KR20210087169A - System for providing customized training service - Google Patents

Abstract

The present invention relates to a system for providing an optimized training service for each user to prevent injuries and increase exercise efficiency. According to one embodiment of the present invention, the system comprises: an input device receiving body information from a first user; a network communication module receiving training motion data related to a first exercise selected by the first user from the outside; and a training analysis module generating reference data of the first exercise on the basis of the body information. The training analysis module generates an artificial neural network model by using the body information and generates the reference data according to a learning result of the artificial neural network model, wherein the reference data includes any one of an angle between the first user's spine and thigh, the position of the first user's hip joint, and a knee joint angle between the first user's thigh and calf.

Description

Training service provision system optimized for each individual {SYSTEM FOR PROVIDING CUSTOMIZED TRAINING SERVICE}

The present invention relates to a training service providing system optimized for each individual.

Exercising with the wrong posture puts strain on the body and may cause injuries to the knee and lumbar spine. For example, in the case of squat, one of self-fitness, if exercise is performed in the wrong posture, excessive shearing force and compressive force are generated in the knee joint and lumbar spine, thereby causing injury.

Therefore, to reduce the risk of injury, exercise while maintaining an appropriate squat depth. Here, the appropriate squat depth refers to the degree to which a person can squat as deeply as possible with an accurate posture, and the appropriate squat depth is determined according to an individual's physical strength and range of motion. However, beginners are easily exposed to the risk of injury because it is difficult to recognize their proper squat depth. Therefore, there is a need for a system that easily evaluates and informs the user of the appropriate squat depth.

According to the user's body information and body composition index, the present invention provides a training service providing system optimized for each individual that can prevent injuries and increase exercise efficiency by providing the posture, appropriate angle and depth of the exercise that the user wants to train. would like to provide

On the other hand, the technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned are clearly to those of ordinary skill in the art to which the present invention belongs from the description below. can be understood

As a technical means for achieving the above-described technical problem, a training service providing system according to an embodiment of the present invention includes an input device for receiving body information from a first user; a network communication module for receiving training motion data related to the first exercise selected by the first user from the outside; a training analysis module for generating reference data of the first exercise based on the body information; a wearable sensor that is worn on the body of the first user and detects the movement of the first user; and a display for outputting the training motion data, the detected movement of the first user, and the reference data, wherein the training analysis module generates an artificial neural network model using the body information, and learns the artificial neural network model The reference data is generated according to the result, but the reference data is an angle between the spine and the thigh of the first user, the position of the hip joint of the first user, and the angle of the knee joint between the thigh and the calf of the first user. includes any one of

The training service providing system optimized for each individual according to an embodiment of the present invention provides the posture, appropriate angle and depth of the exercise that the user wants to train according to the user's body information and body composition index, thereby preventing injury and improving the performance of the exercise. efficiency can be increased.

On the other hand, the effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the following description. will be able

1 is a block diagram schematically illustrating a training service providing system optimized for each individual according to an embodiment of the present invention.
2 shows an example of a statistical model generated using an artificial neural network model according to an embodiment of the present invention.
3 illustrates a wearable sensor and an embodiment worn on a user's body according to an embodiment of the present invention.
4 is a flowchart for explaining in detail a service providing method of a training service providing system according to an embodiment of the present invention.
5 is an image illustrating an example of an image displayed on a display of a training service providing system according to an embodiment of the present invention.
6 schematically illustrates a press detection device used for customer authentication according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Hereinafter, a training service providing system optimized for each individual according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a block diagram schematically illustrating a training service providing system according to an embodiment of the present invention.

Referring to FIG. 1 , the training service providing system according to an embodiment of the present invention includes an input device 100 , a network communication module 200 , a training analysis module 300 , a wearable sensor 400 , and a display 500 . consists of including However, it is not limited to the above-described configuration.

First, the training service providing system according to an embodiment of the present invention may receive the user's body information from the user through the input device 100 .

The input device 100 generates input data for the user to control the operation of the terminal. The input device 100 may include a keypad, a dome switch, a touch pad (static pressure/capacitance), a jog wheel, a jog switch, and the like. Also, the input device 100 may be provided in a display 500 to be described later in the form of a touch pad.

Accordingly, through the display 500 , a list of body information to be input to the user is presented, and a keypad is provided on the screen so that the user can input the corresponding information, and then the user's body information can be input. .

Here, the user's body information may be the user's body size. For example, the body size may be any one of upper body length, lower body length, thigh length, calf length, thigh circumference, calf circumference, weight, and body composition index (BMI).

At this time, in one embodiment of the present invention, the upper body length is the length of the erector spinae muscle, the thigh length and the calf length indicate the length of the rectus femoris muscle and the gastrocnemius muscle, respectively. In addition, the lower body length is the sum of the thigh length and the calf length, the thigh is the circumference of the half of the rectus femoris muscle, and the calf circumference is the circumference of the half of the gastrocnemius muscle.

Also, the input device 100 may further include an electrode for body composition analysis.

In this case, the electrode may be attached to a part of the user's body, and the user's body composition index may be measured through an electrical signal of the user's body. The body composition index may be, for example, any one of a body fat mass, a body fat percentage, a lean mass, an abdominal fat percentage, a skeletal muscle mass, a lean fat percentage, and a skeletal muscle percentage. Since the above-described measurement of the body composition index is the same as that of the conventional body composition analyzer, the above description will be omitted.

The network communication module 200 may receive training motion data related to an exercise that the user wants to train from a server or a trainer terminal.

In this case, the training motion data may be pre-stored in the server, or may be received and stored from the trainer terminal. Alternatively, the network communication module 200 may transmit the exercise information that the user wants to train to the trainer terminal, receive the training image data for the exercise from the trainer, and provide it as an image to the user.

Accordingly, the network communication module 200 may include one or more modules that enable wireless communication between the training service providing system and the trainer terminal according to an embodiment of the present invention. For example, the network communication module 200 may include a broadcast reception module, a mobile communication module, a wireless Internet module, and a short-range communication module.

The broadcast reception module receives a broadcast signal and/or broadcast related information from an external broadcast management server through a broadcast channel. Here, the broadcast channel may include a satellite channel and a terrestrial channel. The broadcast management server may mean a server that generates and transmits a broadcast signal and/or broadcast-related information or a server that receives and transmits a previously generated broadcast signal and/or broadcast-related information to a terminal. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, and a data broadcast signal, as well as a TV broadcast signal or a broadcast signal in which a data broadcast signal is combined with a radio broadcast signal.

The broadcast related information may mean information related to a broadcast channel, a broadcast program, or a broadcast service provider. The broadcast-related information may be provided through a mobile communication network. In this case, it may be received by the mobile communication module.

The mobile communication module transmits/receives wireless signals to and from at least one of a base station, an external terminal, and a server on a mobile communication network. The wireless signal may include various types of data according to transmission/reception of a voice call signal, a video call signal, or a text/multimedia message.

Then, again referring to FIG. 1 , the training analysis module 300 generates reference data of an exercise to be self-trained by using the user's body information and body composition data input through the input device. In this case, the reference data refers to an appropriate training depth and angle of an exercise to be trained. In one embodiment of the present invention, the proper training depth and angle is any of the angle between the first user's spine and the thigh, the position of the first user's hip joint, and the knee joint between the first user's thigh and calf. can be one

In one embodiment of the present invention, the training analysis module 300 may generate a statistical model to calculate the appropriate training depth and angle of the first exercise that the user wants to train.

Meanwhile, in one embodiment of the present invention, the first exercise may be a squat, but is not limited thereto.

In this case, multiple regression analysis and artificial neural networks may be applied as the aforementioned statistical model. Multiple regression analysis and artificial neural network are general statistical models that predict one output value by applying multiple input values. Although the principle and operation method are different, they have similar functions and are compared in several studies.

However, since multiple regression analysis requires various statistical assumptions, the prediction accuracy of data that does not satisfy the statistical assumptions is lowered. Accordingly, the training analysis module 300 according to an embodiment of the present invention may apply an artificial neural network to generate a statistical model, and calculate an appropriate training depth and angle of the first exercise.

Artificial neural network is a statistical learning algorithm for processing various information in a way similar to the brain by modeling the human brain. Artificial neural network refers to a model that has problem-solving ability by changing the bonding strength of synapses through learning after artificial neurons form a network like the information processing method of the brain.

That is, the purpose of the artificial neural network is to learn knowledge based on several presented data and output a result. In an embodiment of the present invention, a three-layer artificial neural network composed of an input layer, a hidden layer, and an output layer may be applied.

2 shows an example of a statistical model generated using an artificial neural network model according to an embodiment of the present invention.

Referring to FIG. 2 , neurons in each layer are connected to each other by links with neurons in other layers, and each link has a neuron’s connection strength (W), which enables the artificial neural network to process data. The artificial neural network learns the input user's body information and body composition data to predict the appropriate training depth and angle of the first exercise selected by the user, that is, the squat. Here, learning refers to the process of changing the connection strength (W) of neurons so that the artificial neural network can operate according to the example of learning data.

More specifically, the training analysis module 300 applies the user's gender, body information, and body composition data as input learning data and an appropriate squat depth as output learning data to the artificial neural network. Therefore, an appropriate squat depth is calculated by analyzing the relationship between the user's gender, body information and body composition data and the appropriate squat depth, and adjusting the neuron's connection strength.

In this case, the number of neurons may be selected through an optimization process. The learning method of the artificial neural network can use Lavenberg-Marquardt (Marquardt, 1963).

The training analysis module 300 may output the calculated appropriate squat angle and depth for each user to be displayed on the display 500 to be described later.

3 illustrates a wearable sensor and an embodiment worn on a user's body according to an embodiment of the present invention.

Next, referring to FIG. 3 , the wearable sensor 400 is worn on a part of the user's body and senses the user's movement. At this time, the wearable sensor 400 is a clip or band type, and may be worn on the user's body, and detects the user's movement posture when the user performs the first exercise.

Accordingly, the wearable sensor 400 may include an acceleration sensor, a gyro sensor, and the like. Also, the wearable sensor 400 may further include an electrode for analyzing the user's body composition.

The display 500 outputs and displays the training motion data received through the network communication module 200 as an image to the user.

Some of these displays may be of a transparent type or a light-transmitting type so that the outside can be viewed through them. This may be referred to as a transparent display, and a typical example of the transparent display is a TOLED (Transparant OLED). The rear structure of the display 500 may also be configured as a light transmissive structure.

On the other hand, when the display 500 and the sensor (hereinafter, referred to as 'touch sensor') for sensing a touch operation of the above-described input device 100 form a layered structure (hereinafter referred to as 'touch screen'), The display 500 may be used as an input device in addition to an output device. The touch sensor may have the form of, for example, a touch film, a touch sheet, a touch pad, or the like.

The touch sensor may be configured to convert a change in pressure applied to a specific part of the display 500 or capacitance generated in a specific part of the display 500 into an electrical input signal. The touch sensor may be configured to detect not only the touched position and area, but also the pressure at the time of the touch.

Hereinafter, a service providing method of the training service providing system according to an embodiment of the present invention will be described in more detail with reference to the drawings.

4 is a flowchart illustrating in detail a service providing method of a training service providing system according to an embodiment of the present invention.

Referring to FIG. 4 , a service providing method of a training service providing system according to an embodiment of the present invention includes: receiving body information of a first user through an input device ( S100 ); receiving training motion data related to the first exercise selected by the first user and outputting it to the display (S200); Calculating an appropriate angle and depth of the first exercise suitable for the first user (S300); Sensing the movement of the first user through the wearable sensor (S400); and outputting the image of the first user and the calculated appropriate angle and depth of the first motion to the display (S500).

Meanwhile, the training service providing system according to an embodiment of the present invention may further include outputting a plurality of list of serviceable exercises through the display 500 . Accordingly, it is possible to select a first exercise to be trained from the exercise list output on the display 500 by the first user. At this time, in an embodiment of the present invention, the first exercise may be a squat, but is not necessarily limited thereto.

In addition, in the step of receiving the body information of the first user through the input device 100 ( S100 ), the gender of the first user and the body information of the user may be input from the first user. Here, the body information of the first user may be the body size of the first user. For example, the body size may be any one of upper body length, lower body length, thigh length, calf length, thigh circumference, calf circumference, weight, and body composition index (BMI).

In this case, in the training service providing method according to an embodiment of the present invention, the body composition index of the first user may be obtained in the step S100 of receiving the body information of the first user. The body composition index may be, for example, any one of a body fat mass, a body fat percentage, a lean mass, an abdominal fat percentage, a skeletal muscle mass, a lean fat percentage, and a skeletal muscle percentage.

Next, in the step (S200) of receiving the training motion data related to the first exercise selected by the first user and outputting it to the display (S200), the training service providing system transmits the first exercise information to the server or through the network communication module 200 It can be transmitted to the trainer terminal, receive training motion data for the first exercise, and output the training motion data for the first exercise as an image through the display.

In this case, the training motion data for the first exercise refers to data for explaining a proper posture and method for the first exercise. Accordingly, the training motion data may be directly produced by the trainer and stored in a server in advance, or an actual image of the first exercise photographed by the trainer upon a request of the first user may be transmitted in real time from the trainer terminal.

5 is an image illustrating an example of an image displayed on a display of a training service providing system according to an embodiment of the present invention.

As shown in (a) of FIG. 5 , the training motion data of the first training exercise received through the network communication module 200 may be output as an image on the first area of the display 500 .

Next, in the step of calculating the appropriate squat angle and depth of the first user (S300), the training analysis module 300 uses the body information of the first user input from the first user and the measured body composition index, an artificial neural network Create a statistical model. Thereafter, by learning the inputted body information and body composition data of the first user, an appropriate training depth and angle of the first exercise selected by the first user, that is, squat is calculated.

Next, in the step of sensing the user's movement through the wearable sensor (S400), the first user's posture, the depth and angle of the first movement, etc. are detected by sensing the movement of the first user through the wearable sensor 400 do.

Finally, the image of the first user and the calculated appropriate angle and depth of the first movement may be output as the first image 10 on the second area of the display 500 ( S500 ).

At this time, in the training service providing system according to an embodiment of the present invention, as shown in FIG. 5 ( b ), the appropriate depth and angle of the first exercise of the first user calculated through the training analysis module 300 ( 20) may be displayed together on the second area of the display 500 . Therefore, it is possible to allow the first user to recognize an incorrect posture and to exercise according to an appropriate angle and depth of the first exercise.

Meanwhile, the present invention may further include a press sensing device 1100 . The press sensing device 1100 may include first plates 1110 , second plates 1120 , and a third plate 1130 therein. The first plates 1110 are arranged at regular intervals and interconnected at the ends and a current flows, and the second plates 1120 are arranged at regular intervals, located between the first plates and interconnected at the ends and current flows. flows The third plate 1130 is made of an elastic body through which a current flows, and is positioned on the first and second plates. As the third plate 1130 is pressed and elastically deformed, the resistance between the first plates 1110 and the second plates 1120 is changed. A press can be sensed by this resistance change.

Meanwhile, the training service providing system according to an embodiment of the present invention may further include a camera module. Accordingly, the image may be an actual movement image of the user obtained through the camera module. Alternatively, an image obtained by virtual reproduction of the user's movement acquired through the wearable sensor may be output to the display 500 , but the present invention is not limited thereto.

In addition, the training service providing system according to an embodiment of the present invention may output any one of the notes of the first exercise selected by the first user, the exercise time, and the number of exercises on one area of the display.

Accordingly, it is possible to allow the first user to recognize the wrong posture during the exercise and to adjust the number and intensity of the first exercise.

Thus, as an example, a component includes components such as software components, object-oriented software components, class components and task components, and processes, functions, properties, procedures, sub It includes routines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables.

In addition, the components and functions provided within the components may be combined into a smaller number of components or further divided into additional components.

The above description of the present invention is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a dispersed form, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

Claims (6)

an input device for receiving body information from a first user;
a network communication module for receiving training motion data related to the first exercise selected by the first user from the outside;
a training analysis module for generating reference data of the first exercise based on the body information;
a temporary storage module for storing and deleting the reference data of the first exercise for only a predetermined time to a temp server;
a wearable sensor that is worn on the body of the first user and detects the movement of the first user; and
Comprising a display for outputting the training motion data, the detected movement of the first user and the reference data,
The training analysis module
An artificial neural network model is generated using the body information, and the reference data is generated according to the learning result of the artificial neural network model,
The reference data is
Which includes any one of an angle between the spine and the thigh of the first user, the position of the hip joint of the first user, and the angle of the knee joint between the thigh and the calf of the first user,
Training service delivery system. The method of claim 1,
The training analysis module
Which one of the number of exercise, precautions, and exercise time of the first exercise is output to the display,
Training service delivery system. The method of claim 1,
The input device is
Further comprising an electrode for obtaining the bio-signal of the first user,
The system for calculating the body composition index (BMI) of the user based on the obtained bio-signals. The method of claim 1,
The trainer terminal includes a camera module,
The training motion data of the first exercise is
The training service providing system will be the actual image of the first exercise of the trainer taken through the camera module. The method of claim 1,
The wearable sensor is
A system for providing training services, including an angular velocity sensor and a gyro sensor. 6. The method of claim 5,
The wearable sensor is
Further comprising a band portion,
That the angular velocity sensor and the gyro sensor are formed to be in close contact with a part of the body of the first user by the band part,
Training service delivery system.

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