173 results about "Mimetic Muscles" patented technology

The invention discloses an intelligent multi-modal virtual digital human interaction system based on an AI language large model. The system comprises a high-authenticity face generation module; the high-authenticity face generation module uses an AdaAN network, based on adaptive feature fusion and voice driving and time sequence modeling of voice features, feature information related to voice is extracted, the extracted voice features are processed through a deep neural network, it is ensured that the voice and facial expressions are highly aligned in time and space, and the face recognition accuracy is improved. Collecting a bio-electricity signal, mapping the signal to facial muscle movement, generating a final facial expression, and interacting with a user; the system further comprises an intelligent interaction module, a training optimization and efficient generation module, an efficient integration module, a multi-modal data acquisition module, an AI large model core processing module, a digital human image generation and driving module, an interaction scene adaptation module and a feedback optimization module. The invention further discloses a multi-mode digital human interaction method which has wide application value.

The invention provides a virtual human design and application platform, method and device based on artificial intelligence, and relates to the technical field of virtual digital humans. The method comprises the steps of performing local anonymization on multi-modal input data on user equipment, encoding generated anonymized multi-modal features to obtain a multi-modal feature vector, and inputting the multi-modal feature vector into an emotion calculation model to obtain a user emotion intensity quantized value; inputting the multi-modal feature vector into a context sensing model, and generating a user intention vector after context correction in combination with a knowledge graph; generating an updated personality parameter matrix according to the user emotion intensity quantized value and the user intention vector; and outputting voice waveform data, facial muscle motion parameters and skeleton joint coordinate data based on the personality parameter matrix, and driving the virtual digital human three-dimensional model to perform real-time rendering. According to the scheme, the naturalness, emotional resonance and long-term user retention rate of virtual digital human interaction can be improved, and user privacy data security is protected.

The invention provides a digital human generation method based on a multi-modal large model. The method comprises the following steps: constructing a digital human basic model; generating a structured training set; generating a question and answer model supporting multi-channel interaction; semantic answers of the user questions are output, text emotional tendencies of the semantic answers are extracted, and emotional intensity parameters are output; generating facial muscle movement track data, and performing real-time rendering on the digital human basic model according to the facial muscle movement track data to output a digital human three-dimensional image with emotion expression. According to the embodiment of the invention, cross-modal alignment is carried out on text, image and audio data, and a multi-modal large model containing visual, voice and knowledge models is optimized by using a joint training method, so that more natural and smoother multi-channel interaction experience is realized; in addition, by introducing an emotion recognition model and a face interaction model, the emotion tendency contained in the semantic answer can be captured and reflected more accurately, so that a digital human three-dimensional image with real emotion expression is output.

The invention relates to the technical field of pain assessment, in particular to a paediatric pain assessment system which comprises a muscle group rhythm recognition module, a behavior linkage screening module, a periodic fluctuation extraction module, a behavior physiological difference module and a pain grading judgment module. According to the method, a linkage offset identification path is constructed through an angle relation between facial muscle groups and a starting time sequence, multi-muscle cooperative imbalance performance is identified, a region-level dynamic behavior judgment basis is formed, and a behavior cooperative judgment mechanism is established by utilizing response overlapping conditions of multiple behavior characteristics in the same time period; path signals which do not form effective cooperation are eliminated, the effectiveness of behavior characteristics is enhanced, a continuous trend structure of peak time in rhythm change is introduced, a periodic response sudden change monitoring channel is constructed, the recognition sensitivity of a short-time fluctuation concentration section is improved, and a response mismatch section is extracted based on a trigger time dislocation state between behavior and physiological response, so that the recognition sensitivity of the short-time fluctuation concentration section is improved. And a pain judgment key point is positioned in the time sequence overlapping region.

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 utility model provides a facial paralysis rehabilitation training robot which comprises a head-mounted robot body, a power system and a traction system, and the power system and the traction system are both installed on the head-mounted robot body. The head-mounted robot body is provided with a guide panel, the traction system passes through the guide panel from the head-mounted robot body and extends to a face area, and / or the traction system does not pass through the guide panel from the head-mounted robot body and extends to the face area; and the power system drives the traction system to pull or relax target facial muscles of the patient. The traction system is driven by the power system to move, appropriate force and resistance are applied to facial muscles of a patient to promote movement and activity of the muscles, the activity range of the facial muscles can be increased, neuromuscular connection can be improved, recovery of facial expressions can be promoted, and appropriate force and resistance can be provided; therefore, the patient is helped to gradually recover the functions of facial muscles.

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 provides an intelligent expression generation method and system based on a facial motion unit, and belongs to the technical field of intelligent generation, and the method comprises the steps: determining a unit data set of each facial motion unit of a corresponding individual based on a multi-modal facial sample; inputting the phoneme codes into an expression predictor to obtain a prediction data set of each facial motion unit; establishing a mapping relationship based on the unit data set of each facial movement unit according to different individuals in various expression states, and establishing a neutral relationship between each facial movement unit and the corresponding expression state in combination with a deviation set determined based on the prediction data set and the unit data set; establishing a facial motion unit expression model; and searching required motion features and parameter settings from the established facial motion unit expression model, and performing dynamic adjustment based on physical constraints of facial muscle motion and natural transition constraints of expression changes to generate expression animations for interaction. And a high-precision, high-reality and controllable expression generation effect is realized.

The invention discloses a physical and psychological health evaluation method based on a facial micro-vibration image, and belongs to the technical field of artificial intelligence emotion calculation. The method comprises the following steps: acquiring a facial video, analyzing and measuring to obtain the frequency and amplitude of pixel points in facial muscles, further calculating various psychological and physiological indexes, and displaying a light ring of a facial contour through a video frame; results based on frequency and amplitude changes of pixel points in facial muscles can be visually seen; and respectively calculating different parameter models based on the obtained frequencies and amplitudes of the pixel points in the facial muscles so as to calculate each psychological index and each physiological index, namely 12 psychological indexes and 2 physiological indexes in total. According to the physical and psychological health evaluation method based on the facial micro-vibration image, psychological indexes and partial physiological indexes related to the emotion can be calculated through the vibration of facial muscles, and the accuracy of facial emotion recognition is improved by integrating multiple indexes.

The invention provides a depression degree assessment method based on space-time relevance of a facial region, belongs to the technical field of computer vision and medical diagnosis, and solves the problem that an existing depression identification method is not high in accuracy. The invention provides a deep learning model fused with a space-time attention mechanism. The method comprises the following steps: dividing a face image into a plurality of sub-regions, and independently calculating the importance of each sub-region; the space importance, the space context, the time context and the space similarity are dynamically fused through a space-time attention mechanism, and a face attention map is generated; based on the constructed recognition model, a time sequence feature fusion module is used for extracting dynamic expression change features, and precise assessment of the depression degree is achieved. Experiments show that the method obtains the identification performance of MAE 5.79 and MAE 5.76 on the AVEC 2013 data set and the AVEC 2014 data set respectively, and is superior to the prior art. According to the method, an efficient and objective solution is provided for automatic depression recognition by capturing a space-time correlation mode of facial muscles through fine grit.

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 provides an informatization wound ticket giving system based on facial recognition, and relates to the technical field of identity verification. The system comprises a physiological status monitoring module, a permission adjustment control module, an identity adaptability matching module, a gait behavior verification module and a terminal data linkage module. By analyzing eyeball movement, blinking frequency, pupil change and facial muscle activity and monitoring the physiological state of an individual, dynamic permission adjustment during identity verification is achieved, matching precision is optimized through micro-expression analysis, mismatching caused by emotion fluctuation is reduced, the adaptability of identity verification is enhanced through behavior data in gait analysis, high accuracy is maintained, and the identity verification efficiency is improved. The real-time performance of bill management and access control is improved through a data linkage mechanism among multiple devices, and the verification safety and the remote operation stability are enhanced in combination with multi-dimensional biological characteristics.

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.

The invention discloses an oral cavity baffle tongue lighting device, which belongs to the technical field of oral cavity equipment, and comprises a lower jaw frame, side arms and an upper jaw, a lower curved wall is fixedly embedded on the upper surface of the lower jaw frame, side grooves are distributed on two sides of the lower jaw frame, elastic pieces are assembled in the side grooves, one end of each side arm is fixedly connected with a side shaft, and the side shafts are rotatably inserted in the side grooves. The upper jaw frame is movably assembled at the top of the lower jaw frame, the purpose of auxiliary supporting on the upper jaw and the lower jaw of a patient in the treatment process can be achieved, the aching pain feeling of facial muscles of the patient is reduced, and the treatment effect of the patient is improved. Meanwhile, the flow speed of pump suction can be autonomously controlled through the occlusion action of the patient, the patient can conveniently and freely adjust the strength of pump suction, the step that treatment personnel manually suck dirty liquid is omitted, the illuminating lamp can be cooled through flowing of liquid, and discomfort of the patient caused by overheating of the lamp source is prevented.

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 lung-heat clearing and sputum excretion device, and relates to the technical field of lung-heat clearing and sputum excretion. The device comprises a shell, a negative pressure pump is arranged in the shell, a connecting cylinder is arranged on one side of the shell, a horn cover is arranged on one side of the connecting cylinder, a plurality of massage air bags are arranged on the inner side of the horn cover, a liquid outlet pipe is fixedly connected to the lower portion of the shell, and a collecting bottle is arranged on the lower portion of the shell. And a connecting pipe which is in threaded connection with the liquid outlet pipe is fixedly connected above the collecting bottle. By arranging the reciprocating assembly, the negative pressure pump can be started to generate suction force to suck sputum and drive the impeller to rotate at the same time, the impeller rotates to drive the extrusion block to reciprocate through the reciprocating assembly, and the extrusion block extrudes the massage air bag to reciprocate to extrude and massage mouth muscles; sputum is sucked through the negative pressure suction force of the negative pressure pump and the extrusion massage of the massage air bag, the situation that facial muscles ache during sputum suction is reduced, and therefore comfort is improved.

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 present invention discloses an oral tongue-isolating lighting device, which belongs to the technical field of oral equipment and comprises a mandibular frame, side arms and an upper jaw, wherein the lower curved wall is fixedly embedded in the upper surface of the mandibular frame, side grooves are arranged on both sides of the mandibular frame, elastic parts are assembled in the side grooves, one end of the side arm is fixedly connected to a side shaft, the side shaft is rotatably inserted into the side groove, and the side arm is movably abutted against the elastic part, and both ends of the maxillary frame are fixedly connected to the maxillary arms, which are respectively assembled and connected to the two groups of side arms. The present invention movably assembles the maxillary frame on the top of the mandibular frame, which can provide auxiliary support for the upper and lower jaws of the patient during treatment, reduce the soreness of the patient's facial muscles, and at the same time can utilize the patient's biting action to autonomously control the flow rate of the pump suction, facilitate the patient to freely adjust the intensity of the pump suction, and save the step of the therapeutic personnel manually sucking up the dirty liquid. The flow of liquid can also be used to dissipate heat from the lighting lamp to prevent the lamp source from overheating and causing discomfort to the patient.

The present invention discloses a video-based muscle contraction measurement and facial muscle synergy analysis system, which includes a data acquisition module, a data processing module, a muscle contraction signal extraction module, a facial muscle synergy analysis module and a comprehensive analysis module. The video-based muscle contraction measurement method extracts muscle contraction strength and direction information through video. In the normal feature entry stage of facial muscle synergy analysis, the synergy feature vectors of the normal user group are stored in a local server, and the standard feature ranges in different modes are obtained as a basis for judging whether the muscle synergy function is normal or abnormal. In the detection stage, the user's synergy feature vector is extracted and compared with the synergy feature vector in the local server. The facial synergy analysis is used to determine whether the current muscle function is normal, and the position of the pathological muscle is located according to the direction of the synergy feature vector.