Artificial Intelligence-Based Dance Teaching Analysis System and Method

Abstract

The present invention discloses an artificial intelligence-based dance teaching analysis system and method, belonging to the field of educational tools. The present invention obtains the training data during the training process and the physical change data during the training process, imports them into the training matching analysis strategy for training matching analysis, obtains the dance training action data, imports it into the training difficulty analysis strategy for training difficulty analysis, conducts training safety analysis based on the obtained training matching analysis results and training difficulty analysis results, issues a warning for the training process through the obtained training safety analysis results, comprehensively analyzes the training situation and physical change data during the training process, evaluates the safety during the dance training process, and comprehensively analyzes and evaluates the danger during the dance process according to the dancers and dance movements, so as to avoid human body injuries caused by unmatched personnel forcing dance training.

Description

Technical Field

[0001] The present invention belongs to the field of educational appliances, and particularly relates to a dance teaching analysis system and method based on artificial intelligence. Background Art

[0002] Dance teaching plays a positive role in promoting the all-round development of students. Firstly, dance teaching can exercise students' bodies and improve their physical fitness and motor ability; secondly, dance teaching can cultivate students' teamwork spirit and communication skills, and promote the development of their social skills; finally, dance teaching can also cultivate students' creativity, imagination and aesthetic ability, and promote the improvement of their artistic accomplishment. Dance teaching is a unique form of art education. Through systematic dance training and diverse teaching methods, it cultivates students' dance skills, artistic accomplishment and aesthetic ability. At the same time, dance teaching can also promote the all-round development of students and lay a solid foundation for their future development.

[0003] During dance training, it is impossible to comprehensively analyze and evaluate the safety during the training process based on the training situation and physical change data during the training. There are often cases of human body injuries caused by mismatched personnel forcing dance training. The prior art cannot solve the above problems.

[0004] To solve the problems raised in this background art, the present application designs a dance teaching analysis system and method based on artificial intelligence. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a dance teaching analysis system and method based on artificial intelligence.

[0006] To achieve the above object, the present invention provides the following technical solutions: A dance teaching analysis method based on artificial intelligence, which includes the following specific steps:

[0007] S1. Obtain dance training action data, and at the same time obtain training data during the training process and physical change data during the training process;

[0008] S2. Import the training data during the training process and the physical change data during the training process into a training matching analysis strategy for training matching analysis;

[0009] S3. Import the dance training action data into a training difficulty analysis strategy for training difficulty analysis;

[0010] S4. Conduct training safety analysis based on the obtained training matching analysis results and training difficulty analysis results;

[0011] S5. Issue a warning during the training process through the obtained training safety analysis results.

[0012] As an optimal technical solution of the dance teaching analysis method based on artificial intelligence, the specific content of obtaining the dance training action data, and simultaneously obtaining the training data during the training process and the physical fitness change data during the training process is as follows:

[0013] S11. Obtain the action data of the standard training images stored in the training teaching aids during dance training, and simultaneously obtain the training data during the training process through sensors, including the position data of each moving part during the training process;

[0014] S12. Obtain the physical fitness change data during the training process through sensors. The physical fitness change data includes heart rate, blood pressure, and body temperature data. Here, it should be noted that when dancing, it is very important to monitor heart rate, blood pressure, and body temperature because they can provide key information about physical health status and exercise intensity. Monitoring heart rate, blood pressure, and body temperature during dancing can help dancers understand their physical conditions and ensure exercise safety;

[0015] S13. Store the action data of the obtained standard training images, the training data during the training process, and the physical fitness change data in the storage component. At the same time, project the training data obtained during the training process onto the standard training images, that is, scale the training images of the training personnel to the images under the same scale as the standard training images, and represent the positions of the corresponding moving parts of the corresponding dance movements on the standard training images.

[0016] As an optimal technical solution of the dance teaching analysis method based on artificial intelligence, importing the training data during the training process and the physical fitness change data during the training process into the training matching analysis strategy for training matching analysis includes the following specific steps:

[0017] S21. Obtain the action data of the standard training images stored in the training teaching aids corresponding to the dance training and the position data of each moving part during the training process, and import them into the training proficiency calculation formula to calculate the training proficiency. The training proficiency calculation formula is: , where T is the time of the dance training process, kt is the training difficulty at time t during the training process, V() is the volume of the three-dimensional image in the parentheses, at is the corresponding image of the training human body projected on the standard training image at time t, bt is the training image on the standard training image at time t, dt is the time integral, is the intersection of the images, that is, the overlapping position of the images, is the union of the images, and km is the training difficulty standard value of the training process;

[0018] S22. Obtain the physical fitness change data during the training process, and import the obtained physical fitness change data during the training process into the physical fitness change outlier calculation formula to calculate the physical fitness change outlier. The physical fitness change outlier calculation formula is as follows: , where N is the type of physical fitness characteristics, ci is the proportion coefficient of the i-th type of physical fitness characteristics, pit is the average value of the i-th type of physical fitness characteristics during the training process, pim is the median of the safety range of the i-th type of physical fitness characteristics, pimax is the maximum value of the safety range of the i-th type of physical fitness characteristics, pimin is the minimum value of the safety range of the i-th type of physical fitness characteristics, and pic is the average value of the i-th type of physical fitness characteristics in the pre-training time period;

[0019] S23. Obtain the calculated training proficiency and the physical fitness change outlier, and import them into the training matching value calculation formula to calculate the training matching value. The training matching value calculation formula is as follows: , where is the training proficiency proportion coefficient.

[0020] As an optimal technical solution of the dance teaching analysis method based on artificial intelligence, the obtaining of the dance training action data and importing it into the training difficulty analysis strategy for training difficulty analysis includes the following specific steps:

[0021] S31. Obtain the action data of the standard training images stored in the training teaching aids during the dance training, and import the action data of the standard training images in the training process into the training difficulty calculation formula to calculate the training difficulty during the training process. The training difficulty calculation formula during the training process is as follows: ;

[0022] S32. Import all the action data of the standard training images stored in the training teaching aids during the dance training into the training difficulty calculation formula to calculate the training difficulty of the entire process. The training difficulty calculation formula of the entire process is as follows: , where Ts is the time experienced by all the actions of the standard training images, gt is the training image at time t during the process of all the actions of the standard training images, and g(t - 1) is the training image at time t - 1 during the process of all the actions of the standard training images.

[0023] As an optimal technical solution of the dance teaching analysis method based on artificial intelligence, the training safety analysis based on the obtained training matching analysis result and training difficulty analysis result includes the following specific contents:

[0024] Obtain the calculated training matching value, the training difficulty during the training process, and the training difficulty of the entire process, and import them into the training safety value calculation formula to calculate the training safety value. The training safety value calculation formula is as follows: , where exp() is the exponential power of the natural constant e.

[0025] As an optimal technical solution of the dance teaching analysis method based on artificial intelligence, the early warning of the training process through the obtained training safety analysis results includes the following specific contents:

[0026] Compare the obtained training safety value with the set training safety threshold. If the training safety value is greater than or equal to the set training safety threshold, give an early warning of the training process to remind the trainer that the dance teaching is not suitable. If the training safety value is less than the set training safety threshold, do not give an early warning of the training process, and the trainer can train normally.

[0027] A dance teaching analysis system based on artificial intelligence is implemented based on the above-mentioned dance teaching analysis method based on artificial intelligence, and specifically includes a data acquisition module, a training matching analysis module, a training difficulty analysis module, a training safety analysis module, and a training process early warning module;

[0028] Among them, the data acquisition module is used to acquire dance training action data, and at the same time acquire training data during the training process and physical change data during the training process;

[0029] The training matching analysis module is used to import the training data during the training process and the physical change data during the training process into the training matching analysis strategy for training matching analysis;

[0030] The training difficulty analysis module is used to import the dance training action data into the training difficulty analysis strategy for training difficulty analysis;

[0031] The training safety analysis module is used to perform training safety analysis according to the obtained training matching analysis results and training difficulty analysis results;

[0032] The training process early warning module is used to give an early warning of the training process through the obtained training safety analysis results.

[0033] An electronic device includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory;

[0034] The processor executes the above-mentioned dance teaching analysis method based on artificial intelligence by calling the computer program stored in the memory.

[0035] A computer-readable storage medium stores instructions. When the instructions run on a computer, the computer is made to execute the dance teaching analysis method based on artificial intelligence as described above.

[0036] Compared with the prior art, the beneficial effects of this application are:

[0037] This application obtains dance training action data, and at the same time obtains training data during the training process and physical change data during the training process. The training data during the training process and the physical change data during the training process are imported into the training matching analysis strategy for training matching analysis. The dance training action data is imported into the training difficulty analysis strategy for training difficulty analysis. Training safety analysis is carried out according to the obtained training matching analysis results and training difficulty analysis results. Training process warning is carried out through the obtained training safety analysis results. The training situation and physical change data during the training process are comprehensively analyzed to evaluate the safety during the dance training process. The danger during the dance process is comprehensively analyzed and evaluated according to the dancers and dance movements, so as to avoid human body injuries caused by dancers who do not match forcing dance training. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic diagram of the overall process of the dance teaching analysis method based on artificial intelligence of the present invention;

[0039] Figure 2 is a schematic diagram of the process of step S1 of the dance teaching analysis method based on artificial intelligence of the present invention;

[0040] Figure 3 is a schematic diagram of the process of step S2 of the dance teaching analysis method based on artificial intelligence of the present invention;

[0041] Figure 4 is a schematic diagram of the overall framework of the dance teaching analysis system based on artificial intelligence of the present invention;

[0042] Figure 5 is a schematic diagram of the image comparison process of the present invention;

[0043] Figure 6 is a schematic diagram of the information transmission of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way limits the present application and its application or use.

[0045] Embodiment 1

[0046] Herein, in combination with Figure 6 describe the application scenario of this embodiment: Figure 6This is a schematic diagram of information transmission for the present invention. The image acquisition terminal acquires the dance training action data played in the training teaching aid and the training data during the training process. The physical fitness information sensor acquires the physical fitness change data during the training process. The data processing terminal obtains the training data during the training process and the physical fitness change data during the training process, imports them into the training matching analysis strategy for training matching analysis, obtains the dance training action data, imports it into the training difficulty analysis strategy for training difficulty analysis, conducts training safety analysis based on the obtained training matching analysis results and training difficulty analysis results, issues a warning during the training process through the obtained training safety analysis results, and transmits the warning information to the training teaching aid to issue an alarm;

[0047] To solve the technical problems raised in the background art: When conducting dance training, due to the variety and danger of dance types, it is impossible to comprehensively analyze and evaluate the safety during the dance training process based on the training situation and physical fitness change data during the training process. There are often situations where mismatched personnel forcefully conduct dance training, resulting in human body injuries. The present invention provides a preferred embodiment: As Figure 1 shown, an artificial intelligence-based dance teaching analysis method includes the following specific steps:

[0048] S1. Obtain the dance training action data, and at the same time obtain the training data during the training process and the physical fitness change data during the training process;

[0049] In one specific embodiment, as Figure 2 shown, Figure 2 This is a schematic flowchart of step S1 of the artificial intelligence-based dance teaching analysis method of the present invention. S1 includes the following steps:

[0050] S11. Obtain the action data of the standard training images stored in the training teaching aid during dance training, and at the same time obtain the training data during the training process through sensors, including the position data of each moving part during the training process;

[0051] S12. Obtain the physical fitness change data during the training process through sensors. Among them, the physical fitness change data includes heart rate, blood pressure, and body temperature data. It should be noted here that when dancing, it is very important to monitor the heart rate, blood pressure, and body temperature because they can provide key information about physical health status and exercise intensity. Monitoring the heart rate, blood pressure, and body temperature during dancing can help dancers understand their physical condition and ensure exercise safety;

[0052] S13. Store the action data of the acquired standard training images, the training data during the training process, and the physical fitness change data in the storage component. At the same time, project the acquired training data during the training process onto the standard training image, that is, scale the training image of the trainee to an image with the same scale as the standard training image, and represent the positions of the corresponding moving parts of the corresponding dance actions on the standard training image;

[0053] As Figure 5 shown, Figure 5 is a schematic diagram of the image comparison process of the present invention. The specific steps to scale the training image of the trainee to an image with the same scale as the standard training image are as follows: S131. Prepare materials: Two images need to be prepared, one is the actual dance action image of the dancer, and the other is the standard dance action image;

[0054] S132. Image processing: Open the two images using image processing software (such as Adobe Photoshop, GIMP, etc.); then, use the move tool to drag the standard action image onto the actual dance action image to ensure that the two images are completely aligned;

[0055] S133. Adjust the layer: In the Layers panel, set the layer blending mode of the standard action image to "Difference" or "Overlay"; in this way, the differences between the two images will be displayed in the form of color changes;

[0056] S134. Analyze the comparison image: Now, analyze the differences between the dance actions and the standard actions by observing the comparison image;

[0057] S2. Import the training data during the training process and the physical fitness change data during the training process into the training matching analysis strategy for training matching analysis;

[0058] In one specific embodiment, as Figure 3 shown, Figure 3 is a schematic diagram of the S2 step process of the dance teaching analysis method based on artificial intelligence of the present invention. S2 includes the following steps: S21. Obtain the action data of the standard training image stored in the training teaching aid during the corresponding dance training and the position data of each moving part during the training process, and import them into the training proficiency calculation formula to calculate the training proficiency. Among them, the training proficiency calculation formula is: , where T is the time of the dance training process, kt is the training difficulty at time t during the training process, V() is the volume of the three-dimensional image in the brackets, at is the corresponding image of the trainee's projection on the standard training image at time t, bt is the training image on the standard training image at time t, dt is the time integral, is the intersection of the images, that is, the overlapping position of the images, is the union of images, and km is the standard value of training difficulty in the training process;

[0059] S22. Obtain the physical fitness change data during the training process, and import the obtained physical fitness change data during the training process into the physical fitness change outlier calculation formula to calculate the physical fitness change outlier. The physical fitness change outlier calculation formula is as follows: , where N is the type of physical fitness characteristics, ci is the proportion coefficient of the i-th type of physical fitness characteristics, pit is the average value of the i-th type of physical fitness characteristics during the training process, pim is the median of the safety range of the i-th type of physical fitness characteristics, pimax is the maximum value of the safety range of the i-th type of physical fitness characteristics, pimin is the minimum value of the safety range of the i-th type of physical fitness characteristics, and pic is the average value of the i-th type of physical fitness characteristics in the time period before training;

[0060] The advantage here is that the impact of dance training on physical fitness changes is reflected by comparing the physical fitness characteristics during the training process with those in the time period before training;

[0061] S23. Obtain the calculated training proficiency and physical fitness change outlier, and substitute them into the training matching value calculation formula to calculate the training matching value. The training matching value calculation formula is as follows: , where is the proportion coefficient of training proficiency;

[0062] S3. Obtain the dance training action data and import it into the training difficulty analysis strategy for training difficulty analysis;

[0063] In one specific embodiment, S3 includes the following steps: S31. Obtain the action data of the standard training images stored in the training aids during dance training, and import the action data of the standard training images in the training process into the training process training difficulty calculation formula to calculate the training process training difficulty. The training process training difficulty calculation formula is as follows: ;

[0064] It should be noted here that the dance difficulty is reflected by the degree of body activity (i.e., the frequency and amplitude of action changes) at intervals of time periods; the difficulty of dance is often closely related to the frequency and amplitude of the body action changes of the dancer. When evaluating the dance difficulty, observing and analyzing the frequency and amplitude of the body action changes of the dancer is a very effective method;

[0065] The action change frequency refers to the number of times or the rate at which a dancer completes actions within a unit of time. High-frequency action changes usually mean that the dance has a higher level of difficulty. For example, fast dance steps, continuous turns, or jumps all require the dancer to have excellent coordination and physical strength. These actions require the dancer to complete multiple action conversions within a short period of time, thus increasing the difficulty of the dance. The action amplitude refers to the range or distance that various parts of the dancer's body move when performing an action. A larger action amplitude usually requires more strength and flexibility, and thus also increases the difficulty of the dance. For example, large jumps, stretches, or rotation actions require the dancer to have a relatively high physical fitness and technical level. These actions not only require the dancer to have enough strength to execute them, but also require them to have excellent balance and control.

[0066] By combining the observation and analysis of the dancer's action change frequency and amplitude, we can more comprehensively evaluate the difficulty of the dance.

[0067] S32. Import all the action data of the standard training images stored in the training teaching aids during dance training into the training difficulty calculation formula to calculate the training difficulty of the entire process. The training difficulty calculation formula for the entire process is as follows: , where Ts is the time experienced by all the actions of the standard training image, gt is the training image at time t during the process of all the actions of the standard training image, and g(t - 1) is the training image at time t - 1 during the process of all the actions of the standard training image.

[0068] S4. Conduct training safety analysis based on the obtained training matching analysis result and training difficulty analysis result.

[0069] In one specific embodiment, S4 includes the following steps: Obtain the calculated training matching value, the training process training difficulty, and the training difficulty of the entire process, and import them into the training safety value calculation formula to calculate the training safety value. The training safety value calculation formula is as follows: , where exp() is the exponential power of the natural constant e.

[0070] S5. Conduct early warning during the training process based on the obtained training safety analysis result.

[0071] In one specific embodiment, S5 includes the following steps: Compare the obtained training safety value with the set training safety threshold. If the training safety value is greater than or equal to the set training safety threshold, conduct early warning during the training process to remind the training personnel that the dance teaching is not suitable. If the training safety value is less than the set training safety threshold, do not conduct early warning during the training process, and the training personnel can train normally.

[0072] In this embodiment, it should be specifically noted that the value-taking methods of the proportion coefficient of the i-th physical characteristic type, the proportion coefficient of training proficiency, and the training safety threshold are as follows: Obtain 500 sets of dance training action data, and at the same time obtain the training data during the training process and the physical change data during the training process. Substitute the obtained data into the training safety value calculation formula to calculate the training safety value, obtain the judgment result of whether a human body injury occurs, and import the training safety value and the judgment result of whether a human body injury occurs into the fitting software to output the values of the proportion coefficient of the i-th physical characteristic type, the proportion coefficient of training proficiency, and the training safety threshold that meet the maximum judgment result accuracy rate.

[0073] The advantages of this embodiment compared with the prior art are as follows: Obtain dance training action data, and at the same time obtain the training data during the training process and the physical change data during the training process. Import the training data during the training process and the physical change data during the training process into the training matching analysis strategy for training matching analysis. Import the dance training action data into the training difficulty analysis strategy for training difficulty analysis. Conduct training safety analysis based on the obtained training matching analysis result and training difficulty analysis result. Conduct training process warning through the obtained training safety analysis result. Conduct comprehensive analysis on the training situation and physical change data during the training process to evaluate the safety during the dance training process. Comprehensively analyze and evaluate the danger during the dance process based on the dancers and dance movements to avoid human body injuries caused by unmatched personnel forcing dance training.

[0074] Embodiment 2

[0075] As Figure 4 shown, the dance teaching analysis system based on artificial intelligence is implemented based on the above-mentioned dance teaching analysis method based on artificial intelligence, and specifically includes a data acquisition module, a training matching analysis module, a training difficulty analysis module, a training safety analysis module, and a training process warning module; among them, the data acquisition module is used to obtain dance training action data, and at the same time obtain the training data during the training process and the physical change data during the training process; the training matching analysis module is used to import the training data during the training process and the physical change data during the training process into the training matching analysis strategy for training matching analysis; the training difficulty analysis module is used to import the dance training action data into the training difficulty analysis strategy for training difficulty analysis; the training safety analysis module is used to conduct training safety analysis based on the obtained training matching analysis result and training difficulty analysis result; the training process warning module is used to conduct training process warning through the obtained training safety analysis result.

[0076] Embodiment 3

[0077] This embodiment provides an electronic device, including: a processor and a memory, wherein, a computer program that can be called by the processor is stored in the memory;

[0078] By calling the computer program stored in the memory, the processor executes the above-mentioned dance teaching analysis method based on artificial intelligence.

[0079] This electronic device may have relatively large differences due to different configurations or performances, and can include one or more processors and one or more memories. Among them, at least one computer program is stored in the memory, and this computer program is loaded and executed by the processor to implement the dance teaching analysis method based on artificial intelligence provided by the above method embodiment. This electronic device can also include other components for implementing the functions of the device. For example, this electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for inputting and outputting data. This embodiment will not be elaborated here.

[0080] Embodiment 4

[0081] This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored;

[0082] When the computer program runs on a computer device, it enables the computer device to execute the above-mentioned dance teaching analysis method based on artificial intelligence.

[0083] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a compact disc read-only memory, magnetic tape, a floppy disk, and an optical data storage device, etc.

[0084] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

Claims

1. A dance teaching analysis method based on artificial intelligence, characterized in that: It includes the following specific steps: S1, obtaining dance training movement data, and simultaneously obtaining training data during the training process and physical fitness change data during the training process; S2, obtaining training data during the training process and physical fitness change data during the training process and importing them into the training matching analysis strategy for training matching analysis; S3, obtaining dance training movement data and importing it into the training difficulty analysis strategy to perform training difficulty analysis; S4. Perform training safety analysis based on the training matching analysis results and training difficulty analysis results obtained by analysis; S5. Early warning of the training process is performed based on the obtained training safety analysis results; The acquisition of training data during the training process and the physical fitness change data during the training process and importing them into the training matching analysis strategy for training matching analysis includes the following specific steps: S21, obtaining the motion data of the standard training image stored in the training teaching aids during the corresponding dance training and the position data of each moving part during the training process, and importing them into the training proficiency calculation formula to calculate the training proficiency, wherein the training proficiency calculation formula is: , where T is the dance training process time, kt is the training difficulty at time t in the training process, V() is the volume of the three-dimensional image in brackets, at is the corresponding image of the training body projected on the standard training image at time t, bt is the training image on the standard training image at time t, and dt is the time integral. is the intersection of the images, that is, the overlapping positions of the images, is the union of images, km is the standard value of the training difficulty in the training process, and the training difficulty calculation formula at time t is: , where b(t-1) is the training image on the standard training image at time t-1; S22, obtaining the physical fitness change data during the training process, and importing the obtained physical fitness change data during the training process into the physical fitness change abnormal value calculation formula to calculate the physical fitness change abnormal value, wherein the physical fitness change abnormal value calculation formula is: , where N is the type of physical characteristics, ci is the proportion coefficient of the i-th physical characteristics, pit is the average value of the i-th physical characteristics during the training process, pim is the median value of the safety range of the i-th physical characteristics, pimax is the maximum value of the safety range of the i-th physical characteristics, pimin is the minimum value of the safety range of the i-th physical characteristics, and pic is the average value of the i-th physical characteristics in the pre-training period; S23, obtaining the calculated training proficiency and physical fitness change abnormality value and substituting them into the training matching value calculation formula to calculate the training matching value, wherein the training matching value calculation formula is: ,in, is the training proficiency ratio.

2. The dance teaching analysis method based on artificial intelligence as claimed in claim 1 is characterized in that: The specific contents of acquiring dance training action data, and acquiring training data during the training process and physical fitness change data during the training process are as follows: S11, obtaining the motion data of the standard training images stored in the training aids during dance training, and obtaining the training data of the training process through the sensor, including the position data of each moving part during the training process; S12, obtaining physical fitness change data during training through sensors, wherein the physical fitness change data includes heart rate, blood pressure and body temperature data; S13. The motion data of the acquired standard training image, the training data during the training process and the physical fitness change data are stored in the storage component, and the training data acquired during the training process are projected on the standard training image. The specific method is: the training image of the trainee is scaled to an image of the same scale as the standard training image, and the position of the corresponding moving part of the corresponding dance movement is indicated on the standard training image.

3. The dance teaching analysis method based on artificial intelligence as claimed in claim 1 is characterized in that: The method of obtaining dance training action data and importing it into the training difficulty analysis strategy to perform training difficulty analysis includes the following specific steps: S31, obtaining the motion data of the standard training image stored in the training teaching aids during dance training, and importing the motion data of the standard training image of the training process into the training difficulty calculation formula to calculate the training difficulty of the training process, wherein the training difficulty calculation formula of the training process is: ; S32, importing all the movement data of the standard training images stored in the training teaching aids during dance training into the training difficulty calculation formula to calculate the training difficulty of the whole process, wherein the training difficulty calculation formula of the whole process is: , where Ts is the time taken for all actions of the standard training image, gt is the training image at time t during the entire action of the standard training image, and g(t-1) is the training image at time t-1 during the entire action of the standard training image.

4. The dance teaching analysis method based on artificial intelligence as claimed in claim 3 is characterized in that: The training safety analysis based on the training matching analysis results and the training difficulty analysis results obtained by analysis includes the following specific contents: obtaining the calculated training matching value, the training difficulty of the training process and the training difficulty of the entire process and importing them into the training safety value calculation formula to calculate the training safety value, wherein the training safety value calculation formula is: , where exp() is the power of the natural constant e.

5. The dance teaching analysis method based on artificial intelligence as claimed in claim 4 is characterized in that: The training process early warning based on the obtained training safety analysis results includes the following specific contents: The obtained training safety value is compared with the set training safety threshold. If the training safety value is greater than or equal to the set training safety threshold, a training process warning is issued to remind the trainee that the dance teaching is not suitable. If the training safety value is less than the set training safety threshold, no training process warning is issued and the trainee can train normally.

6. A dance teaching analysis system based on artificial intelligence, which is implemented based on the dance teaching analysis method based on artificial intelligence as claimed in any one of claims 1 to 5, characterized in that: It specifically includes a data acquisition module, a training matching analysis module, a training difficulty analysis module, a training safety analysis module and a training process early warning module; The data acquisition module is used to acquire dance training movement data, and simultaneously acquire training data during the training process and physical fitness change data during the training process; The training matching analysis module is used to obtain the training data during the training process and the physical fitness change data during the training process and import them into the training matching analysis strategy to perform training matching analysis; The training difficulty analysis module is used to obtain dance training movement data and import it into the training difficulty analysis strategy to perform training difficulty analysis; The training safety analysis module is used to perform training safety analysis based on the training matching analysis results and training difficulty analysis results obtained by analysis; The training process early warning module is used to provide early warning for the training process based on the obtained training safety analysis results.

7. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the dance teaching analysis method based on artificial intelligence as described in any one of claims 1 to 5 by calling the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the dance teaching and analysis method based on artificial intelligence as described in any one of claims 1 to 5.

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