CN116340596A

CN116340596A - Exercise data analysis method, device, equipment and storage medium

Info

Publication number: CN116340596A
Application number: CN202310466418.0A
Authority: CN
Inventors: 刘玮; 孙强; 薄玉峰
Original assignee: Aikete Beijing Technology Co ltd
Current assignee: Aikete Beijing Technology Co ltd
Priority date: 2023-04-26
Filing date: 2023-04-26
Publication date: 2023-06-27

Abstract

The embodiment discloses a method, a device, equipment and a storage medium for analyzing exercise data. Wherein the method comprises the following steps: under the condition that the client side and the target movement equipment are in communication connection, acquiring an operation instruction of a target movement training course input by a user; based on the operation instruction, acquiring real-time exercise data of the user under the target training course; real-time analysis is carried out on the real-time exercise data to obtain a real-time analysis result; and sending the real-time analysis result to the client so that the client displays the real-time analysis result in real time. The method can improve the efficiency of the exercise data in the storage process and the accuracy of the analysis result, and has higher real-time performance.

Description

Exercise data analysis method, device, equipment and storage medium

Technical Field

The disclosure relates to the technical field of exercise data processing, and in particular relates to an exercise data analysis method, an exercise data analysis device, exercise data analysis equipment and a storage medium.

Background

At present, as microchip sensor technology is mature, data transmission between devices is more frequent. The acquisition, transmission and storage of the user motion data obtained by the sensor equipment become particularly important, and the health condition, life habit and the like of the user can be known through analysis of the motion data, so that corresponding healthy life suggestions are conveniently provided for the user.

In the related art, the motion data of a user is usually stored and analyzed after the motion data is collected and stored, and the motion data is analyzed when the analysis is needed, and the motion data is delayed in analysis, so that the storage efficiency of the motion data is low, the real-time performance is poor, and the accuracy of an analysis result is low.

Disclosure of Invention

In view of the above, the embodiments of the present disclosure provide a method, apparatus, device, and storage medium for analyzing exercise data, which can improve efficiency of exercise data in a storage process and accuracy of analysis results, and have higher real-time performance.

In a first aspect, an embodiment of the present disclosure provides a method for analyzing exercise data, which adopts the following technical scheme:

under the condition that the client side and the target movement equipment are in communication connection, acquiring an operation instruction of a target movement training course input by a user;

based on the operation instruction, acquiring real-time exercise data of the user under the target training course;

real-time analysis is carried out on the real-time exercise data to obtain a real-time analysis result;

and sending the real-time analysis result to the client so that the client displays the real-time analysis result in real time.

In some embodiments, the target workout includes a plurality of workouts, each of the workouts having a different corresponding body portion.

In some embodiments, the operating instructions carry information that the user marks training gestures in different training courses; based on the operation instruction, acquiring real-time exercise data of the user under the target training course, including:

based on the operation instruction, acquiring real-time exercise data of the user in the different training courses, wherein the real-time exercise data comprises real-time training postures of the user.

In some embodiments, the real-time analysis of the real-time exercise data to obtain real-time analysis results includes:

screening the real-time exercise data by utilizing the standard training gesture and the real-time training gesture of the user to obtain screened real-time exercise training data; wherein, the real-time training gesture of the user in the screened real-time exercise training data is consistent with the standard training gesture;

and carrying out real-time analysis on the screened real-time exercise training data to obtain a real-time analysis result.

In some embodiments, the target workout is a real-time selected workout or the target workout is a long-term workout set by a user.

In some embodiments, further comprising:

obtaining training guidance suggestions based on the real-time analysis results;

and sending the training guidance suggestion to the client so that the client displays the real-time analysis result in real time.

In some embodiments, the obtaining training guidance advice based on the real-time analysis results includes:

comparing the real-time analysis result with the historical analysis result to obtain a comparison result;

and generating the training guidance suggestion based on the comparison result.

In a second aspect, an embodiment of the present disclosure further provides a motion exercise data analysis apparatus, which adopts the following technical scheme:

the instruction acquisition unit is configured to acquire an operation instruction of a target exercise training course input by a user under the condition that the client side and the target exercise equipment are in communication connection;

a data acquisition unit configured to acquire real-time exercise data of the user under the target exercise course based on the operation instruction;

the analysis unit is configured to analyze the real-time exercise data in real time to obtain a real-time analysis result;

and the sending unit is configured to send the real-time analysis result to the client so that the client displays the real-time analysis result in real time.

In a third aspect, an embodiment of the present disclosure further provides an electronic device, which adopts the following technical scheme:

the electronic device includes:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the athletic exercise data analysis methods described above.

In a fourth aspect, the presently disclosed embodiments also provide a computer readable storage medium storing computer instructions for causing a computer to perform any of the above described exercise data analysis methods.

According to the exercise data analysis method provided by the embodiment of the disclosure, under the condition that a communication connection is established between a client and target exercise equipment, an operation instruction of a target exercise training course input by a user is acquired; based on the operation instruction, acquiring real-time exercise data of the user under the target training course; real-time analysis is carried out on the real-time exercise data to obtain a real-time analysis result; and sending the real-time analysis result to the client so that the client displays the real-time analysis result in real time. The efficiency of the exercise data in the storage process and the accuracy of the analysis result can be improved, and the real-time performance is high.

The foregoing description is only an overview of the disclosed technology, and may be implemented in accordance with the disclosure of the present disclosure, so that the above-mentioned and other objects, features and advantages of the present disclosure can be more clearly understood, and the following detailed description of the preferred embodiments is given with reference to the accompanying drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.

Fig. 1 is a flowchart of a method for analyzing exercise data according to an embodiment of the present disclosure;

fig. 2 is a schematic structural view of a motion exercise data analysis device according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

Embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

It should be appreciated that the following specific embodiments of the disclosure are described in order to provide a better understanding of the present disclosure, and that other advantages and effects will be apparent to those skilled in the art from the present disclosure. It will be apparent that the described embodiments are merely some, but not all embodiments of the present disclosure. The disclosure may be embodied or practiced in other different specific embodiments, and details within the subject specification may be modified or changed from various points of view and applications without departing from the spirit of the disclosure. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure are intended to be within the scope of this disclosure.

It is noted that various aspects of the embodiments are described below within the scope of the following claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present disclosure, one skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.

It should also be noted that the illustrations provided in the following embodiments merely illustrate the basic concepts of the disclosure by way of illustration, and only the components related to the disclosure are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.

In addition, in the following description, specific details are provided in order to provide a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.

As shown in fig. 1, fig. 1 is a flowchart of a method for analyzing exercise data according to an embodiment of the present disclosure, where the method for analyzing exercise data is executed on a server side, and includes the following steps:

s101, the server acquires an operation instruction of a target exercise training course input by a user under the condition that the client and the target exercise equipment are in communication connection.

S102, the server acquires real-time exercise data of the user under the target training course based on the operation instruction.

S103, the server analyzes the real-time exercise data in real time to obtain a real-time analysis result.

And S104, the server sends the real-time analysis result to the client so that the client displays the real-time analysis result in real time.

Optionally, the registered user may log in by inputting a mailbox account and a password on a login interface of the client, and the unregistered user may log in by inputting an account on the login interface of the client, and log in by the user after the account is completely registered.

Alternatively, the client and the target motion device may be communicatively connected by way of a bluetooth connection. After the client login is completed, the user can search for connectable devices within a nearby range by clicking on "connected devices", and select a target moving device among the connectable devices to perform bluetooth connection.

Optionally, the user may switch the exercise mode at the client, where the exercise mode may include a basic mode, a space task mode, a wild animal mode, and the like, different exercise modes may have different training intensities, and the user may select a corresponding exercise mode according to actual needs, which is not limited in the embodiments of the present disclosure.

Alternatively, the user may set a weekly training goal, for example, set a weekly training period; training reminders can also be set, and training reminders can be set at fixed times per week.

According to the embodiment of the disclosure, the efficiency of the exercise data in the storage process and the accuracy of the analysis result can be improved, and the real-time performance is high.

In some embodiments, the target workout includes a plurality of workouts, each of which corresponds to a different body part.

Optionally, the user may screen the target training course through a sliding operation at the training course screening interface of the client. The target workouts may also be screened by other operations, such as a click operation, to which embodiments of the present disclosure are not limited.

For example, the target training session may be an abdominal crazy training, which comprises a plurality of training sessions of: abdomen rolling, right side unilateral aerial bicycle, left side unilateral aerial bicycle, right side stride rotator, left side stride rotator, right side abdominal oblique muscle rotator, etc.

In some embodiments, the operational instructions carry information that the user marks the training pose in different training courses; the server obtains real-time exercise data of the user under the target training course based on the operation instruction, and the method comprises the following steps:

based on the operation instruction, the server acquires real-time exercise data including real-time exercise gestures of the user in different exercise courses.

In some embodiments, the server performs real-time analysis on the real-time exercise data to obtain real-time analysis results, including:

screening the real-time exercise data by using the standard training posture and the real-time training posture of the user to obtain screened real-time exercise training data; wherein, the real-time training gesture of the user in the screened real-time exercise training data is consistent with the standard training gesture;

Optionally, the real-time training posture of the user in the real-time exercise data is inconsistent with the standard training posture and is invalid training data.

Alternatively, the user may pre-screen the standard training gestures at the training gesture screening interface of the client, e.g., the standard training gestures may include sitting, standing, prone, etc.

In some embodiments, the target workout is a real-time selected workout, or the target workout is a long-term workout set by the user. For example, the user may develop a lesson in real-time on the day of training, or the user may set a long-term training lesson for a training period (the training period may include the number of training weeks, the number of training days, the training duration, and the training intensity) on a monthly, weekly, or daily basis, and may set a training period of 1 month without repeatedly setting the training lesson. For example, under the condition that a user logs in the client, a long-term training course with a history of history can be popped up on the interface of the client in a popup window mode, so that the user can conveniently and quickly enter into exercise.

It should be noted that, the user may set the period of the long-term training course according to the actual service requirement, which is not limited by the embodiments of the present disclosure.

In some embodiments, the method further comprises:

and sending training guidance suggestions to the client so that the client displays real-time analysis results in real time.

Optionally, the training instruction suggestion may be whether the training duration of the user is qualified, whether the training period is reasonable, whether the real-time training gesture of the user meets the standard, whether the expected training target of the user can be completed, and the like, which may be set according to the actual service requirement, and the embodiment of the present disclosure is not limited.

In some embodiments, obtaining training guidance advice based on real-time analysis results includes:

based on the comparison result, training guidance suggestions are generated.

For example, the historical analysis result of the user may be that the user exercises only the abdomen yesterday, the real-time analysis result may be that the user exercises only the quadriceps brachii today, and based on the two analysis results, the user may be recommended to train the muscle groups of the whole body more comprehensively so as to achieve a better training effect.

Alternatively, the historical analysis results may also include the achievement rate of the weekly goal completed by the user, a record of continuous exercises by the user, analysis results requiring enhanced exercise strength or increased muscle control, etc., and the historical analysis results may be graphically displayed on the client.

As shown in fig. 2, fig. 2 is a schematic structural diagram of an exercise data analysis device according to an embodiment of the present disclosure, where the exercise data analysis device according to the embodiment of the present disclosure includes:

an instruction acquisition unit 21 configured to acquire an operation instruction of a target exercise training course input by a user in a case where a communication connection is established between a client and a target exercise device;

a data acquisition unit 22 configured to acquire real-time exercise data of a user under a target exercise course based on an operation instruction;

an analysis unit 23 configured to perform real-time analysis on the real-time exercise data to obtain a real-time analysis result;

and a transmitting unit 24 configured to transmit the real-time analysis result to the client so that the client displays the real-time analysis result in real time.

An electronic device according to an embodiment of the present disclosure includes a memory and a processor. The memory is for storing non-transitory computer readable instructions. In particular, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like.

The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform the desired functions. In one embodiment of the present disclosure, the processor is configured to execute the computer readable instructions stored in the memory to cause the electronic device to perform all or part of the steps of the exercise data analysis method of the various embodiments of the present disclosure described above.

It should be understood by those skilled in the art that, in order to solve the technical problem of how to obtain a good user experience effect, the present embodiment may also include well-known structures such as a communication bus, an interface, and the like, and these well-known structures are also included in the protection scope of the present disclosure.

Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. A schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure is shown. The electronic device shown in fig. 3 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.

As shown in fig. 3, the electronic device may include a processing means (e.g., a central processing unit, a graphic processor, etc.) that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) or a program loaded from a storage means into a Random Access Memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM and RAM are connected to each other via a bus. An input/output (I/O) interface is also connected to the bus.

In general, the following devices may be connected to the I/O interface: input means including, for example, sensors or visual information gathering devices; output devices including, for example, display screens and the like; storage devices including, for example, magnetic tape, hard disk, etc.; a communication device. The communication means may allow the electronic device to communicate wirelessly or by wire with other devices, such as edge computing devices, to exchange data. While fig. 3 shows an electronic device having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from ROM. All or part of the steps of the exercise data analysis method of the embodiments of the present disclosure are performed when the computer program is executed by the processing device.

The detailed description of the present embodiment may refer to the corresponding description in the foregoing embodiments, and will not be repeated herein.

A computer-readable storage medium according to an embodiment of the present disclosure has stored thereon non-transitory computer-readable instructions. When executed by a processor, perform all or part of the steps of the exercise data analysis method of the various embodiments of the present disclosure described previously.

The computer-readable storage medium described above includes, but is not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or removable hard disk), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

The basic principles of the present disclosure have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.

In this disclosure, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions, and the block diagrams of devices, apparatuses, devices, systems involved in this disclosure are merely illustrative examples and are not intended to require or implicate that connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.

In addition, as used herein, the use of "or" in the recitation of items beginning with "at least one" indicates a separate recitation, such that recitation of "at least one of A, B or C" for example means a or B or C, or AB or AC or BC, or ABC (i.e., a and B and C). Furthermore, the term "exemplary" does not mean that the described example is preferred or better than other examples.

It is also noted that in the systems and methods of the present disclosure, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered equivalent to the present disclosure.

Various changes, substitutions, and alterations are possible to the techniques described herein without departing from the teachings of the techniques defined by the appended claims. Furthermore, the scope of the claims of the present disclosure is not limited to the particular aspects of the process, machine, manufacture, composition of matter, means, methods and acts described above. The processes, machines, manufacture, compositions of matter, means, methods, or acts, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or acts.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.

Claims

1. A method of analyzing exercise data, comprising:

2. The method of claim 1, wherein the target workout comprises a plurality of workouts, each of the workouts having a different corresponding body portion.

3. The method of claim 2, wherein the operating instructions carry information that the user marks a training posture in different training courses; based on the operation instruction, acquiring real-time exercise data of the user under the target training course, including:

4. The method for analyzing exercise data according to claim 3, wherein the real-time analyzing the real-time exercise data to obtain real-time analysis results comprises:

5. The exercise data analysis method of claim 2, wherein the target workout is a real-time selected workout or a long-term workout set by a user.

6. The method of claim 1, further comprising:

7. The method of claim 6, wherein the obtaining training guidance advice based on the real-time analysis result comprises:

and generating the training guidance suggestion based on the comparison result.

8. A motion exercise data analysis apparatus, comprising:

9. An electronic device, the electronic device comprising:

at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the exercise data analysis method of any one of claims 1 to 7.

10. A computer readable storage medium storing computer instructions for causing a computer to perform the exercise data analysis method of any one of claims 1 to 7.