38 results about "Simulated patient" patented technology

The invention discloses a semi-structured mental disorder interview method based on large model enhancement, and relates to the cross field of clinical psychology and artificial intelligence, and the method comprises the steps: extracting key information according to a medical text to construct an interview question set, generating a standardized question through a large model, and obtaining a standardized question set; the expression style is adjusted, and the problem quality is optimized in combination with a self-evaluation feedback mechanism; identifying similar points and identification points between symptoms by using a BERT classifier, and generating a decision tree structure in combination with an ICL technology and an XOT framework; a multi-Agent collaborative dialogue framework fused with an RAG mechanism is adopted, a large model and a simulated patient are used for multiple rounds of dialogues, context memory, fine-grained questioning and decision rule retrieval are processed respectively, and the inquiry process is guided; a mental disorder interview evaluation system is constructed, expert knowledge and large model ability are fused, interview content is subjected to multi-dimensional evaluation, and a diversified data set is generated through interview simulation. The method can effectively improve the efficiency and accuracy of mental disorder auxiliary diagnosis.

The invention discloses a medical training evaluation method and system based on an intelligent simulation patient, and relates to the field of artificial intelligence technology and medical simulation, and the method comprises a virtual patient model construction step, a multi-modal perception step, an intelligent interaction step and an intelligent evaluation step. By integrating voice recognition, natural language understanding, facial expression recognition, gesture recognition and virtual reality technologies, a high-simulation and high-interactivity intelligent patient model is constructed for medical students or clinical medical staff to perform diagnosis and treatment training and skill operation assessment. The virtual patient model supports custom information such as age, gender, race, medical history, living habits and the like, different virtual patient images and different pathophysiological states are generated, and personalized learning requirements of users are met. In addition, targeted training suggestions are provided, the training difficulty and content can be adjusted according to the performance of the user, and different training requirements are met.

The embodiment of the invention provides an AI standardized patient real-time interaction method and system based on pre-caching. The method comprises the following steps: firstly, splitting a question and answer pair consisting of a doctor question and a patient answer from a standard inquiry dialogue, generating digital human materials containing the doctor question and a corresponding digital human material storage path, and storing the digital human materials in a vector database; when a target question of a user is received, performing semantic matching in the vector database, directly outputting a target digital human material corresponding to the target question when the matching is successful, taking original case data of a current patient as a plug-in knowledge base when the matching is unsuccessful, and generating the digital human material as an answer in real time by utilizing a multi-modal large model; and storing the doctor problem and the generated digital human material into a vector database. According to the interaction mechanism, in actual interaction, real-time full-link calculation of a multi-mode large model does not need to be repeatedly triggered, large model real-time reasoning is started only when a new problem is not hit, and a result is supplemented to a cache, so that doctor-patient interaction efficiency can be improved.

The invention relates to a medical teaching training system based on AI-driven high-simulation SP medical history acquisition, belongs to the field of teaching tools, and is used for extracting corresponding case data according to teaching requirements and determining symptoms and physiological indexes of AI-driven high-simulation SP. Constructing an SP body model; extracting an entity of the medical history acquisition knowledge graph from the current question of the student, and searching a triple corresponding to the entity from the medical history acquisition knowledge graph to obtain a first set; obtaining an SP state entity according to the AI-driven high-simulation SP symptoms, the physiological indexes and the body parameters; searching a triple corresponding to the SP state entity from the first set to obtain a second set; and according to the second set, in combination with the SP character parameters and the emotion parameters, generating an answer of the SP. According to the invention, a large number of medical history collection training opportunities with AI-driven high-simulation SP diversification and low cost can be provided, the teaching cost of standardized patient medical history collection is reduced, and the performance of virtual patients is more stable and objective.

The invention discloses a physiologically-driven standardized intelligent simulation patient system, which comprises an adult simulation patient, a computer, a computer, a computer, a computer, a computer, a computer, a computer and a computer, wherein the adult simulation patient is made of a simulation man-made high polymer material, is environment-friendly and pollution-free, has obvious anatomical marks, touches two nipples, ribs, sternum and xiphoid processes, is flexible in joints, and realizes various operation body positions; wherein the physiological data comprises the heart rate, the blood pressure and the respiratory rate, the data is combined with a built-in physiological model to simulate the physiological state of a patient in real time, a monitor is simulated, real-time physiological data monitoring and feedback are provided, and the vital signs, the heart rate, the blood pressure and the oxyhemoglobin saturation of the simulated patient are displayed; the system has strong physiologically-driven standardized intelligent comprehensive simulation patient, can perform situational teaching according to a real clinical environment, effectively assesses the clinical thinking and personal operation skills of students, can greatly improve the team cooperation spirit of the students, and simulates the real physiological response and clinical scene.

A test platform for simulating patient conditions. In accordance with methods, systems, platforms and modules, the controller of a ventilator, may be tested. Where the ventilator manages automated mechanical ventilation controllers' maintenance of peripheral oxygen saturation (SpO2) for a simulated patient, an analogue blood oxygen output signal that is responsive to the fraction of inspired oxygen (FiO2) and the peak inspiratory pressure ventilator settings of the ventilator is tested by a test platform controller. Where the ventilator manages end-tidal carbon dioxide (EtCO2) of a simulated patient, operation of the test platform controlled by the platform controller of the test platform in providing carbon dioxide generation, lung compliance (CL) and airway resistance (RAW) states while providing an EtCO2 level that is responsive to changes in tidal volume and respiratory rate changes of the patient is tested.

The invention discloses a virtual-real fusion stoma nursing training system based on AI driving, and relates to the technical field of medical education equipment, and the system comprises the steps: carrying out the multi-dimensional data collection of a stoma physical model through a multi-modal data collection device, building a three-dimensional virtual model based on the collected data, building a virtual simulation scene, and carrying out the training of the virtual simulation scene. The virtual simulation scene comprises real-time simulation of a stoma physiological state, dynamic generation of a virtual case according to teaching requirements, dynamic control of excrement and linkage of internal organs; interaction data are collected through AI standardized patient interaction equipment, evaluation is carried out based on the interaction data, and then an interaction-evaluation mechanism is formed; the method comprises the following steps: constructing a multi-dimensional evaluation index system based on an interaction-evaluation mechanism, generating a multi-dimensional evaluation report according to the multi-dimensional evaluation index system, analyzing the multi-dimensional evaluation report through a machine learning model, and automatically adjusting teaching contents according to an analysis result. The stoma nursing device has the effect of improving the stoma nursing efficiency.

A computer system and method for simulating one or more anatomical features of a simulated patient for application with a simulated medical scanning procedure. A medical scanning procedure by a medical scanning device is digitally simulated on a user selected simulated patient, wherein the user defines one or more anatomical features associated with the user selected patient. A computer display is generated enabling user selection of a certain simulated patient, including user selection of one or more anatomical features associated with the user selected simulated patient, for medical scanning simulation with a simulated medical scanning device. Simulation further includes digital simulation of injection of dye material into the simulated patient for application with a simulated medical scan requiring use of dye material.

The invention relates to a teaching system and a teaching method. The teaching system comprises a voice acquisition module used for acquiring inquiry voice of a user; the main control module is connected with the voice acquisition module and is used for converting the inquiry voice into an inquiry text; the question and answer output module is connected with the main control module and used for outputting an answer text according to the inquiry text, and the main control module is further used for outputting an audio signal according to the answer text; and the sound amplification cabin module is arranged in the simulation patient robot, is connected with the main control module and is used for playing the audio signals. The system collects inquiry voice through the voice collection module and transmits the inquiry voice to the main control module, the question and answer output module generates an answer text after text conversion, and the answer text is played through the sound amplification cabin module of the simulation patient robot after voice synthesis, so that the space reality sense and immersion sense of voice output can be improved; and the user can carry out inquiry training close to a real clinical scene.

The invention provides a training assessment method and system integrating diagnosis and treatment simulation and doctor-patient communication assessment. The method comprises the steps of receiving a training scene selection instruction selected by a doctor user; according to the scene selection instruction, calling the matched desensitized medical record data and the corresponding simulation dialogue template, generating and presenting dialogue content of the AI simulation patient, and performing diagnosis and treatment simulation dialogue with the doctor user. In the dialogue process, reply content of the doctor user is monitored, and whether the reply content meets diagnosis and treatment specifications and humanistic care requirements or not is judged according to preset scoring standard specifications; if not, triggering the AI simulation patient to put forward standard questions or expression emotion feedback to the doctor user according to the type of the non-conformity; and after the dialogue is finished, performing quantitative scoring on the performance of the doctor user in the whole dialogue process, and generating an evaluation report containing specific modification opinions. The method can realize synchronous cultivation of diagnosis and treatment and communication ability, is higher in training pertinence, and can improve the clinical application conversion efficiency.

The present invention discloses a doctor training system and method driven by a standardized patient intelligent agent based on a large language model. Compared with the existing technology, the system obtains the patient's main complaint through fuzzy processing, better approximating the uncertainty inherent in the symptoms and concerns reported by the patient, thereby improving the universality of the system in actual medical applications; the standardized patient intelligent agent unit and the standardized doctor intelligent agent unit obtain diagnosis results through multiple rounds of dialogue, and then dynamically learn real-world medical cases. The standardized patient intelligent agent unit handles various types of medical problems, and the standardized doctor intelligent agent unit raises more accurate diagnostic questions. The two are trained in an unsupervised manner, which significantly improves the standardized patient intelligent agent unit's ability to align with medical requirements, thereby improving the confidentiality of the dialogue between patients and doctors, the fidelity of information and a more humane performance, and is more applicable in real-world medical training.

The invention discloses an AI standardized patient interaction method and device based on script priority, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: determining the similarity between a user question and an inquiry question; if a target inquiry problem of which the similarity with the user problem is not less than a preset similarity threshold exists in the inquiry problems, determining a target response corresponding to the user problem based on a problem response corresponding to the target inquiry problem and a variable calculation rule, and returning the target response to the user side; if the target inquiry question does not exist in the inquiry questions, performing classification processing on case contents corresponding to the current virtual patient, determining a question category corresponding to the user question by utilizing a preset large model, recalling target case contents corresponding to the question category from the case contents subjected to classification processing, and displaying the target case contents corresponding to the question category in the current virtual patient. And generating a target response corresponding to the user question based on the target medical record content, and returning the target response generated by the preset large model to the user side. According to the invention, the interaction accuracy is improved.

The invention discloses an interactive virtual ultrasonic training method and system, and the system comprises an acceleration sensor and a gyro sensor which are used for detecting the angle change of a probe handle in real time, and restoring an image visual angle switching effect in a real scanning process; a built-in displacement sensor captures the moving track of the probe in real time by detecting the relative displacement of the contact surface of the probe and the simulated patient, so that the accurate simulation of the scanning range is realized; a built-in thin film pressure sensor which is clamped between the front end of the probe and the handle and is used for judging the pressure applied by a trainer and guiding the trainer to master the pressing force of the probe in clinical operation according to the pressure data; a built-in RFID recognition device is used for recognizing an RFID tag pre-embedded under the skin of the simulated patient; a Bluetooth / wifi dual-mode module is arranged in the probe, transmission modes are switched according to use scenes, and various data collected by the probe are wirelessly transmitted to the host. All the components cooperate with one another, and virtual simulation and interactive training of ultrasonic scanning operation are achieved.

The application relates to a simulation training instrument for upper eyelid ptosis correction surgery, and belongs to the technical field of medical devices, which comprises an eye use data collector and a simulation training table. The application provides a training instrument which can realize upper eyelid ptosis surgery simulation training and individualized simulation of the recovery of the upper eyelid levator muscle after correction surgery of a simulated patient, the setting of the eye use data collector is beneficial to the collection of individualized eye use data of the patient, so that the actual use of the eye muscle of the patient can be accurately simulated, the setting of the artificial muscle and the artificial fascia is beneficial to the training of the operator in a manner closer to the actual situation of the eye of the patient, and the simulation based on the collected eye data is beneficial to the simulation of the actual recovery of the patient after the surgery, so that the surgery scheme can be more accurately formulated according to the simulation result, the feasibility of the surgery scheme and the postoperative recovery effect are improved, and the success rate of the surgery is greatly improved through the simulation muscle surgery practice.

The invention relates to a clinical medical history collection training evaluation system based on AI standardized patients, and belongs to the field of natural language processing, the system is used for collecting a plurality of inquiry records, and each inquiry record comprises a brief medical history, a plurality of question and answer items corresponding to the brief medical history and scores of the question and answer items; acquiring medical history acquisition questioning content submitted by a user and a corresponding brief medical history through the AI standardized patient; according to a brief medical history corresponding to the medical history collection question content submitted by the user, selecting a corresponding medical history collection evaluation index set; and according to the medical history acquisition evaluation index set, determining a medical history acquisition question content score, and returning the medical history acquisition question content score and score details to the user. According to the method, the medical history collection of the student user can be dynamically subjected to multi-dimensional evaluation with higher pertinence, the evaluation mode is more objective and comprehensive, and more accurate teaching feedback can be provided for the teacher user.

This invention provides an educational electronic medical record system and an educational electronic medical record program, which can use patient medical record information with an amount of information equivalent to or greater than that used in actual medical settings to correspond to the diverse needs and highly complex medical information of learners, thereby enabling effective education and training for learners such as medical professionals. The educational electronic medical record system of this invention has at least an educational electronic medical record server (10), which includes: a data file acquisition unit (112) that acquires a data file described in any software data format and including simulated patient information; a storage unit (102) that stores the simulated patient information from the data file acquired by the data file acquisition unit (112); and a patient medical record information generation unit (113) that retrieves the simulated patient information from the storage unit (102) and generates patient medical record information displayed on the learner terminal (40) based on the simulated patient information.

The application discloses a muscle strength detection simulation method for a high-simulation person, wherein the high-simulation person comprises a plurality of movable joints and driving motors to simulate the activities of various joints of a human body, and the method comprises the following steps: S1, acquiring simulation case information issued by a user, wherein the simulation case information comprises a muscle strength part of a simulated patient and a muscle strength grade; S2, acquiring a muscle strength detection action instruction of the user; S3, determining a target active joint of the high-simulation person, a target driving motor for driving the target active joint to move and a target active part based on the muscle strength detection action instruction, wherein the target active part is a human body part from the target active joint to the end of a limb of the high-simulation person; and S4, the high-simulation person performs corresponding simulation feedback based on the muscle strength grade of the target active part, so that the user can observe and experience the state simulation of different parts and different muscle strength grades of the high-simulation person and the instant interactive feedback of the implementation detection operation, and the interactive experience is improved, and the user can quickly master the muscle strength examination skill.

The invention discloses a simulated patient construction method and system for intelligent diagnosis and treatment evaluation, and the method comprises the steps: constructing a data specification of a standard patient, and dividing the standard patient data into basic layer data and behavior layer data; processing according to the doctor-patient dialogue data in the real scene and the corresponding medical record data to obtain seed data of large-model synthesis dialogue data; carrying out standard patient model training; the basic layer information and the behavior layer information are input into the evaluation system, the patient is simulated to start multiple rounds of dialogues with the intelligent diagnosis and treatment model, and evaluation indexes include fluency, safety and accuracy, question-seeking reasonability, friendliness and context relevance. The dynamic standard patient construction method oriented to the large model intelligent diagnosis and treatment system can be effectively realized, and the performance of the intelligent diagnosis and treatment model in dynamic dialogues can be effectively evaluated by simulating multiple rounds of dialogue behaviors of a real patient.

The invention discloses an intelligent evaluation and feedback system for simulating patient teaching based on dialogue analysis, and relates to the technical field of medical education and artificial intelligence. The system comprises a dialogue data acquisition module, an NLP analysis module, a machine learning and deep learning model module, an evaluation and scoring module, a feedback and improvement suggestion module and a data storage and teaching management module. The system is based on technologies of natural language processing, voice recognition, machine learning and the like, analyzes the conversation between students and simulated patients in real time, comprehensively evaluates clinical communication, illness state judgment and treatment decision ability, realizes real-time feedback on the basis, and has the advantages of simple structure, convenient operation and high efficiency. Personalized evaluation reports and suggestions are provided, and decision basis is provided for teaching improvement.

A friendly standardized patient private part examination common sensing system comprises a model end and a sensing glove, and the model end and the sensing glove conduct signal transmission through Bluetooth. The model end comprises a model main body, and a baroreceptor is arranged on the model main body; the sensing glove comprises a glove body, a sensing feedback module and a sensing output module are arranged in an interlayer of the glove body, and the sensing feedback module and the sensing output module are connected through a circuit. According to the system, the standardized patient, the teaching model and the student form a high-simulation and ethical-friendly teaching environment, effective teaching feedback of the standardized patient and the student is realized, and the clinical skill teaching effect is improved.

The application discloses a virtual standardized patient simulation method based on a multi-agent system, and belongs to the technical field of medical education information technology, and aims to solve the technical problems of fact hallucination, key information leakage and lack of structured teaching feedback caused by function coupling of an existing single large model virtual patient system. Technical solution points are as follows: original medical text is structured to generate case representation and build an inquiry intention set; after receiving a natural language question, the question is analyzed into a standard intention in combination with a dialogue history; structured case fact information is retrieved according to the standard intention, and a natural language reply is generated in combination with a patient role; after the inquiry ends, an intention sequence obtained by comparing dialogue records is compared with a standard intention list to generate structured teaching feedback information. The main use is inquiry simulation and training in medical teaching.

A system and method for virtual patient simulations enhances cultural sensitivity training and clinical decision-making in medical education. The system utilizes machine learning techniques and language models to create realistic, diverse patient scenarios reflecting a wide range of cultural, ethnic, and socioeconomic backgrounds. Simulated patient interactions use algorithms to generate responses based on trainee input and training data. A rapport score system evaluates trainee interactions, considering factors such as empathy, active listening, and cultural sensitivity. The system allows trainees to practice gathering patient information, making diagnoses, and developing treatment plans while navigating cultural differences and language barriers. When integrated into formal training programs, it acts as a mechanism for instructors to review and analyze trainee performance along these metrics. By providing diverse simulated patient interactions, the system may help healthcare professionals improve cultural competency and communication skills, potentially leading to better patient outcomes in real-world clinical settings.

The invention provides a standardized patient training platform based on artificial intelligence, and belongs to the field of models for medical teaching, and the platform comprises a data management module which is used for collecting user information, standardized patient resource information and training records; the intelligent recommendation module is used for performing clustering analysis on the learning behavior data of the user to obtain a learning label, and generating a standardized patient recommendation list according to the learning label and the historical score of the user; the appointment scheduling module is used for determining standardized patients to be distributed; the standardized patient training module is used for providing standardized patient training service according to the training type selected by the user, obtaining a current training result and updating a training record according to the current training result; and the evaluation module is used for evaluating the training process of the training module in real time to obtain a score table, and displaying the score table and the training process on the same interface. According to the method, the most suitable standardized patient resources are automatically matched, and the utilization efficiency of the training resources and the training effect are improved.

This invention provides a population pharmacokinetic-guided method and system for administering intravenously administered anti-PD-1 / PD-L1 antibodies. Based on a population pharmacokinetic model, the standard exposure level for a typical patient under a reference dosing regimen is obtained. Based on the standard exposure level, several exposure threshold ranges are set. The dosage intervals for simulated patients at each weight level corresponding to each exposure threshold range are obtained. Based on existing marketed specifications and several dispensing strategies, several combinations of specifications and dispensing strategies are enumerated for each exposure threshold range, and the corresponding dosing regimens for each specification and dispensing strategy combination under each exposure threshold range are obtained. A comprehensive evaluation result is obtained, and based on the comprehensive evaluation result, a target exposure threshold range, target specification, dispensing strategy combination, and its corresponding target dosing regimen are selected. This improves the accuracy of exposure control and reduces drug waste, thereby lowering treatment costs.

The invention relates to the related field of medical education, in particular to a virtual standardized patient construction method based on a multi-modal large model. Comprising a multi-modal data preprocessing module, an interdisciplinary adaptation framework, a hybrid expert model architecture and a dynamic interaction response system. The hybrid expert model architecture performs fusion reasoning on a multi-modal case library of the multi-modal data preprocessing module and scene parameters of the interdisciplinary adaptation framework to generate a virtual standardized patient model with emotions; the dynamic interactive response system asks questions for students according to the virtual standardized patient model of the hybrid expert model, and identifies answers and interactions of the students; the answers and interaction data of the students are transmitted to the virtual standardized patient model of the mixed expert model architecture for reasoning, and the students are further questioned according to the reasoning result of the mixed expert model architecture until the examination is finished; the virtual standardized patient generated by the method has a real emotional state of the patient, interaction is more real, and interaction which better conforms to character features is carried out according to reasoning of student questions.

The invention discloses a dialogue content scene suitability intelligent evaluation method based on text sentiment calculation, and belongs to the technical field of dialogue sentiment detection. The method comprises the following steps: a corpus construction and situation labeling stage: labeling scene labels for dialogues of a corpus by using a multi-layer labeling system through an expert system; an emotion calculation model construction stage: evaluating the matching degree between the output emotion and the expected medical scene by adopting double indexes of KL divergence and cosine similarity, and optimizing a dialogue strategy; an emotion suitability evaluation mechanism establishment stage: generating a comprehensive situation suitability score for evaluating the situation suitability degree of the output content of the intelligent simulation patient ISP; and a real-time optimization and adjustment stage: performing real-time optimization on a dialogue strategy, language expression and emotion adaptation through reinforcement learning and expert system feedback, and dynamically adjusting a dialogue style according to case requirements. According to the method, the limitation of single text sentiment analysis is broken through, accurate recognition and dynamic adaptation of sentiment expression are realized, and the dialogue has higher sentiment naturalness and authenticity.

The invention discloses a digital standardized patient action feedback method and device, equipment and a medium, and relates to the technical field of medical simulation teaching and artificial intelligence, and the method comprises the steps: obtaining current question and answer information issued by a user based on an inquiry training task through a preset interaction interface; determining a target action feedback instruction corresponding to the current question and answer information, and searching a target action video clip matched with the target action feedback instruction in a preset video library; the preset video library is used for storing preset action video clips corresponding to the action feedback instructions; generating a target lip animation corresponding to target voice feedback content corresponding to the current question and answer information; and synthesizing the target action video clip and the target lip animation to obtain a target feedback video of the digital standardized patient, and displaying the target feedback video of the digital standardized patient on a display interface. And the authenticity and the system operation efficiency of digital standardized patient feedback are improved in an inquiry training scene.

The invention relates to the technical field of medical apparatus and instruments, in particular to a sports apparatus for patient waist rehabilitation training, which comprises a supporting table positioned in the middle and two lying tables positioned on two sides of the supporting table in the horizontal direction, the supporting table is used for supporting the waist of a patient, and the two lying tables are respectively used for supporting the upper body and legs of the patient; the power unit is adopted to drive the two lying tables to move, the working effect of assisting a patient in training through instruments can be achieved, the patient does not need to depend on strong supporting of the neck, the shoulders, the back, the elbows and the lower limbs of the patient, the strength burden is greatly relieved, and the old and weak people with weak core strength, the early postoperative stage and the old can be safely and effectively trained; meanwhile, by means of the mode of assisting training through instruments, the lifting / descending height, speed and amplitude of the waist and hip can be preset and standardized, the training action track of the patient better meets the physiological requirement, the secondary injury risk is remarkably reduced, and the training safety is improved.

The embodiment of the invention provides an AI standardized patient training method and system based on a large model. According to the method, firstly, a case library module is used for obtaining a standardized case including doctor-patient interaction question and answer pairs, preliminary diagnosis standard answers, differential diagnosis standard answers and treatment scheme standard answers, and normative and reusable case resources are provided for training; when a user puts forward a target question, the system calls a pre-trained medical large model to perform semantic matching, the target question is matched with a doctor-patient interaction question-answer pair in a case library, a target answer is output in real time in a digital human image through an interaction module, and immediate feedback is achieved. And if the user performs click operation on the digital person, the system calls corresponding physical examination data from the case library based on a click part, and finally outputs a current medical record including current preliminary diagnosis, differential diagnosis and treatment suggestions based on the target answer and the physical examination data. The process replaces traditional SP training, and the inquiry training efficiency of medical students is remarkably improved.

The utility model belongs to the technical field of medical teaching equipment, and provides a head-mounted device for medical teaching simulation, which comprises a head-mounted piece and an organ simulation assembly, the head-mounted part comprises a nose model part, the nose model part is provided with a cavity for placing the nose of a user, and the nose model part is provided with a bandage part for fixing the head of the user and a catheter nasal cavity part for simulating the nasal cavity; the organ simulation assembly comprises an esophagus simulation part, a trachea simulation part and a stomach simulation part. The device can depend on the body of a wearing user as a human body model, the overall structure is smaller and lighter, and the device is convenient to move and store; when medical teaching simulation is carried out, a wearer can become a simulated patient in medical teaching, compared with an existing training model which is independent of students and cannot carry out feedback, the trained students can directly communicate with the wearer and carry out feedback, and a real training interaction feeling can be established.