CN118454203B - Pull-up intelligent test system and pull-up intelligent test method - Google Patents
Pull-up intelligent test system and pull-up intelligent test method Download PDFInfo
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- 238000013473 artificial intelligence Methods 0.000 claims abstract description 8
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
- A63B23/1209—Involving a bending of elbow and shoulder joints simultaneously
- A63B23/1218—Chinning, pull-up, i.e. concentric movement
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B21/00—Exercising apparatus for developing or strengthening the muscles or joints of the body by working against a counterforce, with or without measuring devices
- A63B21/06—User-manipulated weights
- A63B21/068—User-manipulated weights using user's body weight
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0075—Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
- A63B24/0075—Means for generating exercise programs or schemes, e.g. computerized virtual trainer, e.g. using expert databases
- A63B2024/0081—Coaching or training aspects related to a group of users
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/17—Counting, e.g. counting periodical movements, revolutions or cycles, or including further data processing to determine distances or speed
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2220/00—Measuring of physical parameters relating to sporting activity
- A63B2220/62—Time or time measurement used for time reference, time stamp, master time or clock signal
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B2230/00—Measuring physiological parameters of the user
- A63B2230/62—Measuring physiological parameters of the user posture
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Abstract
The invention discloses a pull-up intelligent test system, which comprises: the intelligent test system comprises a data acquisition module, a data storage module, an intelligent test analysis module, a personalized training module and a user interface module; the data acquisition module is used for collecting the performance data of a user in a test; the data storage module stores the collected data in a database for subsequent analysis and personalized training; the intelligent test analysis module analyzes the user's performance data and can adjust the test difficulty by using an artificial intelligent algorithm. The present invention enables a system to more accurately evaluate the level and capacity characteristics of a user by analyzing the user's performance data using artificial intelligence and machine learning algorithms. This accurate assessment will provide an important basis for the development of personalized training programs.
Description
Technical Field
The invention relates to the technical field of pull-up testing, in particular to a pull-up intelligent testing system and method.
Background
With the increasing fitness and exercise demands, people are increasingly concerned about physical training and improvement of themselves. In the physical training process, the pull-up is used as an important upper body strength training action, and has remarkable effect on improving the strength of muscle groups such as back, arms and the like.
However, the conventional pull-up training has the problems of difficult adjustment, lack of personalized guidance and the like, so that some people cannot effectively improve the training effect in the training process.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present invention has been made in view of the above-mentioned problems with existing pull-up intelligent test systems and methods.
It is therefore an object of the present invention to provide a pull-up intelligent test system and method that is capable of more accurately assessing the level and ability characteristics of a user by analyzing the user's performance data using artificial intelligence and machine learning algorithms. This accurate assessment will provide an important basis for the development of personalized training programs.
In order to solve the technical problems, the invention provides the following technical scheme: a pull-up intelligent test system, comprising: the intelligent test system comprises a data acquisition module, a data storage module, an intelligent test analysis module, a personalized training module and a user interface module;
the data acquisition module is used for collecting the performance data of a user in a test;
The data storage module stores the collected data in a database for subsequent analysis and personalized training;
The intelligent test analysis module analyzes the performance data of the user by using an artificial intelligent algorithm and can adjust the test difficulty;
the personalized training module analyzes performance data of the user by utilizing a machine learning algorithm and generates a personalized training plan based on an analysis result;
the user interface module provides an interface through which a user tests and trains, and through which the user tests and views a personalized training program.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the pull-up intelligent test method comprises the following steps:
Step one: and (3) data collection: the system collects data generated by a user in the testing and training process through an interface in the user interface;
Step two: data analysis: analyzing the collected data by using an intelligent test analysis module, and analyzing the performance of a user by using an artificial intelligent algorithm;
Step three: and (3) test adjustment: according to the result of data analysis, the difficulty of the test is adjusted, and the level of the test is matched with that of a user, so that the accuracy and the effectiveness of the test are improved;
Step four: training plan generation: generating a personalized training plan by using a machine learning algorithm to help a user to improve own performance;
Step five: personalized feedback: the system provides personalized feedback information for the user, including test results, learning suggestions and progress conditions, and helps the user to know own performances and improve learning effects.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the user performance data collected in the first step comprises pull-up times, time and posture information of the user, the collection process can be carried out by wearing a bracelet and a foot ring, sensors are arranged on the bracelet and the foot ring, and in addition, an infrared detection head can be arranged on a horizontal bar on the pull-up to monitor the posture information of the user.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the artificial intelligence algorithm in the second step comprises the following steps:
let the number of pull-up times of the user be The time isThe posture isTaking into account that the number of pull-ups of a user is time and gesture dependent, introducing a functionFor comprehensively evaluating user's performance data to form a composite score：
Wherein, Is a multiple function combining different combinations of pull-up times, time and posture;
Function of The following are provided:。
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the difficulty adjustment in the third step is required to be based on the performance data of the user To adjust, so that the test difficulty is matched with the capability of the user, and a function is introducedThe input is the user comprehensive scoreThe output is the adjusted test difficulty，
Wherein the function is adjustedThe following are provided:。
as a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the machine learning algorithm in the fourth step comprises:
Number of pull-up times completed by the user Completion timeError rateDefining pull-up capability scoresFor the comprehensive evaluation index, the calculation formula is as follows:
Wherein, 、、The number of pull-up times, the completion time and the weight of error rate of the user in the evaluation are respectively calculated, the relation between pull-up test data and the score of the user is fitted through a support vector machine, and the optimal parameter configuration is obtained through a training model、、And then predicting the pull-up ability score of the user according to the trained model and giving a corresponding training plan.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the detailed steps for making the personalized training plan in the fourth step are as follows:
S1, preliminary evaluation:
preliminary evaluating the training level of the user according to the pull-up ability score of the user, determining the current strength and improvement space, and setting long-term and short-term training targets;
S2, setting a target:
Based on the preliminary evaluation, specific pull-up training goals are set, including: the number of times of completion is increased, the time of completion is shortened, and the error rate is reduced;
S3, formulating training content:
According to the set training target, specific pull-up training content is formulated;
S4, setting training frequency:
determining a weekly training frequency and duration based on the training content and the pull-up capability score of the user;
S5, monitoring and adjusting:
and in the training process of the user, the performance data and the performance data of the user are monitored regularly, and a training plan is adjusted according to the performance.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the training content comprises targeted pull-up training actions, group numbers, times and rest time.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the pull-up training action includes:
Basic pull-up action: the included angle between the arm and the ground is controlled, and the coordination of the straightening action is paid attention to;
pull-up weight training: training by using a load instrument hung between waists, and increasing the strength of the upper body;
Reverse pull-up: training the forearm and latissimus dorsi;
The hands and feet are pulled up by the pull-up body: the whole body strength is exercised, and the whole stability is improved.
As a preferred embodiment of the pull-up intelligent test system of the present invention, wherein: the system is also provided with a personalized feedback module, when a user performs training, performance data and performance data of the user are monitored in real time, a training plan is continuously adjusted, the user is ensured not to fall into a bottleneck state while continuously improving, and the user can check the personalized training plan and the training progress of the user, so that the training process of the user is better managed.
The invention has the beneficial effects that: 1. personalized test experience: by dynamically adjusting the test difficulty, the system can provide a personalized test experience according to the actual capability level of the user. This will make users feel challenges and accomplishment and increase their engagement and motivation; 2. accurately evaluating user capability: by analyzing the user's performance data using artificial intelligence and machine learning algorithms, the system is able to more accurately assess the user's level and ability characteristics. The accurate evaluation provides important basis for the establishment of personalized training plans; 3. training efficiency is improved: by analyzing the test performance data of the user and generating a personalized training program, the system can train and guide targeted to the advantages and disadvantages of the user. Such personalized training would more efficiently promote the user's ability level.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a schematic diagram of a pull-up intelligent test system and method according to the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Further, in describing the embodiments of the present invention in detail, the cross-sectional view of the device structure is not partially enlarged to a general scale for convenience of description, and the schematic is only an example, which should not limit the scope of protection of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Referring to fig. 1, there is provided a pull-up intelligent test system comprising:
the intelligent test system comprises a data acquisition module, a data storage module, an intelligent test analysis module, a personalized training module and a user interface module;
the data acquisition module is used for collecting the performance data of a user in a test;
The data storage module stores the collected data in a database for subsequent analysis and personalized training;
The intelligent test analysis module analyzes the performance data of the user by using an artificial intelligent algorithm and can adjust the test difficulty;
the personalized training module analyzes performance data of the user by utilizing a machine learning algorithm and generates a personalized training plan based on an analysis result;
the user interface module provides an interface through which a user tests and trains, and through which the user tests and views a personalized training program.
The pull-up intelligent test method comprises the following steps of:
Step one: and (3) data collection: the system collects data generated by a user in the testing and training process through an interface in the user interface;
Step two: data analysis: analyzing the collected data by using an intelligent test analysis module, and analyzing the performance of a user by using an artificial intelligent algorithm;
Step three: and (3) test adjustment: according to the result of data analysis, the difficulty of the test is adjusted, and the level of the test is matched with that of a user, so that the accuracy and the effectiveness of the test are improved;
Step four: training plan generation: generating a personalized training plan by using a machine learning algorithm to help a user to improve own performance;
Step five: personalized feedback: the system provides personalized feedback information for the user, including test results, learning suggestions and progress conditions, and helps the user to know own performances and improve learning effects.
Furthermore, the user performance data collected in the first step includes the pull-up times, time and posture information of the user, the collection process can be carried out by wearing the bracelet and the foot ring, the bracelet and the foot ring are both provided with sensors, and in addition, the infrared detection head can be arranged on the horizontal bar on the pull-up to monitor the posture information of the user.
Specifically, the artificial intelligence algorithm in the second step includes:
let the number of pull-up times of the user be The time isThe posture isTaking into account that the number of pull-ups of a user is time and gesture dependent, introducing a functionFor comprehensively evaluating user's performance data to form a composite score：
Wherein, Is a multiple function combining different combinations of pull-up times, time and posture; function ofThe following are provided:
The difficulty adjustment in the third step is required to be based on the performance data of the user To adjust, so that the test difficulty is matched with the capability of the user, and a function is introducedThe input is the user comprehensive scoreThe output is the adjusted test difficulty，
Wherein the function is adjustedThe following are provided:
let us assume that we have a user a who has completed 10 pull-up actions when performing pull-up tests, completed in 60 seconds with a pose score of 8 (pose score range 0 to 10, 10 being the best pose).
We will calculate the composite score for user a from this dataAnd adjusts the difficulty of the test according to the score。
Specific examples: data carried into user a:，+0.8，.96
Adjusting the testing difficulty D: ，，.9815
Thus, the composite score for user A is about 3.96 and the test difficulty is adjusted to about 0.9815, which means that the test difficulty is adjusted to a relatively high level to match the competency level of user A.
Further, the machine learning algorithm in the fourth step includes:
Number of pull-up times completed by the user Completion timeError rateDefining pull-up capability scoresFor the comprehensive evaluation index, the calculation formula is as follows:
Wherein, 、、The number of pull-up times, the completion time and the weight of error rate of the user in the evaluation are respectively calculated, the relation between pull-up test data and the score of the user is fitted through a support vector machine, and the optimal parameter configuration is obtained through a training model、、Then predicting pull-up ability scores of the users according to the trained models and giving corresponding training plans;
specific examples: let us assume that we get the following parameter configuration by training the support vector machine algorithm: 、、 0.8, 0.6, 0.5, respectively, according to the above formula, we can calculate the pull-up capability score v of the user, and if the number of pull-ups completed by the user is x=15, the completion time y=0.5 seconds, and the error rate z=0.2, then substituting the formula to calculate: ，13.1
the pull-up capability score of the user is 13.1, according to which the user can have a more intuitive knowledge of his own training table and increase the pull-up capability level according to a personalized training plan, specifically as follows:
the detailed steps of making the personalized training plan in the fourth step are as follows:
S1, preliminary evaluation:
preliminary evaluating the training level of the user according to the pull-up ability score of the user, determining the current strength and improvement space, and setting long-term and short-term training targets;
S2, setting a target:
Based on the preliminary evaluation, specific pull-up training goals are set, including: the number of times of completion is increased, the time of completion is shortened, and the error rate is reduced;
S3, formulating training content:
According to the set training target, specific pull-up training content is formulated;
S4, setting training frequency:
determining a weekly training frequency and duration based on the training content and the pull-up capability score of the user;
S5, monitoring and adjusting:
and in the training process of the user, the performance data and the performance data of the user are monitored regularly, and a training plan is adjusted according to the performance.
Specifically, the training content includes a targeted pull-up training action, a group number, a number of times and a rest time, and the pull-up training action includes:
Basic pull-up action: the included angle between the arm and the ground is controlled, and the coordination of the straightening action is paid attention to;
pull-up weight training: training by using a load instrument hung between waists, and increasing the strength of the upper body;
Reverse pull-up: training the forearm and latissimus dorsi;
The hands and feet are pulled up by the pull-up body: the whole body strength is exercised, and the whole stability is improved.
The following is an example table showing pull-up training programs corresponding to different scores. Each training program includes a targeted pull-up training action, a training set number, a number of times per set, and a rest time to adjust to different competence levels of the user.
The system is also provided with a personalized feedback module, when a user performs training, performance data and performance data of the user are monitored in real time, a training plan is continuously adjusted, the user is ensured not to fall into a bottleneck state while continuously improving, and the user can check the personalized training plan and the training progress of the user, so that the training process of the user is better managed.
The invention has the following effects: 1. personalized test experience: by dynamically adjusting the test difficulty, the system can provide a personalized test experience according to the actual capability level of the user. This will make users feel challenges and accomplishment and increase their engagement and motivation; 2. accurately evaluating user capability: by analyzing the user's performance data using artificial intelligence and machine learning algorithms, the system is able to more accurately assess the user's level and ability characteristics. The accurate evaluation provides important basis for the establishment of personalized training plans; 3. training efficiency is improved: by analyzing the test performance data of the user and generating a personalized training program, the system can train and guide targeted to the advantages and disadvantages of the user. Such personalized training would more efficiently promote the user's ability level; 4. user engagement promotion: by providing a user-friendly interface and updating the test system and personalized training program in real time, the system can increase user engagement. The user can conveniently check the performance data and the training plan of the user, and obtain targeted feedback and advice at the same time, so that the user can participate in the test and training more actively; 5. the system can continuously develop: the system adopts advanced artificial intelligence and machine learning technology, and can dynamically adjust the test difficulty and personalized training plan according to the real-time performance of the user. This allows for a good sustainable development of the system, being able to continuously adapt to the needs of the user and to changing circumstances.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (5)
1. A pull-up intelligent test system, comprising:
the intelligent test system comprises a data acquisition module, a data storage module, an intelligent test analysis module, a personalized training module and a user interface module;
the data acquisition module is used for collecting the performance data of a user in a test;
The data storage module stores the collected data in a database for subsequent analysis and personalized training;
The intelligent test analysis module analyzes the performance data of the user by using an artificial intelligent algorithm and can adjust the test difficulty;
the personalized training module analyzes performance data of the user by utilizing a machine learning algorithm and generates a personalized training plan based on an analysis result;
the user interface module provides an interface for testing and training by a user, and the user tests and checks the personalized training plan through the interface;
The testing method of the pull-up intelligent testing system comprises the following steps of:
Step one: and (3) data collection: the system collects data generated by a user in the testing and training process through an interface in the user interface;
Step two: data analysis: analyzing the collected data by using an intelligent test analysis module, and analyzing the performance of a user by using an artificial intelligent algorithm;
Step three: and (3) test adjustment: according to the result of data analysis, the difficulty of the test is adjusted, and the level of the test is matched with that of a user, so that the accuracy and the effectiveness of the test are improved;
Step four: training plan generation: generating a personalized training plan by using a machine learning algorithm to help a user to improve own performance;
step five: personalized feedback: the system provides personalized feedback information for the user, including test results, learning suggestions and progress conditions, and helps the user to know own performances and improve learning effects;
the user performance data collected in the first step comprises the pull-up times, time and posture information of the user, the collection process can be carried out by wearing a bracelet and a foot ring, sensors are arranged on the bracelet and the foot ring, and in addition, an infrared detection head can be arranged on a horizontal bar on the pull-up to monitor the posture information of the user;
The artificial intelligence algorithm in the second step comprises the following steps:
let the number of pull-up times of the user be The time isThe posture isTaking into account that the number of pull-ups of a user is time and gesture dependent, introducing a functionFor comprehensively evaluating user's performance data to form a composite score：
Wherein, Is a multiple function combining different combinations of pull-up times, time and posture;
Function of The following are provided:
The difficulty adjustment in the third step is required to be based on the performance data of the user To adjust, so that the test difficulty is matched with the capability of the user, and a function is introducedThe input is the user comprehensive scoreThe output is the adjusted test difficulty，
Wherein the function is adjustedThe following are provided:
The machine learning algorithm in the fourth step comprises:
Number of pull-up times completed by the user Completion timeError rateDefining pull-up capability scoresFor the comprehensive evaluation index, the calculation formula is as follows:
Wherein, 、、The number of pull-up times, the completion time and the weight of error rate of the user in the evaluation are respectively calculated, the relation between pull-up test data and the score of the user is fitted through a support vector machine, and the optimal parameter configuration is obtained through a training model、、And then predicting the pull-up ability score of the user according to the trained model and giving a corresponding training plan.
2. The pull-up intelligent test system according to claim 1, wherein: the detailed steps for making the personalized training plan in the fourth step are as follows:
S1, preliminary evaluation:
preliminary evaluating the training level of the user according to the pull-up ability score of the user, determining the current strength and improvement space, and setting long-term and short-term training targets;
S2, setting a target:
Based on the preliminary evaluation, specific pull-up training goals are set, including: the number of times of completion is increased, the time of completion is shortened, and the error rate is reduced;
S3, formulating training content:
According to the set training target, specific pull-up training content is formulated;
S4, setting training frequency:
determining a weekly training frequency and duration based on the training content and the pull-up capability score of the user;
S5, monitoring and adjusting:
and in the training process of the user, the performance data and the performance data of the user are monitored regularly, and a training plan is adjusted according to the performance.
3. The pull-up intelligent test system according to claim 2, wherein: the training content comprises targeted pull-up training actions, group numbers, times and rest time.
4. The pull-up intelligent test system according to claim 3, wherein: the pull-up training action includes:
Basic pull-up action: the included angle between the arm and the ground is controlled, and the coordination of the straightening action is paid attention to;
pull-up weight training: training by using a load instrument hung between waists, and increasing the strength of the upper body;
Reverse pull-up: training the forearm and latissimus dorsi;
The hands and feet are pulled up by the pull-up body: the whole body strength is exercised, and the whole stability is improved.
5. The pull-up intelligent test system according to claim 1, wherein: the system is also provided with a personalized feedback module, when a user performs training, performance data and performance data of the user are monitored in real time, a training plan is continuously adjusted, the user is ensured not to fall into a bottleneck state while continuously improving, and the user can check the personalized training plan and the training progress of the user, so that the training process of the user is better managed.
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