CN110727718A - Intelligent generation method and system for fitness course - Google Patents

Intelligent generation method and system for fitness course Download PDF

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Publication number
CN110727718A
CN110727718A CN201910971000.9A CN201910971000A CN110727718A CN 110727718 A CN110727718 A CN 110727718A CN 201910971000 A CN201910971000 A CN 201910971000A CN 110727718 A CN110727718 A CN 110727718A
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course
user
fitness
courses
unit
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申波
赵仁康
郭洪伟
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CHENGDU CODOON INFORMATION TECHNOLOGY Co Ltd
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CHENGDU CODOON INFORMATION TECHNOLOGY Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/248Presentation of query results
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0075Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2457Query processing with adaptation to user needs
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9535Search customisation based on user profiles and personalisation
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2230/00Measuring physiological parameters of the user
    • A63B2230/01User's weight

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  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Linguistics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

The invention discloses a method and a system for intelligently generating fitness courses, wherein the method comprises the following steps: s1: collecting fitness information provided by a user; s2: mapping the fitness information of the user to one user group in a plurality of preset user groups according to a preset classification rule; s3: searching a course arrangement mode corresponding to the user grouping in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groupings and corresponding course arrangement modes thereof, and the course arrangement modes comprise a plurality of course labels arranged according to a preset sequence; s4: according to the course labels in the course arrangement mode, the course corresponding to each course label is searched in a course library, and one course in a plurality of courses corresponding to the course labels is randomly selected, wherein the course library stores a plurality of courses and the corresponding course labels; s5: pushing the selected lessons to the user. The invention can make personalized and scientific fitness courses for users.

Description

Intelligent generation method and system for fitness course
Technical Field
The invention relates to the technical field of internet, in particular to a method and a system for intelligently generating fitness courses.
Background
With the increasing importance of people on health, more and more people participate in body-building exercise, but at present, a sufficient number of body-building coaches are not enough to guide people to exercise, so that most people cannot receive professional and scientific body-building instruction, and the phenomena of poor body-building effect, loss of exercise enthusiasm and even physical injury caused by unscientific body-building occur.
Generally, a way for people to obtain fitness guidance mainly comprises the steps of guiding by a personal fitness coach, simulating fitness plans of other fitness people, self-learning and obtaining relevant fitness knowledge through internet books and the like, but the personal fitness coach is expensive, the coach resources are few, the time limit is also large, the fitness plans of other fitness people are difficult to adapt to everyone, the self-learning through the internet books and the like needs a lot of time for users to pay to screen real and effective contents, and few people successfully master scientific exercise methods and achieve ideal effects through the self-learning.
Disclosure of Invention
The invention mainly solves the technical problem of providing an intelligent generation method and system of fitness courses, which can make personalized and scientific fitness courses for users.
In order to solve the technical problems, the invention adopts a technical scheme that: the method for intelligently generating the fitness course comprises the following steps of; s1: collecting body-building information provided by a user, wherein the body-building information comprises personal basic information, a body-building purpose and a body-building and exercise part of the user, and the personal basic information comprises sex, height, weight and age; s2: mapping the fitness information of the user to one user group in a plurality of preset user groups according to a preset classification rule; s3: searching a course arrangement mode corresponding to the user grouping in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groupings and corresponding course arrangement modes thereof, and the course arrangement modes comprise a plurality of course labels arranged according to a preset sequence; s4: according to the course labels in the course arrangement mode, the course corresponding to each course label is searched in a course library, and one course in a plurality of courses corresponding to the course labels is randomly selected, wherein the course library stores a plurality of courses and the corresponding course labels; s5: pushing the selected lessons to the user.
As a preferred embodiment of the present invention, the method for intelligently generating a fitness course further includes: s6: collecting fitness feedback information provided by a user, wherein the fitness feedback information comprises course difficulty, weight variation and fitness purpose; s7: judging whether the user groups are mapped into new user groups according to the preset classification rules or not according to the fitness feedback information; s8: if yes, looking up the course arrangement mode corresponding to the new user group in the corresponding relation table, and performing steps S4 to S5 again: s9: if the judgment result is negative, the original course is kept unchanged.
As a preferred embodiment of the present invention, the method for intelligently generating a fitness course further includes: s10: receiving a course changing instruction input by a user; s11: searching other courses corresponding to the course labels of the current course in a course library according to the course changing instruction; s12: presenting the found courses in a list mode for a user to select; s13: and pushing the courses selected by the user to the user.
In order to solve the technical problem, the invention adopts another technical scheme that: the utility model provides a body-building course intelligence generates system, body-building course intelligence generates system includes that user information collects the unit, the user divides the group to classify the unit, arranges the course unit, course generation unit and course storehouse, the storage has multiple course and its corresponding course label in the course storehouse, wherein: the user information collecting unit is used for collecting body-building information provided by a user, the body-building information comprises personal basic information, a body-building purpose and a body-building and exercising part of the user, and the personal basic information comprises sex, height, weight and age; the user grouping and classifying unit is used for mapping the fitness information of the user to one user grouping in a plurality of preset user groupings according to a preset classification rule; the course arrangement unit is used for searching course arrangement modes corresponding to the user groups in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groups and corresponding course arrangement modes, and the course arrangement modes comprise a plurality of course labels arranged according to a preset sequence; the course generating unit is used for searching the course corresponding to each course label in the course library according to the course labels in the course arrangement mode, randomly selecting one of a plurality of courses corresponding to the course label, and pushing the selected course to the user.
As a preferred embodiment of the present invention, the user information collecting unit is further configured to collect fitness feedback information provided by the user, where the fitness feedback information includes a course difficulty, a weight variation, and a fitness goal; the user grouping and classifying unit is also used for judging whether the user is mapped into a new user grouping according to the preset classification rule by combining the fitness feedback information; and the course arrangement unit is also used for searching the course arrangement mode corresponding to the new user grouping in the corresponding relation table when the judgment result of the user grouping and classifying unit is yes, and keeping the original course unchanged when the judgment result of the user grouping and classifying unit is no.
As a preferred embodiment of the present invention, the fitness course intelligent generation system further includes a course adjusting unit, and the user information collecting unit is further configured to receive a course changing instruction input by a user; the course adjusting unit is used for searching other courses corresponding to the course labels of the current course in the course library according to the course changing instruction; the course generating unit is further used for presenting the found courses in a list mode for the user to select, and pushing the courses selected by the user to the user.
Different from the prior art, the invention has the beneficial effects that: the system comprises a course library, a course label framework, a course arrangement mode mapping.
Drawings
Fig. 1 is a flowchart illustrating an intelligent generation method for a fitness course according to an embodiment of the present invention.
FIG. 2 is a functional block diagram of an exercise session intelligence generation system in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the method for intelligently generating fitness courses according to the embodiment of the present invention includes the following steps:
s1: collecting body-building information provided by a user, wherein the body-building information comprises personal basic information, a body-building purpose and a body-building exercise position of the user, and the personal basic information comprises sex, height, weight and age.
The body-building information is provided by a user, the user can input the body-building information through a mobile phone and other terminals, the body-building purpose is fat reduction, shaping and muscle increasing, and the body-building exercise parts are divided into chest, back, abdomen, waist, shoulders, arms, legs and buttocks.
S2: and mapping the fitness information of the user to one user group in a plurality of preset user groups according to a preset classification rule.
The preset classification rule may be determined according to actual needs, for example, the preset classification rule is a classification rule of the american society for sports medicine or a classification rule of the chinese society for sports medicine. The user group indicates which fitness group the user belongs to, for example, the user group is male, the BMI range is 24-26, fat is reduced, and the whole body is full, wherein the BMI is the square of weight/height. The user groups are preset and correspond to all possible fitness groups.
S3: and searching the course arrangement mode corresponding to the user grouping in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groupings and corresponding course arrangement modes thereof, and the course arrangement mode comprises a plurality of course labels arranged according to a preset sequence.
The correspondence table includes all popular user groups, and each user group is provided with a corresponding course arrangement mode, for example, the user group is male, the BMI range is 24-26, fat is reduced, the course arrangement mode corresponding to the whole body is aerobic, HIIT, rest, aerobic, core strength, lower limb strength and rest, wherein except the rest, the rest represents course labels. The names, the number and the sorting modes of the course labels included in different course sorting modes may be different.
S4: according to the course labels in the course arrangement mode, the course corresponding to each course label is searched in the course library, and one course in the plurality of courses corresponding to the course label is randomly selected, wherein the course library stores a plurality of courses and the corresponding course labels.
In some specific applications, the curriculums corresponding to aerobic activities are combined with walking and running at levels 2-8, the curriculums corresponding to HIIT are exercises of levels 2-4 and TABATA at levels 2-4, the curriculums corresponding to core strength are exercises of levels 2-5 and abdomen and cores and lower limbs, the curriculums corresponding to lower limb strength are exercises of levels 1-4 and male lower limb strength and lower limb strength 1-4, and numbers in curriculum names represent difficulty levels. When selecting a course, one course is randomly selected from 2-4 levels of HIIT classes and 2-4 levels of TABATA classes of sports courses corresponding to HIIT.
S5: pushing the selected lessons to the user.
The content of the lesson includes, but is not limited to, pictures, audio, video, and the like.
Considering that the body indexes of the user are changed in the exercise process of the user, in order to make the exercise course more fit to the body state of the user, in this embodiment, the method for intelligently generating the exercise course further includes:
s6: and collecting fitness feedback information provided by the user, wherein the fitness feedback information comprises course difficulty, weight variation and fitness purpose.
Wherein the difficulty of the courses is divided into moderate, too big and too small, for example. The user can input the fitness feedback information through the mobile phone.
S7: and judging whether the mapping is carried out to a new user group according to the preset classification rule or not according to the fitness feedback information.
If the user weight variation is too large, or the course difficulty is too large or too small, or the user actively changes the fitness goal, the user may be mapped to a new user group according to the preset classification rule.
S8: if yes, looking up the course arrangement mode corresponding to the new user group in the corresponding relation table, and proceeding the steps S4 to S5 again.
S9: if the judgment result is negative, the original course is kept unchanged.
Further, for some courses, the courses can only be performed outdoors, but if it is rained, it is inconvenient to learn the courses, in this embodiment, the method for intelligently generating fitness courses further includes:
s10: and receiving a course changing instruction input by a user.
S11: and searching other courses corresponding to the course labels of the current course in the course library according to the course changing instruction.
Wherein, the other courses and the current course are the courses with the same training effect.
S12: presenting the found courses in a list mode for a user to select;
s13: and pushing the courses selected by the user to the user.
Referring to fig. 2, the route recommending system according to the embodiment of the present invention includes a user information collecting unit 10, a user grouping unit 20, a course arranging unit 30, a course generating unit 40, and a course library 50, wherein a plurality of courses and corresponding course labels are stored in the course library 50.
The user information collecting unit 10 is used for collecting fitness information provided by a user, wherein the fitness information comprises personal basic information, fitness purposes and fitness exercise positions of the user, and the personal basic information comprises sex, height, weight and age. The body-building information is provided by a user, the user can input the body-building information through a mobile phone and other terminals, the body-building purpose is fat reduction, shaping and muscle increasing, and the body-building exercise parts are divided into chest, back, abdomen, waist, shoulders, arms, legs and buttocks.
The user clustering classifying unit 20 is configured to map the fitness information of the user to one user cluster of a plurality of preset user clusters according to a preset classification rule. The preset classification rule may be determined according to actual needs, for example, the preset classification rule is a classification rule of the american society for sports medicine or a classification rule of the chinese society for sports medicine. The user group indicates which fitness group the user belongs to, for example, the user group is male, the BMI range is 24-26, fat is reduced, and the whole body is full, wherein the BMI is the square of weight/height. The user groups are preset and correspond to all possible fitness groups.
The course arrangement unit 30 is configured to search a preset correspondence table for course arrangement modes corresponding to the user groups, where the correspondence table stores a plurality of user groups and corresponding course arrangement modes, and the course arrangement modes include a plurality of course labels arranged according to a predetermined sequence. The correspondence table includes all popular user groups, and each user group is provided with a corresponding course arrangement mode, for example, the user group is male, the BMI range is 24-26, fat is reduced, the course arrangement mode corresponding to the whole body is aerobic, HIIT, rest, aerobic, core strength, lower limb strength and rest, wherein except the rest, the rest represents course labels. The names, the number and the sorting modes of the course labels included in different course sorting modes may be different.
The course generating unit 40 is configured to search a course corresponding to each course tag in the course library according to the course tags in the course arrangement mode, randomly select one of a plurality of courses corresponding to the course tag, and push the selected course to the user. In some specific applications, the curriculums corresponding to aerobic activities are combined with walking and running at levels 2-8, the curriculums corresponding to HIIT are exercises of levels 2-4 and TABATA at levels 2-4, the curriculums corresponding to core strength are exercises of levels 2-5 and abdomen and cores and lower limbs, the curriculums corresponding to lower limb strength are exercises of levels 1-4 and male lower limb strength and lower limb strength 1-4, and numbers in curriculum names represent difficulty levels. When selecting a course, one course is randomly selected from 2-4 levels of HIIT classes and 2-4 levels of TABATA classes of sports courses corresponding to HIIT. The content of the lesson includes, but is not limited to, pictures, audio, video, and the like.
Considering that the physical indexes of the user change during the exercise process of the user, in order to make the exercise course more fit to the physical state of the user, in this embodiment, the user information collecting unit 10 is further configured to collect exercise feedback information provided by the user, where the exercise feedback information includes a course difficulty, a weight variation, and an exercise purpose.
The user clustering classifying unit 20 is further configured to determine whether to map to a new user cluster according to the fitness feedback information according to a preset classification rule. If the user weight variation is too large, or the course difficulty is too large or too small, or the user actively changes the fitness goal, the user may be mapped to a new user group according to the preset classification rule.
The course arrangement unit 30 is further configured to search a course arrangement mode corresponding to a new user group in the correspondence table when the determination result of the user group classification unit 20 is yes, and keep the original course unchanged when the determination result of the user group classification unit 20 is no.
Further, for some courses, the training can be performed only outdoors, but if it is raining, it is inconvenient to learn the course, and in this embodiment, the fitness course intelligent generation system further includes a course adjusting unit 60. The user information collecting unit 10 is also used for receiving lesson changing instructions input by the user.
The lesson-adjusting unit 60 is configured to search the lesson library 50 for other lessons corresponding to the lesson tags of the current lesson according to the lesson-changing instruction.
The lesson generating unit 40 is further configured to present the found lessons in a list manner for the user to select, and push the lessons selected by the user to the user.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (6)

1. An intelligent generation method of fitness courses is characterized by comprising the following steps;
s1: collecting body-building information provided by a user, wherein the body-building information comprises personal basic information, a body-building purpose and a body-building and exercise part of the user, and the personal basic information comprises sex, height, weight and age;
s2: mapping the fitness information of the user to one user group in a plurality of preset user groups according to a preset classification rule;
s3: searching a course arrangement mode corresponding to the user grouping in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groupings and corresponding course arrangement modes thereof, and the course arrangement modes comprise a plurality of course labels arranged according to a preset sequence;
s4: according to the course labels in the course arrangement mode, the course corresponding to each course label is searched in a course library, and one course in a plurality of courses corresponding to the course labels is randomly selected, wherein the course library stores a plurality of courses and the corresponding course labels;
s5: pushing the selected lessons to the user.
2. The method of claim 1, wherein the method further comprises:
s6: collecting fitness feedback information provided by a user, wherein the fitness feedback information comprises course difficulty, weight variation and fitness purpose;
s7: judging whether the user groups are mapped into new user groups according to the preset classification rules or not according to the fitness feedback information;
s8: if yes, looking up the course arrangement mode corresponding to the new user group in the corresponding relation table, and performing steps S4 to S5 again:
s9: if the judgment result is negative, the original course is kept unchanged.
3. The method of claim 1, wherein the method further comprises:
s10: receiving a course changing instruction input by a user;
s11: searching other courses corresponding to the course labels of the current course in a course library according to the course changing instruction;
s12: presenting the found courses in a list mode for a user to select;
s13: and pushing the courses selected by the user to the user.
4. The utility model provides a body-building course intelligence generating system, its characterized in that, body-building course intelligence generating system includes that user information collects the unit, the user divides the group to classify the unit, arranges the class unit, course generating element and course storehouse, the storage has multiple course and its corresponding course label in the course storehouse, wherein:
the user information collecting unit is used for collecting body-building information provided by a user, the body-building information comprises personal basic information, a body-building purpose and a body-building and exercising part of the user, and the personal basic information comprises sex, height, weight and age;
the user grouping and classifying unit is used for mapping the fitness information of the user to one user grouping in a plurality of preset user groupings according to a preset classification rule;
the course arrangement unit is used for searching course arrangement modes corresponding to the user groups in a preset corresponding relation table, wherein the corresponding relation table stores a plurality of user groups and corresponding course arrangement modes, and the course arrangement modes comprise a plurality of course labels arranged according to a preset sequence;
the course generating unit is used for searching the course corresponding to each course label in the course library according to the course labels in the course arrangement mode, randomly selecting one of a plurality of courses corresponding to the course label, and pushing the selected course to the user.
5. The system for intelligently generating fitness courses according to claim 4, wherein the user information collecting unit is further configured to collect fitness feedback information provided by the user, the fitness feedback information including course difficulty, weight variation and fitness goal;
the user grouping and classifying unit is also used for judging whether the user is mapped into a new user grouping according to the preset classification rule by combining the fitness feedback information;
and the course arrangement unit is also used for searching the course arrangement mode corresponding to the new user grouping in the corresponding relation table when the judgment result of the user grouping and classifying unit is yes, and keeping the original course unchanged when the judgment result of the user grouping and classifying unit is no.
6. The intelligent generation system for fitness courses according to claim 4, further comprising a lesson adjusting unit, wherein the user information collecting unit is further configured to receive lesson changing instructions input by a user;
the course adjusting unit is used for searching other courses corresponding to the course labels of the current course in the course library according to the course changing instruction;
the course generating unit is further used for presenting the found courses in a list mode for the user to select, and pushing the courses selected by the user to the user.
CN201910971000.9A 2019-10-14 2019-10-14 Intelligent generation method and system for fitness course Pending CN110727718A (en)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111408114A (en) * 2020-03-05 2020-07-14 埃欧健身管理(上海)有限公司 Method and apparatus for providing a fitness program
CN113379136A (en) * 2021-06-21 2021-09-10 西安理工大学 Multi-objective optimization algorithm-based motion plan generation method
CN113707271A (en) * 2021-10-28 2021-11-26 海门市三德体育用品有限公司 Fitness scheme generation method and system based on artificial intelligence and big data
CN115089938A (en) * 2022-06-15 2022-09-23 珠海格力电器股份有限公司 Motion mode recommendation method and device, electronic motion equipment and storage medium
CN116010693A (en) * 2022-12-28 2023-04-25 广州市玄武无线科技股份有限公司 Information pushing method, device and equipment based on guest group and computer storage medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107335205A (en) * 2017-06-22 2017-11-10 北京卡路里信息技术有限公司 Body-building course recommends method, apparatus, storage medium and processor
CN107424106A (en) * 2017-08-03 2017-12-01 重庆飞豹健身管理有限公司 Self-service body-building course management method
CN108090742A (en) * 2017-12-28 2018-05-29 重庆勤鸟圈科技有限公司 Sport and body-building project management system
CN109816494A (en) * 2019-01-31 2019-05-28 北京卡路里信息技术有限公司 A kind of course recommended method, device, equipment and storage medium
CN109872795A (en) * 2019-03-20 2019-06-11 北京卡路里信息技术有限公司 Body building management method, device, server and storage medium
CN109935299A (en) * 2019-04-12 2019-06-25 北京卡路里信息技术有限公司 A kind of generation method of drill program, device, equipment and storage medium

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107335205A (en) * 2017-06-22 2017-11-10 北京卡路里信息技术有限公司 Body-building course recommends method, apparatus, storage medium and processor
CN107424106A (en) * 2017-08-03 2017-12-01 重庆飞豹健身管理有限公司 Self-service body-building course management method
CN108090742A (en) * 2017-12-28 2018-05-29 重庆勤鸟圈科技有限公司 Sport and body-building project management system
CN109816494A (en) * 2019-01-31 2019-05-28 北京卡路里信息技术有限公司 A kind of course recommended method, device, equipment and storage medium
CN109872795A (en) * 2019-03-20 2019-06-11 北京卡路里信息技术有限公司 Body building management method, device, server and storage medium
CN109935299A (en) * 2019-04-12 2019-06-25 北京卡路里信息技术有限公司 A kind of generation method of drill program, device, equipment and storage medium

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111408114A (en) * 2020-03-05 2020-07-14 埃欧健身管理(上海)有限公司 Method and apparatus for providing a fitness program
CN113379136A (en) * 2021-06-21 2021-09-10 西安理工大学 Multi-objective optimization algorithm-based motion plan generation method
CN113379136B (en) * 2021-06-21 2023-06-27 西安理工大学 Motion plan generation method based on multi-objective optimization algorithm
CN113707271A (en) * 2021-10-28 2021-11-26 海门市三德体育用品有限公司 Fitness scheme generation method and system based on artificial intelligence and big data
CN113707271B (en) * 2021-10-28 2022-02-25 海门市三德体育用品有限公司 Fitness scheme generation method and system based on artificial intelligence and big data
CN115089938A (en) * 2022-06-15 2022-09-23 珠海格力电器股份有限公司 Motion mode recommendation method and device, electronic motion equipment and storage medium
CN116010693A (en) * 2022-12-28 2023-04-25 广州市玄武无线科技股份有限公司 Information pushing method, device and equipment based on guest group and computer storage medium
CN116010693B (en) * 2022-12-28 2023-11-07 广州市玄武无线科技股份有限公司 Information pushing method, device and equipment based on guest group and computer storage medium

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Application publication date: 20200124