CN111564197A - Intelligent analysis system and method for physical exercise - Google Patents
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Abstract
The invention discloses an intelligent analysis system and method for physical exercise, wherein a physiological parameter of a user is obtained through an exercise analysis terminal, and the physiological parameter is uploaded to a cloud server; the cloud server predicts sports items matched with the user and borne limit exercise amount corresponding to the physiological parameters by using a neural network according to the physiological parameters; pushing the matched sports items to a sports analysis terminal to obtain an instruction selected by a user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed. The intelligent monitoring and analysis of the whole process of the physical exercise of the user are realized, scientific exercise is guided, personalized exercise suggestions can be provided, and the use experience of the user is improved.
Description
Technical Field
The invention relates to the technical field of sports and Internet, in particular to an intelligent analysis system and method for physical exercise.
Background
Physical exercise is a consciously fostered activity of self-body fitness that develops gradually during human development. Various physical activities of walking, running, jumping, casting, and dancing, which are commonly referred to as physical exercise processes, are performed.
It is rich in contents, and has various items such as track and field, ball, swimming, martial arts, aerobics, mountaineering, skating, weightlifting, wrestling, judo, bicycle, etc.
In addition, the development of the internet technology is better and better, and the internet technology refers to an information technology developed and established on the basis of the computer technology. The internet technology connects different devices with each other through a wide area network of a computer network, accelerates the transmission speed of information, widens the acquisition channel of the information, promotes the development of various software applications, and changes the life and learning modes of people.
Nowadays, exercise is more and more focused on, but a vicious event such as sudden death caused by an improper exercise mode also occurs.
Therefore, how to effectively exercise the body based on the internet technology and grasp all exercise states, so as to prevent the body from being harmfully affected by excessive exercise, and therefore a solution is needed.
Disclosure of Invention
In view of the above problems, the present invention provides an intelligent analysis system and method for physical exercise, which can predict the physical exercise items matched with the user and the limited exercise amount born by the user corresponding to the physiological parameters according to the physiological parameters of the user, and display the related exercise data to guide scientific exercise.
In a first aspect, an embodiment of the present invention provides an intelligent analysis method for sports, including:
the method comprises the steps that physiological parameters of a user are obtained through a motion analysis terminal, and the physiological parameters are uploaded to a cloud server;
the cloud server predicts sports items matched with the user and borne limit exercise amount corresponding to the physiological parameters by using a neural network according to the physiological parameters;
pushing the matched sports items to a sports analysis terminal to obtain an instruction selected by a user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
In one embodiment, the acquiring of the physiological parameters of the user through the motion analysis terminal comprises:
acquiring age, sex, heart rate, height and weight data of a user through a motion analysis terminal; wherein, at predetermined intervals, heart rate data of the user is acquired.
In one embodiment, the neural network comprises at least one neural network; predicting the sports items matched with the user and the borne limit exercise amount corresponding to the physiological parameters by utilizing a neural network, which specifically comprises the following steps:
respectively sending the physiological parameters to each neural network, and identifying the physiological parameters by each neural network; the corresponding matched physical exercise program is received from each neural network, along with the amount of extreme motion experienced.
In one embodiment, the real-time monitoring and analysis of physical exercise performed by a user through the exercise analysis terminal comprises:
matching the monitored motion amount of the user with a preset limit motion amount, and sending out a prompt through a motion analysis terminal when the obtained motion amount of the user reaches a threshold value;
or
When the heart rate of the user is monitored to be matched with a preset heart rate condition, when the heart rate duration time reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the motion analysis terminal.
In a second aspect, an embodiment of the present invention further provides an intelligent analysis system for physical exercise, including:
the acquisition uploading module is used for acquiring physiological parameters of a user through the motion analysis terminal and uploading the physiological parameters to the cloud server;
the prediction output module is used for predicting the sports items matched with the users and born limit exercise amount corresponding to the physiological parameters by the cloud server according to the physiological parameters by utilizing a neural network;
the monitoring analysis module is used for pushing the matched sports items to the sports analysis terminal to obtain instructions selected by the user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
In one embodiment, the acquisition and uploading module is specifically configured to acquire data of age, gender, heart rate, height, and weight of a user through a motion analysis terminal; acquiring heart rate data of a user at preset time intervals; and uploading the obtained age, sex, heart rate, height and weight data of the user to a cloud server.
In one embodiment, the neural network in the prediction output module comprises at least one neural network; the physiological parameters are respectively sent to each neural network, and the physiological parameters are identified by each neural network; receiving the corresponding matched sports events and the born limit amount of motion from each neural network
Momentum.
In one embodiment, the monitoring and analyzing module is specifically configured to match the monitored amount of motion of the user with a preset limit amount of motion, and when the amount of motion of the user reaches a threshold value, send a prompt through the motion analyzing terminal; or
When the heart rate of the user is monitored to be matched with a preset heart rate condition, when the heart rate duration time reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the motion analysis terminal.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the intelligent analysis method for sports motion according to any one of the above embodiments.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
according to the intelligent analysis method and system for physical exercise provided by the embodiment of the invention, the physiological parameters of a user are obtained through the exercise analysis terminal, and are uploaded to the cloud server; the cloud server predicts sports items matched with the user and borne limit exercise amount corresponding to the physiological parameters by using a neural network according to the physiological parameters; pushing the matched sports items to a sports analysis terminal to obtain an instruction selected by a user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed. The intelligent monitoring and analysis of the whole process of the physical exercise of the user are realized, scientific exercise is guided, personalized exercise suggestions can be provided, and the use experience of the user is improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of an intelligent analysis method for physical exercise according to an embodiment of the present invention;
fig. 2 is a block diagram of an intelligent analysis system for physical exercise according to an embodiment of the present invention;
fig. 3 is a block diagram of an embodiment of an intelligent analysis system for physical exercise.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides an intelligent analysis method for sports, which is shown in figure 1 and comprises the following steps:
s100, acquiring physiological parameters of a user through a motion analysis terminal, and uploading the physiological parameters to a cloud server;
s200, the cloud server predicts a sports item matched with the user and a borne limit exercise amount corresponding to the physiological parameters by using a neural network according to the physiological parameters;
s300, pushing the matched sports items to a sports analysis terminal to obtain an instruction selected by a user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
The motion analysis terminal may be, for example, a motion bracelet, a motion bicycle terminal, a treadmill, or other motion equipment or monitoring equipment; the motion analysis terminal is provided with a communication module and can be in communication connection with a remote cloud server.
In the embodiment, the method can realize intelligent monitoring and analysis of the whole process of the physical exercise of the user, so as to guide scientific exercise, provide personalized exercise suggestions and improve the use experience of the user.
For example, after calculation according to the big data, a quantitative exercise plan corresponding to the user is generated and pushed to the exercise analysis terminal, so that the user can perform physical exercise.
Further, in the step S100, the age, sex, heart rate, height and weight data of the user are obtained through the motion analysis terminal; wherein, at predetermined intervals, heart rate data of the user is acquired.
For example, age, gender, height, weight may be obtained by active fill-in of the client, while heart rate may be obtained by averaging data over 1 minute, 3 minutes, or 1 hour.
It should be noted here that the physiological parameters may also be preprocessed before being delivered to the neural network, so that the size and format of the physiological parameters match the input requirements of the neural network.
In one embodiment, the neural network in step S200 includes at least one neural network; predicting the sports items matched with the user and the borne limit exercise amount corresponding to the physiological parameters by utilizing a neural network, which specifically comprises the following steps:
respectively sending the physiological parameters to each neural network, and identifying the physiological parameters by each neural network; the corresponding matched physical exercise program is received from each neural network, along with the amount of extreme motion experienced.
In this embodiment, the neural network may obtain the predicted result through a large number of calculations, and the result includes: the physical parameters correspond to the sports events matched with the user and the born limit amount of exercise.
The neural network can comprise a plurality of neural networks, the physiological parameters are respectively identified through the plurality of neural networks to obtain different prediction information, the structure type of the neural network can be a convolutional neural network, a deep neural network and the like, and the structure of the neural network is not strictly limited. The step 200 may be implemented as follows: respectively sending the physiological parameters to each neural network, and identifying the physiological parameters by each neural network; corresponding result information is received from the respective neural networks.
For example, the neural network in the embodiment of the present invention includes a first neural network and a second neural network, the first neural network identifies age, sex, height and weight data in the physiological parameter; the second neural network identifies a heart rate in the physiological parameter.
Taking the first neural network as a convolutional neural network as an example, the physiological parameter can be used as an input of the convolutional neural network, and the convolutional neural network identifies the physical sign information in the physiological parameter. And then outputs the matched sports event. Specifically, the Convolutional Neural Network (CNN) may adopt a CNN model such as Visual Geometry Group (VGG) and AlexNet of google corporation. Of course, those skilled in the art may also use neural networks with other structures to identify the physiological parameters to obtain the matched sports event, and the application is not limited strictly.
Taking the second neural network as the deep neural network as an example, the physiological parameters can be used as the input of the deep neural network, and the deep neural network identifies the heart rate. And predicting the limit exercise amount born by the user according to the heart rate and other physical sign information.
In one embodiment, in step S300, the sports motion performed by the user is monitored and analyzed in real time through the motion analysis terminal,
the method comprises two modes:
the first method comprises the following steps: matching the monitored motion amount of the user with a preset limit motion amount, and sending out a prompt through a motion analysis terminal when the obtained motion amount of the user reaches a threshold value;
and the second method comprises the following steps: when the heart rate of the user is monitored to be matched with a preset heart rate condition, when the heart rate duration time reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the motion analysis terminal.
Such as: the adult age is 43, the height is 165cm, the weight is 90kg, the heart rate is 60, the exercise target of the adult is jogging for 1 hour every day and the weight target is 63kg according to the health big data and prediction through a neural network. Such as: the other age group user information and the moving object are shown in the first table.
Watch 1
The table is only an example of a schematic line, and users in other age groups can also make a relatively suitable sports item and a relatively suitable sports target according to a calculation mode of a neural network and by integrating physiological parameters of the users.
Such as: after the user starts to execute the exercise plan, if the plan is not executed at the exercise starting time, for example, a text reminder is displayed to the user through the exercise analysis terminal, or a sound reminder is sent through an external buzzer. The user can also send a reminder of starting the exercise plan to the user through other clients associated with the exercise and exercise analysis terminal, such as a smart phone, a smart bracelet, a smart watch, a smart jewelry and the like connected with the exercise bicycle terminal through Bluetooth or wireless WiFi; the use experience of the user is further improved.
For another example: and when the physical exercise amount of the user exceeds the limit physical exercise amount of the user, reminding the user to terminate the current physical exercise. For example, the user is prompted by a text prompt displayed by the motion analysis terminal, or the user is forced to stop using the motion analysis terminal by a sound prompt emitted by a buzzer or by directly stopping the motion analysis terminal.
Based on the same inventive concept, the embodiment of the invention also provides an intelligent analysis system for sports, and as the principle of the problem solved by the system is similar to that of the method, the implementation of the system can refer to the implementation of the method, and repeated details are not repeated.
Referring to fig. 2, the method includes:
the acquisition uploading module 21 is used for acquiring physiological parameters of a user through a motion analysis terminal and uploading the physiological parameters to a cloud server;
the prediction output module 22 is used for predicting the sports item matched with the user and the born limit exercise amount corresponding to the physiological parameter by the cloud server according to the physiological parameter by using a neural network;
the monitoring analysis module 23 is configured to push the matched sports event to the sports analysis terminal, and acquire an instruction selected by the user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
In an embodiment, the obtaining and uploading module 21 is specifically configured to obtain data of age, gender, heart rate, height, and weight of the user through a motion analysis terminal; acquiring heart rate data of a user at preset time intervals; and uploading the obtained age, sex, heart rate, height and weight data of the user to a cloud server.
In one embodiment, the neural network in the prediction output module 22 includes at least one neural network; the physiological parameters are respectively sent to each neural network, and the physiological parameters are identified by each neural network; receiving the corresponding matched sports events and the born limit amount of motion from each neural network
Momentum.
In an embodiment, the monitoring and analyzing module 23 is specifically configured to match the monitored exercise amount of the user with a preset limit exercise amount, and when the acquired exercise amount of the user reaches a threshold value, send a prompt through the motion analyzing terminal; or the heart rate of the user during exercise is monitored to be matched with a preset heart rate condition, and when the heart rate duration reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the exercise analysis terminal.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the intelligent analysis method for sports motion according to any one of the above embodiments.
Referring to fig. 3, the treadmill 1 may be communicatively connected to the cloud server 2, taking a treadmill sports terminal as an example. Firstly, acquiring physiological parameters of a user through a treadmill movement terminal, and uploading the physiological parameters to a cloud server; the physiological parameters are: adult age 43, height 165cm, weight 90kg, heart rate 60.
The cloud server predicts a jogging exercise item matched with the user and corresponding to the physiological parameters and the borne limit exercise amount by utilizing a neural network according to the physiological parameters; the adult was prescribed a sport goal of jogging for 1 hour per day and a weight goal of 63 kg.
Pushing the obtained data to a motion analysis terminal, and carrying out corresponding jogging motion by a user; the user is monitored and analyzed in real time by the treadmill moving terminal and the associated jogging speed, step frequency, calories burned, etc. are displayed.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. An intelligent analysis method for sports, characterized by comprising:
the method comprises the steps that physiological parameters of a user are obtained through a motion analysis terminal, and the physiological parameters are uploaded to a cloud server;
the cloud server predicts sports items matched with the user and borne limit exercise amount corresponding to the physiological parameters by using a neural network according to the physiological parameters;
pushing the matched sports items to a sports analysis terminal to obtain an instruction selected by a user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
2. The intelligent analysis method for sports activities according to claim 1, wherein the obtaining of the physiological parameters of the user through the sports analysis terminal comprises:
acquiring age, sex, heart rate, height and weight data of a user through a motion analysis terminal; wherein, at predetermined intervals, heart rate data of the user is acquired.
3. An intelligent analysis method as claimed in claim 1, wherein said neural network comprises at least one neural network; predicting the sports items matched with the user and the borne limit exercise amount corresponding to the physiological parameters by utilizing a neural network, which specifically comprises the following steps:
respectively sending the physiological parameters to each neural network, and identifying the physiological parameters by each neural network; the corresponding matched physical exercise program is received from each neural network, along with the amount of extreme motion experienced.
4. The intelligent analysis method for sports activities according to claim 1, wherein the real-time monitoring and analysis of the sports activities performed by the user through the sports analysis terminal comprises:
matching the monitored motion amount of the user with a preset limit motion amount, and sending out a prompt through a motion analysis terminal when the obtained motion amount of the user reaches a threshold value;
or
When the heart rate of the user is monitored to be matched with a preset heart rate condition, when the heart rate duration time reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the motion analysis terminal.
5. An intelligent analysis system for physical exercise, comprising:
the acquisition uploading module is used for acquiring physiological parameters of a user through the motion analysis terminal and uploading the physiological parameters to the cloud server;
the prediction output module is used for predicting the sports items matched with the users and born limit exercise amount corresponding to the physiological parameters by the cloud server according to the physiological parameters by utilizing a neural network;
the monitoring analysis module is used for pushing the matched sports items to the sports analysis terminal to obtain instructions selected by the user; and the sports motion of the user is monitored and analyzed in real time through the motion analysis terminal, and relevant motion data is displayed.
6. An intelligent analysis system for sports activities according to claim 5, wherein the acquisition and upload module is specifically configured to acquire data of age, sex, heart rate, height and weight of the user through the sports analysis terminal; acquiring heart rate data of a user at preset time intervals; and uploading the obtained age, sex, heart rate, height and weight data of the user to a cloud server.
7. An intelligent analysis system as claimed in claim 5, wherein the neural network in the prediction output module comprises at least one neural network; the physiological parameters are respectively sent to each neural network, and the physiological parameters are identified by each neural network; the corresponding matched sports event is received from each neural network, along with the experienced extreme amount of motion momentum.
8. The intelligent analysis system for sports activities according to claim 5, wherein the monitoring analysis module is specifically configured to match the monitored amount of user's sports motion with a preset limit amount of motion, and when the obtained amount of user's sports motion reaches a threshold value, a prompt is sent through the sports analysis terminal; or the heart rate of the user during exercise is monitored to be matched with a preset heart rate condition, and when the heart rate duration reaches a preset duration and is higher than the preset heart rate, a prompt is sent out through the exercise analysis terminal.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the intelligent analysis method of sports motion according to any one of claims 1 to 4.
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| CN114582447A (en) * | 2022-05-05 | 2022-06-03 | 成都尚医信息科技有限公司 | Test pushing method and system |
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Inventor after: Xie Bin Inventor after: Zhou Yun Inventor before: Xie Bin |
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Application publication date: 20200821 |