157 results about "Physiological Feedbacks" patented technology

The invention discloses an intelligent orthopedic rehabilitation self-adaptive evaluation method and device based on multi-modal physiological feedback. The method comprises the steps that multi-modal physiological data including electromyographic signals, knee joint three-dimensional motion trails, plantar pressure distribution and cognitive input degree of a subject are synchronously collected; constructing a three-dimensional baseline vector according to the MMT muscle force test, knee joint ROM measurement and VAS pain score of the subject; inputting the multi-modal physiological data and the three-dimensional baseline vector into a personalized orthopedic rehabilitation model, and outputting a knee joint function index prediction value and personalized rehabilitation adjustment parameters; dynamically adjusting electrical stimulation parameters according to rehabilitation adjustment parameters output by the personalized orthopedic rehabilitation model; if the cognitive load index exceeds the early warning line, the electrical stimulation intensity is reduced; otherwise, activating the hippocampus body wave stimulation mode. Adjustment is carried out according to the real-time state of the subject, blindness and subjectivity in the rehabilitation process are avoided, and the rehabilitation efficiency and success rate are improved.

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.

The invention discloses a respiratory rehabilitation training management system based on an applet, and relates to the technical field of medical health, and the system comprises a data collection module which collects the physiological data of a user in real time through a sensor at an applet end, and comprises a respiratory rate, thoracic and abdominal movement displacement, airflow pressure and a physiological state calculation module; according to physiological data collected in real time, the actual breathing flow of each patient is dynamically calculated through a thoracico-abdominal movement-airflow dynamics combined equation. According to the respiratory rehabilitation training management system based on the applet, by adopting a thoracico-abdominal movement-airflow dynamics combined equation and a lightweight LSTM network, delay between physiological feedback and training instructions is reduced, the real-time performance and individuation of rehabilitation training are ensured, through local real-time processing and feedback, the problem of traditional cloud delay is avoided, and the system is suitable for popularization and application. And the training compliance and the rehabilitation effect of the patient are effectively improved.

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.

The invention provides a sound coordination method and system based on a tinnitus condition, and relates to the technical field of tinnitus treatment.The method comprises the steps that a tinnitus feature vector of a patient is established through broadband hearing testing and three-dimensional sound field modeling, and a dual-mode treatment audio is generated based on the tinnitus feature vector; the dual-mode treatment audio comprises offset sound waves with opposite phases and masking sound waves with matched frequency bands; establishing a dynamic mapping relationship between a game interaction event and the audio parameters of the dual-mode treatment audio; and dynamically adjusting treatment parameters according to the dynamic mapping relation and the real-time physiological feedback data. The tinnitus characteristic vector of the patient is accurately established through comprehensive application of broadband hearing testing, three-dimensional sound field modeling and binaural sound field matching, and the treatment audio is dynamically adjusted according to personalized characteristics of tinnitus. According to the personalized sound coordination method, the tinnitus symptom can be effectively relieved according to the tinnitus symptom of each patient, and the treatment compliance of the patient is improved.

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 man-machine interaction, in particular to an immersive space-oriented real-time data fusion method and system, and the method comprises the following steps: obtaining the position data of a viewer, extracting the change characteristics of the movement direction, distinguishing the dynamic state of a track, arranging the light source direction, sound pressure parameters and electrocardiogram period data, and matching the nodes with the consistent trend of various types of data. And screening a node group with a high fitting degree, pushing coordinates to a control path, and generating an audio-visual control fusion feedback set. According to the method, dynamic segmentation is carried out according to the movement direction change through the behaviors of the viewer, the track recognition precision is enhanced, space-time pairing of sound pressure parameters and electrocardio cycle data is achieved, the multi-source information synchronization capability is improved, linkage classification among sensing parameters is achieved through difference data trend consistency judgment, and the coordination of interaction response is improved; the node parameters and the position coordinates are synchronously pushed to a control path, a dynamic mapping relation between physiological feedback and audio-visual content is formed, and the response efficiency and coherence of fusion triggering are optimized.

The invention discloses an intelligent control method for a sleep cabin lighting system, and the method is high in adaptability: through monitoring the physiological indexes (such as heart rate, skin conductance and the like) and subjective pressure feeling of a user in real time, lighting parameters, such as brightness, color temperature and the like, can be dynamically adjusted, so as to meet individual demands of different users. The system can adaptively cope with environment changes and user state changes, and the optimal lighting effect is ensured. Reasonable illumination adjustment is beneficial to adjustment of the physiological rhythm of the human body, and the user is promoted to enter a good sleep state. The sleep quality can be improved and the rest experience of the user can be improved by reducing interference and pressure of illumination on the user to the maximum extent. The intelligent control system can adjust lighting parameters in real time according to user requirements, and unnecessary energy consumption waste is avoided. By optimizing the lighting strategy, the overall energy consumption can be greatly reduced, and the energy-saving target is achieved. And real-time feedback and optimization: the system can collect physiological feedback data of the user in real time and perform analysis and optimization in combination with subjective feelings of the user. Through online learning and algorithm iteration, the system can continuously improve the control precision and the user satisfaction. The user does not need complex operation, and the system can automatically provide the best lighting experience according to the user state. The control burden of the user is relieved, and the usability and friendliness of the system are improved.

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 discloses a voice interaction method and system based on an intelligent doll, and relates to the technical field of intelligent acoustic interaction, and the method comprises the steps: carrying out the time-frequency analysis processing of a vibration feature matrix, and generating a modal parameter set of vocal cord vibration through biomechanical modeling in combination with the human neck tissue density features; inputting the modal parameter set of vocal cord vibration into the vibration-acoustic model to generate a sound source excitation field, performing environmental noise compensation on the sound source excitation field by using the acoustic characteristic matrix, and generating a time domain pure voice signal through an acoustic wave equation; and collecting real-time position coordinates of the user, calculating and driving a piezoelectric loudspeaker array of the intelligent doll to adjust the phase according to the frequency spectrum characteristics of the time domain pure voice signal, forming a directional focusing sound field, recording user physiological feedback, and generating a user physiological feedback matrix. According to the method, the vocal cord displacement modal function vector is solved through the nonlinear integral and augmented Lagrange algorithm, so that the acquisition precision and the anti-noise capability of the voice signal are improved from the source.

The invention discloses a whole-body wearable disease symptom simulation system for medical and nursing clinical education. The system comprises a whole-body wearable device; the control unit is used for controlling electrical stimulation parameters of the electrical stimulation unit; the control unit comprises an input module, a disease symptom model library and a stimulation control module; the stimulation control module extracts a corresponding electrical stimulation scheme from the disease symptom model library, adjusts and generates a control instruction, and controls the electrical stimulation unit to perform electrical stimulation according to a set electrical stimulation parameter sequence; the feedback module is used for collecting physiological feedback data of the subject in real time and feeding back the physiological feedback data to the control unit, monitoring the physiological state of the subject and adjusting electrical stimulation parameters; the display interface is used for displaying the simulation process, the control parameters and the physiological feedback data. According to the invention, through integrated control of the wearable device and the computer, accurate electrical stimulation is carried out on the corresponding acupuncture points for comprehensive stimulation, the pain or discomfort experience of specific diseases is completed, and the clinical education effect of medical and nursing is significantly 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 disclosed physiological feedback systems and methods assist with assessing, monitoring and / or treating a patient experiencing a cardiac arrest event. The systems and methods receive multiple inputs and are continuous and / or iterative during a treatment session to provide physiological state trends of the patient. An index of the physiological state of the patient can be derived and confounders, and / or their effects, can be identified, and / or removed, from the index. Additionally, the systems and methods can assist with determining ischemic injury in a patient based on cerebral tissue oxygenation and / or other physiological data.

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.

A system and method for optimizing a patient's Kegel exercises is provided. The system includes a user interface device and a vaginal device. The vaginal device includes an intra-vaginal probe having an accelerometer that is configured to generate a signal in response to movement of the probe. The user interface device is connected to the vaginal device and analyzes signals from the accelerometer to provide physiological feedback information to the patient. The vaginal device may be connected to the user interface device via wireless communications such as Bluetooth or by wire. The user interface device may be a smart device or a computer that transmits information to central web-based data server accessible by the patient or authorized healthcare providers or third-party payers.

The invention relates to the technical field of computer science, and discloses an intelligent auxiliary system and method for rehabilitation nursing, and the method comprises the steps: obtaining and inputting user data, and forming a personalized rehabilitation threshold; a reinforcement learning model is initialized, real-time physiological feedback of the user is collected, a preliminary training scheme is generated in combination with the personalized rehabilitation threshold, and the training scheme is optimized in combination with micro expressions and gestures of the user; performing rehabilitation progress evaluation on the trained user data, and judging whether a training scheme needs to be adjusted or not; and based on a judgment result, updating a training scheme, and adjusting a personalized rehabilitation target. The intelligent decision-making ability of the training strategy is improved, human intervention requirements are reduced, the rehabilitation experience and training effect of the user are finally improved, and the rehabilitation process is accelerated.

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 wireless control method and system for a sacral nerve stimulator, and particularly relates to the technical field of nerve control. Myoelectricity, pressure and temperature signals in a sacral nerve area of a user are collected through a multi-modal sensor, an initial parameter set is generated through feature extraction, and the initial parameter set is dynamically matched with a preset physiological adaptation model to generate a target stimulation parameter set. The target parameters are subpackaged, encrypted and transmitted to the stimulator control module by using wireless communication protocols such as Bluetooth with low power consumption, and an executable stimulation instruction is generated; physiological feedback is monitored in real time in the execution process, and an optimized stimulation parameter set is dynamically adjusted and generated according to the deviation condition of the feedback and target parameters; meanwhile, optimizing parameters and historical data are synchronized to a cloud end, and cross-device data synchronization and mode verification are carried out; finally, a final control instruction is executed according to a safety verification result of the device, the method is suitable for nerve regulation and rehabilitation treatment, the prospect is wide, and self-adaptive adjustment and safety management and control of stimulation parameters are achieved.

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 invention discloses a multi-source physiological information comprehensive feedback type music physiotherapy system, method and equipment. The system comprises a biological signal acquisition module, a data processing and analysis module, a music generation and regulation module, a feedback control module, a user interaction module, a receiving and forwarding module and the like. A physiological signal of a user is collected in real time through wearable equipment; denoising the physiological signals and extracting features, and fusing to generate a comprehensive pressure index (CSI); personalized physiotherapy music is matched or generated according to the CSI, and physiotherapy parameters are dynamically adjusted; music physiotherapy is carried out, physiological feedback is monitored in real time, and loop optimization is carried out until the optimal music physiotherapy state is achieved; synchronous collection of multiple physiological indexes is achieved through the wearable device and the like, and the music physiotherapy effect is enhanced by establishing a multi-stage intervention system and dynamic closed-loop regulation and control.

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 invention provides a method for providing digital feedback of activation or suppression for a target brain region. The method comprises the following steps: carrying out physiological feedback training according to a physiological signal through a digital interface; executing a training configuration according to the physiological feedback training; outputting an execution result, wherein the execution result comprises a physiological signal and behavior data; and analyzing the execution result, and if the execution result meets the expectation, maintaining the training configuration; if the execution result does not conform to the expected result, another training configuration is replaced, and the other training configuration is executed. Therefore, unnecessary activation or inhibition on other non-target brain regions is avoided by means of the effect of activating or inhibiting the target brain region in real time, so that the time required for achieving a predicted target is shortened, and the number of training times is reduced.