WO2023173590A1

WO2023173590A1 - Training plan generation method and system, apparatus, and medium

Info

Publication number: WO2023173590A1
Application number: PCT/CN2022/095420
Authority: WO
Inventors: 奚伟涛; 付勇; 钟芷铃; 张博文
Original assignee: 成都拟合未来科技有限公司
Priority date: 2022-03-14
Filing date: 2022-05-27
Publication date: 2023-09-21
Also published as: CN116797194A

Abstract

The present invention relates to the field of fitness, and relates to a training plan generation method and system, an apparatus, and a medium. The method comprises acquiring the number of actions a of main training parts and the number of actions b of associated training parts according to user information; acquiring main training actions of which number of actions is a matching smoothness in an action library corresponding to the main training parts; acquiring associated training actions of which number of actions is b matching the smoothness in an action library corresponding to the associated training parts; acquiring weight data of each main training action and associated training action according to the user information; and acquiring action sorting according to the smoothness and weight data of the main training actions and the associated training actions. The present invention determines the sorting of the actions by sorting the training parts, combining the main training parts and the associated training parts in the training parts, and according to smoothness information and weight information of each action, a better fitness training effect is achieved, and the use efficiency is improved.

Description

A training plan generation method, system, device and medium

Technical field

The present disclosure relates to the field of fitness, and specifically to a training plan generation method, system, device and medium.

Background technique

With the improvement of people's living standards and the increasing pressure of life, many people's bodies are in a sub-healthy state, but it is difficult to find time for outdoor exercise. Most people choose to exercise and keep fit at home by following online exercise tutorials. The emergence of smart home fitness equipment has made home fitness more standardized.

At present, for scientific fitness, you must formulate a fitness plan that suits your own physical characteristics. To this end, the applicant proposed a fitness exercise training plan generation and evaluation method, system, terminal and medium with application number 2020109609082. Through differences, Individual historical training data provides target subjects with a reliable training plan within their own load range. Subsequently, in order to make the training plan scientific, the applicant proposed a method and system for formulating a fitness training plan with application number 2021109691382, based on user information, training goals, attributes of fitness schedules, and attributes of action segments in several actions. Obtain a group of sorted action clip combinations in the clip, and obtain the recommended times and recommended weights corresponding to each action clip in the action clip combination based on the preset number of actions of the action clips and the user training goals. The recommended times and recommended weights corresponding to one action clip are obtained. Weights form a training exercise set.

However, during long-term use, the applicant found that this method may not be able to survive the training plan when used, and the arrangement and settings between each action cannot be better suitable for different users. Based on this, this method The applicant proposed a more scientific and reasonable training plan generation method.

Contents of the invention

The purpose of this disclosure is to make the user's training plan more scientific and reasonable so as to be applicable to different users. The present disclosure provides a training plan generation method, system, device and medium.

To achieve the above objectives, the present disclosure provides a training plan generation method, including:

A training schedule is generated based on user information, and each training day in the training schedule corresponds to a training part. When generating a training schedule, the user information includes the schedule that the user can train every week, and the schedule is filled in by the user according to his or her own situation. This disclosure uses the user's own schedule to generate a training schedule that conforms to the user's time schedule. Set training parts for each training day in the training schedule. Generally speaking, every training part needs to be covered in the training schedule, that is, the training parts in the training schedule include all preset training parts to ensure that each part All can be trained. At the same time, when setting training parts, the user's key training parts are obtained based on the user's training purpose in the user information. The number of times the user's key training parts appear in the training schedule is greater than the number of times other training parts appear. Secondly, in order to allow different parts to fully rest, the training parts on two adjacent training days in the training schedule are different.

After the training parts are generated in each training day, each training part includes the main training part and the associated training part; for example, when the training part is the arm, the main training part is the arm, and the associated training part is the shoulder; the training part is the shoulder When doing this, the main training parts are the shoulders, and the related training parts are the waist and abdomen. In the present disclosure, the purpose of setting the main training part and the associated training part in the training part is that firstly, due to the different athletic abilities of the users, there may not necessarily be a sufficient number of actions of this part for the user to do. Setting the main training part and the associated training part can On the premise of achieving fitness effects, improve action selection and avoid boring training.

After obtaining the training parts, obtain the number of actions a of the main training parts and the number of actions b of the associated training parts based on the user information; the number of actions b of the associated training parts is 0.4 times the number a of the actions of the main training parts. The total number of actions is the sum between the number of actions a and the number of actions b. The total number of actions is determined by the user information. Specifically, the preset total number of actions can be obtained through the user's athletic ability information and training purpose information. According to The quantitative relationship between the number of actions b and the number of actions a determines the number of actions b and the number of actions a.

Filter the action library based on user information to obtain a library of actions that users can do that match the user's athletic abilities;

In the library of actions that the user can do, based on the training parts corresponding to the training day, the action library corresponding to the main training parts and the action library corresponding to the associated training parts are obtained;

Obtain the number of actions a of the main training parts and the number of actions b of the associated training parts according to the user's athletic ability information and training purpose information;

In the action library corresponding to the main training parts, the main training actions with the number of actions a are obtained based on the smoothness information of the actions; in the action library corresponding to the associated training parts, the associated training actions with the number b are obtained based on the smoothness information of the actions action.

The smoothness information is the accessory information of the action. In the process of fitness training, when training different actions, different fitness accessories may need to be used. If different fitness accessories are used between actions, the user will not To perform an action, you need to replace an accessory, which is cumbersome to operate and the smoothness between actions is poor. Therefore, when filtering actions, in addition to actions that the user can do, that meet the purpose of training, and are suitable for this part of the body, this disclosure In addition, first select actions with exactly the same accessory information that match the number. If the number is not enough, select some actions with the same accessory information. Finally, select actions with completely different accessory information to improve usage efficiency.

After obtaining the main training actions and associated training actions, sort the main training actions and associated training actions according to whether the accessory information is the same; sort the main training actions and associated training actions according to the weight data from large to small, and whether the accessory information has the same priority. Priority over weight data.

Corresponding to the method in this disclosure, this disclosure also provides a training plan generation system, including:

The training schedule module is used to generate a training schedule based on user information. Each training day in the training schedule corresponds to a training part. The training part includes the main training part and the associated training part;

The judgment module is used to obtain the number of actions a of the main training parts and the number of actions b of the associated training parts based on the user's athletic ability information and training purpose information;

The first screening module is used to obtain the main training actions whose smoothness matches the number a from the action library corresponding to the main training parts;

The second screening module is used to obtain associated training actions with a smoothness matching number b from the action library corresponding to the associated training parts;

The weight module is used to obtain weight data of main training actions and related training actions based on the user's athletic ability information and training purpose information;

A sorting module for obtaining action sorting based on smoothness and weight data for primary training actions and associated training actions.

The training plan generation system of the present disclosure can perform operations corresponding to the training plan generation method.

Corresponding to the method in the present disclosure, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the The computer program implements the operation of the above-mentioned method for generating a training plan.

Corresponding to the method in the present disclosure, the present disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the above-mentioned method for generating a training plan is implemented. operation.

One or more technical solutions provided by this disclosure have at least the following technical effects or advantages:

The present disclosure performs fitness training by setting main training parts and related training parts on training days, so that users can arrange each training day more scientifically and rationally during the fitness process, and better achieve the user's own fitness training purposes. At the same time, every The setting of medium movements for each training day is through the arrangement of training parts, the combination of main training parts and related training parts in the training parts, the selection of actions suitable for the main training parts and related training parts, and through the smoothness of each movement. Information and weight information determine the ordering between each action, achieving better fitness training effects and improving usage efficiency.

Description of the drawings

The drawings described here are used to provide a further understanding of the embodiments of the present disclosure, constitute a part of this application, and do not constitute a limitation on the embodiments of the present disclosure. In the attached picture:

Figure 1 is a schematic flow chart of a training plan generation method;

Figure 2 is a schematic diagram of a training plan generation system.

Detailed ways

In order to understand the above objects, features and advantages of the present disclosure more clearly, the present disclosure will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, as long as they do not conflict with each other, the embodiments of the present disclosure and the features in the embodiments can be combined with each other.

Many specific details are set forth in the following description to fully understand the present disclosure. However, the present disclosure can also be implemented in other ways that are different from the scope of this description. Therefore, the protection scope of the present disclosure is not limited by the following disclosure. limitations of specific embodiments.

Those skilled in the art will understand that in the present disclosure, the terms "vertical", "lateral", "upper", "lower", "front", "rear", "left", "right", " The orientations or positional relationships indicated by "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientations or positional relationships shown in the drawings, which are only for the convenience of describing the present disclosure and The description is simplified and is not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore the above terminology is not to be construed as limiting the disclosure.

It should be understood that the term "a" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in other embodiments, the number of the element may be The number may be multiple, and the term "one" shall not be understood as a limitation on the number.

Embodiment 1

Please refer to Figure 1, which is a schematic flow chart of a training plan generation method. The present disclosure provides a training plan generation method, which method includes:

Generate a training schedule based on user information. Each training day in the training schedule corresponds to a training location. The training location includes the main training location and associated training locations;

In the action library corresponding to the main training parts, the main training actions with a number of actions are obtained based on the smoothness information of the actions;

In the action library corresponding to the associated training part, the associated training actions with a number of actions b are obtained based on the smoothness information of the action;

Obtain weight data for each main training action and associated training actions based on user information;

Get movement rankings based on smoothness and weight data for primary and associated training movements.

In this embodiment, the action library of the present disclosure is also preset with pocket actions. When a corresponding number of main training actions and/or associated training actions cannot be output, a corresponding number of actions are randomly obtained from the pocket actions.

The following is an introduction to a training plan generation method in this disclosure with specific examples:

Operation 1 generates a training schedule based on user information;

Operation 1.1 Generate training days in the training schedule based on the schedule that the user can train every week;

Operation 1.2: Obtain the user's key training parts according to the user information; in this embodiment, the user's key training parts are the parts that the user wants to focus on training when the user fills in the user information;

Operation 1.3 Arrange training parts on training days according to the user's key training parts. In this embodiment, the preset training parts include arms, shoulders, waist and abdomen, buttocks, legs, back and chest; training parts in the training schedule Including all preset training parts; the number of times the user focuses on training parts in the training schedule is greater than the number of other training parts; and the training parts on two adjacent training days are different.

Operation 1.4 On the training day, the training part is the main training part, and the associated training parts are obtained according to the main training part; in this embodiment, the associated parts corresponding to the arms, shoulders, waist and abdomen, buttocks, legs, back and chest are respectively For shoulders, waist and abdomen, hips, legs, arms, chest and back.

Operation 2 obtains the number of actions a of the main training parts and the number of actions b of the associated training parts according to the user's athletic ability information and training purpose information. In this embodiment, the relationship between the athletic ability information, training purpose information and the total number of actions As shown in Table 1:

Table 1

Operation 2.1 Obtain the size of the number of actions a and the number of actions b according to the quantitative relationship between the number of actions a and the number of actions b. The number of actions b is 0.4 times the number of actions a; that is, the number of actions a is 0.6 times the total number of actions. In actual calculation, round up to an integer, as shown in Table 1.

Operation 3: Screen the action library according to the user's athletic ability information to obtain an action library that the user can do that matches the user's athletic ability;

Operation 4: From the action library that the user can do, obtain the action library corresponding to the main training parts and the action library corresponding to the associated training parts according to the training parts corresponding to the training day;

Operation 5: In the action library corresponding to the main training parts, obtain the main training actions with a number of actions according to the smoothness information of the actions;

Operation 5.1 In the action library corresponding to the main training parts, select the number a of actions with exactly the same accessory information;

If the number of actions with exactly the same accessory information is less than the number a, select some actions with the same accessory information;

After selecting some actions with the same accessory information, if the number of actions is still less than a, select an action with completely different accessory information.

Operation 6: In the action library corresponding to the associated training part, obtain associated training actions with a number of actions b according to the smoothness information of the actions;

Operation 6.1 In the action library corresponding to the associated training part, select actions with exactly the same accessory information of quantity b;

If the number of actions with exactly the same accessory information is less than the number b, select some actions with the same accessory information;

After selecting some actions with the same accessory information, but the number of actions is still less than b, select an action with completely different accessory information.

Operation 7 sorts the main training actions and related training actions;

Operation 7.1 Obtains the accessory information of the main training movements and related training movements, and sorts the movements in the training day according to whether the accessory information is the same;

Operation 7.2 Obtain action ranking based on the weight data of the main training actions and associated training actions;

The weight data sorts the main training movements and related training movements from large to small.

In this embodiment, the present disclosure is used for a fitness device including a motor, a support arm and a pull rope coupled to the motor through the arm. When in use, the user performs fitness training by pulling the pull rope. When pulling the pull rope , the motor will output a force on the pull rope so that the user can achieve a fitness effect when pulling the pull rope.

When obtaining the weight data of each action, the user's athletic ability information includes the user's strength evaluation. The user will obtain the user's strength evaluation data by pulling the rope, and then generate the weight data of each action based on the user's strength evaluation data, and the The weight data is for one side of the arm.

For example, Table 2 includes action A and action B. When obtaining the weight data of action A and action B, first, each action is preset with the maximum strength of the associated action and the degree of relevance of the action based on the strength evaluation data. At the same time, Based on the user's athletic ability information and training purpose information, the training RM% is preset. RM (Repetition Maximum) is a bodybuilding term. In layman's terms, in the field of fitness, RM is a word with a unit nature, which is used to describe what should be done during training. What kind of weight is chosen. In this embodiment, the training RM% of both action A and action B is 75%.

Table 2

table 3

At the same time, after the weekly training is completed, in the training plan generated by this disclosure, the action weight is updated according to the user's completion of the weight of each action. If the user is very strenuous when completing the actions every week in the training plan, then In the training plan, the weight of the corresponding movements is reduced so that it is more suitable for the user's fitness use in the next week's training plan.

Embodiment 2

Please refer to Figure 2. Figure 2 is a schematic diagram of a training plan generation system. Embodiment 2 of the present disclosure provides a training plan generation system. The system includes:

The training plan generation system of this embodiment can also perform operations corresponding to the training plan generation method of Embodiment 1.

Embodiment 3

Embodiment 3 of the present disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the Operations of a training plan generation method.

The processor may be a central processing unit, or other general-purpose processor, digital signal processor, application-specific integrated circuit, off-the-shelf programmable gate array or other programmable logic device, discrete gate or transistor logic device, discrete hardware components etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

The memory may be used to store the computer program and/or module, and the processor implements various functions of a training plan generating device in the present disclosure by running or executing data stored in the memory. The memory may mainly include a program storage area and a data storage area, where the program storage area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart memory card, secure digital card, flash memory card, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

Embodiment 4

Embodiment 4 of the present disclosure provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the operations of the training plan generation method are implemented.

The computer storage media of the embodiments of the present disclosure may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of computer readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard drive, random access memory (RAM), read only memory (ROM) ), erasable programmable read-only memory ((Erasable Programmable Read Only Memory, EPROM) or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. As used herein, a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device.

Although the preferred embodiments of the present disclosure have been described, those skilled in the art will be able to make additional changes and modifications to these embodiments once the basic inventive concepts are apparent. Therefore, it is intended that the appended claims be construed to include the preferred embodiments and all changes and modifications that fall within the scope of this disclosure.

Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the disclosure. In this way, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and equivalent technologies, the present disclosure is also intended to include these modifications and variations.

Claims

A method for generating a training plan, including:

Generate a training schedule based on user information. Each training day in the training schedule corresponds to a training location. The training location includes the main training location and associated training locations;

Obtain the number of actions a of the main training parts and the number of actions b of the associated training parts according to the user information;

Obtain the main training actions whose smoothness matches the number a from the action library corresponding to the main training parts;

Obtain the associated training actions whose smoothness matches the number b from the action library corresponding to the associated training part;

Obtain weight data for each main training action and associated training actions based on user information;

Get movement rankings based on smoothness and weight data for primary and associated training movements.
A training plan generation method according to claim 1, wherein the user's key training parts are obtained according to the user information, and the number of times the user's key training parts appear in the training schedule is greater than the number of occurrences of other training parts.
A method for generating a training plan according to claim 1, wherein the training parts in the training schedule include all preset training parts.
A method for generating a training plan according to claim 1, wherein the training parts on two adjacent training days are different.
A training plan generation method according to claim 1, wherein:

Filter the action library based on user information to obtain a library of actions that users can do that match the user's athletic ability;

In the library of actions that the user can do, based on the training parts corresponding to the training day, the action library corresponding to the main training parts and the action library corresponding to the associated training parts are obtained;

Obtain the number of actions a of the main training parts and the number of actions b of the associated training parts according to the user's athletic ability information and training purpose information;

In the action library corresponding to the main training parts, the main training actions with a number of actions are obtained based on the smoothness information of the actions;

In the action library corresponding to the associated training part, the associated training actions with a number of actions b are obtained according to the smoothness information of the actions.
A method for generating a training plan according to claim 1 or 5, wherein the number of actions b is 0.4 times the number of actions a.
A training plan generation method according to claim 1, wherein the action ranking is obtained based on the smoothness and weight data of the main training actions and associated training actions, specifically including:

Obtain the accessory information of the main training actions and associated training actions, and sort the main training actions and associated training actions according to whether the accessory information is the same; sort the main training actions and associated training actions according to the weight data from large to small, and whether the accessory information is the same The priority is higher than the priority of weight data.
A training plan generation system, including:

The training schedule module is used to generate a training schedule based on user information. Each training day in the training schedule corresponds to a training part. The training part includes the main training part and the associated training part;

The judgment module is used to obtain the number of actions a of the main training parts and the number of actions b of the associated training parts based on the user's athletic ability information and training purpose information;

The first screening module is used to obtain the main training actions whose smoothness matches the number a from the action library corresponding to the main training parts;

The second screening module is used to obtain associated training actions with a smoothness matching number b from the action library corresponding to the associated training parts;

The weight module is used to obtain weight data of main training actions and related training actions based on the user's athletic ability information and training purpose information;

A ranking module that obtains action rankings based on smoothness and weight data for primary training actions and associated training actions.
A training plan generation system according to claim 8, wherein the user's key training parts are obtained according to the user information, and the number of times the user's key training parts appear in the training schedule is greater than the number of occurrences of other training parts.
A training plan generation system according to claim 8, wherein the training parts in the training schedule include all preset training parts.
A training plan generation system according to claim 8, wherein the training parts on two adjacent training days are different.
A training plan generation system according to claim 8, wherein:

Filter the action library based on user information to obtain a library of actions that users can do that match the user's athletic abilities;

In the library of actions that the user can do, according to the training parts corresponding to the training day, the action library corresponding to the main training parts and the action library corresponding to the associated training parts are obtained;

Obtain the number of actions a of the main training parts and the number of actions b of the associated training parts according to the user's athletic ability information and training purpose information;

In the action library corresponding to the main training parts, the main training actions with a number of actions are obtained based on the smoothness information of the actions;

In the action library corresponding to the associated training part, the associated training actions with a number of actions b are obtained according to the smoothness information of the actions.
A training plan generation system according to claim 8 or 12, wherein the number of actions b is 0.4 times the number of actions a.
A training plan generation system according to claim 8, wherein the action ranking is obtained according to the smoothness and weight data of the main training actions and associated training actions, specifically including:

Obtain the accessory information of the main training actions and associated training actions, and sort the main training actions and associated training actions according to whether the accessory information is the same; sort the main training actions and associated training actions according to the weight data from large to small, and whether the accessory information is the same The priority is higher than the priority of weight data.
A computer-readable storage medium, the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the method of generating a training plan as described in any one of claims 1-7 is implemented. operate.