128 results about "Mimetic Muscles" patented technology

The invention relates to the technical field of face verification, and discloses a face identity verification data processing method based on dynamic feature extraction, which comprises the following steps: acquiring a continuous face video frame sequence and calculating a full-pixel instantaneous velocity vector to generate an original dense optical flow field, selecting rigid region anchor points to calculate a rigid affine transformation matrix and construct a theoretical rigid motion field, performing differential stripping on the theoretical rigid motion field from the original dense optical flow field, and extracting a non-rigid micro-motion residual field; mapping the non-rigid micro-motion residual field to a facial muscle topological grid to generate a time sequence feature tensor, and calculating a geodesic line distance between a covariance matrix of the time sequence feature tensor and a reference dynamic feature in a Riemannian manifold space; when the geodesic distance is smaller than a threshold value, verification is passed, through a rigid-non-rigid orthogonal decomposition mechanism, the special viscoelastic micro-motion and cooperation law of biological soft tissue is captured by utilizing a residual field, and the high-simulation mask is effectively defended.

The invention relates to the field of human-computer interaction, and discloses a human-computer interaction robot facial expression implementation control method, which comprises the following steps: dynamically capturing the face, sound and posture of a user in a human-computer interaction scene, and generating an initial emotion perception sequence; performing hierarchical cross mapping on the initial emotion perception sequence, and performing combinatorial analysis on facial expressions, voices and intonations and body movement features to form an emotion matching vector; based on the emotion matching vector, utilizing a priority regulation model to predict the emotion trend of the user at the next moment, and identifying an expression enhancement point and an emotion attenuation area; mapping the generated facial micro-expression adjusting instruction to a robot facial driving unit, and performing real-time correction and conflict resolution on an expression action sequence; and reversely fusing a user fixation point, facial muscle micro-motion and voice emotion which are acquired in real time into an emotion matching vector, and dynamically updating a perception weight and expression regulation and control parameters. The method has the advantage of improving the emotion matching degree of the robot expressions.

The invention discloses an interactive humanoid robot expression simulation method based on artificial intelligence, and relates to the technical field of expression simulation, and the method comprises the steps: collecting a brain wave signal of a user, carrying out the preprocessing, and generating a power spectrum density feature; inputting the power spectral density features into a pre-trained emotion classification model, and outputting an emotion category and an emotion intensity value of the user; performing emotional expression mapping on the emotional category and the emotional intensity value, and outputting a bionic muscle contraction instruction; performing facial adjustment on facial muscle fibers of the humanoid robot according to the bionic muscle contraction instruction, dynamically adjusting surface texture details of the humanoid robot, and generating a simulated micro expression; and capturing user face feedback data through camera shooting eyeballs, evaluating the acceptance degree of the user on the simulated micro-expression based on the user face feedback data, and outputting an expression optimization strategy. According to the method, through deformation matching and expression optimization double-closed-loop modeling driven by user feedback, biological simulation of micro-expressions of the humanoid robot is realized.

The invention belongs to the technical field of image restoration and computer vision, and particularly relates to a multi-mode face restoration and expression recognition system and method based on semantic guidance of a facial action unit. According to the system, multi-scale features are extracted through visual coding, and an AU activation probability is detected by using a graph neural network; the semantic conversion module converts the numerical probability into an interpretable biomechanical structured text; the multi-modal reasoning module fuses vision and text information, introduces the common sense reasoning ability of a multi-modal large language model, and improves the student network performance through knowledge distillation; and finally, the conditional generation module realizes image restoration by taking the semantic features as guidance. The facial action unit is used as a biomechanical medium, the multi-modal reasoning ability is converted into restoration constraint, the defects that in the prior art, restoration of physiology is distorted, recognition depends on image quality, and two tasks are isolated are overcome, collaborative enhancement of face restoration and expression recognition is achieved, and it is ensured that the restoration result is clear in vision and conforms to the physiological law of facial muscles.

The invention relates to the technical field of English pronunciation learning, and discloses an AI (artificial intelligence) English learning system capable of correcting pronunciation. The system comprises a multi-source voice acquisition layer, an acoustic feature analysis layer, a pronunciation quality evaluation layer, a correction decision generation layer and a biological feedback execution layer. The multi-source voice acquisition layer captures a multi-channel sound wave signal and a maxillofacial electromyographic signal in real time when a user pronounces, and generates an original pronunciation data stream; the acoustic feature analysis layer performs time-frequency domain conversion on original data, separates multi-scale acoustic features and constructs a three-dimensional feature tensor; the pronunciation quality evaluation layer compares the standard template library to output scores and phoneme offset vectors; the correction decision generation layer constructs a pronunciation error topological graph and generates a correction instruction set containing tongue position, airflow and vocal cord parameters; and the biological feedback execution layer synchronously monitors the physiological response and updates the weight of the template library. According to the system, accurate acquisition, analysis, evaluation, correction and dynamic optimization of pronunciation learning are realized, and the English pronunciation learning effect is improved.

The invention relates to the technical field of speech recognition and synthesis, and discloses a multi-mode speech conversion method and system based on user behaviors, and the method comprises the steps: carrying out the vibration separation of a bone conduction signal, obtaining a separation vibration signal, mapping the face muscle micro-current into a muscle deformation gradient, and analyzing the intention intensity of a user through implicit behavior data; mapping the muscle deformation gradient into a voice fundamental frequency of the user, linearly converting the separation vibration signal into a voice formant of the user, and performing noise injection on a non-voice active section based on intention intensity to obtain noise injection voice; constructing user behavior voice corresponding to the voice fundamental frequency, the voice formant and the noise injection voice through an orthogonal projection layer in a preset orthogonal regularization vocoder; and synthesizing the speech feature vector and the user behavior speech into bone conduction propagation speech through a bone conduction synthesis layer in an orthogonal regularization vocoder. According to the invention, the accuracy of the multi-mode voice conversion technology can be improved.

The invention relates to the technical field of bionic robots, and provides a bionic robot head system which comprises a multi-mode sensing unit, a dynamic expression generation unit, an environment analysis unit and a bionic execution unit. The multi-modal sensing unit is used for synchronously acquiring visual, auditory and physiological signals and tactile data, the dynamic expression generation unit is used for generating a non-preprogrammed facial muscle driving instruction in real time by taking the multi-modal sensing data as an input condition, and the bionic execution unit is used for responding to the driving instruction to realize micro-expression movement with 0.1 mm-level precision. Visual, auditory and physiological signals and tactile data are synchronously collected through the multi-modal sensing unit, data fusion is performed by applying a cross-modal attention mechanism, human emotion changes can be accurately captured, and high-fidelity dynamic expression presentation is realized through cooperative operation of the dynamic expression generation unit and the bionic execution unit, so that the dynamic expression presentation efficiency is improved. Compared with a traditional robot, the robot is stiff and single in expression.

The invention provides a smokeless intelligent accurate control method for prevention and control of juvenile myopia. The smokeless intelligent accurate control method comprises the steps of eye movement and facial muscle multi-mode acquisition and noise filtering, dynamic graph convolutional network and spatial-temporal feature fusion analysis, blink and head movement prediction and intelligent moxibustion path adjustment. By constructing a resting state eye movement behavior mode library, coupling face and head dynamic data, utilizing multi-mode feature fusion and AI hierarchical control, accurately recognizing blinking and head disturbance, and generating an avoidance track and a dynamic moxibustion therapy power regulation strategy in advance, the method can effectively avoid periorbital sensitive areas, keep the temperature in the moxibustion therapy process constant, and improve the moxibustion therapy effect. The response speed and path stability are improved, and moxibustion safety and continuity are guaranteed.

The invention discloses a Parkinson's disease patient video analysis and evaluation system based on artificial intelligence. The method comprises the following steps: collecting a multi-modal data set; extracting face key point data in the multi-modal data set by using a Mediappe face detection algorithm, and analyzing blink frequency, eyelid movement symmetry and face muscle tension change; extracting a hand joint motion track through an OpenPose model, and calculating tremor frequency, motion completion time and motion smoothness; detecting step length, step width, step speed and coordination of left and right limbs in the gait of the human body based on a YOLOv8 target detection algorithm; dynamically weighting the facial tremor features, the limb movement features and the gait dynamics features through a multi-head attention mechanism; and outputting the symptom evaluation index of the Parkinson's disease patient through the LSTM network. And the efficiency and accuracy of illness state assessment are improved.

The invention relates to a cranial nerve motor function evaluation system and method based on a terminal with a camera. The system comprises a camera used for collecting a high-definition video sequence of facial actions; the model is used for identifying positioning points of the face according to the high-definition video sequence acquired by the camera; the analysis and evaluation module is used for quantitatively evaluating the cranial nerve motor function state according to the change of the positioning points of the face acquired by the model; the analysis and evaluation module performs analysis and evaluation according to the change quantitative indexes of the positioning points of the face; the camera, the model and the analysis and evaluation module are all deployed at the terminal; and the model and the analysis and evaluation module are deployed in an operating system of the terminal. The evaluation system and method are deployed on a common terminal, and are used for collecting a video sequence of a user completing a standard evaluation action, automatically identifying the movement of a positioning point of a face, and outputting a quantitative score according to a medical standard so as to evaluate human face muscle movement and a cranial nerve function state.

To provide a mask inner made of a non-stretchable adhesive sheet which adheres to a facial skin, is expected to have an anti-fogging effect on glasses when wearing a sanitary mask, can also train facial muscles and can suppress inhalation of fine dust such as pollen.SOLUTION: A mask inner is made of a non-stretchable double-sided adhesive sheet 11 having a hood-like structure (hood part 1a) having a function of guiding exhaled breath downward and a breathing hole 1b.SELECTED DRAWING: Figure 10

The utility model discloses an oral and facial muscle function training device which can be worn between dentition and labial muscle or labial and buccal muscle of a patient, is used for blocking contact between the labial muscle or the labial and buccal muscle and the dentition, and comprises an approximately C-shaped blocking screen and a first expandable part, the first expandable part is at least arranged at the corresponding position, corresponding to the deepest position of the bottom of the vestibular sulcus of the patient, of the outer contour of the blocking screen, and after the oral and facial muscle function training device is worn, the first expandable part expands through saliva infiltration and abuts against the bottom of the vestibular sulcus. Thus, according to the size of the oral cavity space of a patient, the first expandable part expands after being infiltrated by saliva, does not continue to expand after meeting the bottom of the vestibular groove of the patient, and can stably abut against the position, so that the oral and facial muscle function training device can be stably worn between the dentition of the patient and the lip muscle or the lip-buccal muscle; the contact between the labial muscle or the labial cheek muscle and the dentition is blocked.

The present application relates to a kind of based on two-way optical flow to realize the method for fast micro-expression recognition processing, comprising the following steps: according to visual system acquisition tester face micro-expression video segment information;Extract the emotional video segment in emotional memory library, and the facial muscle movement situation of micro-expression in emotional video segment is captured by positive and negative two-way optical flow;Extract method extracts key frame in emotional video segment, and the redundant frame in continuous sequence image is eliminated;Call the optical flow information between key frame in optical flow information memory library.The present application also relates to a kind of two-way optical flow to realize fast micro-expression recognition device, processor and storage medium.The method for fast micro-expression recognition processing based on two-way optical flow of the present application, device, processor and its computer readable storage medium, the facial muscle movement situation of micro-expression is captured by positive and negative two-way optical flow, the micro-expression of tester is identified using muscle movement trend, and the micro-expression recognition accuracy is improved.

The invention provides a peripheral facial paralysis rehabilitation device. The peripheral facial paralysis rehabilitation device comprises a host and at least one stimulation patch electrically connected with the host, the stimulation patch is prefabricated into a special-shaped geometric structure matched with the anatomical direction of facial muscles, and at least integrates a myoelectricity acquisition part, an electrical stimulation part and a heating part; the host is configured to collect a surface electromyographic signal sequence of a user under a specified facial action through the electromyographic collection part of the worn stimulation patch, and the stimulation patch worn by the user is in one-to-one correspondence with target facial muscles involved in the specified facial action; determining at least one muscle function state index according to the surface electromyogram signal sequence; determining a working mode according to the muscle function state index; and controlling the electrical stimulation part and / or the heating part of the stimulation patch worn by the user to work according to the working parameters corresponding to the determined working mode.

The invention discloses a facial muscle convulsion monitoring system based on multi-sensor fusion. The facial muscle convulsion monitoring system comprises a detection device and a visualization device. The detection device comprises a main control unit, a multi-channel sensor unit and a wireless communication unit. The multi-channel sensor unit collects muscle movement signals of multiple groups of symmetrical facial muscle monitoring areas of a target person in a preset posture; the main control unit carries out filtering processing and comparison processing on the muscle movement signals of each group of symmetrical facial muscle monitoring areas to obtain target detection data after noise suppression; the wireless communication unit transmits the target detection data to visual equipment; and the visualization device generates a multi-dimensional display chart according to the target detection data and displays the multi-dimensional display chart. Interference data are eliminated through filtering processing and symmetric region data comparison processing, so that data with a high signal-to-noise ratio is obtained, and the detection accuracy is improved; and the cost is low, and the requirements of home autonomous monitoring and long-term illness state tracking of common users can be met.

The invention relates to the technical field of traditional Chinese medicine compositions, and provides a traditional Chinese medicine composition for treating facioplegia and a preparation method thereof, the traditional Chinese medicine composition comprises radix paeoniae rubra, ligusticum wallichii, angelica sinensis, lumbricus, astragalus membranaceus, peach kernel, safflower, scorpion, centipede, stiff silkworm, rhizoma typhonii, divaricate saposhnikovia root and gastrodia elata. The astragalus membranaceus can tonify qi of the spleen and the lung, promote blood circulation and eliminate stasis; angelica sinensis, radix paeoniae rubra, ligusticum wallichii, peach kernel and safflower are coordinated to promote blood circulation to remove blood stasis, improve facial microcirculation and relieve muscular disorder caused by deficiency of qi and blood; lumbricus has the effects of clearing and activating channels and collaterals and enhancing blood- Scorpio, centipede and stiff silkworm are insect wind-expelling medicines, penetrate into meridians and collaterals to expel wind and relieve convulsion, and especially aim at facial muscle convulsion; rhizoma typhonii and divaricate saposhnikovia root expel wind and remove cold, and relieve facial paralysis caused by wind-cold attacks; the gastrodia elata can calm liver and stop endogenous wind and assist in controlling abnormal twitch of the face The traditional Chinese medicine composition is remarkable and stable in medicine effect, symptoms disappear after the traditional Chinese medicine composition is taken for 3-8 treatment courses, and relapse is avoided.

The invention relates to an expression line resisting composition containing cell signal factors and plant active ingredients and a skin care product of the expression line resisting composition. The expression line resisting composition is prepared from the following components in percentage by mass: 10 to 50 percent of cell signal factors, 10 to 50 percent of flos chrysanthemi extract and 10 to 50 percent of camellia seed oil. By adopting a composite strategy of metabolism regulation and neuromuscular regulation, nerve-muscular signal conduction is regulated, facial muscle tension is weakened, and dynamic formation of expression lines is reduced; the AMPK energy metabolism pathway is activated, and the cell activity is improved; rOS accumulation in cells is reduced, and the mitochondrial function is improved; strong fat-soluble anti-oxidation protection is provided, the action time is prolonged, barrier repair, moistening and anti-inflammation are facilitated, and therefore the more efficient expression line resisting effect is achieved.

The invention discloses an interactive toy for training psychological toughness of teenagers in the technical field of psychological training. The interactive toy comprises a VR glasses body used for providing a virtual reality training scene for a user; the first acquisition unit is used for acquiring facial muscle pressure change data of an area, shielded by the VR glasses, of a user; the second acquisition unit is used for synchronously acquiring facial expression dynamic data of an unshielded area of the user; the processing unit is used for establishing a personalized psychological state model of the user; acquiring dynamic data of the first acquisition unit and the second acquisition unit in real time, inputting the dynamic data into the personalized psychological state model, evaluating the current psychological state of the user, and generating an adjustment instruction according to an evaluation result; and the adjusting unit is used for adjusting the content presented in the VR glasses body in real time based on the adjusting instruction so as to match the current psychological state of the user. According to the scheme, the adverse effect on the training result caused by the fact that the facial expression cannot be completely captured due to the fact that the VR glasses shield the face can be reduced, and the training effect is improved.

The disclosure provides a digital human generation method based on a multi-modal large model, comprising: constructing a digital human basic model; generating a structured training set; generating a question and answer model supporting multi-channel interaction; outputting a semantic answer to a user question, extracting a text emotional tendency of the semantic answer, and outputting an emotional intensity parameter; generating facial muscle movement trajectory data, and performing real-time rendering on the digital human basic model according to the facial muscle movement trajectory data to output a digital human three-dimensional image with emotional expression. Through cross-modal alignment of text, image and audio data, and by using a joint training method to optimize a multi-modal large model containing a visual, speech and knowledge model, a more natural and smooth multi-channel interaction experience is realized. In addition, by introducing an emotional recognition model and a facial interaction model, the emotional tendency implied in the semantic answer can be more accurately captured and reflected, thereby outputting a digital human three-dimensional image with real emotional expression.

The present application relates to the technical field of functional woven fabric, in particular to a face-slimming beauty headgear and a weaving process for weaving the face-slimming beauty headgear. The face-slimming beauty headgear is an elastic fabric structure woven by an integrated weaving process. The face-slimming beauty headgear comprises a body matched with the head, the bottom of the body has a neck opening for wearing, the face of the body has a mouth and nose opening and two eye openings, the back of the body has a back opening, and the two sides of the body are provided with elastic stretch parts extending to the back of the brain. The face-slimming beauty headgear can form a covering effect on the whole head and face, prevent the irradiation of sunlight, protect the facial skin from external interference, and achieve the purpose of face slimming. The face-slimming beauty headgear utilizes the elastic stretch parts to stretch the facial muscles backward, so that the facial muscles can be relaxed and contracted backward at the same time, thereby achieving the purpose of face slimming. The face-slimming beauty headgear is convenient to wear and can be adjusted after being worn, and is suitable for different head shapes.

This technology efficiently improves the accuracy of musculoskeletal model simulations that take into account variations in muscle development among individuals. [Solution] The simulation device 1 of a musculoskeletal model including multiple muscle parts arranged along the skeleton includes a measurement result acquisition unit 11 that acquires a first measurement result, which is the measurement result of muscle strength measurement using multiple muscle parts belonging to the subject's SFL, and a second measurement result, which is the measurement result of muscle strength measurement using multiple muscle parts belonging to the subject's SBL, and an adjustment unit 12 that performs an adjustment process to adjust the muscle strength of at least one of the multiple muscle parts belonging to the SFL and the multiple muscle parts belonging to the SBL in the musculoskeletal model based on a comparison result of the first measurement result and the second measurement result.

The utility model discloses a line sculpture wire which comprises a wire body, a plurality of continuous barb portions are arranged on the wire body, barbs are arranged on the barb portions, projections of the barbs on the adjacent barb portions on the horizontal plane are staggered, a wrapping net is further wrapped outside the wire body, a plurality of grids are formed on the wrapping net, and the barbs are arranged on the wrapping net. Connecting points are arranged at the positions, corresponding to the barb parts, of the wrapping net, the wrapping net is fixedly connected with the line body through the connecting points, the connecting points are arranged at the edges of the grids, the grids are arranged in a rhombus shape, and the inverted pierces penetrate out of the grids. The facial mask is reasonable in structural layout, can be fixed with facial muscles more firmly, is not easy to rotate and loosen, and has a good use effect.

Provided is an authentication device which includes an authentication moving picture obtaining unit which obtains authentication moving picture in which a person is captured for authentication and an authentication unit which authenticates the person based on the motions of the facial muscle of the person identified by analyzing the authentication moving picture. Provided is an authentication device which includes an authentication moving picture obtaining unit which obtains authentication moving picture in which a person is captured for authentication while walking and an authentication unit that authenticates the person based on the motions of the body muscles of the person identified by analyzing the authentication moving picture.

The invention discloses a multi-channel-based facial muscle cooperative adjustment device, and solves the technical defects that an existing electronic face patch is provided with a plurality of controllers, cooperative control over a multi-channel electrode plate group cannot be realized, the use effect is not ideal, and the comfort is poor. An adopted controller comprises a power supply unit, a boosting unit, a main control unit, a left face electrode control unit and a right face electrode control unit. A left face electrode control unit, comprising a fifth switch circuit arranged between the first left electrode and the ground, an eleventh switch circuit arranged between the second left electrode and the output end of the boosting unit, an eighth switch circuit arranged between the first left electrode and the output end of the boosting unit, and a fourteenth switch circuit arranged between the second left electrode and the ground. And the whole face muscle lifting and movement consistency is realized. The multiple electrode plate sets achieve multi-channel facial muscle cooperative adjustment, and the comfort is good in the using process.

A system includes at least one wearable device having a housing, at least one sensor disposed within the housing, at least one output device disposed within the housing, and at least one processor operatively connected to the sensors and output devices, wherein one or more sensors are configured to detect electrical activity from a user's facial muscles and to transmit a data signal concerning the electrical activity of the user's facial muscles to one of more of the processors. A method of controlling a wearable device includes determining facial muscular electrical data of a facial gesture made by a user, interpreting the facial muscular electrical data to determine a user response, and performing an action based on the user response.

This invention relates to the field of health data analysis technology, and particularly to a method and application for analyzing the correlation between eating micro-expressions and food satisfaction based on deep learning. The method includes the following steps: S1, capturing facial video images of users during the eating process using a camera device, and extracting eating facial feature sequences from them; S2, separating chewing actions and facial muscle movements from the eating facial feature sequences based on the spatial displacement differences of facial key points, and obtaining target micro-expression feature vectors. In this invention, by cross-evaluating the captured eating micro-expression emotional state with the user's physiological health indicators, nutritional threshold constraints and weight corrections are applied to the initial food preferences generated based on emotions. This allows for strict control of the intake of core risk nutrients while catering to the user's personal taste satisfaction, ultimately generating personalized recommended recipes that balance emotional experience and medical health standards.

The present invention relates to the field of pain assessment technology, specifically a pediatric pain assessment system, including a muscle group rhythm recognition module, a behavioral linkage screening module, a periodic fluctuation extraction module, a behavioral-physiological difference module, and a pain grading judgment module. In the present invention, a linkage offset recognition path is constructed through the angular relationship between facial muscle groups and the start-up timing, the multi-muscle coordination imbalance manifestation is identified, and a regional-level dynamic behavior judgment basis is formed. The response overlap of multiple behavioral characteristics in the same time period is used to establish a behavioral coordination discrimination mechanism, exclude path signals that do not form effective coordination, enhance the effectiveness of behavioral characteristics, introduce a continuous trend structure of peak time in rhythmic changes, construct a periodic response mutation monitoring channel, improve the recognition sensitivity of short-term fluctuation concentrated segments, extract response mismatch segments based on the trigger time misalignment state between behavioral and physiological responses, and locate pain judgment key points in the timing overlap area.

The application discloses a Unity implementation method and terminal for muscle skinning animation; a prefabricated character model with a set skeleton is imported, a muscle system object is created, and muscle data is configured in a muscle list of the muscle system object; the muscles are initialized according to the muscle data, and an initial conversion matrix of the muscle system is established; a muscle skinning object is created and initialized, muscle weight information is configured for vertices contained in the muscle skinning object; a skeleton animation is played, a muscle list is synchronously refreshed, a muscle matrix is calculated and synchronously updated, a position conversion matrix and a vector conversion matrix are calculated according to the muscle matrix and the initial conversion matrix; the muscle skinning object is refreshed according to the position conversion matrix and the vector conversion matrix and is applied according to the muscle weight information; the application realizes muscle driving by a skeleton, muscle driving body model deformation, muscle skinning animation, and more realistic and more accurate simulation of muscle deformation.

The utility model relates to an auxiliary device for monitoring facial muscle movement, the auxiliary device comprises a head-mounted mechanism and a measuring mechanism, the head-mounted mechanism is used for being worn on the head of a user, the measuring mechanism comprises a measuring arm, a sensor and a trigger springback assembly, the measuring arm is adjustably connected to the side part of the head-mounted mechanism, the sensor is arranged in the measuring arm, and the trigger springback assembly is arranged in the measuring arm. The trigger springback assembly is mounted on the measuring arm in a springback manner; the trigger rebound assembly comprises a contact piece and a touch pressing piece arranged on the contact piece, the contact piece protrudes out of the measuring arm and is used for being attached to the face, and the touch pressing piece is located between the contact piece and the sensor and is used for touching and pressing the sensor. The device is convenient to wear and carry about, the measuring arm can be flexibly adjusted according to the rehabilitation training requirement, the sensor can be protected, the trigger rebound assembly is designed into the structural form of the contact piece and the touch pressing piece, the sensor can more sensitively sense the pressure change, and the monitoring sensitivity is improved.

This invention discloses an artificial intelligence-based method for simulating facial expressions in an interactive humanoid robot, belonging to the field of facial expression simulation technology. The method includes: acquiring and preprocessing user brainwave signals to generate power spectral density features; inputting the power spectral density features into a pre-trained emotion classification model to output the user's emotion category and intensity value; mapping the emotion category and intensity value to an emotional expression and outputting biomimetic muscle contraction commands; adjusting the facial muscle fibers of the humanoid robot according to the biomimetic muscle contraction commands to dynamically adjust the surface texture details of the humanoid robot and generate simulated micro-expressions; capturing user facial feedback data through camera eyes, evaluating the user's acceptance of the simulated micro-expressions based on the user's facial feedback data, and outputting an expression optimization strategy. This invention achieves bio-realistic micro-expressions in a humanoid robot through a dual closed-loop modeling approach of deformation matching and user feedback-driven expression optimization.