CN115620868A

CN115620868A - Method and device for recommending exercise scheme to user, electronic equipment and medium

Info

Publication number: CN115620868A
Application number: CN202211386307.0A
Authority: CN
Inventors: 朱鹏; 朱晔
Original assignee: Gezhi Health Management Co ltd
Current assignee: Gezhi Health Management Co ltd
Priority date: 2022-11-07
Filing date: 2022-11-07
Publication date: 2023-01-17
Also published as: TW202420324A

Abstract

The present disclosure provides a method and apparatus, an electronic device, and a medium for recommending a motion scheme to a user. The method comprises the following steps: acquiring a candidate motion course set, wherein the candidate motion course set comprises a plurality of motion courses; acquiring a target course quantity and a plurality of constitutional characteristic parameters of a user; determining a first course subset from the set of candidate athletic courses based on at least a first fitness characteristic parameter of the plurality of fitness characteristic parameters; determining a second lesson subset from the first lesson subset at least according to at least one second physical characteristic parameter of the plurality of physical characteristic parameters except the at least one first physical characteristic parameter; selecting a plurality of target courses from the first course subset and the second course subset, wherein the total amount of the plurality of target courses accords with the amount of the target courses; and providing the plurality of target lessons to the user as a recommended exercise regimen.

Description

Method and device for recommending exercise scheme to user, electronic equipment and medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and apparatus for recommending a motion scheme to a user, an electronic device, a non-transitory computer-readable storage medium, and a computer program product.

Background

With the rapid development of society and the rapid rise of living standard, the incidence of some chronic diseases (such as hyperlipidemia) is also increased, and besides the means of medication, exercise-based rehabilitation schemes are becoming more and more popular.

The approaches described in this section are not necessarily approaches that have been previously conceived or pursued. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, the problems mentioned in this section should not be considered as having been acknowledged in any prior art, unless otherwise indicated.

Disclosure of Invention

The present disclosure provides a method and apparatus for recommending a motion scheme to a user, an electronic device, a non-transitory computer-readable storage medium, and a computer program product.

According to an aspect of the present disclosure, a method of recommending an exercise program to a user is provided. The method comprises the following steps: acquiring a candidate motion course set, wherein the candidate motion course set comprises a plurality of motion courses; acquiring a target course quantity and a plurality of constitutional characteristic parameters of a user; determining a first lesson subset from the set of candidate athletic lessons based at least on at least a first fitness feature parameter of the plurality of fitness feature parameters; determining a second lesson subset from the first lesson subset at least according to at least one second physical characteristic parameter of the plurality of physical characteristic parameters except the at least one first physical characteristic parameter; selecting a plurality of target courses from the first course subset and the second course subset, wherein the total amount of the plurality of target courses accords with the amount of the target courses; and providing the plurality of target lessons to the user as a recommended exercise regimen.

According to another aspect of the present disclosure, there is provided an apparatus for recommending an exercise program to a user. The device includes: a candidate course acquisition unit configured to acquire a set of candidate movement courses, the set of candidate movement courses including a plurality of movement courses; a user parameter acquisition unit configured to acquire a target curriculum amount and a plurality of constitutional characteristic parameters of a user; a first determining unit configured to determine a first lesson subset from the set of candidate athletic lessons based on at least one first fitness characteristic parameter of the plurality of fitness characteristic parameters; a second determining unit configured to determine a second lesson subset from the first lesson subset at least according to at least one second physical characteristic parameter of the plurality of physical characteristic parameters except the at least one first physical characteristic parameter; a third determining unit configured to select a plurality of target courses from the first course subset and the second course subset, a total amount of the plurality of target courses corresponding to a target course amount; and a target course providing unit configured to provide the plurality of target courses to the user as the recommended exercise scheme.

According to another aspect of the present disclosure, there is provided an electronic device including: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform the method of recommending an exercise program to a user.

According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the above-described method of recommending a motion solution to a user.

According to another aspect of the present disclosure, there is provided a computer program product comprising instructions which, when executed by a processor, cause the processor to perform the above-mentioned method of recommending an exercise regimen to a user.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the embodiments and, together with the description, serve to explain the exemplary implementations of the embodiments. The illustrated embodiments are for purposes of illustration only and do not limit the scope of the claims. Throughout the drawings, identical reference numbers designate similar, but not necessarily identical, elements.

FIG. 1 shows a schematic diagram of an example system in which various methods described herein may be implemented, according to an embodiment of the present disclosure;

FIG. 2 illustrates a flow chart of a method of recommending a movement plan to a user according to an embodiment of the present disclosure;

FIG. 3 shows a flow diagram of a method of recommending a movement plan to a user according to another embodiment of the present disclosure;

FIG. 4 shows a flow diagram of a portion of a process of a method of recommending an exercise regimen to a user in accordance with an embodiment of the present disclosure;

FIG. 5 shows a flow diagram of a portion of a process of a method of recommending an exercise regimen to a user in accordance with an embodiment of the present disclosure;

FIG. 6 is a block diagram illustrating an apparatus for recommending a motion program to a user according to an embodiment of the present disclosure; and

fig. 7 shows a block diagram of an electronic device according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, the timing relationship, or the importance relationship of the elements, and such terms are used only to distinguish one element from another. In some examples, a first element and a second element may refer to the same instance of the element, while in some cases they may refer to different instances based on the context of the description.

The terminology used in the description of the various described examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the elements may be one or more. Furthermore, the term "and/or" as used in this disclosure is intended to encompass any and all possible combinations of the listed items.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

Exercise-based rehabilitation programs are increasingly being used. In the related art, an athletic rehabilitation specialist may design an exercise scheme suitable for a user for different users. In addition, the intelligent system for recommending the exercise scheme can be designed by utilizing the collected expert experience data, so that different exercise courses are recommended to the users by utilizing the intelligent system according to the personalized parameters of the different users.

In the related art, when the intelligent system recommends the exercise scheme according to the characteristic parameters input by the user, the number of recommended schemes filtered from the initial selectable exercise schemes may be insufficient (for example, the exercise requirement of the user cannot be met) due to more characteristic parameters input by the user or due to less initial selectable exercise schemes, and even no suitable recommended scheme may be available for the user.

In view of this, the present disclosure provides a method and apparatus, an electronic device, a non-transitory computer-readable storage medium, and a computer program product for recommending a motion scheme to a user.

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

Fig. 1 is a schematic diagram illustrating an example system 100 in which various methods described herein may be implemented, according to an example embodiment.

Referring to fig. 1, the system 100 includes a client device 110, a server 120, and a network 130 communicatively coupling the client device 110 and the server 120.

The client device 110 includes a display 114 and a client Application (APP) 112 that may be displayed via the display 114. The client application 112 may be an application that needs to be downloaded and installed before running or an applet (lite app) that is a lightweight application. In the case where the client application 112 is an application program that needs to be downloaded and installed before running, the client application 112 may be installed on the client device 110 in advance and activated. In the case where the client application 112 is an applet, the user 102 can run the client application 112 directly on the client device 110 without installing the client application 112 by searching the client application 112 in a host application (e.g., by the name of the client application 112, etc.) or by scanning a graphical code (e.g., barcode, two-dimensional code, etc.) of the client application 112, etc. In some embodiments, client device 110 may be any type of mobile computer device, including a mobile computer, a mobile phone, a wearable computer device (e.g., a head-mounted device such as a smart watch, smart glasses, etc.), or other type of mobile device. In some embodiments, client device 110 may alternatively be a stationary computer device, such as a desktop, server computer, or other type of stationary computer device.

The server 120 is typically a server deployed by an Internet Service Provider (ISP) or Internet Content Provider (ICP). Server 120 may represent a single server, a cluster of multiple servers, a distributed system, or a cloud server providing an underlying cloud service (such as cloud database, cloud computing, cloud storage, cloud communications). It will be understood that although the server 120 is shown in fig. 1 as communicating with only one client device 110, the server 120 may provide background services for multiple client devices simultaneously.

Examples of network 130 include a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), and/or a combination of communication networks such as the Internet. The network 130 may be a wired or wireless network. In some embodiments, data exchanged over network 130 is processed using techniques and/or formats including hypertext markup language (HTML), extensible markup language (XML), and the like. In addition, all or some of the links may also be encrypted using encryption techniques such as Secure Sockets Layer (SSL), transport Layer Security (TLS), virtual Private Network (VPN), internet protocol security (IPsec), and so on. In some embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.

For purposes of embodiments of the present disclosure, in the example of fig. 1, the client application 112 may be an exercise health application that may provide various exercise health-based functions, such as obtaining user-entered physical characteristics information, exercise course demand parameters, providing exercise courses and exercise programs, and the like. Accordingly, the server 120 may be a server for use with an exercise health application. The server 120 may provide a service such as motion scenario recommendation to the client application 112 running in the client device 110 based on the road network data. Alternatively, the server 120 may provide the road network data to the client device 110, and the client application 112 running in the client device 110 provides a service such as motion scenario recommendation.

FIG. 2 shows a flow diagram of a method 200 of recommending an exercise regimen to a user in accordance with an embodiment of the present disclosure.

As shown in fig. 2, the method 200 includes:

step S210, a candidate movement course set is obtained, wherein the candidate movement course set comprises a plurality of movement courses;

step S220, acquiring a target course quantity and a plurality of constitution characteristic parameters of a user;

step S230, determining a first course subset from the candidate exercise course set at least according to at least one first physique characteristic parameter in the plurality of physique characteristic parameters;

step S240, determining a second course subset from the first course subset at least according to at least one second body characteristic parameter except for at least one first body characteristic parameter in the plurality of body characteristic parameters;

step S250, selecting a plurality of target courses from the first course subset and the second course subset, wherein the total amount of the plurality of target courses accords with the amount of the target courses; and

step S260, providing the plurality of target courses as recommended exercise programs to the user.

In an example, the set of candidate motion lessons may include a plurality of motion lessons stored in a database, and the motion lessons may be lessons in text, picture, audio, video form, or a combination of multiple forms of text, picture, audio, video. In an example, the set of candidate motion lessons may include motion lesson videos of different durations. And the set of candidate athletic lessons may include different types of athletic lessons, for example, fat reduction lessons, lessons for improving cardiopulmonary endurance, and the like, each type of athletic lesson may be associated with the lesson in the form of tag data to facilitate retrieval in a lesson database.

In an example, the target amount of lessons for the user may be a target amount of lessons or a target length of lessons entered by the user and obtained from the client device. For example, the target lesson amount may be a target lesson length of 50 hours.

In an example, the physical characteristic parameter may be a weight, a height, a gender, an age, etc. of the user input acquired from the user-side device. The user end device may be a medical measurement device or an exercise measurement device (e.g., a blood lipid monitor, a blood pressure and heart rate measurement device), and accordingly, the physical characteristic parameters may further include a blood lipid parameter, a blood pressure parameter, a heart rate parameter, and the like.

In step S230, a first course subset may be determined from the candidate set of athletic courses, for example, based on two first fitness characteristics (e.g., weight, height) of the plurality of fitness characteristics. Each lesson of the first subset of lessons may have a label corresponding to the first fitness characteristic parameter such that each lesson of the first subset of lessons is in compliance with the first fitness characteristic parameter (weight, height), i.e., each lesson of the first subset of lessons is applicable to users of the weight (or the weight range) and the height (or the height range).

In step S240, a second lesson subset may be determined from the first lesson subset according to a plurality of second physical characteristic parameters (e.g., blood pressure, age) of the plurality of physical characteristic parameters, except for the at least one first physical characteristic parameter. Thus, each lesson in the second subset of lessons has not only a label corresponding to the first body characteristic parameter but also a label corresponding to the second body characteristic parameter (blood pressure, age), so that each lesson in the second subset of lessons conforms not only to the first body characteristic parameter (weight, height) but also to the second body characteristic parameter (blood pressure, age), i.e. each lesson in the second subset of lessons applies to users of that blood pressure (or that blood pressure range) and that age (or that age range).

In step S250, a plurality of target courses (which may have different course time lengths) having a total time length of 20 hours may be determined from the first subset of courses based on a target course amount (e.g., a target course time length of 50 hours) set by the user; and determining a plurality of target lessons having a total length of 30 hours from the second subset of lessons (the plurality of target lessons may have different lesson lengths).

Whereby each lesson of the first subset of lessons determined from the set of candidate athletic lessons matches the first fitness characteristics parameter; and further, each lesson in the second subset of lessons determined from the first subset of lessons matches not only the first physical characteristic parameters but also the second physical characteristic parameters. When the exercise scheme is provided for the user, a plurality of target courses with the total amount meeting the target course amount set by the user are determined from the first course subset and the second course subset respectively, so that the problem of insufficient total amount of the recommended exercise scheme caused by more characteristic parameters of the user can be avoided; and the recommended exercise course is determined according to the user constitution characteristic parameters, so that the exercise quality of the user can be ensured, and the user experience is improved.

In addition, according to the method of the embodiment of the present disclosure, for a user whose value of one or some of the fitness characteristics is rare, in a case that the total number of candidate lessons is limited, the first lesson subset may be determined from the candidate sports lesson set according to other fitness characteristics of the user (i.e., fitness characteristics whose value is relatively common). Thus, when the determined amount of courses in the second course subset is small, since the amount of courses in the first course subset is relatively sufficient, it can be ensured that the exercise course conforming to the target amount of courses and physical characteristics thereof is recommended to the user.

According to some embodiments, the target lesson amount may include a target lesson length, and the total length of the plurality of target lessons may be greater than or equal to the target lesson length.

According to some embodiments, the plurality of constitutional characteristic parameters may include a plurality of: weight, height, heart rate, sex, age, disease characteristic parameter, blood lipid characteristic parameter.

The disease characteristic parameters can include whether hypertension exists, whether sports injury exists, whether a guardian is needed in the sports process and the like; the blood lipid characteristic parameters may include triglyceride content, total cholesterol content, low density lipoprotein cholesterol content, high density lipoprotein cholesterol content, and the like. The disease characteristic parameter and the blood lipid characteristic parameter can be measured, for example, by a medical measuring device or a sports measuring device.

Fig. 3 shows a flow diagram of a method 300 of recommending an exercise regimen to a user according to another embodiment of the present disclosure. As shown in fig. 3, the method 300 includes steps S310 to S370, wherein the steps S310, S320, S340, S350 and S360 are similar to the steps S210, S220, S240, S250 and S260 described above with respect to fig. 2, respectively, and are not repeated herein for brevity.

According to some embodiments, the method 300 may further include step S370, obtaining course selection parameters for the user.

And step S330 may include: a first course subset is determined from the set of candidate athletic courses based on the course selection parameters and the at least one first fitness feature parameter.

In an example, the lecture selection parameter may be a type of target course or a desired movement frequency, etc.

Therefore, the first course subset is determined based on the physique characteristic parameters of the user and the course selection parameters, and therefore the exercise scheme more suitable for the requirements of the user can be recommended to the user according to the personalized setting of the user.

According to some embodiments, the course selection parameters may comprise at least one of: target course difficulty, target course type. For example, the target course difficulty level may be set to a plurality of levels including easy, medium, difficult, etc.; the target class types may include a plurality of types for reducing fat, improving cardiopulmonary endurance, and the like.

FIG. 4 shows a flowchart of a portion of a process of a method 300 of recommending an exercise regimen to a user, according to an embodiment of the present disclosure.

According to some embodiments, as shown in fig. 4, the step S330 may include:

and step S431, performing corresponding filtering on the candidate motion course set according to the course selection parameters and the at least one first body characteristic parameter respectively to obtain a first course subset.

And the method may further comprise:

step S440, responding to the completion of each filtering, determining the total amount of the curriculum remained after the filtering; and

step S450, in response to determining that the total amount of the remaining lessons is less than or equal to the target lesson amount, providing the remaining lessons to the user as a recommended exercise regimen.

In an example, the candidate motion lesson set may be filtered once according to a lesson selection parameter (e.g., a lesson difficulty level) to obtain an intermediate subset; the intermediate subset is filtered again according to a first body characteristic parameter (e.g. the user's weight) to obtain a first lesson subset. After filtering the intermediate subset, if it is determined that the total amount of lessons remaining in the intermediate subset is less than or equal to the target amount of lessons, all of the lessons in the intermediate subset may be provided to the user as a recommended exercise regimen. Therefore, the situation that the residual amount of the courses to be recommended does not meet the requirement of the user in the course of filtering the courses can be avoided.

It will be appreciated that in other examples, the set of candidate athletic lessons may be first filtered once according to a first fitness characteristic parameter (e.g., user weight) to obtain an intermediate subset; and filtering the intermediate subset again according to course selection parameters (such as course difficulty) to obtain a first course subset.

FIG. 5 shows a flowchart of a portion of a process of a method 300 of recommending an exercise regimen to a user, according to an embodiment of the present disclosure.

According to some embodiments, the step S340 may include:

step S541, respectively performing a corresponding filtering on the first course subset according to each second body characteristic parameter of the at least one second body characteristic parameter, so as to obtain a second course subset.

And the method may further comprise:

step S550, responding to the completion of each filtering, determining the total amount of the curriculum remained after the filtering; and

step S560, in response to determining that the total amount of the remaining lessons is less than or equal to the target lesson amount, providing the remaining lessons to the user as a recommended exercise regimen.

In an example, the first lesson subset may be filtered once according to a second physical characteristic parameter (e.g., user gender) to obtain an intermediate subset; the intermediate subset is again filtered according to another second physical characteristic parameter (e.g. user age) to obtain a second lesson subset. After filtering the intermediate subset, if it is determined that the total amount of lessons remaining in the intermediate subset is less than or equal to the target amount of lessons, all of the lessons in the intermediate subset may be provided to the user as a recommended exercise regimen. Therefore, the situation that the residual amount of the courses to be recommended does not meet the requirement of the user in the course of filtering the courses can be further avoided.

According to another aspect of the present disclosure, an apparatus for recommending an exercise program to a user is provided. Fig. 6 shows a block diagram of an apparatus 600 for recommending an exercise scheme to a user according to an embodiment of the present disclosure.

As shown in fig. 6, the apparatus 600 includes:

a candidate course acquiring unit 610 configured to acquire a set of candidate motion courses, the set of candidate motion courses including a plurality of motion courses;

a user parameter acquiring unit 620 configured to acquire a target curriculum amount and a plurality of physical fitness characteristic parameters of the user;

a first determining unit 630 configured to determine a first course subset from the candidate sports course set at least according to at least one first fitness feature parameter of the plurality of fitness feature parameters;

a second determining unit 640 configured to determine a second lesson subset from the first lesson subset at least according to at least one second body characteristic parameter of the plurality of body characteristic parameters other than the at least one first body characteristic parameter;

a third determining unit 650 configured to select a plurality of target courses from the first and second subsets of courses, the total amount of the plurality of target courses corresponding to the target course amount; and

a target course providing unit 660 configured to provide the plurality of target courses to the user as a recommended exercise scheme.

It should be understood that the various elements of the apparatus 600 shown in fig. 6 may correspond to various steps in the method 200 described with reference to fig. 2. Thus, the operations, features and advantages described above with respect to the method 200 are equally applicable to the apparatus 600 and the units comprised thereby. Certain operations, features and advantages may not be described in detail herein for the sake of brevity.

It should also be appreciated that various techniques may be described herein in the general context of software, hardware elements, or program modules. The various elements described above with respect to fig. 6 may be implemented in hardware or in hardware in combination with software and/or firmware. For example, the units may be implemented as computer program code/instructions configured to be executed in one or more processors and stored in a computer readable storage medium. Alternatively, the units may be implemented as hardware logic/circuits. For example, in some embodiments, one or more of units 610-660 may be implemented together in a System on Chip (SoC). The SoC may include an integrated circuit chip (which includes one or more components of a Processor (e.g., a Central Processing Unit (CPU), microcontroller, microprocessor, digital Signal Processor (DSP), etc.), memory, one or more communication interfaces, and/or other circuitry), and may optionally execute received program code and/or include embedded firmware to perform functions.

According to another aspect of the present disclosure, there is also provided an electronic device including: a processor; and a memory; wherein the memory stores instructions that, when executed by the processor, cause the processor to perform the method of recommending an exercise regimen to a user as described above.

According to another aspect of the present disclosure, there is also provided a non-transitory computer readable storage medium storing instructions, wherein the instructions, when executed by a processor, cause the processor to perform the above-mentioned method of recommending a motion scheme to a user.

According to another aspect of the present disclosure, there is also provided a computer program product comprising instructions, wherein the instructions, when executed by a processor, cause the processor to perform the above-mentioned method of recommending an exercise regimen to a user.

Referring to fig. 7, a block diagram of a structure of an electronic device 700, which may be the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. The electronic devices may be different types of computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

FIG. 7 shows a block diagram of an electronic device in accordance with an embodiment of the disclosure. As shown in fig. 7, the electronic device 700 may include at least one processor 701, a working memory 702, I/O devices 704, a display device 705, a storage 706, and a communication interface 707, which may communicate with each other through a system bus 703.

Processor 701 may be a single processing unit or multiple processing units, all of which may include single or multiple computing units or multiple cores. The processor 701 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitry, and/or any devices that manipulate signals based on operational instructions. The processor 701 may be configured to retrieve and execute computer readable instructions, such as program code for an operating system 702a, program code for an application 702b, and the like, stored in the working memory 702, the storage device 706, or other computer readable medium.

Working memory 702 and storage 706 are examples of computer-readable storage media for storing instructions that are executed by processor 701 to perform the various functions described above. The working memory 702 may include both volatile and non-volatile memory (e.g., RAM, ROM, etc.). Further, storage 706 may include a hard disk drive, solid state drive, removable media, including external and removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., CDs, DVDs), storage arrays, network attached storage, storage area networks, and so forth. Both the working memory 702 and the storage 706 may be collectively referred to herein as memory or computer-readable storage medium, and may be non-transitory media capable of storing computer-readable, processor-executable program instructions as computer program code, which may be executed by the processor 701 as a particular machine configured to implement the operations and functions described in the examples herein.

The I/O devices 704 may include input devices and/or output devices, and the input devices may be any type of device capable of inputting information to the electronic device 700, which may include, but are not limited to, a mouse, keyboard, touch screen, track pad, track ball, joystick, microphone, and/or remote control. Output devices may be any type of device capable of presenting information and may include, but are not limited to including, video/audio output terminals, vibrators, and/or printers.

Communication interface 707 allows electronic device 700 to communicate via, for exampleThe extranet computer network and/or various telecommunications networks exchange information/data with other devices and may include, but are not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth ^TM Devices, 802.11 devices, wi-Fi devices, wiMAX devices, cellular communication devices, and/or the like.

The application program 702b in the working register 702 may be loaded to perform the various methods and processes described above. In some embodiments, some or all of the computer program may be loaded and/or installed onto electronic device 700 via storage 706 and/or communication interface 707. When loaded and executed by the processor 701, may perform one or more of the steps of the method of recommending a movement plan to a user described above.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable task scheduling device, such that the program codes, when executed by the processor or controller, cause the functions/acts specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.

The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be performed in parallel, sequentially or in different orders, and are not limited herein as long as the desired results of the technical aspects of the present disclosure can be achieved.

Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the above-described methods, systems and apparatus are merely exemplary embodiments or examples and that the scope of the present invention is not limited by these embodiments or examples, but only by the claims as issued and their equivalents. Various elements in the embodiments or examples may be omitted or may be replaced with equivalents thereof. Further, the steps may be performed in an order different from that described in the present disclosure. Further, various elements in the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced with equivalent elements that appear after the present disclosure.

Claims

1. A method of recommending an exercise regimen to a user, comprising:

acquiring a candidate motion course set, wherein the candidate motion course set comprises a plurality of motion courses;

acquiring a target course quantity and a plurality of constitutional characteristic parameters of the user;

determining a first course subset from said set of candidate athletic courses based on at least a first fitness characteristic parameter of said plurality of fitness characteristic parameters;

determining a second lesson subset from the first lesson subset based on at least one second physical characteristic parameter of the plurality of physical characteristic parameters other than the at least one first physical characteristic parameter;

selecting a plurality of target courses from the first and second subsets of courses, the total amount of the plurality of target courses corresponding to the target course amount; and

providing the plurality of target lessons to the user as a recommended exercise regimen.

2. The method of claim 1, further comprising obtaining course selection parameters for the user,

wherein determining a first course subset from the set of candidate athletic courses based at least on at least a first fitness feature parameter of the plurality of fitness feature parameters comprises:

determining the first course subset from the set of candidate athletic courses based on the course selection parameter and the at least one first fitness feature parameter.

3. The method of claim 2, wherein determining the first course subset from the set of candidate athletic courses based on the course selection parameter and the at least one first fitness characteristic parameter comprises:

performing corresponding filtering on the candidate motion course set according to the course selection parameter and the at least one first quality characteristic parameter respectively to obtain the first course subset; and is

Wherein the method further comprises:

in response to completing each filtering, determining a total amount of lessons remaining from the filtering; and

in response to determining that the total amount of the remaining lessons is less than or equal to the target lesson amount, providing the remaining lessons to the user as a recommended exercise regimen.

4. The method of claim 2, wherein the course selection parameters comprise at least one of: target course difficulty, target course type.

5. The method of claim 1, wherein determining a second lesson subset from the first lesson subset based at least on at least a second body characteristic parameter of the plurality of body characteristic parameters other than the at least one first body characteristic parameter comprises:

respectively performing corresponding primary filtering on the first course subset according to each second body characteristic parameter in the at least one second body characteristic parameter to obtain a second course subset; and is provided with

Wherein the method further comprises:

6. The method according to any one of claims 1 to 5, wherein said plurality of constitutional characteristic parameters comprises a plurality of: weight, height, heart rate, sex, age, disease characteristic parameter, blood lipid characteristic parameter.

7. The method as recited in any one of claims 1 to 5, wherein the target lesson amount comprises a target lesson length, and

wherein the total duration of the plurality of target lessons is greater than or equal to the target lesson duration.

8. An apparatus for recommending an exercise regimen to a user, comprising:

a candidate course acquisition unit configured to acquire a set of candidate motion courses, the set of candidate motion courses including a plurality of motion courses;

a user parameter acquisition unit configured to acquire a target curriculum amount and a plurality of physical fitness characteristic parameters of the user;

a first determining unit configured to determine a first course subset from the candidate sports course set at least according to at least one first fitness feature parameter of the plurality of fitness feature parameters;

a second determining unit configured to determine a second lesson subset from the first lesson subset at least according to at least one second physical characteristic parameter of the plurality of physical characteristic parameters except the at least one first physical characteristic parameter;

a third determining unit configured to select a plurality of target courses from the first and second subsets of courses, a total amount of the plurality of target courses corresponding to the target course amount; and

a target course providing unit configured to provide the plurality of target courses to the user as a recommended exercise scheme.

9. An electronic device, comprising:

a processor; and

a memory storing instructions that, when executed by the processor, cause the processor to perform the method of any of claims 1-7.

10. A non-transitory computer readable storage medium having stored thereon instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1-7.

11. A computer program product comprising instructions which, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-7.