CN116246780A - Method and device for evaluating fitness, electronic equipment and storage medium - Google Patents
Method and device for evaluating fitness, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116246780A CN116246780A CN202211611162.XA CN202211611162A CN116246780A CN 116246780 A CN116246780 A CN 116246780A CN 202211611162 A CN202211611162 A CN 202211611162A CN 116246780 A CN116246780 A CN 116246780A
- Authority
- CN
- China
- Prior art keywords
- user
- data
- fitness
- evaluation
- dead time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/1036—Measuring load distribution, e.g. podologic studies
- A61B5/1038—Measuring plantar pressure during gait
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1116—Determining posture transitions
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The present disclosure relates to a method, an apparatus, an electronic device, and a storage medium for evaluating fitness, the method comprising: acquiring basic information of a user currently performing body fit assessment; after a user finishes a target action by using an auxiliary sports apparatus, collecting sensing data of a motion capture sensor on the auxiliary sports apparatus; collecting mechanical data based on a preset plantar force measuring device; based on the sensory data and the mechanical data, the user's fitness can be assessed. Compared with the prior art, the method and the device for evaluating the fitness of the user based on the sensing data and the mechanical data have the advantages that the dependence on the expertise of the evaluator is reduced, the transformation of the artificial subjective evaluation to the standardization and the datamation evaluation is realized, the rapid and scientific evaluation of the fitness of different people can be realized, and the method is convenient to apply and quick to use, and has the large-area popularization and general adaptability.
Description
Technical Field
The disclosure relates to the field of computer technology, and in particular relates to a method and device for evaluating fitness, electronic equipment and a storage medium.
Background
The fitness evaluation mainly evaluates physical quality of a human body, namely the ability of the human body to perform skills such as strength, speed, endurance, flexibility, sensitivity, balance, coordination and the like in the exercise process, and is an important component in exercise training and exercise physiology.
Along with the progress and development of scientific technology, the exercise capacity and physical quality are subjected to refinement, data and standardization assessment and monitoring, the relevant exercise level can be analyzed, calculated and enhanced, and a more reasonable method is adopted to improve the exercise performance and reduce the exercise damage. The use of more advanced intelligent aids for exercise assessment and training is also a major advantage.
The existing fitness evaluation method is mainly characterized in that evaluation staff tests and scores some specific actions by means of own professional knowledge, so that the evaluation method is a subjective evaluation mode, different evaluation staff can generate different evaluations for the same athlete, the error is large, and quantitative and accurate evaluation cannot be performed on a large number of sports people.
Disclosure of Invention
In order to solve the technical problems described above or at least partially solve the technical problems described above, the present disclosure provides a method, an apparatus, an electronic device, and a storage medium for evaluating fitness.
In a first aspect, embodiments of the present disclosure provide a method of assessing fitness, the method including pre-installing a motion capture sensor on an auxiliary sports implement, the method comprising:
acquiring basic information of a user currently performing body fit assessment;
after a user finishes a target action by using an auxiliary sports apparatus, collecting sensing data of a motion capture sensor on the auxiliary sports apparatus;
collecting mechanical data based on a preset plantar force measuring device;
based on the sensory data and the mechanical data, the user's fitness can be assessed.
In some embodiments, after the obtaining the basic information of the user currently performing the fitness evaluation, the method further includes:
determining an evaluation item to be evaluated by the user;
and determining a target action corresponding to the evaluation item.
In some embodiments, the assessment item includes at least one of:
strength, speed, endurance, flexibility, sensitivity, balance, and coordination.
In some embodiments, before the assessing the fitness of the user based on the sensed data and the mechanical data, the method further comprises:
acquiring moving image data of the user based on a camera;
the moving image data is displayed on a display of the terminal so that an evaluator views the evaluation process in real time.
In some embodiments, the evaluating the fitness of the user based on the sensed data and the mechanical data comprises:
converting the sensory data into torso pose data of the user;
calculating the dead time of the user based on the mechanical data;
and respectively evaluating the body fit of the user according to the first difference value of the trunk gesture data and the standard trunk gesture data of the user and the second difference value of the dead time and the standard dead time of the user to obtain a body fit evaluation result of the user.
In some embodiments, the converting the sensory data into torso pose data of the user includes:
acquiring a conversion relation between the sensing data and trunk posture data of the user;
and converting the sensing data into trunk gesture data of the user based on the conversion relation.
In some embodiments, the estimating the fitness of the user according to the first difference value between the torso gesture data and the standard torso gesture data of the user and the second difference value between the dead time and the standard dead time of the user, to obtain a fitness estimation result of the user includes:
determining a trunk gesture grade corresponding to trunk gesture data of the user from the corresponding relation between the first difference value and the trunk gesture grade;
determining a dead time grade corresponding to the dead time of the user 5 from the corresponding relation between the second difference value and the dead time grade;
based on the trunk gesture grade and the dead time grade, obtaining the overall grade of the body fit of the user;
according to the torso posture level, the dead time level and the user's fitness
And (3) generating a fitness evaluation result of the user according to the overall grade, wherein the fitness evaluation result 0 comprises a fitness evaluation report and a guiding suggestion.
In a second aspect, embodiments of the present disclosure provide a fitness evaluation device, comprising:
the acquisition module is used for acquiring basic information of a user currently performing body fit evaluation;
the first acquisition module is used for acquiring sensing data of a motion capture sensor on the auxiliary sports apparatus after a user finishes a target motion by using the auxiliary sports apparatus;
the second acquisition module is used for acquiring mechanical data based on a preset plantar force measuring device;
and the evaluation module is used for evaluating the body fitness of the user based on the sensing data and the mechanical data.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including:
a memory;
a 0 processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to the first aspect.
In a fourth aspect, embodiments of the present disclosure provide a storage medium having stored thereon a computer 5 program for execution by a processor to implement the method as described in the first aspect.
In a fifth aspect, embodiments of the present disclosure also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implement a method as described in the first aspect.
According to the body fit energy assessment method, the device, the electronic equipment and the storage medium, basic information of a user currently performing body fit energy assessment is acquired, after the user finishes a target action by using an auxiliary sports apparatus, sensing data of a motion capture sensor on the auxiliary sports apparatus are acquired, mechanical data are acquired based on a preset plantar force measuring device, and body fit energy of the user is assessed based on the sensing data and the mechanical data. Compared with the prior art, the method reduces the dependence on the expertise of the evaluator, can realize the rapid and scientific evaluation of the adaptability of different crowds, is convenient to apply and quick to use, and has the capacity of large-area popularization and universality.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flowchart of a method for assessing fitness according to an embodiment of the present disclosure;
FIG. 2 is a flowchart of a method for assessing fitness according to another embodiment of the present disclosure;
FIG. 3 is a flowchart of a method for assessing fitness according to another embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a fitness evaluation device according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
The fitness evaluation mainly evaluates physical quality of a human body, namely the ability of the human body to perform skills such as strength, speed, endurance, flexibility, sensitivity, balance, coordination and the like in the exercise process, and is an important component in exercise training and exercise physiology.
Along with the progress and development of scientific technology, the exercise capacity and physical quality are subjected to refinement, data and standardization assessment and monitoring, the relevant exercise level can be analyzed, calculated and enhanced, and a more reasonable method is adopted to improve the exercise performance and reduce the exercise damage. The use of more advanced intelligent aids for exercise assessment and training is also a major advantage.
The existing fitness evaluation method is mainly characterized in that evaluation staff tests and scores some specific actions by means of own professional knowledge, so that the evaluation method is a subjective evaluation mode, different evaluation staff can generate different evaluations for the same athlete, the error is large, and quantitative and accurate evaluation cannot be performed on a large number of sports people.
In view of this problem, embodiments of the present disclosure provide a method for assessing fitness, which is described below in connection with specific embodiments.
Fig. 1 is a flowchart of a method for evaluating fitness according to an embodiment of the present disclosure, where the method may be applied to a terminal, for example, a computer, as shown in fig. 1, and the method includes the following steps:
s101, acquiring basic information of a user currently performing fitness evaluation.
The terminal obtains basic information of the user currently performing the fitness assessment, which in some embodiments includes age, gender, height, weight, etc.
S102, after a user finishes a target action by using an auxiliary sports apparatus, acquiring sensing data of a motion capture sensor on the auxiliary sports apparatus.
The motion capture sensor is mounted on the auxiliary sports apparatus in advance. The motion capture sensor is fixed with auxiliary sports equipment (such as a sports rod and a ball) through a fitting part in a hardware connection mode, and is connected with a terminal in a wired/wireless mode and used for data transmission. After a user finishes a target action by using the auxiliary sports apparatus, the action capturing sensor collects sensing data of the auxiliary sports apparatus and sends the sensing data to the terminal, and the terminal can be used for collecting sensing data of all parts of the body of the tested user in real time during the movement. For example, the target motion is a scoliosis motion, the auxiliary sports apparatus can indirectly reflect the scoliosis angle, and the change value of the sports angle in the scoliosis direction can be read and recorded by collecting the data of the sensor. The sensing data may be attitude angle data of the auxiliary sports apparatus, including pitch angle, yaw angle, roll angle.
S103, acquiring mechanical data based on a preset plantar force measuring device.
The plantar force measuring device needs an external power supply, is connected with the terminal in a wired/wireless mode and transmits data, and can be used for collecting real-time data and change data of plantar pressure distribution of a measured user in real time and transmitting the data to the terminal. For example, the user to be tested stands on the plantar force measuring device with feet, the gravity center distribution data of the user to be tested can be recorded, and the pressure change data at each moment can be recorded when the user to be tested jumps. The terminal can collect mechanical data based on a preset plantar force measuring device. The mechanical data comprise gravity center distribution data and pressure change data at each moment, and the dead time of the tested user can be calculated according to the pressure change data at each moment to reflect the body fit condition of the user.
And S104, based on the sensing data and the mechanical data, assessing the fitness of the user.
After the sensing data and the mechanical data are collected, the terminal can evaluate the body fit of the user according to the sensing data and the mechanical data. In some embodiments, standard sensing data and standard mechanical data corresponding to users of various ages, sexes, heights and weights are stored in the terminal, the terminal compares the sensing data and differences between the mechanical data and the corresponding standard sensing data and standard mechanical data, and the body fit of the users is evaluated according to the difference conditions.
In some embodiments, the terminal may upload the sensing data and the mechanical data to a server, and evaluate, by the server, the fitness of the user, and return the evaluation result to the terminal.
According to the embodiment of the disclosure, basic information of a user currently performing body fit energy assessment is acquired, after the user finishes a target action by using an auxiliary sports apparatus, sensing data of a motion capture sensor on the auxiliary sports apparatus are acquired, mechanical data are acquired based on a preset plantar force measuring device, and body fit energy of the user is assessed based on the sensing data and the mechanical data. Compared with the prior art, the method reduces the dependence on the expertise of the evaluator, can realize the rapid and scientific evaluation of the adaptability of different crowds, is convenient to apply and quick to use, and has the capacity of large-area popularization and universality.
Fig. 2 is a flowchart of a method for assessing fitness according to another embodiment of the present disclosure, as shown in fig. 2, where the method includes the following steps:
s201, acquiring basic information of a user currently performing fitness evaluation.
Specifically, the implementation process and principle of S201 and S101 are consistent, and will not be described herein.
S202, determining the evaluation items to be evaluated by the user.
For example, the user may select an evaluation item, and the terminal determines the evaluation item to be evaluated by the user in response to the selection operation of the user. The evaluation item includes at least one of: strength, speed, endurance, flexibility, sensitivity, balance, and coordination. The user may select one or more items for fitness evaluation.
S203, determining a target action corresponding to the evaluation item.
After determining the evaluation item to be evaluated, the terminal may determine a target action corresponding to the evaluation item. The items evaluated are different, as are the target actions. For example, when the assessment item is strength, the target action may be weight lifting or the like.
S204, after the user finishes the target action by using the auxiliary sports apparatus, collecting the sensing data of the action capturing sensor on the auxiliary sports apparatus.
Specifically, the implementation process and principle of S204 and S102 are consistent, and will not be described herein.
S205, mechanical data are collected based on a preset plantar force measuring device.
Specifically, the implementation process and principle of S205 and S103 are consistent, and will not be described herein.
S206, converting the sensing data into trunk gesture data of the user.
The sensing data of the auxiliary sports apparatus can be directly read through collecting the data of the sensor, and the terminal converts the sensing data into the trunk gesture data of the user, so that the motion angle change value of the trunk of the user can be read. The sensing data may be attitude angle data of the auxiliary sports apparatus, including pitch angle, yaw angle, roll angle. Torso pose data also includes pitch angle, yaw angle, roll angle. The sensing data and the trunk gesture data of the user have a corresponding relation, so that conversion can be realized.
In some embodiments, S206 includes, but is not limited to, S2061, S2062:
s2061, acquiring a conversion relation between the sensing data and the trunk gesture data of the user.
The terminal stores the conversion relation between the sensing data and the trunk gesture data of the user, and the terminal can acquire the conversion relation between the sensing data and the trunk gesture data of the user.
S2062, converting the sensing data into torso posture data of the user based on the conversion relationship.
Further, the terminal can convert the sensing data into torso posture data of the user according to the conversion relation.
S207, calculating the dead time of the user based on the mechanical data.
After the mechanical data is acquired, the terminal can calculate the dead time of the user according to the mechanical data. The mechanical data comprise gravity center distribution data and pressure change data at each moment, the dead time of the tested user can be calculated through the pressure change data at each moment, and the time interval corresponding to the non-zero pressure value at two times is the dead time of the tested user, so that the condition of the body fit of the user is reflected. For example, if the measured pressure value is 100N at 0 seconds, 0 at 1-4 seconds, and 100N at 5 seconds, the dead time is 5-0=5 seconds.
S208, according to the first difference value of the trunk gesture data and the standard trunk gesture data of the user and the second difference value of the dead time and the standard dead time of the user, the body fit of the user is evaluated respectively, and the body fit evaluation result of the user is obtained.
The terminal obtains the standard value corresponding to each motion parameter (namely the trunk gesture data and the dead time in the example), the trunk gesture data of the user and the dead time of the user are equivalent to the test value when the tested user executes the target action, and the quality of the current execution target action of the tested user can be evaluated through the difference between the test value and the standard value. Specifically, the terminal evaluates the body fit of the user according to a first difference value of the trunk gesture data and the standard trunk gesture data of the user and a second difference value of the dead time and the standard dead time of the user, and obtains a body fit evaluation result of the user.
According to the method and the device, basic information of a user currently performing fitness evaluation is acquired, an evaluation item to be evaluated of the user is determined, and a target action corresponding to the evaluation item is determined. After a user finishes a target action by using an auxiliary sports apparatus, sensing data of an action capturing sensor on the auxiliary sports apparatus are collected, and mechanical data are collected based on a preset plantar force measuring device. Further, the sensing data is converted into trunk gesture data of the user, and the dead time of the user is calculated based on the mechanical data. And further, according to the first difference value of the trunk gesture data and the standard trunk gesture data of the user and the second difference value of the dead time and the standard dead time of the user, the body fit of the user is respectively evaluated, and the body fit evaluation result of the user is obtained. The motion capture sensor and the plantar force measuring device are used as tools, the fitness level is comprehensively analyzed through a sensor algorithm, background data analysis and a motion scheme data calculation method, the motion capacity of a user is evaluated in real time, the fitness evaluation result of the user is obtained, the fitness capacity of different people is rapidly and scientifically evaluated, the dependence on the expertise of an evaluator is reduced, and the method is convenient to apply and quick to use and has the capacity of large-area popularization and general application.
Fig. 3 is a flowchart of a method for assessing fitness according to another embodiment of the present disclosure, as shown in fig. 3, where the method includes the following steps:
s301, acquiring basic information of a user currently performing fitness evaluation.
Specifically, the implementation process and principle of S301 and S101 are identical, and will not be described herein.
S302, after a user finishes a target action by using an auxiliary sports apparatus, sensing data of a motion capture sensor on the auxiliary sports apparatus are collected.
Specifically, the implementation process and principle of S302 and S102 are consistent, and will not be described herein.
S303, acquiring mechanical data based on a preset plantar force measuring device.
Specifically, the implementation process and principle of S303 and S103 are identical, and will not be described herein.
S304, acquiring the moving image data of the user based on the camera.
The camera and the terminal are connected in a wired/wireless mode and are used for acquiring image data of a tested user in real time in a target action process, transmitting the data to the terminal, and the terminal acquires moving image data of the user through the camera.
And S305, displaying the moving image data on a display of the terminal so that an evaluator can watch the evaluation process in real time.
After the moving image data of the user is acquired, the moving image data is displayed on a display of a terminal, so that an evaluator can watch the evaluation process in real time, and the evaluator can monitor the evaluation process to realize visualization.
S306, converting the sensing data into trunk gesture data of the user.
Specifically, the implementation process and principle of S306 and S206 are consistent, and will not be described herein.
S307, calculating the dead time of the user based on the mechanical data.
Specifically, the implementation process and principle of S307 and S207 are identical, and will not be described here again.
S308, determining the trunk gesture grade corresponding to the trunk gesture data of the user from the corresponding relation between the first difference value and the trunk gesture grade.
The corresponding relation between the first difference value and the trunk posture grade is stored in the terminal, the terminal can calculate the first difference value between the trunk posture data of the user and the standard trunk posture data, and then the trunk posture grade corresponding to the trunk posture data of the user is determined from the corresponding relation between the first difference value and the trunk posture grade.
S309, determining the idle time grade corresponding to the idle time of the user from the corresponding relation between the second difference value and the idle time grade.
The corresponding relation between the second difference value and the dead time grade is stored in the terminal, the terminal can calculate the second difference value between the dead time of the user and the standard dead time, and further the dead time grade corresponding to the dead time of the user is determined from the corresponding relation between the second difference value and the dead time grade.
And S310, obtaining the overall fitness level of the user based on the trunk gesture level and the dead time level.
The terminal can obtain the overall level of the fitness of the user according to the body posture level and the dead time level. For example, the torso posture level and the dead time level are integrated to obtain an overall level of fitness of the user, which corresponds to a single score level according to each action, and a total score level is obtained.
And S311, generating a fitness evaluation result of the user according to the torso posture grade, the dead time grade and the fitness overall grade of the user, wherein the fitness evaluation result comprises a fitness evaluation report and a guiding suggestion.
The terminal can generate the body fit assessment result of the user, namely a professional body fit assessment report and a guidance suggestion according to the body posture grade, the dead time grade and the body fit overall grade of the user, so that quick and scientific analysis and guidance of the body fit capacities of different people are realized.
According to the embodiment of the disclosure, basic information of a user currently performing fitness evaluation is acquired, after the user finishes a target action by using an auxiliary sports apparatus, sensing data of a motion capture sensor on the auxiliary sports apparatus are acquired, and mechanical data are acquired based on a preset plantar force measuring device. And acquiring moving image data of the user based on a camera, and displaying the moving image data on a display of a terminal so that an evaluator can watch the evaluation process in real time. Further, the sensing data are converted into trunk gesture data of the user, the dead time of the user is calculated based on the mechanical data, the trunk gesture grade corresponding to the trunk gesture data of the user is determined from the corresponding relation between the first difference value and the trunk gesture grade, the dead time grade corresponding to the dead time of the user is determined from the corresponding relation between the second difference value and the dead time grade, and the body fitness integral grade of the user is obtained based on the trunk gesture grade and the dead time grade. And generating a fitness evaluation result of the user according to the trunk gesture grade, the dead time grade and the fitness overall grade of the user, wherein the fitness evaluation result comprises a fitness evaluation report and a guiding suggestion. The motion capture sensor, the plantar force measuring device and the camera are used as tools, the fitness level is comprehensively analyzed through a sensor algorithm, background data analysis and a motion scheme data calculation method, the motion capability of a user is evaluated in real time, and a fitness evaluation report and a guidance suggestion are given according to an evaluation result, so that the rapid and scientific analysis and guidance of the fitness capability of different people are realized, the dependence on the expertise of an evaluator is reduced, the transformation of the artificial subjective evaluation to the standardized and dataized evaluation is realized, and the method is convenient to apply and quick to use, and has the capability of large-area popularization and general application.
Fig. 4 is a schematic structural diagram of a fitness evaluation device according to an embodiment of the present disclosure. The fitness evaluation device may be a terminal as described in the above embodiments, or the fitness evaluation device may be a part or component in the terminal. The fitness evaluation device provided in the embodiments of the present disclosure may execute the processing flow provided in the embodiment of the method for evaluating the fitness, as shown in fig. 4, where the fitness evaluation device 40 includes: an acquisition module 41, a first acquisition module 42, a second acquisition module 43, an evaluation module 44; the acquiring module 41 is configured to acquire basic information of a user currently performing a fitness evaluation; the first acquisition module 42 is used for acquiring sensing data of a motion capture sensor on the auxiliary sports apparatus after a user finishes a target motion by using the auxiliary sports apparatus; the second acquisition module 43 is used for acquiring mechanical data based on a preset plantar force measuring device; the evaluation module 44 is configured to evaluate the fitness of the user based on the sensing data and the mechanical data.
Optionally, the apparatus 40 further includes: a first determination module 45, a second determination module 46; the first determining module 45 is configured to determine an evaluation item to be evaluated by the user; the second determining module 46 is configured to determine a target action corresponding to the evaluation item.
Optionally, the evaluation item includes at least one of: strength, speed, endurance, flexibility, sensitivity, balance, and coordination.
Optionally, the apparatus 40 further includes: a third acquisition module 47, a display module 48; the third acquisition module 47 is configured to acquire moving image data of the user based on a camera; the display module 48 is used for displaying the moving image data on a display of the terminal so that an evaluator can watch the evaluation process in real time.
Optionally, when the evaluation module 44 evaluates the fitness of the user based on the sensing data and the mechanical data, the evaluation module is specifically configured to: converting the sensory data into torso pose data of the user; calculating the dead time of the user based on the mechanical data; and respectively evaluating the body fit of the user according to the first difference value of the trunk gesture data and the standard trunk gesture data of the user and the second difference value of the dead time and the standard dead time of the user to obtain a body fit evaluation result of the user.
Optionally, when the evaluation module 44 converts the sensing data into torso pose data of the user, the evaluation module is specifically configured to: acquiring a conversion relation between the sensing data and trunk posture data of the user; and converting the sensing data into trunk gesture data of the user based on the conversion relation.
Optionally, the evaluation module 44 evaluates the fitness of the user according to a first difference value between the torso gesture data and the standard torso gesture data of the user, and a second difference value between the dead time and the standard dead time of the user, so as to obtain a fitness evaluation result of the user, which is specifically configured to: determining a trunk gesture grade corresponding to trunk gesture data of the user from the corresponding relation between the first difference value and the trunk gesture grade; determining a dead time grade corresponding to the dead time of the user from the corresponding relation between the second difference value and the dead time grade; based on the trunk gesture grade and the dead time grade, obtaining the overall grade of the body fit of the user; and generating a fitness evaluation result of the user according to the trunk gesture grade, the dead time grade and the fitness overall grade of the user, wherein the fitness evaluation result comprises a fitness evaluation report and a guiding suggestion.
The fitness evaluation device of the embodiment shown in fig. 4 may be used to implement the technical solution of the above method embodiment, and its implementation principle and technical effects are similar, and are not described here again.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. The electronic device may be a terminal as described in the above embodiments. The electronic device provided in the embodiment of the present disclosure may perform the processing flow provided in the embodiment of the method for evaluating body fitness, as shown in fig. 5, the electronic device 50 includes: memory 51, processor 52, computer programs and communication interface 53; wherein the computer program is stored in the memory 51 and configured to be executed by the processor 52 for the method of fitness evaluation as described above.
In addition, the embodiment of the present disclosure also provides a storage medium having stored thereon a computer program that is executed by a processor to implement the fitness evaluation method described in the above embodiment.
Furthermore, embodiments of the present disclosure also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implements a method of fitness evaluation as described above.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:
acquiring basic information of a user currently performing body fit assessment;
after a user finishes a target action by using an auxiliary sports apparatus, collecting sensing data of a motion capture sensor on the auxiliary sports apparatus;
collecting mechanical data based on a preset plantar force measuring device;
based on the sensory data and the mechanical data, the user's fitness can be assessed.
Alternatively, the electronic device may perform other steps described in the above embodiments when the above one or more programs are executed by the electronic device.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Moreover, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (10)
1. A method of assessing fitness, the method comprising pre-installing a motion capture sensor on an auxiliary sports implement, the method comprising:
acquiring basic information of a user currently performing body fit assessment;
after a user finishes a target action by using an auxiliary sports apparatus, collecting sensing data of a motion capture sensor on the auxiliary sports apparatus;
collecting mechanical data based on a preset plantar force measuring device;
based on the sensory data and the mechanical data, the user's fitness can be assessed.
2. The method of claim 1, wherein after the obtaining the basic information of the user currently performing the fitness evaluation, the method further comprises:
determining an evaluation item to be evaluated by the user;
and determining a target action corresponding to the evaluation item.
3. The method of claim 1, wherein the assessment item comprises at least one of:
strength, speed, endurance, flexibility, sensitivity, balance, and coordination.
4. The method of claim 1, wherein prior to the assessing the user's fitness based on the sensed data and the mechanical data, the method further comprises:
acquiring moving image data of the user based on a camera;
the moving image data is displayed on a display of the terminal so that an evaluator views the evaluation process in real time.
5. The method of claim 1, wherein the assessing the user's fitness based on the sensed data and the mechanical data comprises:
converting the sensory data into torso pose data of the user;
calculating the dead time of the user based on the mechanical data;
and respectively evaluating the body fit of the user according to the first difference value of the trunk gesture data and the standard trunk gesture data of the user and the second difference value of the dead time and the standard dead time of the user to obtain a body fit evaluation result of the user.
6. The method of claim 5, wherein the converting the sensory data into torso pose data of the user comprises:
acquiring a conversion relation between the sensing data and trunk posture data of the user;
and converting the sensing data into trunk gesture data of the user based on the conversion relation.
7. The method according to claim 5, wherein the evaluating the fitness of the user according to the first difference value between the torso posture data of the user and the standard torso posture data, and the second difference value between the dead time of the user and the standard dead time, respectively, to obtain the fitness evaluation result of the user includes:
determining a trunk gesture grade corresponding to trunk gesture data of the user from the corresponding relation between the first difference value and the trunk gesture grade;
determining a dead time grade corresponding to the dead time of the user from the corresponding relation between the second difference value and the dead time grade;
based on the trunk gesture grade and the dead time grade, obtaining the overall grade of the body fit of the user;
and generating a fitness evaluation result of the user according to the trunk gesture grade, the dead time grade and the fitness overall grade of the user, wherein the fitness evaluation result comprises a fitness evaluation report and a guiding suggestion.
8. A body fit assessment device, the device comprising:
the acquisition module is used for acquiring basic information of a user currently performing body fit evaluation;
the first acquisition module is used for acquiring sensing data of a motion capture sensor on the auxiliary sports apparatus after a user finishes a target motion by using the auxiliary sports apparatus;
the second acquisition module is used for acquiring mechanical data based on a preset plantar force measuring device;
and the evaluation module is used for evaluating the body fitness of the user based on the sensing data and the mechanical data.
9. An electronic device, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-7.
10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211611162.XA CN116246780A (en) | 2022-12-14 | 2022-12-14 | Method and device for evaluating fitness, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211611162.XA CN116246780A (en) | 2022-12-14 | 2022-12-14 | Method and device for evaluating fitness, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116246780A true CN116246780A (en) | 2023-06-09 |
Family
ID=86630370
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211611162.XA Pending CN116246780A (en) | 2022-12-14 | 2022-12-14 | Method and device for evaluating fitness, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116246780A (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101589860A (en) * | 2009-06-23 | 2009-12-02 | 中国科学院合肥物质科学研究院 | Based on the health monitoring sport footwear of flexible array pressure sensor and the method for health monitoring thereof |
| CN101934135A (en) * | 2010-07-26 | 2011-01-05 | 南京理工大学 | Physical ability automated test system |
| CN103577686A (en) * | 2013-09-11 | 2014-02-12 | 奥美之路(北京)技术顾问有限公司 | Chinese people health-related fitness evaluation model |
| CN107122585A (en) * | 2011-02-17 | 2017-09-01 | 耐克创新有限合伙公司 | Selected using view data and associate sports data |
| CN107970556A (en) * | 2017-12-29 | 2018-05-01 | 深圳市瀚翔生物医疗电子股份有限公司 | speed and sensitivity cognitive training system and method |
| CN108091380A (en) * | 2017-11-30 | 2018-05-29 | 中科院合肥技术创新工程院 | Teenager's basic exercise ability training system and method based on multi-sensor fusion |
| CN108665956A (en) * | 2018-06-05 | 2018-10-16 | 陈燕 | The integrated estimation system and method for physical efficiency and muscle performance |
| CN110639197A (en) * | 2019-09-27 | 2020-01-03 | 上海淡竹体育科技有限公司 | Sports test method, device and system |
| CN114495177A (en) * | 2022-04-06 | 2022-05-13 | 北京蓝田医疗设备有限公司 | Scene interactive human body action and balance intelligent evaluation method and system |
| CN114596451A (en) * | 2022-04-01 | 2022-06-07 | 此刻启动(北京)智能科技有限公司 | Body fitness testing method and device based on AI vision and storage medium |
-
2022
- 2022-12-14 CN CN202211611162.XA patent/CN116246780A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101589860A (en) * | 2009-06-23 | 2009-12-02 | 中国科学院合肥物质科学研究院 | Based on the health monitoring sport footwear of flexible array pressure sensor and the method for health monitoring thereof |
| CN101934135A (en) * | 2010-07-26 | 2011-01-05 | 南京理工大学 | Physical ability automated test system |
| CN107122585A (en) * | 2011-02-17 | 2017-09-01 | 耐克创新有限合伙公司 | Selected using view data and associate sports data |
| CN103577686A (en) * | 2013-09-11 | 2014-02-12 | 奥美之路(北京)技术顾问有限公司 | Chinese people health-related fitness evaluation model |
| CN108091380A (en) * | 2017-11-30 | 2018-05-29 | 中科院合肥技术创新工程院 | Teenager's basic exercise ability training system and method based on multi-sensor fusion |
| CN107970556A (en) * | 2017-12-29 | 2018-05-01 | 深圳市瀚翔生物医疗电子股份有限公司 | speed and sensitivity cognitive training system and method |
| CN108665956A (en) * | 2018-06-05 | 2018-10-16 | 陈燕 | The integrated estimation system and method for physical efficiency and muscle performance |
| CN110639197A (en) * | 2019-09-27 | 2020-01-03 | 上海淡竹体育科技有限公司 | Sports test method, device and system |
| CN114596451A (en) * | 2022-04-01 | 2022-06-07 | 此刻启动(北京)智能科技有限公司 | Body fitness testing method and device based on AI vision and storage medium |
| CN114495177A (en) * | 2022-04-06 | 2022-05-13 | 北京蓝田医疗设备有限公司 | Scene interactive human body action and balance intelligent evaluation method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20190325257A1 (en) | Systems and Methods for Non-Contact Tracking and Analysis of Physical Activity Using Imaging | |
| US10512423B2 (en) | Determining energy expenditure of a user | |
| Gindre et al. | Reliability and validity of the Myotest® for measuring running stride kinematics | |
| US11484225B2 (en) | Rehabilitation evaluation apparatus, rehabilitation evaluation method, and rehabilitation evaluation program | |
| US20180184947A1 (en) | Integrated Goniometry System and Method for Use of Same | |
| US20110178760A1 (en) | Power measurement method and apparatus | |
| CN115428050B (en) | Mixed gait analysis device for preventing falling and falling prevention management system comprising same | |
| US20180235517A1 (en) | System and Method For Identifying Posture Details and Evaluating Athletes' Performance | |
| CN106419938B (en) | A kind of attention deficit hyperactivity disorder (ADHD) detection system based on kinergety release estimation | |
| Mejia-Trujillo et al. | Kinect™ and Intel RealSense™ D435 comparison: A preliminary study for motion analysis | |
| US20220378349A1 (en) | A novel means of assessing muscular function and frailty | |
| US11771327B2 (en) | System and method for human motion detection and tracking | |
| CA3150925A1 (en) | Method and system for analysing biomechanical activity and exposure to a biomechanical risk factor on a human subject in a context of physical activity | |
| Ladha et al. | Toward a low-cost gait analysis system for clinical and free-living assessment | |
| KR20180097091A (en) | Apparatus and method for estimating fall risk based on machine learning | |
| KR101221784B1 (en) | A movement analysis and evaluation system using a camera and its control method | |
| CN116246780A (en) | Method and device for evaluating fitness, electronic equipment and storage medium | |
| CN111896119A (en) | Infrared temperature measurement method and electronic equipment | |
| CN111382641A (en) | Body state recognition method and motion guidance system of motion sensing game | |
| CN115568823A (en) | Method, system and device for evaluating human body balance ability | |
| JP5360093B2 (en) | Energy consumption measuring device, energy consumption measuring method, and motion analysis system | |
| Rodríguez-Barbero et al. | Reliability and validity of three portable devices for quantifying spatiotemporal parameters in runners of different athletic abilities during treadmill running | |
| CN103743819A (en) | Detection method and device for content of fat in swine muscle | |
| CN112741620A (en) | Cervical spondylosis evaluation device based on limb movement | |
| CN106991290B (en) | Gait ability assessment method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |