KR20210132335A - System for providing training service in fitness service center - Google Patents

Abstract

The present invention relates to a training service providing system for a fitness center to prevent injuries and increase exercise efficiency. According to the present invention, a training service providing terminal comprises: an input device receiving body information from a first user; a network communication module receiving training motion data related to the first exercise selected by the first user from the outside; a training analysis module generating reference data of the first exercise on the basis of the body information; a wearable sensor worn on the body of the first user and detecting movement of the first user; and a display outputting the training motion data, the detected movement of the first user, and the reference data. 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 spine and the thigh of the first user, a position of the hip joint of the first user, and an angle of the knee joint between the thigh and calf of the first user.

Description

Training service provision system of a fitness center {SYSTEM FOR PROVIDING TRAINING SERVICE IN FITNESS SERVICE CENTER}

The present invention relates to a training service providing system and a service providing method.

'Self-fitness' for those who lack a place and time to exercise is spreading recently. Self-fitness refers to exercising alone at home or in the office using various online contents, and the number of people using self-fitness is gradually increasing.

However, if you exercise with the wrong posture, it puts a strain on your body and may cause injuries to your knees 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.

The present invention provides a training service providing system and a service providing method in order to solve the problems of the prior art.

Specifically, according to the user's body information and body composition index, a training service providing system and service providing method 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

As a technical means for achieving the above-described technical problem, a training service providing terminal 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, wherein the reference data includes 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

According to any one of the above-described problem solving means of the present invention, it is possible to provide a training service providing system and service providing method.

Specifically, the training service providing system and service providing method according to an embodiment of the present invention provides a posture, an appropriate angle and depth of an exercise that a user wants to train according to the user's body information and body composition index, thereby preventing injury. and increase exercise efficiency.

1 is a block diagram schematically illustrating a training service providing system 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 illustrating in detail a service providing method of a training service providing terminal 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 is a diagram illustrating an app screen of a training service providing system according to an embodiment of the present invention.

Hereinafter, a training service providing system and a service providing method 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, a list of body information to be input may be presented to the user through the display 500 , and a keypad may be provided on the screen so that the user can input the corresponding information, and then the user's body information may 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 portion 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 to the user as an image.

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, referring back 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 appropriate 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 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 inputted 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. In this case, 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.

In this case, the display 500 includes a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), a flexible display ( It may include at least one of a flexible display) and a three-dimensional display (3D display).

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 terminal according to an embodiment of the present invention.

Referring to FIG. 4 , a service providing method of a training service providing terminal according to an embodiment of the present invention includes: receiving body information of a first user through an input device (S100); Receiving the 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 movement 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 movement on 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 first user's body information through the input device 100 ( S100 ), the first user's gender and user's body information 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 and outputting the training motion data related to the first exercise selected by the first user on the display, 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 input 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 (b) of FIG. 5 , the appropriate depth and angle ( 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 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 motion 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 an incorrect posture during exercise and to adjust the number and intensity of the first exercise.

The present invention may include a cutting unit, a first transfer and a second transfer, and a combine unit.

The cutting unit may generate a plurality of pieces by dividing the data, and may assign an address to each of the pieces. Here, the addresses of the pieces may be composed of a combination of a plurality of letters and numbers.

Also, the cutting unit may generate a combination rule in consideration of each address. Here, the combination rule refers to a rule that allows a plurality of data pieces to be combined into data before being divided based on each address.

The first transfer may transmit a plurality of data pieces in an arbitrary order. Here, a plurality of data pieces may be transmitted together with an assigned address, respectively.

The second transfer may transmit a combination rule corresponding to the plurality of data pieces transmitted by the first transfer. Here, it may be preferable that the second transfer transmits the combination rule with a time difference with respect to the transmission of the plurality of data pieces by the first transfer.

The functional operations described in this specification and the embodiments related to the present subject matter can be implemented in a digital electronic circuit, computer software, firmware, or hardware, including the structures disclosed herein and structural equivalents thereof, or in a combination of one or more thereof do.

Embodiments of the subject matter described herein are one or more computer program products, ie one or more modules directed to computer program instructions encoded on a tangible program medium for execution by or for controlling the operation of a data processing device. can be implemented. A tangible program medium may be a radio wave signal or a computer-readable medium. A radio wave signal is an artificially generated signal, eg a machine generated electrical, optical or electromagnetic signal, that is generated to encode information for transmission to an appropriate receiver device for execution by a computer. The computer-readable medium may be a machine-readable storage device, a machine-readable storage substrate, a memory device, a combination of materials that affect a machine-readable radio wave signal, or a combination of one or more of these.

A computer program (also known as a program, software, software application, script or code) may be written in any form of programming language, including compiled or interpreted language or a priori or procedural language, and may be written as a stand-alone program or module; It can be deployed in any form, including components, subroutines, or other units suitable for use in a computer environment.

A computer program does not necessarily correspond to a file in a file system. A program may be in a single file provided to the requested program, or in multiple interacting files (eg, files that store one or more modules, subprograms, or portions of code), or portions of files that hold other programs or data. (eg, one or more scripts stored within a markup language document).

A computer program may be deployed to be executed on a single computer or multiple computers located at one site or distributed over a plurality of sites and interconnected by a communication network.

Additionally, the logic flows and structural block diagrams described herein describe corresponding acts and/or specific methods supported by corresponding functions and steps supported by the disclosed structural means, and corresponding software. It can also be used to build structures and algorithms and their equivalents.

The processes and logic flows described herein may be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.

Processors suitable for the execution of computer programs include, for example, both general and special purpose microprocessors and any one or more processors of any kind of digital computer. Typically, the processor will receive instructions and data from read-only memory, random access memory, or both.

A key element of a computer is one or more memory devices for storing instructions and data and a processor for executing instructions. Further, a computer is generally operably coupled to receive data from, transfer data to, or both of one or more mass storage devices for storing data, such as, for example, magnetic, magneto-optical disks or optical disks. or will include However, the computer need not have such a device.

The present description sets forth the best mode of the invention, and provides examples to illustrate the invention, and to enable any person skilled in the art to make or use the invention. This written specification does not limit the present invention to the specific terms presented.

Accordingly, although the present invention has been described in detail with reference to the above-described examples, those skilled in the art can make modifications, changes, and modifications to the examples without departing from the scope of the present invention. In short, in order to achieve the intended effect of the present invention, it is not necessary to separately include all the functional blocks shown in the drawings or follow all the orders shown in the drawings. indicate that it may be within the scope

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;
distributed storage servers for distributed storage of data transmitted between the modules;
a wearable sensor that is worn on the body of the first user and detects the movement of the first user; and
and a display for outputting the training motion data, the detected movement of the first user, and the reference data. The method of claim 1,
The first movement is
The training service provision system which is a squat. 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 wearable sensor is
A system for providing training services, including an angular velocity sensor and a gyro sensor. 5. The method of claim 4,
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. The method of claim 1,
Which further comprises a camera module for acquiring the image of the first user,
Training service delivery system.

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