Dance teaching analysis system and method based on artificial intelligence

Abstract

The invention discloses a dance teaching analysis system and method based on artificial intelligence, and belongs to the field of educational appliances. Training data in a training process and physique change data in the training process are acquired and imported into a training matching analysis strategy for training matching analysis; dance training action data are acquired and imported into a training difficulty analysis strategy for training difficulty analysis, training safety analysis is performed according to a training matching analysis result obtained through analysis and a training difficulty analysis result, and training process early warning is performed through an obtained training safety analysis result. The training condition and physical change data in the training process are comprehensively analyzed, the safety in the dance training process is evaluated, the danger in the dance process is comprehensively analyzed and evaluated according to dancers and dance actions, and human body injuries caused by forced dance training of mismatched persons are avoided.

Description

Technical Field

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

[0002] Dance teaching has a positive role in promoting the all-round development of students. First of all, dance teaching can exercise students' bodies and improve their physical fitness and athletic 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 quality. Dance teaching is a unique form of art education. It cultivates students' dance skills, artistic accomplishment and aesthetic ability through systematic dance training and diversified teaching methods. At the same time, dance teaching can also promote the all-round development of students and lay a solid foundation for their future development. During dance training, it is impossible to conduct a comprehensive analysis and evaluation of the safety of the dance training process based on the training status and physical fitness change data during the training process. It often happens that unmatched personnel are forced to undergo dance training, resulting in human injuries. The existing technology cannot solve the above problem. In order to solve the problems raised by this background technology, this application designs a dance teaching analysis system and method based on artificial intelligence. Summary of the invention

[0003] In view of the deficiencies of the prior art, the present invention proposes a dance teaching analysis system and method based on artificial intelligence.

[0004] To achieve the above object, the present invention provides the following technical solution: a dance teaching analysis method based on artificial intelligence, which comprises 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. Provide early warning for the training process based on the obtained training safety analysis results.

[0005] As a preferred technical solution of the dance teaching analysis method based on artificial intelligence, the specific contents of obtaining dance training movement data, and simultaneously obtaining 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. Acquiring physical fitness change data during training through sensors, wherein the physical fitness change data includes heart rate, blood pressure and body temperature data. It should be noted that it is very important to monitor heart rate, blood pressure and body temperature when dancing, because they can provide key information about physical health and exercise intensity. Monitoring heart rate, blood pressure and body temperature when dancing can help dancers understand their physical condition and ensure exercise safety. 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, that is, the training image of the trainee is scaled to an image at the same scale of the standard training image, and the position of the corresponding moving part of the corresponding dance movement is indicated on the standard training image.

[0006] As a preferred technical solution of the dance teaching analysis method based on artificial intelligence, the acquisition of training data during the training process and the physical fitness change data during the training process are imported into the training matching analysis strategy for training matching analysis, which 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 training difficulty in the training process; 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.

[0007] As a preferred technical solution of the dance teaching analysis method based on artificial intelligence, the acquisition of dance training action data and importing it into the training difficulty analysis strategy for 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.

[0008] As a preferred technical solution of the dance teaching analysis method based on artificial intelligence, 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: The calculated training matching value, training difficulty of the training process and training difficulty of the entire process are obtained and imported 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.

[0009] As a preferred technical solution of the dance teaching analysis method based on artificial intelligence, the training process early warning obtained through the 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.

[0010] An artificial intelligence-based dance teaching analysis system, which is implemented based on the artificial intelligence-based dance teaching analysis method, 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; 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.

[0011] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned dance teaching analysis method based on artificial intelligence by calling the computer program stored in the memory.

[0012] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned dance teaching analysis method based on artificial intelligence.

[0013] Compared with the prior art, the beneficial effects of this application are: The present application obtains dance training movement data, and simultaneously obtains training data during the training process and physical fitness change data during the training process, imports 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, obtains dance training movement data and imports it into the training difficulty analysis strategy for training difficulty analysis, performs training safety analysis based on the training matching analysis results and training difficulty analysis results obtained by analysis, performs training process early warning based on the obtained training safety analysis results, conducts a comprehensive analysis of the training situation and physical fitness change data during the training process, evaluates the safety of the dance training process, evaluates the danger of the dance process based on the comprehensive analysis of dancers and dance movements, and avoids human injuries caused by forced dance training by unmatched personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The figure is a schematic diagram of the overall process of the dance teaching analysis method based on artificial intelligence of the present invention; Figure 2 This is a schematic flow chart of step S1 of the dance teaching analysis method based on artificial intelligence of the present invention; Figure 3 This is a schematic flow chart of step S2 of the dance teaching analysis method based on artificial intelligence of the present invention; Figure 4 Schematic diagram of the overall framework of the dance teaching analysis system based on artificial intelligence of the present invention; Figure 5 It is a schematic diagram of the image comparison process of the present invention; Figure 6 It is a schematic diagram of information transmission of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use.

[0016] Example 1

[0017] Combined with this Figure 6 The application scenario of this embodiment is described as follows: Figure 6This is a schematic diagram of information transmission of the present invention, wherein the image acquisition terminal acquires the dance training action data played in the training aid and the training data in the training process, the physical information sensor acquires the physical change data in the training process, the data processing terminal acquires the training data in the training process and the physical change data in the training process and imports them into the training matching analysis strategy to perform training matching analysis, acquires the dance training action data and imports them into the training difficulty analysis strategy to perform training difficulty analysis, performs training safety analysis based on the obtained training matching analysis results and training difficulty analysis results, performs training process warning based on the obtained training safety analysis results, and transmits the warning information to the training aid to issue an alarm; In order to solve the technical problem raised in the background technology: during dance training, due to the variety of dance types and dangers, it is impossible to conduct a comprehensive analysis and evaluation of the safety of the dance training process based on the training conditions and physical fitness change data during the training process, and it often happens that unmatched personnel are forced to perform dance training, resulting in human injuries. The present invention provides a preferred embodiment: Figure 1 As shown, the dance teaching analysis method based on artificial intelligence 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; In one specific embodiment, Figure 2 As shown, Figure 2 The figure is a flow chart of step S1 of the dance teaching analysis method based on artificial intelligence of the present invention, and S1 includes the following steps: 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. Acquiring physical fitness change data during training through sensors, wherein the physical fitness change data includes heart rate, blood pressure and body temperature data. It should be noted that it is very important to monitor heart rate, blood pressure and body temperature when dancing, because they can provide key information about physical health and exercise intensity. Monitoring heart rate, blood pressure and body temperature when dancing can help dancers understand their physical condition and ensure exercise safety. S13, storing the acquired motion data of the standard training image, the training data during the training process, and the physical fitness change data in the storage component, and projecting the acquired training data during the training process onto the standard training image, i.e. scaling the training image of the trainee to an image at the same scale as the standard training image, and representing the position of the corresponding moving part of the corresponding dance action on the standard training image; like Figure 5 As shown, Figure 5The image comparison process diagram of the present invention is as follows: S131, preparing 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; S132. Image processing: Use image processing software (such as Adobe Photoshop, GIMP, etc.) to open the two images; then, use the move tool to drag the standard action image onto the actual dance action image, making sure the two images are completely aligned; S133. Adjustment layer: In the Layers panel, set the layer blending mode of the standard action image to "Difference" or "Overlay"; in this way, the difference between the two images will be displayed in the form of color changes; S134, analyzing the comparison image: Now, analyzing the difference between the dance movements and the standard movements by observing the comparison image; 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; In one specific embodiment, Figure 3 As shown, Figure 3 The figure is a flow chart of step S2 of the dance teaching analysis method based on artificial intelligence of the present invention, wherein S2 comprises the following 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 training difficulty in the training process; 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; The benefit here is that the effect of dance training on physical changes can be reflected by comparing physical characteristics during training with those before training; 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 coefficient; S3, obtaining dance training movement data and importing it into the training difficulty analysis strategy to perform training difficulty analysis; In one specific embodiment, S3 includes the following 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: ; It should be noted that the difficulty of dance is reflected by the degree of body activity (i.e. the frequency and amplitude of movement changes) at different time intervals. The difficulty of dance is often closely related to the frequency and amplitude of the dancer's body movements. When evaluating the difficulty of dance, observing and analyzing the frequency and amplitude of the dancer's body movements is a very effective method. The frequency of movement changes refers to the number of times or the rate at which a dancer completes movements per unit time. A high frequency of movement changes usually means that the dance has a higher difficulty; for example, fast dance steps, continuous turns or jumps require dancers to have excellent coordination and physical strength; these movements require dancers to complete multiple movement transitions in a short period of time, which increases the difficulty of the dance. The range of motion refers to the range or distance that the dancer's body parts move when performing movements. A larger range of motion usually requires more strength and flexibility, which also increases the difficulty of the dance; for example, large-scale jumps, stretches or rotations require dancers to have high physical fitness and technical levels. These movements not only require dancers to have enough strength to perform, but also require them to have excellent balance and control. By combining observation and analysis of the frequency and amplitude of a dancer’s movement changes, we can more fully assess the difficulty of a dance; 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 whole process of the standard training image, and g(t-1) is the training image at time t-1 during the whole process of the standard training image; S4. Perform training safety analysis based on the training matching analysis results and training difficulty analysis results obtained by analysis; In one specific embodiment, S4 includes the following steps: Obtain the calculated training matching value, training difficulty of the training process and training difficulty of the entire process and import 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; S5. Early warning of the training process is performed based on the obtained training safety analysis results; In one specific embodiment, S5 includes the following steps: comparing 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, then issuing a training process warning to remind the trainee that the dance teaching is not suitable, if the training safety value is less than the set training safety threshold, then not issuing a training process warning, and the trainee can train normally; In the present embodiment, it should be particularly noted that the value determination method of the proportion coefficient of the i-th physical characteristic type, the training proficiency proportion coefficient and the training safety threshold is as follows: 500 groups of dance training movement data are obtained, and at the same time, the training data during the training process and the physical fitness change data during the training process are obtained, and the obtained data are substituted into the training safety value calculation formula to calculate the training safety value, and the judgment result of whether human body injury occurs is obtained, and the training safety value and the judgment result of whether human body injury occurs are imported into the fitting software, and the value of the proportion coefficient of the i-th physical characteristic type, the training proficiency proportion coefficient and the training safety threshold that meet the maximum judgment result accuracy is output.

[0018] The advantages of this embodiment over the prior art are as follows: obtaining dance training movement data, and simultaneously obtaining training data during the training process and physical fitness change data during the training process, importing the training data during the training process and physical fitness change data during the training process into the training matching analysis strategy for training matching analysis, obtaining dance training movement data and importing it into the training difficulty analysis strategy for training difficulty analysis, performing training safety analysis based on the training matching analysis results and training difficulty analysis results obtained by analysis, performing early warning of the training process based on the obtained training safety analysis results, conducting a comprehensive analysis of the training situation and physical fitness change data during the training process, evaluating the safety of the dance training process, evaluating the danger in the dance process based on the comprehensive analysis of dancers and dance movements, and avoiding human injuries caused by forced dance training by unmatched personnel.

[0019] Example 2

[0020] like Figure 4 As shown, an artificial intelligence-based dance teaching analysis system is implemented based on the above-mentioned artificial intelligence-based dance teaching analysis method, 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; wherein, the data acquisition module is used to acquire dance training movement data, and at the same time acquire training data in the training process and physical fitness change data in the training process; the training matching analysis module is used to acquire training data in the training process and physical fitness change data in the training process and import them into the training matching analysis strategy for training matching analysis; the training difficulty analysis module is used to acquire dance training movement data and import them into the training difficulty analysis strategy for 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 perform training process early warning based on the obtained training safety analysis results.

[0021] Example 3

[0022] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned dance teaching analysis method based on artificial intelligence by calling the computer program stored in the memory.

[0023] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memory stores at least one computer program, and the 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. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0024] Example 4

[0025] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device executes the above-mentioned dance teaching analysis method based on artificial intelligence.

[0026] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0027] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by 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 a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through 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 data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

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. Provide early warning for the training process based on the obtained training safety analysis results.

2. The dance teaching analysis method based on artificial intelligence as claimed in claim 1, 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 2 is characterized in that: 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.

4. The dance teaching analysis method based on artificial intelligence as claimed in claim 3 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.

5. The dance teaching analysis method based on artificial intelligence as claimed in claim 4 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.

6. The dance teaching analysis method based on artificial intelligence as claimed in claim 5, 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.

7. 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 6, 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.

8. 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 6 by calling the computer program stored in the memory.

9. 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 6.

Images