Method and device for playing sports follow-along video, and electronic device

Abstract

This application discloses a method, apparatus, and electronic device for playing exercise follow-along videos. Relating to the field of digital fitness, the method includes: upon detecting that a target user is playing a follow-along video of a target exercise, obtaining the current number of movements at the current moment from the target user's wearable exercise device, wherein the current number of movements is the cumulative number of movements completed by the target user from the start moment to the current moment; determining the preset number of movements in the follow-along video at the current moment; obtaining the playback state of the follow-along video at the current moment, and obtaining the total number of movements in the follow-along video; and changing the playback mode of the follow-along video based on the playback state, the current number of movements, the preset number of movements, and the total number of movements. This application solves the problem of low matching degree between the user's exercise state and the playback content of the follow-along video in related technologies.

Description

Technical Field

[0001] This application relates to the field of digital fitness, and more specifically, to a method, device, and electronic device for playing exercise training videos. Background Technology

[0002] With the development of the internet, using fitness apps to watch workout videos and follow along at home has become an important way for people to stay fit. Users can conveniently access professional course content through mobile phones, tablets, and other devices, enabling self-training without a venue or coach. These apps, with their rich content and flexible scheduling, are widely used in daily exercise scenarios.

[0003] However, when users follow along with exercise videos, the videos play automatically according to a preset playback method, which cannot recognize the user's movement status and rhythm. It cannot detect whether the user's movements are completed, nor can it determine whether the user's movement status is lagging or ahead. As a result, beginners cannot keep up with the video rhythm, and users who finish the exercise early have to wait for the video to finish playing. This reduces the matching degree between the user and the video content and affects the user's training effect.

[0004] There is currently no effective solution to the problem of low matching between user movement status and the content of the training video in related technologies. Summary of the Invention

[0005] The main objective of this application is to provide a method, device, and electronic device for playing exercise training videos, in order to solve the problem of low matching degree between the user's exercise state and the content of the training video in related technologies.

[0006] To achieve the above objectives, according to one aspect of this application, a method for playing a sports follow-up video is provided. The method includes: upon detecting that a target user is playing a follow-up video of a target sport, obtaining the current number of actions at the current moment from the target user's wearable device, wherein the current number of actions is the cumulative number of actions completed by the target user from the start moment to the current moment; determining a preset number of actions for the follow-up video at the current moment, wherein the preset number of actions represents the cumulative number of actions completed by the follow-up video from the start moment to the current moment; obtaining the playback state of the follow-up video at the current moment, and obtaining the total number of actions for the follow-up video; and changing the playback mode of the follow-up video based on the playback state, the current number of actions, the preset number of actions, and the total number of actions.

[0007] Optionally, changing the playback mode of the follow-up video based on the playback status, current number of actions, preset number of actions, and total number of actions includes: when the playback status is complete, determining whether the current number of actions is equal to the preset number of actions; when the current number of actions is equal to the preset number of actions, keeping the playback mode unchanged; when the current number of actions is less than the preset number of actions, determining a first difference value between the current number of actions and the preset number of actions; extracting the corresponding video segment from the follow-up video based on the first difference value, and replaying the video segment.

[0008] Optionally, changing the playback mode of the follow-up video based on the playback status, current number of actions, preset number of actions, and total number of actions includes: when the playback status is incomplete, determining whether the current number of actions is less than the total number of actions; when the current number of actions is greater than or equal to the total number of actions, ending the playback of the follow-up video; and when the current number of actions is less than the total number of actions, keeping the playback mode unchanged.

[0009] Optionally, before detecting that the target user is playing a follow-up video of the target movement, the method further includes: acquiring the target user's historical movement records, and acquiring the N historical movement records with the smallest time difference from the current time, where N is a positive integer; determining the number of times the target user extends the playback of the historical movement follow-up video based on the N historical movement records, obtaining a first count, and determining the number of times the target user ends the historical movement follow-up video early, obtaining a second count; if the first count is greater than a preset count threshold, playing the follow-up video at a first preset speed, where the first preset speed is less than 1; if the second count is greater than the preset count threshold, playing the follow-up video at a second preset speed, where the second preset speed is greater than 1.

[0010] Optionally, the method further includes: obtaining the action timeline of the target user when performing the target movement from the target user's wearable device; obtaining the execution speed of the target user's most recent complete movement from the action timeline to obtain a first speed value; obtaining the execution speed of the target user's fastest complete movement from the action timeline to obtain a second speed value; determining the target user's speed loss rate based on the first speed value and the second speed value; and sending a prompt message to the target user based on the speed loss rate, wherein the prompt message is used to display the target user's exercise fatigue state.

[0011] Optionally, determining the speed loss rate of the target user based on the first speed value and the second speed value includes: calculating the difference between the second speed value and the first speed value to obtain the speed difference; calculating the ratio of the speed difference to the second speed value, and determining the ratio as the speed loss rate.

[0012] Optionally, after obtaining the speed loss rate, the method further includes: determining the exercise fatigue state corresponding to the speed loss rate according to a preset lookup table, wherein the preset lookup table includes multiple speed loss rate intervals and the exercise fatigue state corresponding to each speed loss rate interval; determining the adjustment strategy for the follow-up video according to the exercise fatigue state, and adjusting the video content of the follow-up video according to the adjustment strategy.

[0013] To achieve the above objectives, according to another aspect of this application, a device for playing a sports training video is provided. The device includes: a first acquisition unit, configured to acquire the current number of actions at the current moment from the target user's sports wearable device when detecting that a target user is playing a training video of a target sport, wherein the current number of actions is the cumulative number of actions completed by the target user from the start moment to the current moment; a first determination unit, configured to determine a preset number of actions in the training video at the current moment, wherein the preset number of actions represents the cumulative number of actions completed in the training video from the start moment to the current moment; a second acquisition unit, configured to acquire the playback state of the training video at the current moment and acquire the total number of actions in the training video; and a modification unit, configured to modify the playback mode of the training video according to the playback state, the current number of actions, the preset number of actions, and the total number of actions.

[0014] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described method for playing exercise training videos when it runs.

[0015] To achieve the above objectives, according to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the above-described method for playing a motion training video.

[0016] In this embodiment, when a target user is detected playing a follow-up video of a target movement, the following steps are taken: The current number of actions at the current moment is obtained from the target user's wearable device. The current number of actions is the cumulative number of actions completed by the target user from the start time to the current moment. A preset number of actions for the follow-up video at the current moment is determined, where the preset number of actions represents the cumulative number of actions completed from the start time to the current moment. The playback state of the follow-up video at the current moment is obtained, and the total number of actions for the follow-up video is also obtained. The follow-up exercise is then modified based on the playback state, the current number of actions, the preset number of actions, and the total number of actions. The video playback method obtains the target user's current number of movements from the wearable device, as well as the preset number of movements and the total number of movements in the follow-up video. Based on the relationship between the current number of movements, the preset number of movements, and the total number of movements, the follow-up video is adjusted to ensure that the playback content of the follow-up video is consistent with the user's current movement state. This improves the matching degree between the user's movement state and the playback content of the follow-up video, thereby enhancing the user's comfort and satisfaction during exercise follow-up. This solves the technical problem of low matching degree between user movement state and playback content in related technologies. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 A hardware block diagram of a computer terminal for implementing a method of playing exercise training videos is shown.

[0019] Figure 2 This is a flowchart of a method for playing exercise training videos according to Embodiment 1 of this application;

[0020] Figure 3 This is a schematic diagram of a video playback device for exercise training provided according to Embodiment 2 of this application;

[0021] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] It should be noted that the methods, devices, and electronic devices for playing exercise videos as defined in this disclosure can be used in the field of digital fitness, or in any field other than digital fitness. The application fields of the methods, devices, and electronic devices for playing exercise videos as defined in this disclosure are not limited.

[0026] It should be noted that all information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) used in this application are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with the relevant regulations and standards of the relevant regions, have taken necessary measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse use. If the user chooses to refuse, the process proceeds to the expert decision-making process. For example, this system has interfaces with relevant users or organizations. Before obtaining relevant information, a request to obtain the information needs to be sent to the aforementioned user or organization through the interface. After receiving consent from the aforementioned user or organization, the relevant information is obtained. Users can view the purpose of data use in real time through the authorization interface and have the right to withdraw authorization or delete data at any time. After authorization is withdrawn, the system will terminate the relevant data processing within 24 hours.

[0027] The embodiments or examples disclosed herein are not exhaustive, but merely illustrative of some embodiments or examples, and are not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment or example can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment or example can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment or example can be arbitrarily interchanged. Furthermore, optional methods or examples in a particular embodiment or example can be arbitrarily combined; moreover, embodiments or examples can be arbitrarily combined. For example, some or all steps of different embodiments or examples can be arbitrarily combined, and a particular embodiment or example can be arbitrarily combined with optional methods or examples of other embodiments or examples.

[0028] Example 1

[0029] According to an embodiment of this application, an embodiment of a method for playing exercise training videos is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a method of playing exercise training videos is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, processing devices such as microprocessors or programmable logic devices), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface, a universal serial bus port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method of playing the exercise training video in this embodiment of the application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the above-mentioned method of playing the exercise training video. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0034] The display may be, for example, a touchscreen LCD display that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0035] Under the aforementioned operating environment, this application provides the following: Figure 2 The instructions for playing the exercise video are shown. Figure 2 This is a flowchart of the method for playing exercise training videos according to Embodiment 1 of this application, as follows: Figure 2 As shown, the method includes:

[0036] Step S201: When it is detected that the target user is playing a follow-up video of the target movement, the current number of actions at the current moment is obtained from the target user's sports wearable device. The current number of actions is the cumulative number of times the target user has completed the target movement from the start moment to the current moment.

[0037] It should be noted that the execution entity in this embodiment can be a sports training video playback system. This system can be configured in a sports application. This system can interact with the wearable device used by the user during exercise, receive the number of times of exercise collected by the wearable device, and compare the number of times of exercise with the preset number of times in the training video to determine whether the user's exercise state is synchronous, advanced, or delayed. Then, the playback method of the training video is adjusted according to the exercise state.

[0038] It should be noted that the target movement refers to the specific physical action the user is currently performing, such as squats or push-ups. Follow-along videos are exercise videos loaded into a fitness application by the user's terminal device. Users can perform the corresponding exercises by watching these videos. Follow-along videos can represent a complete exercise video or a specific exercise unit within a comprehensive exercise follow-along video consisting of multiple sets of exercises. Wearable fitness devices refer to sensing terminals worn on the user's limbs, with built-in inertial measurement units that collect three-dimensional acceleration and three-dimensional angular velocity signals at a fixed sampling frequency to count the number of times the user moves.

[0039] For example, after a target user starts a follow-up video of a target exercise, the video playback system in the exercise application can continuously obtain the current number of movements collected by the user's wearable device, thereby determining the user's exercise status based on the current number of movements.

[0040] It should be noted that wearable devices acquire 3D acceleration, 3D angular velocity, and attitude angles via a built-in IMU, collecting 3D acceleration and 3D angular velocity signals of the user's limbs at a frequency of 50Hz or higher. To eliminate errors caused by different user wearing habits, a unified physical coordinate system for the devices is also necessary. Taking a sports watch as an example, the 3D coordinate system can be defined as follows: the X-axis is parallel to the user's arm direction, the Y-axis is parallel to the tangent direction of the watch face, and the Z-axis is perpendicular to the watch face and points outwards.

[0041] Furthermore, after acquiring the three-dimensional acceleration and angular velocity signals of the user's limbs and calibrating the data coordinate system, the data needs to enter the edge-side preprocessing module. Through temporal interpolation and signal length normalization techniques, the original sequences with inconsistent action durations due to individual differences are uniformly mapped to standardized temporal data of a fixed length. For example, due to individual differences in the duration of action execution, temporal interpolation (such as cubic spline interpolation) can be performed on the data sequences within the extracted dynamic time window to align action sequences of different durations to a fixed data frame length, thus meeting the requirements of the subsequent neural network for a fixed input dimension.

[0042] Furthermore, the obtained standardized sequence is input into a locally deployed lightweight deep learning model. This model can identify the current action category and detect the start and end of its cycle based on the trained weight parameters and standardized time-series data, thereby accumulating and generating the current action count. This process is completed entirely locally on the wearable device, without relying on cloud computing, maintaining low latency and privacy security in data collection operations.

[0043] It should be noted that when the wearable device is running the motion recognition and counting algorithm, it can maintain a local state machine and send lightweight data packets to the terminal video playback device at a frequency of 1Hz-5Hz via the Bluetooth Low Energy GATT (Generic Attribute Profile) protocol. The data packets can contain motion action identifiers and the current number of actions.

[0044] Step S202: Determine the preset number of actions in the follow-up video at the current moment, wherein the preset number of actions is used to represent the cumulative number of actions completed in the follow-up video from the start moment to the current moment.

[0045] It should be noted that the preset number of movements refers to the cumulative number of target movement movements completed by the instructor in the video content from the beginning of the video to the current moment, as set in the training video.

[0046] For example, after obtaining the current number of movements, it is also necessary to extract the motion unit information corresponding to that moment from the metadata of the training video, and calculate the total number of standard movements that should be completed from the beginning of the video to the current moment, i.e., the preset number of movements, based on the video playback timeline and the preset structured timestamp.

[0047] For example, if the video is defined as completing the 5th squat at the 30-second mark, then at the current time (30 seconds), the preset number of squats is 5. This process is achieved by matching the player's internal timestamp with the metadata index table, without needing to analyze user actions or sensor data in real time, relying solely on the video's own preset structure.

[0048] It should be noted that in order to accurately obtain the preset number of movements, video metadata preprocessing and timestamp anchor injection are required when creating the follow-up video. During the follow-up video production stage, structured metadata tags need to be injected into the video stream, which can include the type of movement contained in the video, the preset start timestamp and preset end timestamp of a set of movements in each type of movement, as well as the rest duration, etc., so that the preset number of movements can be determined based on the above information.

[0049] Step S203: Obtain the playback status of the follow-up video at the current moment, and obtain the total number of movements in the follow-up video.

[0050] It should be noted that playback status refers to the current running mode of the video, which can include completed playback and incomplete playback. Total number of actions is the total number of repetitions of the actions during the duration of the follow-up video from the start to the end of playback.

[0051] For example, it is also necessary to synchronously obtain the video playback status and the total number of movements in the follow-up video at the current moment. This status is used to indicate whether the follow-up video has finished playing at the current moment, so as to determine how to process the current number of movements, the preset number of movements, and the total number of movements based on the playback status, thereby accurately determining the playback method of the follow-up video.

[0052] Step S204: Change the playback mode of the follow-up video according to the playback status, current number of actions, preset number of actions, and total number of actions.

[0053] For example, once the playback state is determined, the playback method of the practice video can be changed based on the comparison method under that playback state, the current number of actions, the preset number of actions, and the total number of actions.

[0054] For example, if the playback status is "playing" and the current number of actions is less than the preset number of actions, it is determined that the user's actions are lagging behind, triggering the anchor point loop mechanism. This causes the follow-up video to loop before the end time of the current action unit until the current number of actions equals the preset number of actions, giving the user enough time to complete the required actions.

[0055] The exercise follow-up video playback method provided in this application embodiment involves: upon detecting that a target user is playing a follow-up video of a target exercise, obtaining the current number of actions at the current moment from the target user's wearable device, wherein the current number of actions is the cumulative number of actions completed by the target user from the start moment to the current moment; determining the preset number of actions in the follow-up video at the current moment, wherein the preset number of actions is used to represent the cumulative number of actions completed in the follow-up video from the start moment to the current moment; obtaining the playback state of the follow-up video at the current moment, and obtaining the total number of actions in the follow-up video; and based on the playback state, the current number of actions, the preset number of actions, and the total number of actions... The method of adjusting the playback mode of the follow-up video by changing the number of repetitions involves obtaining the target user's current number of movements from the wearable device, as well as the preset number of movements and the total number of movements in the follow-up video. Based on the relationship between the current number of movements, the preset number of movements, and the total number of movements, the follow-up video is adjusted to ensure that the playback content of the follow-up video is consistent with the user's current movement state. This improves the matching degree between the user's movement state and the playback content of the follow-up video, thereby enhancing the user's comfort and satisfaction during exercise follow-up. This also solves the technical problem of low matching degree between the user's movement state and the playback content of the follow-up video in related technologies.

[0056] Optionally, in the method for playing exercise follow-up videos provided in this application embodiment, changing the playback mode of the follow-up video according to the playback status, the current number of movements, the preset number of movements, and the total number of movements includes: when the playback status is completed, determining whether the current number of movements is equal to the preset number of movements; when the current number of movements is equal to the preset number of movements, keeping the playback mode unchanged; when the current number of movements is less than the preset number of movements, determining a first difference value between the current number of movements and the preset number of movements; and extracting the corresponding video segment from the follow-up video according to the first difference value and replaying the video segment.

[0057] It should be noted that the first difference value refers to the numerical difference between the current number of actions and the preset number of actions, and the video segment refers to a continuous video subsequence extracted from the follow-up video based on the timestamp anchor point.

[0058] For example, when the playback status is "completed," the video should then proceed to the summary screen. However, it's possible to first determine if the user's current number of actions matches the preset number of actions. If they match, it indicates that the user's actual number of actions completed by the time the video finishes playing is completely consistent with the video's standard rhythm. The system determines that the training process is without deviation, therefore maintaining the playback mode unchanged—that is, not performing any playback position adjustments, looping, or skipping operations—keeping the video in the "completed" state, and playing the summary screen.

[0059] However, if the current number of actions is less than the preset number of actions, the first difference value needs to be calculated, which is the preset number of actions minus the current number of actions, to determine the number of actions the user has not completed. Based on the first difference value, the timestamp anchor point of the last action unit corresponding to the target movement in the training video metadata is queried to determine the start and end time boundaries of the action unit in the video, thereby extracting the video segment corresponding to the number of incomplete actions.

[0060] It should be noted that this video clip can be a standalone segment of the last complete demonstration of the action in the video, with a length consistent with the standard action cycle, and without any transitions or breaks.

[0061] Furthermore, after the video segment is determined, a replay operation can be performed to restart the playback of the captured video segment from the starting point until the segment is played completely, or to loop the playback until the current number of actions equals the preset number of actions. In this way, even if the user has not completed the standard action, the action guidance can be strengthened by partial replay, so that the user can still get a complete action demonstration before the end of training.

[0062] For example, if a user is doing squats and the preset number of repetitions in the follow-up video is 10, and the current number of repetitions is 8, then the video clips corresponding to the last two squat repetitions can be extracted and replayed until the user's current number of repetitions is 10.

[0063] This embodiment quantifies the user's incomplete exercise volume by using a first difference value, and extracts the corresponding replay segment based on the first difference value. This achieves supplementary guidance only for the missing parts, rather than repeating the entire training content, thereby improving training integrity while reducing the amount of replay content.

[0064] Optionally, in the method for playing exercise follow-up videos provided in this application embodiment, changing the playback mode of the follow-up video according to the playback status, the current number of movements, the preset number of movements, and the total number of movements includes: when the playback status is incomplete, determining whether the current number of movements is less than the total number of movements; when the current number of movements is greater than or equal to the total number of movements, ending the playback of the follow-up video; and when the current number of movements is less than the total number of movements, keeping the playback mode unchanged.

[0065] For example, when the playback status is incomplete, it is determined that the follow-up video has not yet reached the preset total number of movements endpoint. At this time, the training is still in progress, and the follow-up video is played normally. At this time, it is necessary to determine whether the current number of movements is less than the total number of movements, so as to determine whether the user has completed the training unit content contained in the follow-up video ahead of schedule.

[0066] If the current number of movements is greater than or equal to the total number of movements, it indicates that the user has completed all the target movements designed in the video. At this point, it can be determined that the training task has been achieved, and the operation of ending the follow-up video is triggered to stop playing the follow-up video. This avoids continuing to play meaningless video content after training is completed, and no manual adjustment is required from the user. By directly ending the follow-up video, the follow-up video of the next movement unit can be played quickly, or the training results can be quickly displayed, reducing the amount of operation required from the user.

[0067] If the current number of actions is less than the total number of actions, it means that the user has not completed all the required actions. In this case, the playback mode remains unchanged, and the system continues to receive real-time updates on the number of actions from the sports wearable device, waiting for subsequent judgment logic to be triggered.

[0068] This embodiment detects the user's current number of actions in real time when the playback status is incomplete. This allows the playback of the follow-up video to end early if the user completes the training plan in the follow-up video ahead of schedule, thereby reducing the user's workload and optimizing the user's training experience.

[0069] Optionally, in the method for playing exercise training videos provided in this application embodiment, before detecting that a target user is playing a training video of a target exercise, the method further includes: obtaining the target user's historical exercise records, and obtaining the N historical exercise records with the smallest time difference from the current time, where N is a positive integer; determining the number of times the target user extends the playback of the historical exercise training video based on the N historical exercise records, obtaining a first count, and determining the number of times the target user ends the historical exercise training video early, obtaining a second count; if the first count is greater than a preset count threshold, playing the training video at a first preset speed, where the first preset speed is less than 1; if the second count is greater than the preset count threshold, playing the training video at a second preset speed, where the second preset speed is greater than 1.

[0070] It should be noted that historical exercise records refer to complete behavioral data related to the target exercise recorded and stored by the system during the target user's historical training process. This may include the start and end times of the video playback corresponding to the target exercise, the actual number of movements completed, the preset number of movements, playback status change nodes, and records of user actions such as actively ending playback early or extending playback. The first preset speed refers to the video playback speed multiplier set by the system to accommodate the user's tendency to lag when the first number of movements exceeds a preset threshold. Its value is less than 1, i.e., slow playback, used to extend the video exercise demonstration time. The second preset speed refers to the video playback speed multiplier set by the system to accommodate the user's tendency to end early when the second number of movements exceeds a preset threshold. Its value is greater than 1, i.e., fast playback, used to compress the video demonstration time, reduce waiting redundancy, and improve the compactness of the training rhythm.

[0071] For example, before the target user starts playing the follow-up video of the target movement, the user's historical movement records can be retrieved from local or cloud storage. These records contain structured data such as the start and end times of video playback in each training session, the completion status of the movement, and the user's active intervention behaviors (such as pausing, skipping, and exiting).

[0072] Furthermore, using the current moment as the time base, all historical records can be sorted by timestamp, and the N records with the smallest time difference can be selected. Based on these N records, the number of times the user extended playback due to incomplete actions in similar past training sessions can be counted as the first count; at the same time, the number of times the user actively ended playback due to early completion of actions can be counted as the second count.

[0073] Furthermore, the first count is compared with a preset count threshold. If the first count exceeds the preset count threshold, it indicates that the user has a persistent problem of lagging in the execution of the movement and not keeping up with the rhythm of the video. In this training session, the video playback speed can be set to the first preset speed, which is lower than the normal playback speed. This slows down the pace of the coach's movement demonstration in the video, extends the demonstration time of each set of movements, and provides the user with more time to complete the movement.

[0074] If the second count exceeds the preset threshold, it indicates that the user frequently terminates the exercise prematurely. In this training session, the video playback speed can be set to the second preset speed, which is higher than the normal playback speed. This compresses the duration of the action demonstration and rest segments in the video, making the video rhythm match the user's faster execution habits, reducing redundant waiting, and improving training efficiency.

[0075] This embodiment introduces a personalized playback speed prediction mechanism based on historical behavior before playback starts, which pre-optimizes the playback rhythm without requiring user feedback, thereby improving the matching degree between the user and the training video, thus optimizing the training experience and improving the user's training efficiency.

[0076] When a user is practicing exercise, it is also necessary to detect the user's fatigue level. Optionally, in the method for playing exercise videos provided in this application embodiment, the method further includes: obtaining the action timeline of the target user when performing the target exercise from the target user's sports wearable device; obtaining the execution speed of the target user's most recent complete exercise action from the action timeline to obtain a first speed value; obtaining the execution speed of the target user's fastest complete exercise action from the action timeline to obtain a second speed value; determining the target user's speed loss rate based on the first speed value and the second speed value; and sending a prompt message to the target user based on the speed loss rate, wherein the prompt message is used to display the target user's exercise fatigue state.

[0077] It should be noted that the action timeline refers to a time-series record constructed from continuously collected and time-aligned sensor data sequences by the wearable device during the target user's execution of the target movement. Each frame of data corresponds to three-dimensional acceleration and angular velocity information at a specific time point, used to fully characterize the dynamic execution process of the target movement in the time dimension, including the start and end times and movement states of all complete action cycles. Execution speed refers to the linear velocity characteristics of the target user's limb movements within a single complete action cycle, and its value is calculated by integrating the acceleration data extracted from the action timeline and performing posture calculations.

[0078] For example, during the target user's execution of the target movement, it is also necessary to continuously obtain the action timeline from the sports wearable device. This timeline is a high-precision time-series data stream generated locally in real time by the device. After coordinate system calibration and signal filtering, the start and end points of each complete action cycle can be identified in the action timeline, and the execution speed corresponding to each complete cycle can be calculated based on acceleration integral and attitude angle calculation.

[0079] For example, the execution speed of the squatting and standing movements can be determined based on the acceleration of squatting down and the acceleration of standing up.

[0080] Furthermore, while the user is continuously performing the target movement, among all the identified movement cycles in the action timeline, the complete action that is closest in time to the current moment is selected, and its execution speed is extracted as the first speed value, thereby representing the current movement state of the target user through the first speed value.

[0081] Similarly, it is also necessary to traverse the entire complete action cycle in the action timeline to find the maximum value of the execution speed, which is used as the second speed value. This value represents the user's peak motion ability when not affected by fatigue.

[0082] Furthermore, the first speed value and the second speed value can be substituted into the speed loss rate calculation formula to obtain the user's speed loss rate, thereby characterizing the degree of decline in the user's current exercise ability and fatigue state through the speed loss rate.

[0083] Finally, based on preset fatigue mapping rules, the speed loss rate can be divided into several levels, such as: less than 10% is mild fatigue, 10% to 20% is moderate fatigue, 20% to 30% is severe fatigue, and more than 30% is near exhaustion. According to the level of the calculated speed loss rate, corresponding prompts such as "Good condition", "Beware of fatigue" and "Stop exercising" are generated and presented to the user through the wearable device screen or vibration feedback, thereby completing the detection and reminder of the user's exercise fatigue status.

[0084] This embodiment determines the user's fatigue state based on the user's movement speed, achieving the technical effect of accurately determining the user's fatigue state, and thus accurately determining the prompt information based on the user's fatigue state.

[0085] Optionally, in the method for playing exercise training videos provided in this application embodiment, determining the speed loss rate of the target user based on the first speed value and the second speed value includes: calculating the difference between the second speed value and the first speed value to obtain the speed difference; calculating the ratio of the speed difference to the second speed value, and determining the ratio as the speed loss rate.

[0086] For example, the following formula can be used to calculate the speed loss rate:

[0087]

[0088] Where Vs is the speed loss rate, V2 is the second speed value, and V1 is the first speed value.

[0089] According to the above formula, the user's speed loss can be determined based on the user's speed loss amount and maximum speed, and then the user's fatigue state can be determined based on the speed loss rate.

[0090] This embodiment determines the user's speed loss rate based on the user's speed loss amount and maximum speed, achieving the technical effect of accurately determining the user's speed loss rate.

[0091] Optionally, in the method for playing exercise training videos provided in this application embodiment, after obtaining the speed loss rate, the method further includes: determining the exercise fatigue state corresponding to the speed loss rate according to a preset lookup table, wherein the preset lookup table includes multiple speed loss rate intervals and the exercise fatigue state corresponding to each speed loss rate interval; determining an adjustment strategy for the training video according to the exercise fatigue state, and adjusting the video content of the training video according to the adjustment strategy.

[0092] It should be noted that the preset reference table can be as shown in Table 1, which may include multiple speed loss rate intervals and the corresponding RPE (Rate of Perceived Exertion) for each speed loss rate interval.

[0093] Table 1

[0094]

[0095] For example, after obtaining the user's speed loss rate, the user's current fatigue state can be determined according to the comparison relationship in Table 1, and intervention instructions for the user's movement can be generated based on the movement fatigue state. At the same time, the adjustment strategy for the video content can be determined based on the movement fatigue state, so that the user can safely follow along with the exercise based on the adjusted video, thereby improving the safety of the user's exercise operation.

[0096] For example, based on the Responsive Physical Exertion (RPE) value of the current group, corresponding exercise strategy prompts can be provided to the user on the wearable device or video playback device, and the parameters of subsequent exercise operations can be adjusted. Furthermore, the content of the follow-up video can be adjusted based on the parameters of the exercise operations.

[0097] For example, decision branch A: overload (RPE≥10), intervention instruction: "Current load exceeds today's tolerance range." Adjustment strategy: forcibly stop the subsequent movements of this set; suggest reducing the weight of the next set of exercises by 10%–15%, or reducing the number of training sessions by 2–3.

[0098] Decision branch B: Excellent condition (RPE≤6), intervention instruction: "Excellent condition, it is recommended to increase the load." Adjustment strategy: Increase the weight by 2.5kg–5kg in the next set, or add 2–3 exercises to this workout.

[0099] Decision branch C: Mid-course fatigue correction (RPE∈7–9), intervention instruction: "Accumulate fatigue, extend rest duration." Adjustment strategy: automatically lock the start button for the next set, extend the rest countdown by 30–60 seconds, or reduce the number of subsequent sets (e.g., reduce 5 sets to 4 sets).

[0100] This embodiment determines the adjustment strategy for the user's training plan based on the fatigue loss rate, thereby determining the adjustment strategy for the follow-up video and achieving the technical effect of improving the matching degree between the follow-up video and the user.

[0101] It should be noted that the video playback method provided in this embodiment can also be used in live streaming scenarios. In a live streaming scenario, the live streaming equipment can collect the current number of movements of multiple users' wearable devices to determine the movement status and fatigue level of each user. The equipment can also perform statistical analysis on the movement status and fatigue level of all users to determine the proportion of users in each fatigue state in the live streaming room. This allows the staff in the live streaming room to adjust the live streaming content based on the statistical data obtained above, thereby improving the matching degree between the live streaming content and the users.

[0102] It should be noted that, to reduce information latency between the live stream and individual users, this technical solution employs an edge computing architecture, where motion feature extraction and data dimensionality reduction are performed locally on the user's wearable device. The wearable device continuously collects 3D acceleration and 3D angular velocity signals output by the inertial measurement unit. After coordinate system alignment, temporal interpolation, and motion cycle recognition, a lightweight deep learning model deployed on the device calculates key motion parameters in real time, such as the number of motion completions, motion execution status, and velocity loss rate. These parameters are then structured and encoded into two types of simplified data: event frames (less than 100 bytes each) and velocity loss features. The user application only needs to upload this simplified data to the cloud server at fixed time intervals via WebSocket (Web Socket Protocol) or MQTT (Message Queuing Telemetry Transport Protocol), without transmitting the original sensor data stream. This design significantly reduces the amount of data uploaded per user, enabling the live stream equipment to maintain stable network load and low-latency communication even in scenarios with tens of thousands of concurrent users. After receiving lightweight data packets from a massive number of terminals, the cloud server aggregates the data in real time through a streaming computing engine, generating macro-level indicators such as the overall completion rate, pace distribution, and fatigue warnings for the live stream, allowing broadcasters to dynamically adjust the live stream pace. This architecture, combining edge computing and cloud aggregation, effectively avoids bandwidth bottlenecks and processing delays caused by high-frequency raw data uploads, achieving a reasonable division of labor between data collection, processing, and analysis. While ensuring data real-time performance, it significantly improves the system's concurrent load capacity and operational reliability, enabling the system to easily support concurrent data uploads from massive numbers of users, thereby improving data transmission efficiency and reducing data transmission latency.

[0103] Furthermore, in a live streaming scenario, after the live streaming device receives the motion status information of each user, it can count the number and percentage of users in the four intervals of "ahead", "synchronized", "lagging", and "stagnant / abandoned", and then determine the adjustment of the live streaming content based on the percentage.

[0104] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0105] Example 2

[0106] This application also provides a device for playing exercise training videos. It should be noted that the device for playing exercise training videos in this application can be used to execute the exercise training video playback method provided in the above embodiments. The following describes the device for playing exercise training videos provided in this application.

[0107] According to an embodiment of this application, an apparatus for implementing the above-described method for playing exercise training videos is also provided. Figure 3 This is a schematic diagram of a video playback device for exercise training provided in Embodiment 2 of this application, as shown below. Figure 3 As shown, the device includes:

[0108] The first acquisition unit 31 is used to acquire the current number of actions at the current moment from the target user's sports wearable device when the target user plays a follow-up video of the target movement. The current number of actions is the cumulative number of times the target user has completed the target movement from the start moment to the current moment.

[0109] The first determining unit 32 is used to determine the preset number of actions in the follow-up video at the current moment, wherein the preset number of actions is used to represent the cumulative number of actions completed in the follow-up video from the start moment to the current moment.

[0110] The second acquisition unit 33 is used to acquire the playback status of the follow-up video at the current moment and to acquire the total number of actions in the follow-up video.

[0111] The modification unit 34 is used to change the playback mode of the follow-up video according to the playback status, the current number of actions, the preset number of actions, and the total number of actions.

[0112] The exercise follow-up video playback device provided in this application embodiment, through the first acquisition unit 31, when detecting that a target user is playing a follow-up video of a target exercise, acquires the current number of actions at the current moment from the target user's sports wearable device, wherein the current number of actions is the cumulative number of actions completed by the target user from the start moment to the current moment; the first determination unit 32 determines the preset number of actions of the follow-up video at the current moment, wherein the preset number of actions is used to represent the cumulative number of actions completed by the follow-up video from the start moment to the current moment; the second acquisition unit 33 acquires the playback status of the follow-up video at the current moment and acquires the total number of actions of the follow-up video; the change unit 34 changes the playback mode of the follow-up video according to the playback status, the current number of actions, the preset number of actions, and the total number of actions. By acquiring the target user's current number of movements from the wearable device, and obtaining the preset number of movements and the total number of movements in the follow-up video, the follow-up video is adjusted based on the relationship between the current number of movements, the preset number of movements, and the total number of movements. This achieves the goal of keeping the playback content of the follow-up video consistent with the user's current movement state, thereby improving the technical effect of matching the user's movement state with the playback content of the follow-up video. This, in turn, improves the user's comfort and satisfaction when performing exercise follow-up operations, and solves the technical problem of low matching degree between the user's movement state and the playback content of the follow-up video in related technologies.

[0113] Optionally, in the exercise follow-up video playback device provided in this application embodiment, the change unit 34 includes: a first judgment module, used to determine whether the current number of movements is equal to the preset number of movements when the playback state is completed; a first processing module, used to keep the playback mode unchanged when the current number of movements is equal to the preset number of movements; a determination module, used to determine a first difference value between the current number of movements and the preset number of movements when the current number of movements is less than the preset number of movements; and a playback module, used to extract the corresponding video segment from the follow-up video according to the first difference value and replay the video segment.

[0114] Optionally, in the exercise follow-up video playback device provided in the embodiments of this application, the change unit 34 includes: a second judgment module, used to determine whether the current number of movements is less than the total number of movements when the playback state is incomplete; a second processing module, used to end the playback of the follow-up video when the current number of movements is greater than or equal to the total number of movements; and a third processing module, used to keep the playback mode unchanged when the current number of movements is less than the total number of movements.

[0115] Optionally, in the exercise training video playback device provided in this application embodiment, before detecting that a target user is playing a target exercise training video, the device further includes: a third acquisition unit, used to acquire the target user's historical exercise records and acquire the N historical exercise records with the smallest time difference from the current time, where N is a positive integer; a second determination unit, used to determine, based on the N historical exercise records, the number of times the target user extends the playback of the historical exercise training video to obtain a first count, and to determine, the number of times the target user ends the historical exercise training video early to obtain a second count; a first playback unit, used to play the training video at a first preset speed when the first count is greater than a preset count threshold, where the first preset speed is less than 1; and a second playback unit, used to play the training video at a second preset speed when the second count is greater than a preset count threshold, where the second preset speed is greater than 1.

[0116] Optionally, in the sports training video playback device provided in this application embodiment, the device further includes: a fourth acquisition unit, used to acquire the action timeline of the target user when performing the target movement from the target user's sports wearable device; a fifth acquisition unit, used to acquire the execution speed of the target user's most recent complete movement from the action timeline, to obtain a first speed value; a sixth acquisition unit, used to acquire the execution speed of the target user's fastest complete movement from the action timeline, to obtain a second speed value; a third determination unit, used to determine the target user's speed loss rate based on the first speed value and the second speed value; and a sending unit, used to send a prompt message to the target user based on the speed loss rate, wherein the prompt message is used to display the target user's sports fatigue state.

[0117] Optionally, in the motion training video playback device provided in the embodiments of this application, the third determining unit includes: a first calculation module, used to calculate the difference between the second speed value and the first speed value to obtain a speed difference; and a second calculation module, used to calculate the ratio of the speed difference to the second speed value, and determine the ratio as the speed loss rate.

[0118] Optionally, in the sports training video playback device provided in this application embodiment, after obtaining the speed loss rate, the device further includes: a fourth determining unit, used to determine the sports fatigue state corresponding to the speed loss rate according to a preset lookup table, wherein the preset lookup table includes multiple speed loss rate intervals and the sports fatigue state corresponding to each speed loss rate interval; and a fifth determining unit, used to determine the adjustment strategy of the training video according to the sports fatigue state, and adjust the video content of the training video according to the adjustment strategy.

[0119] It should be noted that the first acquisition unit 31, the first determination unit 32, the second acquisition unit 33, and the change unit 34 mentioned above correspond to steps S201 to S204 in Embodiment 1. The instances and application scenarios implemented by each of the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware components or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0120] Example 3

[0121] Embodiments of this application may provide an electronic device. Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (Only one is shown) processor 1002, memory 1004, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0122] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0123] Those skilled in the art will understand that Figure 4 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 4 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 4 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 4 The different configurations shown.

[0124] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0125] Example 4

[0126] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the method for playing the exercise training video provided in Embodiment 1.

[0127] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0128] Embodiments of this application also provide a computer program product, which, when executed on a data processing device, is adapted to perform the steps of a method for playing a motion training video.

[0129] Embodiments of this application also provide a computer-readable storage medium, which includes a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to execute the above-described method for playing exercise training videos.

[0130] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0131] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0132] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0133] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0134] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0136] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for playing a motion training video, characterized by, include: When it is detected that a target user is playing a follow-up video of a target movement, the current number of actions at the current moment is obtained from the target user's sports wearable device, wherein the current number of actions is the cumulative number of times the target user has completed the target movement from the start moment to the current moment; Determine the preset number of actions in the follow-up video at the current time, wherein the preset number of actions is used to characterize the cumulative number of actions completed in the follow-up video from the start time to the current time; Obtain the playback status of the follow-up video at the current moment, and obtain the total number of movements in the follow-up video; The playback method of the follow-up video is changed according to the playback status, the current number of actions, the preset number of actions, and the total number of actions.

2. The method of claim 1, wherein, Changing the playback method of the follow-up video based on the playback status, the current number of actions, the preset number of actions, and the total number of actions includes: If the playback status is complete, determine whether the current number of actions is equal to the preset number of actions; If the current number of actions equals the preset number of actions, the playback method remains unchanged; If the current number of actions is less than the preset number of actions, a first difference value is determined between the current number of actions and the preset number of actions; Based on the first difference value, the corresponding video segment is extracted from the training video, and the video segment is replayed.

3. The method of claim 1, wherein, Changing the playback method of the follow-up video based on the playback status, the current number of actions, the preset number of actions, and the total number of actions includes: If the playback status is incomplete, determine whether the current number of actions is less than the total number of actions; If the current number of actions is greater than or equal to the total number of actions, the playback of the follow-up video will end; If the current number of actions is less than the total number of actions, the playback method remains unchanged.

4. The method of claim 1, wherein, Before detecting that a target user is playing a follow-up video of the target movement, the method further includes: Obtain the target user's historical activity records, and obtain the N historical activity records with the smallest time difference from the current time, where N is a positive integer; Based on the N historical exercise records, determine the number of times the target user extends the playback of the historical exercise training video to obtain the first count, and determine the number of times the target user ends the historical exercise training video early to obtain the second count; If the first number of times is greater than a preset number of times threshold, the follow-up video is played at a first preset speed, wherein the first preset speed is less than 1; If the second number of times is greater than the preset number of times threshold, the practice video is played at a second preset speed, wherein the second preset speed is greater than 1.

5. The method of claim 1, wherein, The method further includes: Obtain the action timeline of the target user when performing the target movement from the target user's wearable device; The execution speed of the target user's most recent complete motion action is obtained from the action timeline to obtain a first speed value; The second speed value is obtained by acquiring the fastest execution speed of the target user in a single complete motion action from the action timeline. The speed loss rate of the target user is determined based on the first speed value and the second speed value; A prompt message is sent to the target user based on the speed loss rate, wherein the prompt message is used to display the target user's exercise fatigue status.

6. The method of claim 5, wherein, Determining the speed loss rate of the target user based on the first speed value and the second speed value includes: Calculate the difference between the second speed value and the first speed value to obtain the speed difference; Calculate the ratio of the speed difference to the second speed value, and determine the ratio as the speed loss rate.

7. The method of claim 5, wherein, After obtaining the velocity loss rate, the method further includes: The motion fatigue state corresponding to the speed loss rate is determined according to a preset lookup table, wherein the preset lookup table includes multiple speed loss rate intervals and the motion fatigue state corresponding to each speed loss rate interval. Based on the exercise fatigue state, an adjustment strategy for the follow-up video is determined, and the video content of the follow-up video is adjusted according to the adjustment strategy.

8. A device for playing exercise training videos, characterized in that, include: The first acquisition unit is used to acquire the current number of actions at the current moment from the target user's sports wearable device when the target user plays a follow-up video of the target movement. The current number of actions is the cumulative number of times the target user has completed the target movement from the start moment to the current moment. The first determining unit is used to determine the preset number of actions in the follow-up video at the current time, wherein the preset number of actions is used to characterize the cumulative number of actions completed in the follow-up video from the start time to the current time; The second acquisition unit is used to acquire the playback status of the follow-up video at the current moment and to acquire the total number of actions in the follow-up video. The modification unit is used to change the playback mode of the follow-up video according to the playback status, the current number of actions, the preset number of actions, and the total number of actions.

9. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method for playing the exercise training video as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, executes the method for playing the exercise training video according to any one of claims 1 to 7.

Images