A Traditional Chinese Medicine Acupuncture Simulation Method for Pulsed Electrotherapy Training

Abstract

This invention relates to the field of acupuncture simulation technology. Specifically, it relates to a method for simulating acupuncture at TCM acupoints for pulsed electrotherapy training. The method includes the following steps: S1, collecting training needs from the user and inputting these needs into an acupuncture simulation device; S2, establishing a human morphology database. This invention analyzes human body vibration data under different current intensities based on human morphology data and a list of training acupoints, sets trigger rates, and establishes standard acupuncture data for each acupoint. During training, simulated needle position data is combined with an optical image to generate training acupuncture data. The trigger rate of the human body vibration data is dynamically adjusted based on the deviation of the training acupuncture data. Simultaneously, the optical image and standard acupuncture data are adjusted based on the triggered human body vibration data, highly simulating the human body's reaction during real acupuncture and providing trainees with a training experience close to clinical practice.

Description

Technical Field

[0001] This invention relates to the field of acupuncture simulation technology, and more specifically, to a traditional Chinese medicine acupuncture simulation method for pulsed electrotherapy training. Background Technology

[0002] In the field of TCM acupuncture teaching and training, especially in pulsed electrotherapy training, learners can improve their proficiency and accuracy in acupuncture operations through simulation training, so that they can accurately and effectively treat patients in clinical practice in the future.

[0003] Currently, most TCM acupuncture training is conducted in traditional classroom environments or with simple simulation equipment. In traditional classrooms, the training mainly relies on on-site demonstrations by teachers and hands-on practice by learners. However, due to differences in human bodies and the lack of simulation of complex physiological reactions during acupuncture, learners find it difficult to truly experience the changes in acupuncture under different human body conditions. At the same time, many current acupuncture simulation devices use fixed acupoint models, which cannot be adjusted according to different human body shapes and training needs, and it is also difficult to simulate the effects of different current intensities on the human body. Therefore, a TCM acupuncture simulation method for pulsed electrotherapy training is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a traditional Chinese medicine acupuncture simulation method for pulsed electrotherapy training, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, a traditional Chinese medicine acupuncture simulation method for pulsed electrotherapy training is provided, comprising the following steps:

[0006] S1. Collect training requirements from users and input the training requirements into the acupuncture simulation device;

[0007] S2. Establish a human morphology database, and then generate optical human images by matching the human morphology database according to training needs. At the same time, generate a corresponding list of training acupoints based on the matched optical human images and training needs.

[0008] S3. Analyze human body vibration data by combining optical human images with a list of training acupoints and different current intensities, set a trigger rate for each type of human body vibration data, and then set standard acupuncture data for each acupoint according to the list of training acupoints.

[0009] S4. Obtain the position data of the simulated needle, combine the position data of the simulated needle with the optical image to generate training acupuncture data, and at the same time combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate.

[0010] S5. Adjust the optical image based on the triggered human body shaking data, and dynamically adjust the standard acupuncture data based on the human body shaking data. Then, compare the position and current of the training acupuncture data with the standard acupuncture data, and remind the user to adjust based on the comparison results.

[0011] S6. Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings.

[0012] As a further improvement to this technical solution, the acupuncture simulation device in S1 includes a sensor, a display screen, a holographic optical projector, a simulated needle, and an acupuncture model that can be adjusted in multiple directions.

[0013] The acupuncture model dynamically follows the user's training acupoints. When the user completes a training acupoint, it automatically moves to the next training acupoint of the optical image, waiting for the user to continue training.

[0014] As a further improvement to this technical solution, step S1 is as follows:

[0015] S1.1. The user logs into the training system, and then the training system sends training requirement collection information to the user. Based on the data filled in by the user, the training difficulty, training target skills, and training simulation character are obtained.

[0016] S1.2. Summarize the training difficulty, training target skills, and training simulation characters into training requirements, and then input the training requirements into the acupuncture simulation model.

[0017] As a further improvement to this technical solution, step S2 is as follows:

[0018] S2.1 Collect human morphology data of different health states, and then establish a human morphology database based on the collected human morphology data;

[0019] S2.2. Combine the training requirements with the human body morphology database to match the human body, obtain the human body morphology data with the highest matching degree with the training requirements, and generate an optical portrait based on the obtained human body morphology data.

[0020] S2.3 Extract relevant training acupoints according to training needs, then combine the extracted training acupoints with optical images for acupoint positioning, and arrange the training acupoints in the order of needling according to training needs to obtain a list of training acupoints.

[0021] As a further improvement to this technical solution, step S3 is as follows:

[0022] S3.1. Combine the human body morphology data corresponding to the optical image with the training acupoint list to analyze human body shaking data, obtain the probability of human body shaking data generated during acupuncture at different training acupoints, and then refine and update the human body shaking data with different current intensities to obtain the probability of human body shaking data generated during acupuncture at each training acupoint under different current intensities.

[0023] S3.2 Analyze the difficulty of each type of human body shaking data, obtain the difficulty coefficient corresponding to each type of human body shaking data, and then set the initial trigger rate for each type of human body shaking data according to the training requirements and the difficulty coefficient.

[0024] S3.3 Combine the list of training acupoints with the optical image to perform standard acupuncture analysis, and obtain the standard acupuncture data of each training acupoint in the optical image based on the analysis results.

[0025] As a further improvement to this technical solution, the specific steps of S3.1 for obtaining the probability data of human body shaking generated by each training acupoint during acupuncture under different current intensities are as follows:

[0026] ;

[0027] Among them, P shake (A) represents the probability of shaking, A represents the needle puncture location, and P j1 P j2 , ..., P jn Let f be the feature of human morphology data, f be the regression model function, and P be the value of the regression model. A Human morphological data characteristics of the acupuncture site;

[0028] ;

[0029] Where M0 is the base intensity, β is the sensitivity of the current to the jitter intensity, M is the intensity, I is the current intensity, and M(A,I) is the jitter intensity caused by the needle insertion location combined with the current intensity.

[0030] ;

[0031] Where F0 is the fundamental frequency, γ is the influence coefficient of current on frequency, F is the frequency, and F(A,I) is the jitter frequency caused by the needle puncture position combined with the current intensity.

[0032] ;

[0033] Shake(A, I) represents the shaking data of each training acupoint under different current intensities, covering both intensity and frequency.

[0034] As a further improvement to this technical solution, step S4 is as follows:

[0035] S4.1. Obtain the position data of the simulated needle, and then combine the position data of the simulated needle with the optical image to perform needle penetration depth analysis, obtain the needle penetration depth of the simulated needle with the optical image, and at the same time obtain the current intensity set by the user from the training system, and then combine the needle penetration depth with the current intensity as training needle penetration data.

[0036] S4.2. Combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate;

[0037] The greater the deviation in the training acupuncture data for each training acupoint, the higher the trigger rate of the human body shaking data should be.

[0038] The smaller the deviation in training acupuncture data for each training acupoint, the lower the trigger rate of human body shaking data should be.

[0039] As a further improvement to this technical solution, step S5 is as follows:

[0040] S5.1 When human body shaking data is detected and triggered, the triggered human body shaking data is combined with the optical image to adjust the shaking performance, so that the optical image shakes according to the human body shaking data, and at the same time the standard acupuncture data corresponding to the shaking optical image is dynamically adjusted.

[0041] S5.2. Compare the training acupuncture data with the standard acupuncture data for position and current comparison. When there is a positional deviation between the training acupuncture data and the standard acupuncture data, provide a corresponding voice prompt based on the deviation angle. When there is a current deviation between the training acupuncture data and the standard acupuncture data, provide a corresponding voice prompt based on the deviation value.

[0042] Continue monitoring as long as there is no positional or current deviation between the training acupuncture data and the standard acupuncture data.

[0043] As a further improvement to this technical solution, step S6 is as follows:

[0044] S6.1 When the user completes a training acupoint, the simulated needle is moved sequentially to the next training acupoint until the training acupoint list is completed, and the training analysis begins. S6.2

[0045] S6.2 Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] 1. This method for simulating acupuncture at TCM acupoints in pulsed electrotherapy training analyzes human body vibration data under different current intensities based on human morphological data and a list of training acupoints, sets trigger rates, and establishes standard acupuncture data for each acupoint. During training, simulated needle position data is combined with optical images to generate training acupuncture data. The trigger rate of human body vibration data is dynamically adjusted based on the deviation of the training acupuncture data. Simultaneously, the optical images and standard acupuncture data are adjusted based on the triggered human body vibration data, highly simulating the human body's reaction during real acupuncture and providing trainees with a training experience close to clinical practice.

[0048] 2. In this method of simulating acupuncture at acupoints for pulsed electrotherapy training, the user's training needs, including training difficulty, training target skills, and training simulation characters, are collected and input into the acupuncture simulation device. Based on these needs, the acupuncture simulation device matches and generates corresponding optical images from a human morphology database, customizes training content and paths, and can also generate a corresponding list of training acupoints to meet the personalized training needs of different users at different learning stages, for different training goals and simulation scenarios.

[0049] 3. In this method of simulating acupuncture at acupoints for pulsed electrotherapy training, the training acupuncture data and standard acupuncture data are compared in terms of position and current. If any deviation occurs, a voice reminder mechanism is immediately issued to the user to help the operator make timely adjustments, ensuring the accuracy and standardization of the training process and improving the training effect. During the training process, the optical image and acupuncture data are updated in real time to continuously provide accurate feedback to the user. Attached Figure Description

[0050] Figure 1 This is an overall flowchart of the present invention;

[0051] Figure 2 This is a flowchart illustrating how training requirements are input into the acupuncture simulation model according to the present invention.

[0052] Figure 3 This is a flowchart illustrating the process of establishing a human morphology database based on collected human morphology data according to the present invention.

[0053] Figure 4 This is a flowchart illustrating the process of setting the initial trigger rate for each type of human body shaking data based on training requirements and difficulty coefficients according to the present invention.

[0054] Figure 5 This is a flowchart illustrating the process of dynamically adjusting the trigger rate by combining training acupuncture data with a list of human body shaking data in this invention.

[0055] Figure 6 This is a flowchart illustrating the process of providing corresponding voice prompts based on deviation values ​​according to the present invention.

[0056] Figure 7 The flowchart for generating radar chart analysis skills gaps in this invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Please see Figures 1-7 As shown, the purpose of this embodiment is to provide a traditional Chinese medicine acupuncture simulation method for pulsed electrotherapy training, including the following steps:

[0059] S1. Collect training requirements from users and input the training requirements into the acupuncture simulation device;

[0060] The acupuncture simulation device in S1 includes sensors, a display screen, a holographic optical projector, a simulated needle, and an acupuncture model that can be adjusted in multiple directions.

[0061] The acupuncture model dynamically follows the user's training acupoints. When the user completes a training acupoint, it automatically moves to the next training acupoint of the optical image, waiting for the user to continue training.

[0062] The steps for S1 are as follows:

[0063] S1.1. The user logs into the training system, and then the training system sends training requirement collection information to the user. Based on the data filled in by the user, the training difficulty, training target skills, and training simulation character are obtained.

[0064] Users enter the system through the login interface. After logging in, the system will automatically enter the information collection interface and ask the user about their training needs.

[0065] Users fill in specific information about the training, including training difficulty (e.g., beginner, intermediate, advanced), training target skills (e.g., basic acupuncture skills, current intensity adaptation, etc.), and training simulation characters (e.g., specific body shapes such as male, female, elderly, etc.).

[0066] S1.2. Summarize the training difficulty, training target skills, and training simulation characters into training requirements, and then input the training requirements into the acupuncture simulation model.

[0067] The system summarizes the training difficulty, training target skills, and training simulation characters input by the user to form a complete training requirement. The system then inputs the summarized training requirement data into the acupuncture simulation model, which will customize the corresponding training content and path based on these requirements.

[0068] S2. Establish a human morphology database, and then generate optical human images by matching the human morphology database according to training needs. At the same time, generate a corresponding list of training acupoints based on the matched optical human images and training needs.

[0069] The steps for S2 are as follows:

[0070] S2.1 Collect human morphology data of different health states, and then establish a human morphology database based on the collected human morphology data;

[0071] First, it is necessary to collect body shape data under various health conditions. This data may come from medical devices, user-provided measurement data, sensors, etc., including indicators such as weight, height, waist circumference, body fat percentage, muscle mass, and age. The collected body shape data are then categorized according to different health conditions to establish a structured database. Each body shape data needs to be associated with specific health conditions, gender, age, and other tags.

[0072] S2.2. Combine the training requirements with the human body morphology database to match the human body, obtain the human body morphology data with the highest matching degree with the training requirements, and generate an optical portrait based on the obtained human body morphology data.

[0073] Matching training needs with human morphology database: By combining user-provided training needs (such as training objectives, difficulty, simulated characters, etc.) with data in the human morphology database, a matching algorithm is used to find the human morphology that best matches the training needs.

[0074] Generate optical portrait: Based on the body data with the highest matching degree, generate the corresponding optical portrait, and use a holographic optical projector to display the generated optical portrait to the user.

[0075] S2.3. Extract relevant training acupoints according to training needs, then locate the extracted acupoints using optical imaging, and arrange the acupoints in the order of needling according to training needs to obtain a list of training acupoints. The steps are as follows:

[0076] Extracting relevant training acupoints based on training needs: First, relevant acupoints need to be extracted based on the training needs provided by the user (such as goals, locations, training intensity, etc.). Each training need may correspond to different training acupoints, which are then selected using existing acupoint databases and medical knowledge.

[0077] The extracted training acupoints are combined with optical images for acupoint localization: Based on the user's optical image, the extracted acupoint locations are marked on the optical image using image processing technology. Typically, the optical image needs to be matched with the coordinate system corresponding to the human acupoints.

[0078] Arrange the acupuncture sequence of training acupoints according to training needs: Arrange the extracted acupoints in the order of needling according to training needs (such as the priority of training goals, the influence of specific parts, etc.). For example, for some training, it is necessary to stimulate certain specific acupoints first, and then stimulate other acupoints.

[0079] Generate the final training acupoint list: Finally, combine the arranged acupuncture order with the acupoint locations (using optical image localization) to generate the final training acupoint list.

[0080] S3. Analyze human body vibration data by combining optical human images with a list of training acupoints and different current intensities, set a trigger rate for each type of human body vibration data, and then set standard acupuncture data for each acupoint according to the list of training acupoints.

[0081] The steps for S3 are as follows:

[0082] S3.1. Combine the human morphology data corresponding to the optical image with the training acupoint list to analyze human body vibration data, obtain the probability of human body vibration data generated during acupuncture at different training acupoints, and then refine and update the human body vibration data with different current intensities to obtain the probability of human body vibration data generated by each training acupoint during acupuncture under different current intensities. The specific formula is as follows:

[0083] ;

[0084] Among them, P shake (A) represents the probability of shaking, A represents the acupuncture point (training acupoint), and P represents the probability of shaking. j1 P j2 , ..., P jn Here, f represents the characteristics of human morphological data, f is the regression model function, and P represents the interaction between acupoints and joints. A Human morphological data characteristics of the acupuncture site;

[0085] The regression model function receives standardized human morphological data (such as the location parameters of acupoints, and the quantified values ​​of joint angles / mechanical characteristics). These inputs need to be pre-processed into feature forms (such as vectors and matrices) that the function can recognize to ensure they can participate in the function's internal calculations. According to the internal calculation rules, the multi-dimensional morphological features of the input are mapped to a single "shaking probability" result, completing the transformation from physiological feature data to probability prediction, allowing the abstract possibility of human shaking to be output in numerical form for analysis.

[0086] In practical applications, f might be a simple linear regression equation (such as f(x) = aP). A +bP j1 +...+c, where a, b, and c are coefficients obtained during training), or it could be a complex deep learning network (multilayer perceptron, convolutional network, etc.), the specific form of which depends on the data scale, the complexity of physiological associations, and the algorithm framework chosen during modeling. Its core is to encapsulate the association logic of "acupoint-joint-shaking" using mathematical functions, realizing the prediction calculation from morphological data to shaking probability. ;

[0087] Where M0 is the base intensity, β is the sensitivity of the current to the jitter intensity, M is the intensity, I is the current intensity, and M(A,I) is the jitter intensity caused by the needle insertion location combined with the current intensity.

[0088] ;

[0089] Where F0 is the fundamental frequency, γ is the influence coefficient of current on frequency, F is the frequency, and F(A,I) is the jitter frequency caused by the needle puncture position combined with the current intensity.

[0090] ;

[0091] Shake(A, I) represents the shaking data of each training acupoint under different current intensities, covering both intensity and frequency.

[0092] S3.2. Perform difficulty analysis on each type of human body tremor data to obtain the difficulty coefficient corresponding to each type of human body tremor data. Then, based on the training requirements and the difficulty coefficient, set the initial trigger rate for each type of human body tremor data, as follows:

[0093] ;

[0094] Where w1 and w2 are weighting coefficients, representing the contribution of intensity and frequency to the total difficulty, and D is the difficulty coefficient;

[0095] ;

[0096] Where T(A) is the initial trigger rate, T base (A) represents the base trigger rate at acupuncture point A, and λ is an adjustment coefficient that reflects the impact of difficulty on the trigger rate.

[0097] S3.3. Combine the list of training acupoints with the optical image to perform standard acupuncture analysis. Based on the analysis results, obtain the standard acupuncture data for each training acupoint in the optical image. The specific steps are as follows:

[0098] Acupuncture angle calculation: The acupuncture angle is usually the angle at which the needle tip enters the skin. This angle is obtained by calculating the relative position of the acupoint and the joint. It is necessary to take into account the tilt angle of the skin and the anatomical structure of the area. During acupuncture, the angle between the direction of the needle tip and the three-dimensional coordinate vector of the acupoint and the three-dimensional coordinate vector of the target joint can be calculated using the dot product formula of vectors.

[0099] Acupuncture depth calculation: The depth of acupuncture determines how far the needle enters the body. This is related to the thickness of the skin, the subcutaneous fat layer, and the thickness of the muscle. The acupuncture depth can be estimated based on the relative distance between the acupoint and the joint.

[0100] Acupuncture intensity calculation: Acupuncture intensity is usually related to current intensity, frequency and the responsiveness of acupoints. Different acupuncture treatment methods require different acupuncture intensities. Intensity can be estimated based on the distance between the training acupoint and the joint and the intensity coefficient.

[0101] Standard acupuncture data output: Based on the previous calculations, standard acupuncture data is generated for each training acupoint. The standard acupuncture data includes acupuncture angle, acupuncture depth, and acupuncture intensity.

[0102] S4. Obtain the position data of the simulated needle, combine the position data of the simulated needle with the optical image to generate training acupuncture data, and at the same time combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate.

[0103] The steps for S4 are as follows:

[0104] S4.1. Obtain the position data of the simulated needle, then combine the position data of the simulated needle with the optical image to perform needle penetration depth analysis, obtain the needle penetration depth of the simulated needle on the optical image, and at the same time obtain the current intensity set by the user from the training system. Then, combine the needle penetration depth with the current intensity as training needle penetration data. The specific steps are as follows:

[0105] Simulated needle position data acquisition: The simulated needle position data comes from the sensor, which provides the coordinate information of the needle in three-dimensional space in real time. Assuming that the target of the acupuncture is a specific acupoint, the simulated needle will move in the target area and record the three-dimensional coordinate data at each moment.

[0106] Needle insertion depth analysis: Needle insertion depth refers to the distance between the simulated needle and the skin surface. This distance determines the accuracy of the simulated needle and its impact on the treatment effect. The formula is as follows:

[0107] ;

[0108] Among them, V g To simulate the depth of needle insertion, (x g y g , zg (x) represents the position data of the simulated needle. A y A , z A (This refers to the skin location data for training acupoints;)

[0109] The current intensity is adjusted based on the baseline current value set by the user in the system;

[0110] S4.2. Combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate;

[0111] The greater the deviation in the training acupuncture data for each training acupoint, the higher the trigger rate of the human body shaking data should be.

[0112] The smaller the deviation of the training acupuncture data for each training acupoint, the lower the trigger rate of the human body shaking data should be.

[0113] The trigger rate for human body tremor data is dynamically adjusted based on the deviation of the training data. The larger the deviation, the more frequent the human body tremors may be, so the trigger rate needs to be increased; when the deviation is small, the trigger rate should be decreased. During acupuncture, if the acupuncture depth deviation is large, the human body will produce more tremors. The system needs to dynamically adjust the trigger rate according to the deviation to ensure that the device can adapt to the changes in tremors and make corresponding adjustments according to the tremor frequency.

[0114] S5. Adjust the optical image based on the triggered human body shaking data, and dynamically adjust the standard acupuncture data based on the human body shaking data. Then, compare the position and current of the training acupuncture data with the standard acupuncture data, and remind the user to adjust based on the comparison results.

[0115] The steps for S5 are as follows:

[0116] S5.1 When human body shaking data is detected and triggered, the triggered human body shaking data is combined with the optical image to adjust the shaking performance, so that the optical image shakes according to the human body shaking data, and at the same time the standard acupuncture data corresponding to the shaking optical image is dynamically adjusted.

[0117] Based on the jitter data, the three-dimensional coordinates of the optical portrait are adjusted. Each point of the optical portrait is finely adjusted according to the acceleration changes of the human body. The coordinate update of each optical portrait is synchronized with the jitter data of the human body, ensuring that the performance of the optical portrait can accurately reflect human movements in real-time applications.

[0118] S5.2. Compare the training acupuncture data with the standard acupuncture data for position and current comparison. When there is a positional deviation between the training acupuncture data and the standard acupuncture data, provide corresponding voice prompts based on the deviation angle (e.g., "Please adjust the acupuncture position", "Deviation angle is * degrees", "Acupuncture position deviation is * millimeters", "Please make fine adjustments"). When there is a current deviation between the training acupuncture data and the standard acupuncture data, provide corresponding voice prompts based on the deviation value (e.g., "Current deviation is * amperes", "Current setting is inaccurate").

[0119] When there is no positional or current deviation between the training acupuncture data and the standard acupuncture data, continue monitoring and update the optical image and acupuncture data in real time during the training process to ensure real-time feedback during training.

[0120] The system achieves optical image adjustment based on human body tremor data, real-time comparison of training acupuncture data with standard acupuncture data, and dynamic adjustment through voice prompts. These detailed steps ensure the system's high efficiency, accuracy, and real-time feedback capabilities, making acupuncture training more accurate.

[0121] S6. Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings.

[0122] The steps for S6 are as follows:

[0123] S6.1 When the user completes a training acupoint, the simulated needle is moved sequentially to the next training acupoint until the training acupoint list is completed, and the training analysis begins. S6.2

[0124] S6.2 Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings;

[0125] The radar chart dimension divides the user's skills into multiple dimensions, including positioning accuracy, current matching degree, adjustment response speed, and needle penetration accuracy;

[0126] Based on the scores for each dimension, the data is transformed into data suitable for creating radar charts. Radar charts are then created based on the scores for each dimension to display the user's skill level in various aspects and help identify skill gaps.

[0127] From the sequential movement of acupoints during training, to the recording and adjustment reminders for each acupoint's data, and then to skill assessment, radar chart analysis, and the generation of the final report, this method allows users to clearly understand their performance during training and make targeted improvements to address their skill shortcomings.

[0128] The basic principles, main features, and advantages of the present invention have been shown and described. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training, characterized in that: Includes the following steps: S1. Collect training requirements from users and input the training requirements into the acupuncture simulation device; S2. Establish a human morphology database, and then generate optical human images by matching the human morphology database according to training needs. At the same time, generate a corresponding list of training acupoints based on the matched optical human images and training needs. S3. Analyze human body vibration data by combining optical human images with a list of training acupoints and different current intensities, set a trigger rate for each type of human body vibration data, and then set standard acupuncture data for each acupoint according to the list of training acupoints. S4. Obtain the position data of the simulated needle, combine the position data of the simulated needle with the optical image to generate training acupuncture data, and at the same time combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate. S5. Adjust the optical image based on the triggered human body shaking data, and dynamically adjust the standard acupuncture data based on the human body shaking data. Then, compare the position and current of the training acupuncture data with the standard acupuncture data, and remind the user to adjust based on the comparison results. S6. Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings.

2. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The acupuncture simulation device in S1 includes a sensor, a display screen, a holographic optical projector, a simulated needle, and an acupuncture model that can be adjusted in multiple directions. The acupuncture model dynamically follows the user's training acupoints. When the user completes a training acupoint, it automatically moves to the next training acupoint of the optical image, waiting for the user to continue training.

3. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S1 are as follows: S1.

1. The user logs into the training system, and then the training system sends training requirement collection information to the user. Based on the data filled in by the user, the training difficulty, training target skills, and training simulation character are obtained. S1.

2. Summarize the training difficulty, training target skills, and training simulation characters into training requirements, and then input the training requirements into the acupuncture simulation model.

4. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S2 are as follows: S2.1 Collect human morphology data of different health states, and then establish a human morphology database based on the collected human morphology data; S2.

2. Combine the training requirements with the human body morphology database to match the human body, obtain the human body morphology data with the highest matching degree with the training requirements, and generate an optical portrait based on the obtained human body morphology data. S2.3 Extract relevant training acupoints according to training needs, then combine the extracted training acupoints with optical images for acupoint positioning, and arrange the training acupoints in the order of needling according to training needs to obtain a list of training acupoints.

5. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S3 are as follows: S3.

1. Combine the human body morphology data corresponding to the optical image with the training acupoint list to analyze human body shaking data, obtain the probability of human body shaking data caused during acupuncture at different training acupoints, and then refine and update the human body shaking data with different current intensities to obtain the probability of human body shaking data caused by each training acupoint during acupuncture under different current intensities. S3.2 Analyze the difficulty of each type of human body shaking data, obtain the difficulty coefficient corresponding to each type of human body shaking data, and then set the initial trigger rate for each type of human body shaking data according to the training requirements and the difficulty coefficient. S3.3 Combine the list of training acupoints with the optical image to perform standard acupuncture analysis, and obtain the standard acupuncture data of each training acupoint in the optical image based on the analysis results.

6. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The specific steps in S3.1 for obtaining the probability of human body shaking caused by acupuncture at each training acupoint under different current intensities are as follows: ； Among them, P shake (A) represents the probability of shaking, A represents the needle puncture location, and P j1 P j2 , ..., P jn Let f be the feature of human morphology data, f be the regression model function, and P be the value of the regression model. A Human morphological data characteristics of the acupuncture site; ； Where M0 is the base intensity, β is the sensitivity of the current to the jitter intensity, M is the intensity, I is the current intensity, and M(A,I) is the jitter intensity caused by the needle insertion location combined with the current intensity. ； Where F0 is the fundamental frequency, γ is the influence coefficient of current on frequency, F is the frequency, and F(A,I) is the jitter frequency caused by the needle puncture position combined with the current intensity. ； Shake(A, I) represents the shaking data of each training acupoint under different current intensities, covering both intensity and frequency.

7. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S4 are as follows: S4.

1. Obtain the position data of the simulated needle, and then combine the position data of the simulated needle with the optical image to perform needle penetration depth analysis, obtain the needle penetration depth of the simulated needle with the optical image, and at the same time obtain the current intensity set by the user from the training system, and then combine the needle penetration depth with the current intensity as training needle penetration data. S4.

2. Combine the training acupuncture data with the human body shaking data list to dynamically adjust the trigger rate; The greater the deviation in the training acupuncture data for each training acupoint, the higher the trigger rate of the human body shaking data should be. The smaller the deviation in training acupuncture data for each training acupoint, the lower the trigger rate of human body shaking data should be.

8. The method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S5 are as follows: S5.1 When human body shaking data is detected and triggered, the triggered human body shaking data is combined with the optical image to adjust the shaking performance, so that the optical image shakes according to the human body shaking data, and at the same time the standard acupuncture data corresponding to the shaking optical image is dynamically adjusted. S5.

2. Compare the training acupuncture data with the standard acupuncture data for position and current comparison. When there is a positional deviation between the training acupuncture data and the standard acupuncture data, provide a corresponding voice prompt based on the deviation angle. When there is a current deviation between the training acupuncture data and the standard acupuncture data, provide a corresponding voice prompt based on the deviation value. Continue monitoring as long as there is no positional or current deviation between the training acupuncture data and the standard acupuncture data.

9. A method for simulating acupuncture at traditional Chinese medicine acupoints for pulsed electrotherapy training according to claim 1, characterized in that: The steps in S6 are as follows: S6.1 When the user completes a training acupoint, the simulated needle is moved sequentially to the next training acupoint until the training acupoint list is completed, and the training analysis begins. S6.2 S6.2 Summarize the training acupuncture data and adjustment reminder records for each training acupoint, evaluate the user's positioning accuracy and electrical parameter matching degree, and generate a radar chart to analyze skill shortcomings.

Images