132 results about "Physiological Feedbacks" patented technology

The invention relates to the technical field of intelligent health, and discloses an intelligent health middle-aged and elderly people behavior data real-time monitoring and analysis method and system, and the method comprises the steps: collecting a biological resonance signal, a gas spectrum and a sound wave signal of middle-aged and elderly people; constructing a resonance characteristic spectrum of the middle-aged and elderly people, and analyzing physiological feedback characteristics of the middle-aged and elderly people by using the resonance characteristic spectrum; constructing an odor-behavior association map of the middle-aged and elderly people, and identifying gas feedback characteristics of the middle-aged and elderly people by using the odor-behavior association map; performing frequency domain decomposition on the sound wave signal to obtain an infrasonic frequency band and an ultrasonic frequency band, identifying internal organ vibration characteristics and body surface action characteristics of the middle-aged and elderly people, and analyzing voiceprint feedback characteristics of the middle-aged and elderly people; the physiological feedback features, the gas feedback features and the voiceprint feedback features are used for conducting behavior analysis on the middle-aged and elderly people, and a behavior monitoring report is obtained. The method can improve the reliability of behavior abnormality analysis of the elderly in smart health.

According to the self-adaptive safety planning method based on the multi-modal intention perception and the physiological signals, through fusion of multi-modal information such as vision, IMU and the physiological signals, accurate intention perception and motion trail prediction are achieved, so that balance is achieved between safety margin and efficiency, and the safety performance of the system is improved. Through fusion of human behavior intention prediction, physiological state feedback and environmental perception data, in combination with advanced planning of intention prediction and immediate adjustment of physiological feedback, sudden actions and environmental changes are coped with. The behavior of the robot or the mechanical arm is dynamically adjusted through feature fusion and a human body intention classification algorithm, the collision probability is effectively reduced, and the man-machine cooperation efficiency and the user comfort degree are optimized while safety is guaranteed.

An Adaptive Neuro-Fuzzy Inference System (ANFIS) for total intravenous anesthesia management is disclosed, enabling control over administration of anesthetic agents and dynamic adjustment according to patient physiological feedback. The system processes patient data, including processed EEG signals, hemodynamic information, capnography, and pulse oximetry, to facilitate real-time anesthetic dosage adjustments.

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 data processing, and provides a data-driven EBT training scene generation method and system, and the method comprises the steps: obtaining a flight control data flow, a physiological feedback data flow and a voice interaction data flow in real time, and enabling the physiological feedback data flow to comprise a pupil diameter change rate; based on the physiological feedback data stream, generating a quantitative score of the system management capability dimension; when the capacity is lower than the preset capacity threshold value, determining the complexity level of the concurrent system fault event; according to the voice interaction data stream, generating a cooperative defect feature set, and combining the complexity level, retrieving a candidate fault event set from a pre-constructed aviation threat knowledge graph, generating a global visual dynamic parameter instruction set, and generating an EBT training scene based on the global visual dynamic parameter instruction set; according to the method, the problems of insufficient authenticity and effectiveness of training and the like are solved, and the individuation degree and actual combat fidelity of an EBT training scene are improved.

The invention relates to the technical field of medical education, and discloses a virtual simulation method for an interactive anesthesia crisis skill training scene, and the method comprises the following steps: constructing a high-fidelity operating room and a crisis processing scene in a virtual environment; physiological parameter changes of the patient are simulated in real time and fed back to the student interface; recording and analyzing operation steps, decision-making time and physiological feedback of the trainee in training; and the learning path of the trainee is dynamically adjusted through a multi-objective optimization algorithm, so that the training effect is enhanced. According to the invention, through a personalized learning path and a real-time feedback mechanism, the effectiveness of anesthesia crisis skill training is improved. Students practice in a vivid virtual environment, and the clinical decision-making ability and the operation accuracy are enhanced. Meanwhile, the system is continuously updated to ensure that the training content is consistent with the latest medical practice, high-quality medical professionals are cultivated, and the medical service quality is comprehensively improved.

The invention discloses an intelligent diopter training system and method based on a multi-modal physiological feedback and reinforcement learning algorithm. The intelligent diopter training system comprises a multi-modal physiological data acquisition module, a central processing PC, a user terminal and a cloud data platform. Visual behavior data, ciliary muscle state data and autonomic nerve reaction data of a user are collected in real time through a multi-modal physiological data collection module, multi-modal physiological data fusion and feature extraction are carried out, and a refraction state evaluation model is used for calculating a comprehensive score of a refraction state grade, visual fatigue and adjustment sensitivity of the current user. A personalized training parameter set of the next training period is dynamically decided and generated based on a reinforcement learning algorithm, and the user terminal presents visual training stimulation according to the current personalized training parameter set. The cloud data platform stores the data and generates a visual training effect trend chart, a diopter change prediction report and personalized training suggestions to complete training scheme personalization, training means intellectualization and feedback evaluation comprehensiveness.

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 provides a robot navigation path planning method and system which are applied to the technical field of robot navigation, and the method comprises the steps: obtaining a preset navigation path to carry out surface interaction operation (such as ultrasonic scanning, physiotherapy massage and other scenes) on a target muscle group, and extracting a real-time muscle group activation degree index; the deviation between the current surface interaction operation effect and the expected target is quantified through the error signal, and the navigation path parameters of the surface interaction robot are dynamically adjusted by calculating the control quantity to obtain a corrected navigation path instruction; by executing the corrected navigation path instruction, the robot can adjust its behavior according to real-time physiological feedback, so that the surface interaction operation process can be continuously optimized towards the preset target muscle group activation degree target value, thereby improving the effectiveness and individuation degree of physiotherapy. The method has the advantages that the dynamic adjustment of the navigation path is realized through real-time electromyographic signal feedback, and the individuation, the self-adaptability and the effect of the surface interaction operation are improved.

The invention discloses a robot lacrimation control method and a microfluid lacrimation execution device for a robot, and relates to the technical field of bionic robot emotional interaction.The robot lacrimation control method comprises the steps that multi-modal sensing data of the robot is obtained, determining a first code used for judging an emotional state and a second code used for judging a physical stimulation response of the robot according to the multi-modal sensing data; and according to the first code and / or the second code, determining an emotion code of the robot, and according to the emotion code, determining a tear instruction for controlling the operation of a microfluid tear execution device of the robot, so that the robot tears. The emotional codes are generated through an emotional state and physical stimulation double-path mechanism, the simulated lacrimation effect matched with the human emotional state can be achieved, the purpose of rich physiological feedback is achieved, and the lacrimation performance is improved through a liquid storage device, a lacrimation channel, a lacrimation outlet and a miniature pressure pump of the lacrimation execution device. And the robot can realize accurate tear control on the basis of emotion perception of physiological feedback.

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 discloses a method for establishing a massage manipulation standard database and an auxiliary teaching method. The method comprises the following steps: acquiring three-dimensional coordinates of skeleton mark points of a massage expert, interaction data between the massage expert and a receiver, and physiological feedback data generated when the receiver bears massage manipulation; performing feature extraction on the three-dimensional coordinates, the interaction data and the physiological feedback data of the skeleton mark points to form kinematics features, mechanical features and physiological feedback features corresponding to the massage manipulation; and performing normalization processing on the kinematic features, the mechanical features and the physiological feedback features to form a standard data set of the manipulation manipulation. By means of the method, the massage manipulation depending on personal experience is converted into a quantized digital standard, standardization of manipulation skills is achieved, and optimization and improvement of the manipulation are facilitated. Meanwhile, standardized archives of different massage manipulations executed by different massage experts are stored, and digital inheritance of manipulation skills is achieved.

The invention relates to the technical field of postoperative risk prediction, in particular to a cardiovascular intervention postoperative nursing risk prediction system based on physiological feedback. The method comprises the following steps: firstly, acquiring physiological data of historical patients and risk values of postoperative care, and grouping; the aggregation of the risk values of the patients is further analyzed, and the initial typical degree is obtained in combination with the risk values; further analyzing the reference weight of other groups for each physiological data of the target group, analyzing the correlation between the physiological data of other groups and the maximum initial typical degree in other groups, and obtaining the prediction importance of each physiological data of the target group; the final typical degree is further obtained; and finally, based on the final canonical degree fusion risk value of the patients in each group, obtaining a risk optimization value and constructing a prediction decision tree, thereby improving the representativeness and individualized prediction capability of the decision tree.

The application belongs to the technical field of virtual reality, and particularly relates to a sound-driven VR serious game interaction control method for semi-blind people. The method comprises the following steps: constructing a 3D sound scene space and a motion guide field, and converting a motion path into a sound change rule; collecting and fusing user pose and physiological feedback signals in real time; dynamically adjusting sound source parameters and tactile feedback according to pose deviation to realize non-visual orientation guidance; performing boundary verification and area determination through ray projection to ensure interaction safety; synchronously processing collision by using a bounding box model and quaternion interpolation; and establishing a mapping model of emotional parameters and sound characteristics to synthesize exciting sound effects. Through multi-modal collaborative interaction, the application significantly improves the perception accuracy and safety of semi-blind users in a virtual space, realizes the cooperation of psychological intervention and motion rehabilitation, and has excellent real-time response capability.

The technical scheme of the invention discloses a dynamic optimization system for the household rehabilitation training content of a stroke patient based on GRPO. The exercise performance and physiological feedback of the patient are collected in real time, the system can adjust the training content in a closed-loop mode, the scientificity, safety and efficiency of rehabilitation training are remarkably improved, and the purposes of progressive training difficulty and individualization are both achieved. The system disclosed by the invention not only breaks through the limitations of fixed templates, manual adjustment, feedback lag and the like of traditional rehabilitation training, but also has good expansibility, can be integrated with a rehabilitation robot, intelligent wearable equipment and a mobile health management platform, and promotes collaborative development of rehabilitation medicine, intelligent medical treatment and health industries. Therefore, a new personalized rehabilitation mode based on frontier artificial intelligence decision is provided for patients with cerebral apoplexy and related diseases, theory and engineering systems in the field of intelligent rehabilitation are greatly enriched, and the method has important clinical application value and wide industrial popularization prospects.

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 application discloses a blood pressure monitoring device based on multi-source physiological parameter adaptive control, comprising a blood pressure measurement module, an electrocardiogram measurement module and a processing module. The blood pressure measurement module comprises a microcontroller unit and an air pump and a deflation valve controlled thereby. The processing module acquires multi-source physiological parameters and controls the air path accordingly: when the skin conductance response is high, the deflation time is shortened to reduce the stress stimulus of the patient; when the pulse pressure difference of the initial measurement is large, the deflation frequency is increased to adapt to the rapid change of blood pressure and avoid false hypotension; when the electrocardiogram QT interval is long, the inflation time is prolonged to ensure measurement accuracy. The application dynamically adjusts the inflation and deflation physical process through multi-source physiological feedback, significantly improving the measurement accuracy and adaptability of the device under complex physiological conditions.

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 present invention provides a control system and method for personalized treatment of a left ventricular assist device, relating to the field of artificial heart technology. The method comprises: for each cardiac cycle, a Starling-like regulator receives a left atrial pressure signal fed back by a physiological feedback module, and outputs a desired cardiac index based on the patient's body surface area; a pump flow quantification feedback module calculates the pump flow in real time based on the rotational speed and current of the left ventricular assist device, and outputs the feedback cardiac index in combination with the patient's body surface area; calculates the deviation between the desired cardiac index and the feedback cardiac index, inputs the deviation into a controller, and the controller determines the output current increment based on the deviation; and repeats the above process until the control system stabilizes. Ventricular pressure is monitored by the physiological feedback module and the cardiovascular coupling module, and personalized physiological characteristics analysis is performed in combination with the patient's body surface area, so that the pump speed parameters can be automatically optimized according to the patient's real-time physiological state.

The present invention provides a sound quality adjustment method combining a vacuum tube and a TFT screen display, and relates to the technical field of audio processing. The present invention obtains spectrum optimization information through a vacuum tube module to preliminarily implement sound quality processing, and uses a TFT screen to display the initial sound quality parameter combination and distortion information in real time, so that the user can intuitively understand the current sound quality status; based on a deep learning model, the user's physiological feedback data is analyzed to generate a sound quality adjustment strategy that dynamically adapts to the user's status, further optimizes the sound quality parameter combination, and makes the adjustment process more intelligent; the user can modify the sound quality parameters in real time on an interactive adjustment interface, generate a final optimized secondary sound quality parameter combination indicator, and apply it to the adjustment of digital audio equipment; the accuracy and personalization of sound quality adjustment are improved, and at the same time, efficient real-time feedback and interactive experience are provided.

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 invention relates to the technical field of sleep scene adjustment, in particular to an immersive sleep scene adjustment method and system based on rhythm planning analysis. And acquiring real-time physiological feedback data and immersive sleep state data of the target user to construct a real-time sleepiness index curve, and performing mapping planning on saturated and unsaturated sleepiness rhythms in the sliding sub-window to obtain a real-time sleep rhythm phase. And simulating a preset creation control strategy of the immersive sleep scene through simulation software, and determining a response offset analysis scene for the rhythm phase in combination with electroencephalogram signal inversion calculation. And when the analysis result is a rhythm confusion scene, the real-time rhythm phase in the sleep staging mode is used as a driving benchmark to calculate the phase opportunity difference, and an amplitude compensation mechanism is designed to perform parameter adjustment of a chaos scene factor. According to the invention, dynamic and personalized regulation and control of the immersive sleep scene can be realized, the rhythm disorder or inertia problem is effectively improved, and the immersive sleep quality of the user is improved.