Exercise guidance and display method and device, electronic equipment and storage medium

Abstract

Embodiments of the present disclosure disclose a sports guidance and display method, device, electronic equipment and storage medium, the sports guidance method is applied to a server, the sports guidance method comprises: acquiring a sports data set of a first user in a set first sports place; wherein the first sports place comprises at least one sports equipment, and the sports data set comprises sports data collected based on at least one target sports equipment; and determining a target sports guidance scheme of the first user based on the sports data set.

Description

Technical Field

[0001] This disclosure relates to, but is not limited to, the field of computer technology, and in particular to a motion guidance and display method, apparatus, electronic device, and storage medium. Background Technology

[0002] With social development and improved living standards, people are paying more and more attention to their health, and exercise, as a major way to maintain physical health, has received much attention. However, in public sports venues (such as gyms and stadiums), users can only plan their own exercise, refer to others' suggestions, or customize exercise guidance programs through coaches. This often results in poor guidance and exercise effects that fall short of expectations, failing to adequately meet users' exercise needs. Summary of the Invention

[0003] This disclosure provides at least one motion guidance and display method, device, electronic device, storage medium, and computer program product.

[0004] The technical solution of this disclosure embodiment is implemented as follows:

[0005] This disclosure provides a motion guidance method applied in a server, the motion guidance method comprising:

[0006] Obtain a sports dataset of a first user in a designated first sports venue; wherein the first sports venue includes at least one type of sports equipment, and the sports dataset includes sports data collected based on at least one type of target sports equipment;

[0007] Based on the motion dataset, a target motion guidance scheme for the first user is determined.

[0008] This disclosure provides a display method applied in a terminal, the display method comprising:

[0009] In response to receiving a first query operation from a first user, a first query request is sent to the server; wherein, the first query request is used to request a target motion guidance scheme from the first user;

[0010] In response to receiving the target exercise guidance scheme sent by the server, the target exercise guidance scheme is displayed in a set information interface; wherein, the target exercise guidance scheme is determined by the server based on the exercise dataset of the first user in a set first exercise venue, the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0011] This disclosure provides a motion guidance device applied in a server, the motion guidance device comprising:

[0012] The acquisition module is used to acquire a sports dataset of a first user in a designated first sports venue; wherein the first sports venue includes at least one type of sports equipment, and the sports dataset includes sports data collected based on at least one type of target sports equipment;

[0013] The determination module is used to determine the target motion guidance scheme for the first user based on the motion dataset.

[0014] This disclosure provides a display device for use in a terminal, the display device comprising:

[0015] The sending module is used to send a first query request to the server in response to receiving a first query operation from a first user; wherein the first query request is used to request a target motion guidance scheme from the first user.

[0016] The display module is used to display the target exercise guidance scheme in a set information interface in response to receiving the target exercise guidance scheme sent by the server; wherein the target exercise guidance scheme is determined by the server based on the exercise dataset of the first user in a set first exercise venue, the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0017] This disclosure provides an electronic device including a processor and a memory, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the above-described method.

[0018] This disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0019] This disclosure provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements the above-described method.

[0020] In this embodiment, a target exercise guidance plan for the first user is determined by acquiring a dataset of the user's exercise data in a designated first exercise venue. The first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one target exercise equipment. This approach improves the comprehensiveness of the exercise data compared to acquiring data from only one type of equipment, facilitating accurate assessment of the user's current exercise status and enhancing the accuracy and comprehensiveness of the subsequently determined exercise guidance plan. Furthermore, determining the exercise guidance plan using a dataset of the user's exercise data from multiple types of equipment enables personalized analysis of the exercise data, improving both the accuracy and relevance of the exercise guidance plan, thereby increasing user retention at the exercise venue and better meeting the user's exercise needs.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0023] Figure 1 A schematic diagram illustrating the implementation process of a motion guidance method provided in this embodiment of the present disclosure;

[0024] Figure 2 A schematic diagram illustrating the implementation process of a motion guidance method provided in this embodiment of the present disclosure;

[0025] Figure 3A A schematic diagram illustrating the implementation process of a display method provided in an embodiment of this disclosure;

[0026] Figure 3B A schematic diagram of an information interface provided in an embodiment of this disclosure;

[0027] Figure 4A A schematic diagram illustrating the implementation process of a motion guidance method provided in this embodiment of the present disclosure;

[0028] Figure 4B A schematic diagram illustrating the implementation process of a motion guidance method provided in this embodiment of the present disclosure;

[0029] Figure 5 This is a schematic diagram of the composition structure of a motion guidance device provided in an embodiment of the present disclosure;

[0030] Figure 6This is a schematic diagram of the composition structure of a display device provided in an embodiment of the present disclosure;

[0031] Figure 7 This is a schematic diagram of a hardware entity of an electronic device according to an embodiment of this disclosure. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this disclosure clearer, the disclosure will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this disclosure. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0033] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0034] In the following description, the terms “first, second, third” are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that “first, second, third” may be interchanged in a specific order or sequence where permitted, so that the embodiments of this disclosure described herein can be implemented in an order other than that illustrated or described herein.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing embodiments of this disclosure only and is not intended to be limiting of this disclosure.

[0036] This disclosure provides a motion guidance method that can be applied to a server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. This disclosure does not limit the scope of the method.

[0037] The technical solutions in the embodiments of this disclosure will now be clearly and completely described with reference to the accompanying drawings.

[0038] Figure 1 This is a schematic diagram illustrating the implementation process of a motion guidance method provided in an embodiment of this disclosure, as shown below. Figure 1As shown, the method includes steps S11 to S12, wherein:

[0039] Step S11: Obtain the exercise dataset of the first user in the designated first exercise venue; wherein the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0040] Here, "first user" can refer to a person or a person's pet (e.g., cat, dog).

[0041] The first sports venue can be any suitable place that provides sports equipment, sports fields, and other sports resources. For example, gyms, stadiums, swimming pools, playgrounds, fitness plazas, etc., are not limited to this in the embodiments disclosed herein.

[0042] The quantity of each type of exercise equipment can be at least one. In practice, the types of exercise equipment are related to the sports venue; that is, different sports venues may have the same or different exercise equipment. For example, in a gym, the exercise equipment may include, but is not limited to, at least one of the following: treadmill, elliptical trainer (also known as an air elliptical), strength training equipment, waist trimmer, stationary bike, dance equipment, yoga equipment, etc. Strength training equipment may include, but is not limited to, dumbbells, chest expanders, bench press machines, rowing machines, etc. As another example, in a stadium, the exercise equipment may include, but is not limited to, balls (e.g., badminton, table tennis, basketball, tennis, football, etc.), horizontal bars, high jump equipment, barbells, etc.

[0043] The target exercise equipment is the exercise equipment used by the first user in the exercise venue. Different exercise equipment corresponds to different exercise data. For example, on a treadmill, this exercise data may include, but is not limited to, running duration, running mode, and running distance. Among them, running mode may include, but is not limited to, jogging and running. As another example, on an elliptical machine, this exercise data may include, but is not limited to, stride length and stride distance.

[0044] In some implementations, the exercise data collected by each type of target exercise equipment can be collected by the same piece of equipment or by different pieces of the same type of equipment. For example, a gym may include six treadmills A1 to A6. The exercise data collected by these treadmills could be data collected by treadmill A1, or data collected by treadmill A2 and treadmill A3. In practice, each piece of exercise equipment uploads its collected exercise data to a server. The server categorizes each piece of exercise data according to the type of exercise equipment, user, etc., and stores the categorized exercise data in each user's corresponding account.

[0045] In some implementations, the first sports venue includes at least a first image acquisition device (e.g., a camera, video camera, etc.), which acquires multiple images to obtain the first user's exercise dataset. In practice, the first image acquisition device uploads the acquired images to a server. The server categorizes each image according to the type of sports equipment, user, etc., determines the exercise data of each user based on the categorization results, and synchronously stores it in each user's corresponding account.

[0046] In some embodiments, at least one of the sports equipment is equipped with an information acquisition device; step S11 includes step S111, wherein:

[0047] Step S111: For each target sports equipment, use the information acquisition device of the target sports equipment to acquire the first user's sports data.

[0048] Here, the information acquisition device can be any suitable device capable of collecting information. Examples include sensors (such as cameras, fingerprint sensors, posture sensors, speed sensors, touch sensors, accelerometers, angular velocity sensors, etc.), information collectors, timers, etc. In implementation, the information acquisition device can incorporate various types of sensors.

[0049] In some implementations, the information acquisition device includes at least an image acquisition device (e.g., a camera, video camera, etc.). The user authenticates themselves using this image acquisition device through methods such as facial recognition or scanning. After successful authentication, the motion data collected by the target sports equipment is synchronized to the user's account. In practice, any suitable facial recognition algorithm (e.g., a deep learning facial recognition model) can be used to compare the first user's facial image captured by the camera with multiple facial images stored in a database to authenticate the first user and obtain their account. The facial recognition algorithm may include, but is not limited to, Convolutional Neural Networks (CNN) algorithms, Region-based CNN (R-CNN) algorithms, Fast R-CNN algorithms, and deep learning facial recognition models.

[0050] In this way, by linking facial recognition technology with server-side data, user identity can be bound. Compared with users logging in and authenticating through display devices, this speeds up the matching of user information and solves the inconvenience of using other biometric information (such as fingerprints, voiceprints, etc.) for identity verification.

[0051] In some implementations, the information collection device includes at least a fingerprint sensor. Users authenticate themselves using their fingerprints, and upon successful authentication, the exercise data collected by the target sports equipment is synchronized to the user's account. In practice, a preset fingerprint recognition algorithm can be used to compare the fingerprint information of the first user collected by the fingerprint sensor with multiple fingerprints stored in a database to authenticate the first user and obtain their account.

[0052] In some implementations, the information collection device includes at least one sensor corresponding to the exercise equipment. In practice, each sensor for different exercise equipment can be the same or different. For example, on a treadmill, the information collection device may include, but is not limited to, at least one of a camera, speed sensor, position sensor, and touch sensor. As another example, on an elliptical trainer, the information collection device may include, but is not limited to, at least one of a camera, position sensor, and touch sensor. In this way, on the one hand, the information collection device on the exercise equipment automatically collects the user's exercise data without requiring user intervention or confirmation, reducing operational complexity and improving the user experience; on the other hand, by linking various exercise equipment in the sports venue through a server, its application scenarios are broadened compared to home or personal exercise equipment.

[0053] In some embodiments, each of the information acquisition devices includes an image acquisition device, and the method further includes step S112, wherein:

[0054] Step S112: For each target sports equipment, use the image acquisition device of the target sports equipment to obtain the identity information of the first user, and associate and store the identity information of the first user with the sports data of the first user on the target sports equipment.

[0055] Here, the image acquisition device can be any suitable device capable of image acquisition, such as a camera or video camera. In implementation, the server receives the captured images sent by the image acquisition device, uses a preset facial recognition algorithm to identify the user in the captured image, obtains the user's identity information, and associates and stores the user's movement data on the target exercise equipment in the corresponding account. In implementation, the captured image can be compared with images of multiple users stored in the database to obtain the user's identity information in the captured image.

[0056] By associating users with motion datasets, not only is information security improved, but the speed of subsequent information retrieval is also accelerated.

[0057] Step S12: Based on the motion dataset, determine the target motion guidance scheme for the first user.

[0058] Here, the target exercise guidance plan may include, but is not limited to, at least one of the following: exercise equipment, exercise duration, exercise intensity, exercise frequency, diet, target muscle groups, exercise goals, and exercise data. The exercise goals may include, but are not limited to, at least one of the following: muscle gain, muscle loss, fat reduction, endurance improvement, and coordination improvement. The exercise dataset refers to the exercise data of the first user over a period of time.

[0059] In some implementations, the content of the target motion guidance scheme can be determined based on preset rules. These preset rules may include, but are not limited to, default, custom, random, user preference, user operation, and usage frequency. In implementation, those skilled in the art can independently set preset rules according to actual needs; this disclosure does not impose such limitations.

[0060] For example, the server provides a configuration page through which users can customize the content of the target motion guidance plan.

[0061] For example, several items can be randomly selected from a variety of options to form the content of the target exercise guidance plan. For instance, the target exercise equipment, exercise duration, and diet could be included in the target exercise guidance plan.

[0062] For example, the most frequently used content from various sources can be used as the content of the target movement guidance program.

[0063] For example, the content of a target exercise guidance plan can be determined based on the attribute information of user operations. This attribute information may include, but is not limited to, the type of operation, operation distance, speed, location, duration, and number of repetitions. For instance, when the user operation is a single click, the target exercise equipment, exercise duration, and recipe are selected as the content of the target exercise guidance plan; when the user operation is a double click, the target exercise equipment, exercise body part, exercise frequency, and recipe are selected as the content of the target exercise guidance plan. In implementation, those skilled in the art can independently set the correspondence between the attribute information of user operations and the content of the target exercise guidance plan according to actual needs; this disclosure does not impose such limitations.

[0064] In some implementations, the server also stores at least one motion guidance scheme. During implementation, using this motion dataset, at least one second motion guidance scheme is determined from each motion guidance scheme, and the target motion guidance scheme is determined based on each second motion guidance scheme.

[0065] Here, each exercise guidance scheme is determined based on an exercise dataset of at least one second user in at least one second exercise location. The second user may be the same as or different from the first user. The second exercise location may be the same as or different from the first exercise location.

[0066] The method for determining the second exercise guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's exercise dataset, distance to the first user, exercise location, and frequency of use. The first similarity (and other similarities mentioned later) can be calculated using any suitable method capable of calculating similarity. Examples include Euclidean / Manhattan / Maslow / cosine / Hamming / Chebyshev / Minkowski distance, Pearson Linear Correlation Coefficient (PLCC), and Jaccard similarity coefficient. In implementation, those skilled in the art can choose the method for calculating the first similarity and the method for determining the second exercise guidance scheme according to actual needs; this disclosure does not limit such choices.

[0067] For example, all exercise guidance plans belonging to the same exercise venue as the first user can be treated as a second exercise guidance plan.

[0068] For example, each exercise guidance plan can be sorted according to the number of times it is used, and the top N most used exercise guidance plans can be used as a second exercise guidance plan. Here, N is a positive integer.

[0069] For example, all exercise guidance schemes belonging to the same exercise venue as the first user are respectively regarded as a third exercise guidance scheme. A first similarity is determined between the exercise dataset in each third exercise guidance scheme and the user's exercise dataset. The exercise guidance scheme whose first similarity meets a first preset condition is then regarded as the second exercise guidance scheme. The first similarity preset condition (other similarity preset conditions mentioned later) may include, but is not limited to, similarity not less than a similarity threshold, similarity within a certain range, and similarity close to a certain value. In implementation, those skilled in the art can independently set the similarity threshold, a certain range, and a certain value according to actual needs; this disclosure does not limit such settings.

[0070] For example, multiple exercise guidance schemes with a first similarity within a certain range can be treated as a single second exercise guidance scheme. Alternatively, multiple exercise guidance schemes with a first similarity not less than a similarity threshold can be treated as a single second exercise guidance scheme.

[0071] From each second exercise guidance scheme, the method for determining the target exercise guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's exercise dataset, distance to the first user, exercise location, frequency of use, and user's basic information. The user's basic information may include, but is not limited to, height, weight, age, occupation, hobbies, family situation, and social groups. In implementation, those skilled in the art can choose the method for determining the target exercise guidance scheme according to actual needs; this disclosure does not limit this method.

[0072] For example, based on the first user's interests, each second exercise guidance scheme is screened to obtain at least one fourth exercise guidance scheme, and a target exercise guidance scheme is determined from each of these fourth exercise guidance schemes. In implementation, if there is only one fourth exercise guidance scheme, that fourth exercise guidance scheme is used as the target exercise guidance scheme. If there are at least two fourth exercise guidance schemes, the target exercise guidance scheme is determined from multiple fourth exercise guidance schemes according to a preset first selection rule (other selection rules mentioned later). The first selection rule may include, but is not limited to, randomness, usage frequency, user definition, generation time, etc. For example, sorting by generation time, the fourth exercise guidance scheme with the most recent generation time is used as the target exercise guidance scheme. Another example is using the fourth exercise guidance scheme with the most usage frequency as the target exercise guidance scheme.

[0073] For example, based on the first user's occupation, each second exercise guidance plan is screened to obtain at least one fifth exercise guidance plan, and a target exercise guidance plan is determined from each fifth exercise guidance plan. In implementation, the method for determining the target exercise guidance plan from each fifth exercise guidance plan is similar to the aforementioned method for determining the target exercise guidance plan from each fourth exercise guidance plan; therefore, the method for determining the target exercise guidance plan from each fourth exercise guidance plan can be referred to during implementation.

[0074] In some implementations, the target exercise guidance scheme can be determined based on the first user's status information and the first user's exercise dataset. The first user's status information may include, but is not limited to, the first user's basic information, the first user's physical information, and the first user's exercise information. The first user's physical information may include, but is not limited to, blood pressure, heart rate, and health status. The first user's exercise information may include, but is not limited to, exercise frequency, exercise intensity, and exercise duration. In practice, based on the first user's status information, at least one first exercise guidance scheme is determined from each exercise guidance scheme; based on the first user's exercise dataset, at least one second exercise guidance scheme is determined from each exercise guidance scheme; and the target exercise guidance scheme is determined based on each first exercise guidance scheme and each second exercise guidance scheme.

[0075] The method for determining the first exercise guidance scheme may include, but is not limited to, at least one of the following: second similarity to the state information of the first user, distance to the first user, exercise location, and number of uses. In implementation, those skilled in the art can choose the method for determining the first exercise guidance scheme according to actual needs; this disclosure does not limit such methods.

[0076] For example, all exercise guidance programs that belong to the same profession as the first user can be treated as a separate first exercise guidance program.

[0077] For example, at least one exercise guidance scheme that satisfies the second similarity preset condition with the first user's social group can be designated as a sixth exercise guidance scheme. Each sixth exercise guidance scheme is then ranked according to its usage frequency, and the top N most frequently used sixth exercise guidance schemes are designated as a first exercise guidance scheme. Here, N is a positive integer. Alternatively, multiple exercise guidance schemes with a second similarity within a certain range can be designated as a sixth exercise guidance scheme.

[0078] The method for determining the target exercise guidance scheme from each first exercise guidance scheme and each second exercise guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's exercise dataset, distance to the first user, exercise location, and number of uses. In implementation, those skilled in the art can choose the method for determining the target exercise guidance scheme according to actual needs; this disclosure does not limit this method. In some embodiments, the target exercise guidance scheme may be a single exercise guidance scheme or a scheme resulting from the merging of at least two exercise guidance schemes.

[0079] For example, based on the number of times each exercise guidance scheme is used, each exercise guidance scheme in the set (including each first exercise guidance scheme and each second exercise guidance scheme) is ranked, and the target exercise guidance scheme is determined from at least one exercise guidance scheme with the most uses. In implementation, if there is only one exercise guidance scheme, that exercise guidance scheme is used as the target exercise guidance scheme. If there are at least two exercise guidance schemes, the target exercise guidance scheme is determined from multiple exercise guidance schemes according to a second selection rule.

[0080] For example, based on the first user's occupation, each exercise guidance plan in the set of exercise guidance plans (including each first exercise guidance plan and each second exercise guidance plan) is screened to obtain at least one seventh exercise guidance plan, and a target exercise guidance plan is determined from each seventh exercise guidance plan. In implementation, the method for determining the target exercise guidance plan from each seventh exercise guidance plan is similar to the aforementioned method for determining the target exercise guidance plan from each fourth exercise guidance plan; therefore, the method for determining the target exercise guidance plan from each fourth exercise guidance plan can be referred to in implementation.

[0081] In this embodiment, a target exercise guidance plan for the first user is determined by acquiring a dataset of the user's exercise data in a designated first exercise venue. The first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one target exercise equipment. This approach improves the comprehensiveness of the exercise data compared to acquiring data from only one type of equipment, facilitating accurate assessment of the user's current exercise status and enhancing the accuracy and comprehensiveness of the subsequently determined exercise guidance plan. Furthermore, determining the exercise guidance plan using a dataset of the user's exercise data from multiple types of equipment enables personalized analysis of the exercise data, improving both the accuracy and relevance of the exercise guidance plan, thereby increasing user retention at the exercise venue and better meeting the user's exercise needs.

[0082] In some embodiments, the method further includes step S13, wherein:

[0083] Step S13: Push the target exercise guidance scheme to the first user so that the first user can exercise based on the target exercise guidance scheme.

[0084] Here, the first user can view the target exercise guidance plan through any terminal. The terminal can include, but is not limited to, mobile phones, tablets, wearable devices, in-vehicle devices, smart displays, laptops, personal computers, netbooks, personal digital assistants, etc. During implementation, an information interface can be displayed on the terminal's running applications, browsers, or mini-programs, and the target exercise guidance plan can be displayed on that interface.

[0085] In some implementations, the terminal and the server may be the same electronic device or different electronic devices.

[0086] In this embodiment, the target exercise guidance plan is pushed to the first user, enabling the first user to exercise based on the target exercise guidance plan. This timely delivery of the exercise guidance plan allows the user to view their exercise status at any time and adjust their exercise plan accordingly, thereby improving the user experience.

[0087] In some embodiments, the method further includes step S14, wherein:

[0088] Step S14: In response to receiving a first query request sent by a first user, determine the target exercise guidance scheme for the first user based on the first query request, and send the target exercise guidance scheme to the first user so that the first user can exercise based on the target exercise guidance scheme.

[0089] Here, the first query request is used to request a target motion guidance scheme for the first user. In implementation, the first query request carries at least the identifier of the first user. After receiving the first query request, the server parses the first query request to obtain the identifier of the first user, and obtains the target motion guidance scheme corresponding to the first user based on the identifier of the first user.

[0090] In this embodiment of the disclosure, in response to receiving a first query request from a first user, a target exercise guidance plan for the first user is determined based on the first query request, and the target exercise guidance plan is sent to the first user so that the first user can exercise based on the target exercise guidance plan. In this way, the user can obtain and view the corresponding target exercise guidance plan in real time through the first query request, allowing the user to understand their exercise status and adjust and arrange their exercise accordingly, thereby improving the user experience.

[0091] In some embodiments, the method further includes step S15, wherein:

[0092] Step S15: In response to receiving a second query request sent by the first user, determine the first user's motion dataset based on the second query request, and send the motion dataset to the first user so that the first user can view the motion dataset through the terminal's information interface.

[0093] Here, the second query request is used to request the first user's motion dataset. The number of motion datasets can be at least one. The motion dataset can be a dataset covering a specific time period or a dataset covering all time periods. In implementation, the second query request carries at least the first user's identifier and the query time period. After receiving the second query request, the server parses it to obtain the first user's identifier and, based on the first user's identifier and the query time period, obtains the first user's motion dataset. If the query time period is empty, the motion dataset within a default time period is returned to the terminal. The default time period can be a specific day, all time periods, etc.

[0094] In this embodiment of the disclosure, in response to receiving a second query request sent by a first user, the system determines the first user's exercise dataset based on the second query request and sends the exercise dataset to the first user, enabling the first user to view the exercise dataset through the terminal's information interface. In this way, the user can obtain and view their own exercise dataset in real time through the second query operation, allowing the user to understand their exercise status and results.

[0095] In some embodiments, the method further includes step S16, wherein:

[0096] Step S16: In response to receiving an authentication request sent by the first user, determine the authentication result based on the authentication request, and send the authentication result to the first user so that the first user can view the authentication result through the terminal's information interface.

[0097] Here, the authentication request is used to request the authentication result for the first user. The authentication request carries at least the first user's identity information, which may include, but is not limited to, facial images, voiceprints, and fingerprints. In implementation, after receiving the authentication request, the server parses the request to obtain the first user's identity information, and compares this information with the identity information of multiple users stored in the database to obtain the authentication result.

[0098] The authentication result may include, but is not limited to, authentication passed or authentication failed. In some implementations, if authentication fails, the authentication result may also include the reason for the failure.

[0099] In this embodiment of the disclosure, in response to receiving an authentication request sent by a first user, an authentication result is determined based on the authentication request, and the authentication result is sent to the first user so that the first user can view the authentication result through the terminal's information interface. In this way, the user can obtain the authentication result in real time through the authentication request, which speeds up information matching while also improving information security.

[0100] Figure 2 This is a schematic diagram illustrating the implementation process of a motion guidance method provided in an embodiment of this disclosure, applied in a server, such as... Figure 2 As shown, the method includes steps S21 to S23, wherein:

[0101] Step S21: Obtain the exercise dataset of the first user in the designated first exercise venue; wherein the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0102] Here, step S21 corresponds to step S11 mentioned above. In implementation, the specific implementation method of step S11 mentioned above can be referred to.

[0103] Step S22: Based on the motion dataset, determine the amount of exercise the first user performs on at least one of the target exercise devices.

[0104] Here, exercise volume, also known as "exercise load," refers to the physiological and psychological load and calories consumed by the human body during physical activities. The amount of exercise volume is determined by factors such as the intensity and duration of the exercise, the accuracy of the movements, and the characteristics of the sport.

[0105] In some implementations, for the same duration, the amount of exercise corresponding to different target exercise equipment can be the same or different. In practice, the exercise dataset can be classified according to the type of target exercise equipment to obtain at least one subset of exercise data. The amount of exercise corresponding to each subset of exercise data can then be obtained according to the calculation method corresponding to the target exercise equipment. Different target exercise equipment corresponds to different calculation methods. For example, for a treadmill, the corresponding amount of exercise can be calculated based on data such as running mode, incline, and mileage. As another example, for an elliptical trainer, the corresponding amount of exercise can be calculated based on data such as duration and stride length.

[0106] Step S23: Based on the status information of the first user and the amount of exercise the first user does on at least one of the target exercise equipment, determine the target exercise guidance plan for the first user.

[0107] Here, status information may include, but is not limited to, basic information, physical information, and exercise information. Basic information may include, but is not limited to, height, weight, age, occupation, hobbies, family situation, and social groups. Physical information may include, but is not limited to, blood pressure, heart rate, and health status. Exercise information may include, but is not limited to, exercise frequency, exercise intensity, and exercise duration.

[0108] In some implementations, during the user registration process, the status information of the first user (including at least one of basic information, exercise information, and body information) is entered and synchronously stored in the server. During implementation, the status information of the first user can be obtained from the server.

[0109] In some implementations, the first user's physical information is acquired through various acquisition devices (e.g., sensors, detection devices, etc.) in the first exercise area and simultaneously stored in a server. For example, the first user's blood pressure is measured using a blood pressure monitor. Another example is the first user's heart rate being monitored using a fitness tracker worn by the first user. Yet another example is the acquisition of the first user's exercise information through multiple images captured by an image acquisition device.

[0110] In some implementations, at least one first exercise guidance scheme can be determined from multiple exercise guidance schemes based on the first user's status information; at least one second exercise guidance scheme can be determined from multiple exercise guidance schemes based on the first user's exercise volume on each exercise equipment; and the target exercise guidance scheme can be determined based on each first exercise guidance scheme and each second exercise guidance scheme.

[0111] In this embodiment, a first user's exercise dataset in a designated first exercise venue is acquired. The first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one target exercise equipment. Based on the exercise dataset, the amount of exercise performed by the first user on at least one target exercise equipment is determined. Based on the first user's status information and the amount of exercise performed by the first user on at least one target exercise equipment, a target exercise guidance plan for the first user is determined. In this way, on the one hand, the server links various exercise equipment in the exercise venue, which, compared to exercise equipment suitable for home or personal use, not only improves the comprehensiveness of exercise data but also broadens the application scenarios. On the other hand, by comprehensively determining the exercise guidance plan through the user's status information and the user's exercise dataset, the accuracy and relevance of the exercise guidance plan are improved, thereby increasing the user's exercise effectiveness and user retention rate in the exercise venue, and ultimately better meeting the user's exercise needs.

[0112] In some embodiments, step S22 includes step S221, wherein:

[0113] Step S221: For each target exercise equipment, obtain the equipment parameters of the target exercise equipment, and determine the amount of exercise the first user does on the target exercise equipment based on the equipment parameters and the exercise data collected based on the target exercise equipment.

[0114] Here, different target exercise equipment corresponds to the same or different equipment parameters. For example, for a treadmill, the equipment parameters may include, but are not limited to, running mode, running duration, incline, and mileage; for an elliptical trainer, the equipment parameters may include, but are not limited to, duration, stride length, and stride position.

[0115] During implementation, a first correspondence between various sports equipment and various equipment parameters can be stored in advance. Based on this first correspondence, the corresponding equipment parameters of the sports equipment can be obtained.

[0116] In some embodiments, step S221, "determining the amount of exercise of the first user on the target exercise equipment based on the equipment parameters and the exercise data collected based on the target exercise equipment," includes steps S241 to S242, wherein:

[0117] Step S241: Using a preset correspondence, determine the target calculation method that matches the equipment parameters.

[0118] Here, the correspondence includes a relationship between at least one equipment parameter and at least one calculation method. In implementation, based on this correspondence, a calculation method matching the equipment parameter can be obtained. Different equipment parameters correspond to different calculation methods.

[0119] Step S242: Based on the target calculation method and the motion data collected from the target exercise equipment, determine the amount of exercise the first user does on the target exercise equipment.

[0120] Here, based on this target calculation method, the amount of exercise the first user does on the target exercise equipment can be obtained. For example, for a treadmill, the exercise data collected on the treadmill is converted into the corresponding amount of exercise according to the target calculation method corresponding to the treadmill. For example, the amount of exercise on the treadmill is 200 calories.

[0121] In this embodiment, for each target exercise equipment, the equipment parameters of the target exercise equipment are acquired, and the amount of exercise performed by the first user on the target exercise equipment is determined based on the equipment parameters and the exercise data collected from the target exercise equipment. This improves the accuracy of determining the corresponding amount of exercise by using the equipment parameters, thereby increasing the accuracy of the subsequently determined exercise guidance plan. Furthermore, converting the collected exercise data into exercise volume allows users to more clearly and intuitively understand the current exercise effect, improving the user experience and thus increasing user retention at the exercise venue.

[0122] In some embodiments, step S23 includes steps S231 to S233, wherein:

[0123] Step S231: Based on the status information of the first user, determine at least one first exercise guidance scheme from at least one exercise guidance scheme.

[0124] Here, each exercise guidance scheme is determined based on an exercise dataset of at least one second user in at least one second exercise location. The second user may be the same as or different from the first user. The second exercise location may be the same as or different from the first exercise location.

[0125] The method for determining the first exercise guidance scheme may include, but is not limited to, at least one of the following: second similarity to the first user's status information, distance to the first user, exercise location, and number of uses. In implementation, those skilled in the art can choose the method for determining the first exercise guidance scheme according to actual needs; this disclosure does not limit this method. For example, all exercise guidance schemes belonging to similar social groups as the first user can be considered as a single first exercise guidance scheme. Another example is that all exercise guidance schemes belonging to the same age group as the first user can be considered as a single exercise guidance scheme, and each scheme can be sorted according to the number of uses, with the top X sorted schemes being designated as each first exercise guidance scheme. Here, X is a positive integer.

[0126] Step S232: Based on the amount of exercise the first user performs on at least one of the target exercise equipment, determine at least one second exercise guidance scheme from each of the exercise guidance schemes.

[0127] Here, the method for determining the second exercise guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's exercise dataset, distance to the first user, exercise location, and number of uses. In implementation, those skilled in the art can choose the method for determining the second exercise guidance scheme according to actual needs; this disclosure does not limit such methods.

[0128] For example, each exercise guidance plan can be sorted according to the number of times it is used, and the N most frequently used exercise guidance plans can be used as a second exercise guidance plan. Here, N is a positive integer.

[0129] For example, all exercise guidance schemes belonging to the same exercise venue as the first user are respectively regarded as a third exercise guidance scheme. The first similarity between the exercise dataset in each third exercise guidance scheme and the user's exercise dataset is determined, and the exercise guidance scheme whose first similarity meets the first preset condition is regarded as the second exercise guidance scheme.

[0130] Step S233: Determine the target motion guidance scheme based on at least one first motion guidance scheme and at least one second motion guidance scheme.

[0131] Here, the method for determining the target motion guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's motion dataset, distance to the first user, exercise location, and number of uses. In implementation, those skilled in the art can choose the method for determining the target motion guidance scheme according to actual needs; this disclosure does not limit such methods.

[0132] For example, based on the number of times each exercise guidance scheme is used, each exercise guidance scheme in the set (including each first exercise guidance scheme and each second exercise guidance scheme) is ranked, and the target exercise guidance scheme is determined from at least one exercise guidance scheme with the most uses. In implementation, if there is only one exercise guidance scheme, that exercise guidance scheme is used as the target exercise guidance scheme. If there are at least two exercise guidance schemes, the target exercise guidance scheme is determined from multiple exercise guidance schemes according to a second selection rule.

[0133] In some implementations, the target motion guidance scheme can be a single motion guidance scheme or a scheme that combines at least two motion guidance schemes.

[0134] In some embodiments, step S233 includes steps S2331 to S2333, wherein:

[0135] Step S2331: Based on the first target information, determine the first target motion guidance scheme from each of the first motion guidance schemes.

[0136] Here, the first target information may include, but is not limited to, at least one of the following: the number of times each first exercise guidance program is used, the exercise location of each first exercise guidance program, and the status information of the first user.

[0137] The method for determining the first target exercise guidance scheme may include, but is not limited to, at least one of the following: first similarity to the first user's exercise volume, second similarity to the first user's status information, distance to the first user, exercise location, number of uses, randomness, and user-defined methods. In implementation, those skilled in the art can choose the method for determining the first target exercise guidance scheme according to actual needs; this disclosure does not limit this method. For example, each first exercise guidance scheme can be sorted from most to least used, and the first first exercise guidance scheme can be selected as the first target exercise guidance scheme. Another example is that a first exercise guidance scheme can be randomly selected from all the first exercise guidance schemes as the first target exercise guidance scheme. Yet another example is that a first exercise guidance scheme belonging to the same age group as the first user and belonging to the same exercise location as the first user can be selected as the first target exercise guidance scheme.

[0138] Step S2332: Based on the second target information, determine the second target movement guidance scheme from each of the second movement guidance schemes.

[0139] Here, the second target information may include, but is not limited to, at least one of the following: the number of times each second exercise guidance program is used, the exercise location of each second exercise guidance program, the status information of the first user, and the amount of exercise the first user performs on at least one target exercise equipment.

[0140] The method for determining the second target motion guidance scheme is similar to the method for determining the first target motion guidance scheme in step S2331. When implementing it, you can refer to the specific implementation method in step S2331.

[0141] Step S2333: Determine the target motion guidance scheme based on the first target motion guidance scheme and the second target motion guidance scheme.

[0142] Here, the target exercise guidance plan can be a single exercise guidance plan, or it can be a combination of at least two exercise guidance plans. For example, the target exercise guidance plan can be a first target exercise guidance plan or a second target exercise guidance plan. Another example is that the target exercise guidance plan is a combination of the first target exercise guidance plan and the second target exercise guidance plan.

[0143] In some embodiments, step S2333 includes step S251 and / or step S252, wherein:

[0144] Step S251: Use the first target motion guidance scheme or the second target motion guidance scheme as the target motion guidance scheme.

[0145] Here, a third target exercise guidance scheme can be determined from the first target exercise guidance scheme and the second target exercise guidance scheme based on the third target information, and this third target exercise guidance scheme can be used as the target exercise guidance scheme. The third target information may include, but is not limited to, at least one of the following: the number of times the first exercise guidance scheme is used, the number of times the second exercise guidance scheme is used, the exercise location of the first exercise guidance scheme, the exercise location of the second exercise guidance scheme, and the status information of the first user.

[0146] The methods for determining the third target exercise guidance scheme may include, but are not limited to, at least one of the following: first similarity to the first user's exercise volume, second similarity to the first user's status information, distance to the first user, exercise location, number of uses, randomness, and user-defined methods. In implementation, those skilled in the art can choose the method for determining the third target exercise guidance scheme according to actual needs; this disclosure does not limit such methods.

[0147] For example, the first or second target exercise guidance scheme may be randomly selected as the third target exercise guidance scheme.

[0148] For example, if the number of times the first target exercise guidance plan is used is greater than the number of times the second target exercise guidance plan is used, the first target exercise guidance plan will be used as the third target exercise guidance plan; if the number of times the first target exercise guidance plan is used is less than the number of times the second target exercise guidance plan is used, the second target exercise guidance plan will be used as the third target exercise guidance plan; if the number of times the first target exercise guidance plan is used is the same as the number of times the second target exercise guidance plan is used, either the first target exercise guidance plan or the second target exercise guidance plan will be randomly selected as the third target exercise guidance plan.

[0149] Step S252: Combine the first target motion guidance scheme and the second target motion guidance scheme to obtain the target motion guidance scheme.

[0150] Here, the merging methods can include, but are not limited to, overlaying, replacement, etc.

[0151] For example, if the first target exercise guidance plan includes exercise duration but the second target exercise guidance plan does not include exercise duration, then the exercise duration is added to the target exercise guidance plan.

[0152] For example, if both the first and second target motion guidance schemes include motion duration, the target motion duration in the target motion guidance scheme can be determined based on these two motion durations. The methods for determining the target motion duration may include, but are not limited to, a single motion duration (i.e., the larger or smaller of the two motion durations), the mean / mean square deviation of the two motion durations, or the mean / mean square deviation after weighting the two motion durations. In implementation, those skilled in the art can choose the method for determining the target motion duration according to actual needs; this disclosure does not limit this method. For example, the mean of the two motion durations can be used as the target motion duration.

[0153] In some implementations, other elements of the target motion guidance scheme (e.g., motion frequency, motion intensity, etc.) can be determined by referring to the aforementioned implementation of determining the target motion duration in the target motion guidance scheme.

[0154] In this embodiment, at least one first exercise guidance scheme is determined from at least one exercise guidance scheme based on the first user's status information; at least one second exercise guidance scheme is determined from each of the exercise guidance schemes based on the first user's exercise volume on at least one of the target exercise equipment; and the target exercise guidance scheme is determined based on at least one first exercise guidance scheme and at least one second exercise guidance scheme. This approach, by determining the target exercise guidance scheme from both the user's status information and exercise volume, improves the accuracy, relevance, and scientific rigor of the target exercise guidance scheme.

[0155] Based on the above embodiments, this disclosure also provides a display method applied to a terminal. The terminal can be various types of terminals such as laptops, tablets, desktop computers, set-top boxes, and mobile devices (e.g., mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable gaming devices), or it can be implemented as a server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0156] Figure 3A This is a schematic diagram illustrating the implementation flow of a display method provided in an embodiment of this disclosure, as shown below. Figure 3A As shown, the method includes steps S31 to S32, wherein:

[0157] Step S31: In response to receiving the first query operation from the first user, send a first query request to the server.

[0158] Here, the first query operation can be any suitable query operation, and this embodiment of the disclosure is not limited to it. For example, it can be an operation that the first user inputs or selects in a preset information interface, such as a query gesture or a query button in the information interface. The information interface can be an interface displayed on the terminal for viewing the user's exercise information, which may include, but is not limited to, exercise datasets and exercise guidance plans. Another example is the voice output by the first user.

[0159] The first query request is used to request a target motion guidance scheme for the first user. In practice, the first query request carries at least the identifier of the first user. After receiving the first query request, the server parses the first query request to obtain the identifier of the first user and sends the target motion guidance scheme corresponding to the first user to the terminal.

[0160] In some implementations, the server and the terminal can be the same electronic device or different electronic devices.

[0161] Step S32: In response to receiving the target exercise guidance scheme sent by the server, the target exercise guidance scheme is displayed in the set information interface; wherein, the target exercise guidance scheme is determined by the server based on the exercise dataset of the first user in the set first exercise venue, the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0162] Here, the target motion guidance plan can be displayed in any suitable way, such as a graph or table. During implementation, the target motion guidance plan can be displayed in the information interface or as a pop-up window on the information interface.

[0163] In this embodiment, in response to receiving a first query operation from a first user, a first query request is sent to the server; in response to receiving the target exercise guidance plan sent by the server, the target exercise guidance plan is displayed in a designated information interface; wherein, the target exercise guidance plan is determined by the server based on an exercise dataset of the first user in a designated first exercise location, the first exercise location including at least one type of exercise equipment, and the exercise dataset including exercise data collected based on at least one type of target exercise equipment. In this way, the user can obtain and view the corresponding target exercise guidance plan in real time through a query operation, allowing the user to understand their exercise status and adjust and arrange their exercise accordingly, thereby improving the user experience.

[0164] In some embodiments, the method further includes steps S33 to S34, wherein:

[0165] Step S33: In response to receiving the second query operation from the first user, send a second query request to the server.

[0166] Here, the second query operation can be any suitable query operation, and this embodiment of the disclosure is not limited to it. For example, it is an operation that the first user inputs or selects in a preset information interface, such as a query gesture, a query button in the information interface, etc. Another example is the voice output by the first user.

[0167] The second query request is used to request the first user's motion dataset. The number of motion datasets can be at least one. The motion dataset can be a dataset covering a specific time period or a dataset covering all time periods. In implementation, the second query request must at least include the first user's identifier and the query time period. After receiving the second query request, the server parses it to obtain the first user's identifier and sends the corresponding motion dataset to the terminal. If the query time period is empty, the motion dataset within a default time period is returned to the terminal. The default time period can be a specific day, all time periods, etc.

[0168] Step S34: In response to receiving the motion dataset sent by the server, display the motion dataset in the information interface according to the display method.

[0169] Here, the display method can be any suitable display method, such as graphs, tables, etc.

[0170] In some implementations, the display method can be based on preset rules. These preset rules may include, but are not limited to, default, custom, random, user preference, user operation, usage frequency, and terminal configuration. In implementation, those skilled in the art can independently set preset rules according to actual needs; this disclosure does not impose such limitations.

[0171] For example, the display mode can be selected through the display mode control in the information interface.

[0172] For example, the display method can be selected based on the attribute information of the user's operation. This attribute information may include, but is not limited to, the type of operation, operation distance, speed, position, duration, and number of times. For instance, if the user's operation is a swipe and the swipe distance falls within a first distance range, a graph will be used as the display method; if the user's operation is a swipe and the swipe distance falls within a second distance range, a table will be used as the display method. The first and second distance ranges are different ranges.

[0173] For example, if the terminal's display state is a preset state, a table will be used as the display mode; otherwise, a graph will be used. The terminal's display state may include, but is not limited to, landscape mode and portrait mode.

[0174] Figure 3B This is a schematic diagram of an information interface provided in an embodiment of the present disclosure, such as... Figure 3B As shown, the information interface 300 includes a display area 310, a first query control 311, and a second query control 312. The display area 310 is used to display at least the user's basic information. The first query control 311 is used to obtain the user's target exercise guidance plan and display it in the display area 310 in the form of graphs, tables, etc. The second query control 312 is used to obtain the user's exercise dataset and display it in the display area 310 in the form of graphs, tables, etc.

[0175] In this embodiment, in response to receiving a second query operation from the first user, a second query request is sent to the server; in response to receiving the exercise dataset sent by the server, the exercise dataset is displayed in the information interface according to a display method. Thus, on the one hand, the user can obtain and view their own exercise dataset in real time through the second query operation, allowing the user to understand their exercise status and results; on the other hand, displaying the exercise dataset through a specific display method improves the display effect of the exercise data.

[0176] In some embodiments, the method further includes steps S35 to S36, wherein:

[0177] Step S35: In response to receiving the authentication operation from the first user, send an authentication request to the server.

[0178] Here, the authentication operation can be any suitable authentication operation, and this embodiment of the disclosure is not limited to it. For example, the operation entered or selected by the first user in a preset information interface, such as authentication gestures, authentication buttons in the information interface, etc. Another example is that the first user performs authentication operations through the terminal's image acquisition device using methods such as face scanning, fingerprint, voiceprint, or SMS verification. Yet another example is that the first user performs authentication operations through the information acquisition device on sports equipment using methods such as face scanning, fingerprint, or voiceprint.

[0179] An authentication request is used to request the authentication result of the first user's identity verification. The authentication result may include, but is not limited to, authentication successful or authentication failed. In some implementations, if authentication fails, the authentication result may also include the reason for the failure.

[0180] Step S36: In response to receiving the authentication result sent by the server, display the authentication result in the information interface.

[0181] Here, if the authentication result indicates that the authentication is successful, the corresponding information can be obtained through query operations (first query operation and / or second query operation).

[0182] In this embodiment, in response to receiving an authentication operation from the first user, an authentication request is sent to the server; in response to receiving the authentication result sent by the server, the authentication result is displayed in the information interface. Thus, by identifying the user through an authentication operation, the speed of information matching is accelerated while also improving information security.

[0183] The following describes the application of the exercise guidance method provided in this disclosure in a real-world scenario, using a gym as an example.

[0184] This disclosure provides an exercise guidance method that can be applied to a server. In implementation, various sensors on at least one target fitness device (corresponding to the aforementioned target exercise equipment) collect a user's exercise data set, which is then uploaded to a server. The server performs statistical analysis on the exercise data set to obtain the target exercise guidance plan, which is then pushed to the user's terminal so that the user can view the plan. This approach improves the comprehensiveness of exercise data compared to data from only one piece of equipment, by acquiring exercise data from multiple fitness devices in a gym. This allows for accurate assessment of the user's current exercise status, thereby enhancing the accuracy and comprehensiveness of the subsequently determined exercise guidance plan. Furthermore, determining the exercise guidance plan using data from multiple fitness devices enables personalized analysis of the exercise data, improving both the accuracy and relevance of the guidance plan, ultimately increasing user retention in the fitness environment and better meeting user exercise needs.

[0185] Figure 4A This is a schematic diagram illustrating the implementation process of a motion guidance method provided in an embodiment of this disclosure, as shown below. Figure 4A As shown, the method includes steps S401 to S405, wherein:

[0186] Step S401: Acquire images of users captured by at least one target fitness device;

[0187] Step S402: Using a deep learning face recognition algorithm, identify each image to obtain the user's account;

[0188] Here, the server can pre-store the identification information and accounts of different users. The identification information may include, but is not limited to, ID numbers and identity information. During implementation, a facial recognition algorithm is used to identify each image, obtaining the user's identification information and corresponding account, so that the user's motion dataset can be synchronously stored under that account. In this way, deep learning-based facial recognition algorithms can quickly match user information, solving the problem of inconvenience in verifying identity using other biometric information.

[0189] Step S403: Obtain the exercise data collected by at least one target fitness equipment, and perform statistics and classification on each exercise data to obtain the user's exercise volume on each type of target fitness equipment, and synchronously store each exercise volume in the user's account.

[0190] Here, sensors and other components on the target fitness equipment determine detailed information about the user's equipment usage, such as running time, running mode, and number of laps on a treadmill. Another example is stride length and stride distance on an elliptical trainer.

[0191] During implementation, each exercise data point can be converted into a corresponding exercise volume according to the calculation method corresponding to the parameters of each target fitness equipment. For example, it can be converted into calories burned. For instance, how many kilometers and how many calories are equivalent to running for 2 hours using an elliptical machine? This allows users to more clearly and directly understand their current exercise results.

[0192] Step S404: Based on the user's status information and the amount of exercise the user does on each type of target fitness equipment, determine the user's fitness plan (corresponding to the aforementioned target exercise guidance plan), and synchronously store the fitness plan in the user's account;

[0193] Here, status information can include, but is not limited to, basic information, physical information, and exercise information. Basic information can include, but is not limited to, height, weight, age, occupation, hobbies, family situation, and social groups. Physical information can include, but is not limited to, blood pressure, heart rate, and health status. Exercise information can include, but is not limited to, exercise frequency, exercise intensity, and exercise duration. For example, by analyzing each exercise session based on the user's height, weight, and age, and combining this with factors such as workout frequency and duration, a more scientific fitness plan can be provided.

[0194] Fitness plans can include, but are not limited to, the selection of fitness equipment, exercise time, exercise intensity, exercise frequency, and diet.

[0195] Step S405: Push the user's fitness plan to the user's terminal so that the user can exercise according to the fitness plan.

[0196] Here, fitness plans are sent to users through gym apps, gym mini-programs, and other similar means.

[0197] Figure 4B This is a schematic diagram illustrating the implementation process of a motion guidance method provided in an embodiment of this disclosure, as shown below. Figure 4B As shown, the method includes steps S411 to S418, wherein:

[0198] Step S411: Acquire images of users captured by at least one target fitness device;

[0199] Step S412: Using a deep learning face recognition algorithm, identify each image to obtain the user's account;

[0200] Step S413: Obtain the exercise data collected by at least one target fitness equipment, and perform statistics and classification on each exercise data to obtain the user's exercise volume on each type of target fitness equipment, and synchronously store each exercise volume in the user's account.

[0201] Step S414: Based on the user's status information and the amount of exercise the user does on each type of target fitness equipment, determine the user's fitness plan and synchronously store each amount of exercise in the user's account.

[0202] Step S415: In response to receiving the first query request from the terminal, obtain the user's identification information carried in the first query request;

[0203] Step S416: Based on the user's identification information, obtain the user's fitness plan and send the fitness plan to the terminal so that the user can view the fitness plan through the terminal's information interface.

[0204] Step S417: In response to receiving the second query request from the terminal, obtain the user's identification information carried in the second query request;

[0205] Step S418: Based on the user's identification information, obtain the user's motion dataset within the default time period, and send the motion dataset to the terminal so that the user can view the motion dataset through the terminal's information interface.

[0206] Based on the above embodiments, this disclosure provides a motion guidance device. Figure 5 An exercise guidance device provided in this disclosure embodiment, such as Figure 5 As shown, the device 50 includes an acquisition module 51 and a determination module 52, wherein:

[0207] The acquisition module 51 is used to acquire the exercise dataset of the first user in a set first exercise venue; wherein, the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment;

[0208] The determining module 52 is used to determine the target exercise guidance scheme for the first user based on the exercise dataset.

[0209] In some implementations, the determining module 52 is further configured to: determine the amount of exercise performed by the first user on at least one of the target exercise equipment based on the exercise dataset; and determine the target exercise guidance scheme based on the status information of the first user and the amount of exercise performed by the first user on at least one of the target exercise equipment.

[0210] In some embodiments, the determining module 52 is further configured to: for each target exercise device, acquire the device parameters of the target exercise device, and determine the amount of exercise of the first user on the target exercise device based on the device parameters and the exercise data collected based on the target exercise device.

[0211] In some embodiments, the determining module 52 is further configured to: determine a target calculation method that matches the equipment parameters using a preset correspondence; wherein the correspondence includes a correspondence between at least one equipment parameter and at least one calculation method; and determine the amount of exercise performed by the first user on the target sports equipment based on the target calculation method and the exercise data collected from the target sports equipment.

[0212] In some embodiments, the determining module 52 is further configured to: determine at least one first exercise guidance scheme from at least one exercise guidance scheme based on the state information of the first user; wherein each exercise guidance scheme is determined based on a dataset of at least one second user in at least one second exercise venue; determine at least one second exercise guidance scheme from each exercise guidance scheme based on the amount of exercise performed by the first user on at least one of the target exercise equipment; and determine the target exercise guidance scheme based on at least one first exercise guidance scheme and at least one second exercise guidance scheme.

[0213] In some embodiments, the determining module 52 is further configured to: determine a first target exercise guidance scheme from each of the first exercise guidance schemes based on first target information; wherein the first target information includes at least one of the following: the exercise location of each of the first exercise guidance schemes, and the status information of the first user; determine a second target exercise guidance scheme from each of the second exercise guidance schemes based on second target information; wherein the second target information includes at least one of the following: the exercise location of each of the second exercise guidance schemes, and the amount of exercise performed by the first user on at least one of the target exercise equipment; and determine the target exercise guidance scheme based on the first target exercise guidance scheme and the second target exercise guidance scheme.

[0214] In some embodiments, the determining module 52 is further configured to: select either the first target motion guidance scheme or the second target motion guidance scheme as the target motion guidance scheme; and / or, merge the first target motion guidance scheme and the second target motion guidance scheme to obtain the target motion guidance scheme.

[0215] In some embodiments, at least one of the sports equipment is equipped with an information acquisition device; the acquisition module 51 is further configured to: acquire the exercise data of the first user using the information acquisition device of the target sports equipment for each target sports equipment.

[0216] In some embodiments, each of the information acquisition devices includes an image acquisition device, and the device further includes a storage module, which is used to: for each target sports equipment, use the image acquisition device of the target sports equipment to acquire the identity information of a first user, and associate and store the identity information of the first user with the sports data of the first user on the target sports equipment.

[0217] In some embodiments, the device further includes a push module, which is configured to: push the target exercise guidance scheme to the first user so that the first user exercises based on the target exercise guidance scheme.

[0218] The description of the above embodiments of the exercise guidance device is similar to that of the above embodiments of the exercise guidance method, and has similar beneficial effects. For technical details not disclosed in the embodiments of the exercise guidance device of this disclosure, please refer to the description of the embodiments of the exercise guidance method of this disclosure for understanding.

[0219] Based on the above embodiments, this disclosure provides a display device. Figure 6 A display device provided in the embodiments of this disclosure, such as Figure 6As shown, the device 60 includes a transmitting module 61 and a display module 62, wherein:

[0220] The sending module 61 is used to send a first query request to the server in response to receiving a first query operation from a first user; wherein the first query request is used to request a target motion guidance scheme from the first user.

[0221] The display module 62 is configured to display the target exercise guidance scheme in a set information interface in response to receiving the target exercise guidance scheme sent by the server; wherein the target exercise guidance scheme is determined by the server based on the exercise dataset of the first user in a set first exercise venue, the first exercise venue includes at least one type of exercise equipment, and the exercise dataset includes exercise data collected based on at least one type of target exercise equipment.

[0222] In some embodiments, the sending module 61 is further configured to: in response to receiving a second query operation from the first user, send a second query request to the server; wherein the second query request is used to request the first user's motion dataset; the display module 62 is further configured to: in response to receiving the motion dataset sent by the server, display the motion dataset in the information interface according to a display method.

[0223] In some embodiments, the sending module 61 is further configured to: in response to receiving the authentication operation of the first user, send an authentication request to the server; wherein the authentication request is used to request the authentication result for authenticating the identity of the first user; the display module 62 is further configured to: in response to receiving the authentication result sent by the server, display the authentication result in the information interface.

[0224] The description of the display device embodiments above is similar to the description of the display method embodiments above, and has similar beneficial effects. For technical details not disclosed in the display device embodiments of this disclosure, please refer to the description of the display method embodiments of this disclosure for understanding.

[0225] If the technical solution disclosed herein involves personal information, the product using this technical solution has clearly informed the user of the personal information processing rules and obtained the user's voluntary consent before processing the personal information. If the technical solution disclosed herein involves sensitive personal information, the product using this technical solution has obtained the user's separate consent before processing the sensitive personal information, and also meets the requirement of "express consent". For example, at personal information collection devices such as cameras, clear and prominent signs are set up to inform users that they have entered the scope of personal information collection and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed that they have agreed to the collection of their personal information; or on the personal information processing device, with clear signs / information informing users of the personal information processing rules, authorization is obtained from the individual through pop-up information or by asking the individual to upload their personal information; wherein, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the types of personal information processed.

[0226] It should be noted that, in the embodiments of this disclosure, if the above methods are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this disclosure, or the parts that contribute to related technologies, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this disclosure are not limited to any specific hardware and software combination.

[0227] This disclosure provides an electronic device, including a memory and a processor. The memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the above-described method.

[0228] This disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method. The computer-readable storage medium can be transient or non-transient.

[0229] This disclosure provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above-described method. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied as a computer storage medium; in another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0230] It should be noted that, Figure 7 This is a schematic diagram of a hardware entity of an electronic device in an embodiment of this disclosure, such as... Figure 7 As shown, the hardware entity of the electronic device 700 includes: a processor 701, a communication interface 702, and a memory 703, wherein:

[0231] The processor 701 typically controls the overall operation of the electronic device 700.

[0232] Communication interface 702 enables electronic devices to communicate with other terminals or servers via a network.

[0233] The memory 703 is configured to store instructions and applications executable by the processor 701, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data, and video communication data) in the processor 701 and various modules in the electronic device 700. It can be implemented using flash memory or random access memory (RAM). Data transfer between the processor 701, the communication interface 702, and the memory 703 can be performed via bus 704.

[0234] It should be noted that the descriptions of the storage medium and device embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this disclosure, please refer to the descriptions of the method embodiments of this disclosure for understanding.

[0235] It should be understood that the phrase "an embodiment" or "one embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this disclosure. Therefore, "in one embodiment" or "one embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this disclosure, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure. The sequence numbers of the above-described embodiments are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0236] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0237] In the several embodiments provided in this disclosure, it should be understood that the disclosed devices and methods 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, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0238] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0239] In addition, each functional unit in the embodiments of this disclosure can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0240] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0241] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, or the part that contributes to related technologies, 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 an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, magnetic disks, or optical disks.

[0242] The above description is merely an embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for guiding exercise, characterized in that, When applied to a server, the method includes: The system acquires an image of a first user captured by at least one target sports equipment in a first sports venue; the at least one target sports equipment is equipped with an information acquisition device; each of the information acquisition devices includes an image acquisition device. Using a deep learning-based face recognition algorithm, each of the images is identified to obtain the account of the first user; Acquire the exercise data collected by the first user based on at least one target exercise device; The exercise data is synchronously stored in the first user's account; Based on the exercise data, the amount of exercise performed by the first user on at least one of the target exercise devices is determined; Based on the status information of the first user, at least one first exercise guidance scheme is determined from at least one exercise guidance scheme; wherein each exercise guidance scheme is determined based on exercise data collected by at least one second user in at least one second exercise venue based on at least one target exercise equipment; Based on the amount of exercise the first user performs on at least one of the target exercise equipment, at least one second exercise guidance scheme is determined from each of the exercise guidance schemes; A target exercise guidance scheme is determined based on at least one first exercise guidance scheme and at least one second exercise guidance scheme.

2. The method according to claim 1, characterized in that, Determining the amount of exercise performed by the first user on at least one of the target exercise devices based on the exercise data includes: For each target exercise device, the device parameters are obtained, and based on the device parameters and the exercise data collected from the target exercise device, the amount of exercise performed by the first user on the target exercise device is determined.

3. The method according to claim 2, characterized in that, Determining the amount of exercise the first user performs on the target exercise equipment based on the equipment parameters and the exercise data collected from the target exercise equipment includes: Using a preset correspondence, a target calculation method matching the equipment parameters is determined; wherein the correspondence includes a correspondence between at least one equipment parameter and at least one calculation method. Based on the target calculation method and the motion data collected from the target exercise equipment, the amount of exercise the first user does on the target exercise equipment is determined.

4. The method according to claim 1, characterized in that, The step of determining a target exercise guidance scheme based on at least one first exercise guidance scheme and at least one second exercise guidance scheme includes: Based on the first target information, a first target exercise guidance scheme is determined from each of the first exercise guidance schemes; wherein, the first target information includes at least one of the following: the exercise location of each first exercise guidance scheme, and the status information of the first user; Based on the second target information, a second target exercise guidance scheme is determined from each of the second exercise guidance schemes; wherein the second target information includes at least one of the following: the exercise location of each second exercise guidance scheme, and the amount of exercise performed by the first user on at least one of the target exercise equipment; The target motion guidance scheme is determined based on the first target motion guidance scheme and the second target motion guidance scheme.

5. The method according to claim 4, characterized in that, The determination of the target motion guidance scheme based on the first target motion guidance scheme and the second target motion guidance scheme includes at least one of the following: The first target motion guidance scheme or the second target motion guidance scheme shall be used as the target motion guidance scheme; The first target motion guidance scheme and the second target motion guidance scheme are combined to obtain the target motion guidance scheme.

6. The method according to any one of claims 2 to 4, characterized in that, The method further includes: The target exercise guidance plan is pushed to the first user so that the first user can exercise based on the target exercise guidance plan.

7. A display method, characterized in that, When applied in a terminal, the method includes: In response to receiving a first query operation from a first user, a first query request is sent to the server; wherein, the first query request is used to request a target motion guidance scheme from the first user; In response to receiving the target exercise guidance scheme sent by the server, the target exercise guidance scheme is displayed in a set information interface; wherein, the target exercise guidance scheme is determined by the server based on at least one first exercise guidance scheme and at least one second exercise guidance scheme, the first exercise guidance scheme is determined from at least one exercise guidance scheme based on the first user's status information, the second exercise guidance scheme is determined from at least one exercise guidance scheme based on the first user's exercise volume on at least one target exercise equipment, each exercise guidance scheme is determined based on exercise data collected by at least one second user in at least one second exercise location based on at least one target exercise equipment, the first user's exercise volume on at least one target exercise equipment is determined based on the exercise data, the exercise data is synchronously stored in the first user's account, the first user's account is obtained by recognizing the first user's image collected by at least one target exercise equipment in the first exercise location using a deep learning face recognition algorithm, and the at least one target exercise equipment is equipped with an information collection device; each information collection device includes an image collection device.

8. The method according to claim 7, characterized in that, The method further includes: In response to receiving a second query operation from the first user, a second query request is sent to the server; wherein the second query request is used to request the first user's exercise dataset; the exercise dataset includes exercise data collected based on at least one target exercise device; In response to receiving the motion dataset sent by the server, the motion dataset is displayed in the information interface according to the display method.

9. The method according to claim 7 or 8, characterized in that, The method further includes: In response to receiving the authentication operation from the first user, an authentication request is sent to the server; wherein the authentication request is used to request the authentication result of the first user's identity authentication. In response to receiving the authentication result sent by the server, the authentication result is displayed in the information interface.

10. A motion guidance device, characterized in that, The device, used in a server, includes: The acquisition module is used to acquire images of a first user collected by at least one target sports equipment in a first sports venue; the at least one target sports equipment is equipped with an information acquisition device; each information acquisition device includes an image acquisition device; a deep learning face recognition algorithm is used to recognize each image to obtain the account of the first user; the exercise data of the first user collected based on at least one target sports equipment is acquired; and the exercise data is synchronously stored in the account of the first user. A determining module is configured to: determine the amount of exercise performed by the first user on at least one of the target exercise equipment based on the exercise data; determine at least one first exercise guidance scheme from at least one exercise guidance scheme based on the first user's status information; wherein each exercise guidance scheme is determined based on exercise data collected by at least one second user in at least one second exercise location based on at least one target exercise equipment; determine at least one second exercise guidance scheme from each of the exercise guidance schemes based on the amount of exercise performed by the first user on at least one of the target exercise equipment; and determine a target exercise guidance scheme based on at least one first exercise guidance scheme and at least one second exercise guidance scheme.

11. A display device, characterized in that, The device, used in a terminal, includes: The sending module is used to send a first query request to the server in response to receiving a first query operation from a first user; wherein the first query request is used to request a target motion guidance scheme from the first user. A display module is configured to display the target exercise guidance scheme in a set information interface in response to receiving the target exercise guidance scheme sent by the server. The target exercise guidance scheme is determined by the server based on at least one first exercise guidance scheme and at least one second exercise guidance scheme. The first exercise guidance scheme is determined from at least one exercise guidance scheme based on the first user's status information. The second exercise guidance scheme is determined from at least one exercise guidance scheme based on the first user's exercise volume on at least one target exercise equipment. Each exercise guidance scheme is determined based on exercise data collected by at least one second user in at least one second exercise location using at least one target exercise equipment. The first user's exercise volume on at least one target exercise equipment is determined based on the exercise data. The exercise data is synchronously stored in the first user's account. The first user's account is obtained by recognizing the first user's image collected by at least one target exercise equipment in a first exercise location using a deep learning facial recognition algorithm. Each target exercise equipment is equipped with an information acquisition device; each information acquisition device includes an image acquisition device.

12. An electronic device comprising a processor and a memory, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 9.

13. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 9.

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