustment on sports parameters of the sports device to obtain an adjustment result. The application can improve the accuracy of non-sensing user identification and self-adaptive training based on the AI display screen.

This invention discloses an adaptive moxibustion robot system and control method based on multimodal physiological feedback, belonging to the field of intelligent medical equipment for traditional Chinese medicine. The system includes a main control computer, a power supply unit, a six-degree-of-freedom robotic arm, and an end effector module. The end effector integrates a carbon fiber infrared heating module, a high-resolution infrared thermal imager, and a laser Doppler blood flow probe. The method uses a multimodal sensing module to non-contactly acquire video streams of skin heat distribution and time-series data of microcirculation blood perfusion in the moxibustion area. After preprocessing, this data is input into a moxibustion sensation quantification mapping model of a dual-stream spatiotemporal neural network, achieving a quantification mapping between objective physiological indicators and the three phases of moxibustion sensation. Then, through a deep reinforcement learning adaptive control algorithm, using the quantified moxibustion sensation value as the state observation, the robotic arm posture and heating power are dynamically adjusted to form a closed-loop control. This invention breaks through the subjective barrier of moxibustion, achieving personalized adaptive moxibustion and improving the safety and clinical efficacy of moxibustion.

This invention discloses an emotion monitoring system based on sleep HRV characteristics, belonging to the field of intelligent health monitoring technology. The system includes: simultaneously collecting PPG, EEG, and near-infrared light signals during sleep; analyzing HRV sequences and respiratory wave morphology based on PPG signals; achieving sleep microstructure staging through cardiopulmonary coupling analysis; extracting dynamic HRV features based on the staging results and comparing them with personalized stage baselines; detecting and labeling emotional load events; constructing and updating a nighttime emotional event atlas; predicting safe intervention time windows based on the atlas and sleep staging; executing personalized interventions and collecting physiological feedback data to form a closed-loop optimization system. This invention achieves high temporal resolution, event-oriented nighttime emotional dynamic identification and safe intervention, improving the accuracy and reliability of emotion monitoring.

The present application relates to a kind of hemodialysis patient rehabilitation exercise auxiliary decision system and method, the system includes: data acquisition layer, intelligent analysis and decision-making layer, interactive execution layer and feedback optimization closed loop, data interconnection is realized between the data acquisition layer, intelligent analysis and decision-making layer, interactive execution layer and feedback optimization closed loop.By utilizing artificial intelligence technology, the multidimensional static and dynamic data of patient are fused, accurate and completely personalized rehabilitation exercise prescription is generated, rehabilitation effect and efficiency are improved, real-time risk monitoring and early warning model is established, exercise suggestion is adjusted or terminated according to patient physiological feedback before exercise and during exercise, patient safety is ensured, in addition, the present application constructs "evaluation-decision-execution-feedback-reoptimization" digital closed loop, improves the scientificity, safety and patient compliance of exercise rehabilitation, provides an efficient, accurate and intelligent auxiliary tool for hemodialysis room nurse.

The invention discloses a dynamic simulation VR racing simulator and a use method, and belongs to the technical field of virtual reality simulation. The simulator comprises a dynamic physical simulation frame, a VR head display assembly and a dynamic simulation control system. The dynamic physical simulation frame adopts a three-degree-of-freedom motion platform, and simulates the motion posture and acceleration impact of the vehicle through a driving motor, an actuator and a sliding plate; the VR head-mounted display assembly is integrated with an eyeball tracking module and a biosensor, and captures a visual focus and a physiological state of a user in real time; the dynamic simulation control system synchronously processes multi-source data through a data fusion module, generates a low-delay control instruction by using a vestibular-visual conflict elimination algorithm, and dynamically optimizes exercise intensity and a rendering strategy according to physiological feedback of a user through an adaptive adjustment module. According to the invention, multi-sensory synchronous feedback of vision, vestibular sense and touch sense is realized, the occurrence of motion sickness is effectively reduced, and highly immersive and personalized racing car simulation experience is provided.

The invention provides a physiological measurement parameter self-adaptive configuration method and system based on a signal separation degree, and relates to the technical field of measurement for diagnosis purposes, and the method comprises the following steps: analyzing prior data of a target object, and determining a corresponding measurement configuration classification; according to measurement configuration classification mapping, obtaining an initial stimulation parameter set, and constructing control instruction output to trigger test stimulation for inducing physiological response; acquiring a physiological feedback signal corresponding to the test stimulation, determining an artifact influence time interval and a response analysis time interval based on the triggering moment, identifying a stimulation artifact component and a physiological response component, and calculating a signal separation index; when the signal separation degree index does not meet the preset threshold value, iteratively adjusting the time domain distribution parameters in the stimulation parameter set until the signal separation degree index meets the threshold value; and outputting the physiological measurement indexes. According to the method, the effective response extractability and the measurement result reliability can be improved under the condition that interference and response are overlapped due to individual differences and detection condition changes.

The invention relates to the technical field of medical care information processing, and discloses a rehabilitation nursing planning method and system, and the method comprises the steps: obtaining a physiological feedback sequence of a subject through a state perception module, and generating a real-time state vector representing a physiological load state through an attribute mapping unit; and the logic arbitration module calculates a planned load index of the current path based on the logic migration matrix, and screens a target primitive from the alternative task pool to replace a conflict task according to the dimension orthogonal relation and the migration cost when a vector triggers a limit threshold. Neural remodeling phase jump caused by plan switching is avoided, the total flux of rehabilitation tasks is autonomously maintained to be constant on the premise of guaranteeing the physiological safety envelope of a subject, and the consistency and evolution toughness of home rehabilitation decisions are improved.

The application relates to the technical field of industrial cyber-physical systems and man-machine cooperation, and discloses a collaborative mechanical arm adaptive explanation method and device based on man-machine-environment risk field and physiological feedback, equipment and a medium. First, a Bayesian space-time graph convolution network is used to process operator bone sequence to predict the action trajectory; the electroencephalogram and eye movement signals of the operator are synchronously collected to calculate a behavior field coefficient; the mechanical arm kinetic field, the obstacle potential field and the above behavior field are combined to construct a "man-machine-environment" comprehensive risk field and calculate a criticality field strength. Based on the criticality, the system dynamically infers the attention level of the operator, adaptively configures explanation content including what, why and how to do and a pushing time, drives multimodal pushing of an audible and visual screen and mechanical arm obstacle avoidance intervention; the application breaks the "only physical distance theory" deadlock, effectively reduces alarm fatigue, and realizes high-safety, high-transparency dynamic man-machine cooperation.

The invention relates to the technical field of high-voltage equipment practical training, in particular to a multi-mode intelligent high-voltage practical training system, which comprises a practical training data sensing module for acquiring a practical training environment, a high-voltage equipment virtual-real state, student behaviors and physiological feedback data; the practical training simulation module constructs a dynamic practical training scene and simulates complex faults, extreme working conditions and emergency processes; the training evaluation center evaluates the operation specification, the fault diagnosis logic and the emergency response capability of the trainee through an improved Transform-ConvNeXt model, generates a score and a short board report, and carries out risk early warning; the scene interaction unit provides a multi-mode interaction function and visually demonstrates disassembly of the high-voltage equipment and an internal electric field and a magnetic field; and the practical training adjustment pushing unit dynamically adjusts the practical training scene difficulty and the content emphasis according to the evaluation result, the student state and the equipment load, generates a practical training report and pushes a personalized improvement scheme. Therefore, the problems of single practical training scene, inaccurate evaluation and the like in the prior art are solved.

The invention discloses a VR large-space multi-mode sensory fusion immersive experience system, and the system comprises a large-space positioning and motion capturing module which is used for obtaining the position and posture data of a user in a physical space in real time; the multi-modal sensory data acquisition module is used for synchronously acquiring physiological feedback data of the user and environment state data of the physical space; the fusion control system is in communication connection with the large-space positioning and motion capturing module and the multi-mode sensory data acquisition module, and the fusion control system is used for driving a virtual scene containing audio-visual content to update according to the position and posture data; and based on the physiological feedback data, the environmental state data and a current virtual scene event, performing calculation through a dynamic sensory weight distribution model, and generating a sensory channel weight coefficient set at least corresponding to a touch sense, a force sense and an environmental simulation feedback channel. According to the invention, high-quality immersive experience of deep adaptation of people, scenes and environments in a large-space scene can be realized.