KR101864987B1 - Apparatus for providing training service and method thereof - Google Patents

Apparatus for providing training service and method thereof Download PDF

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Publication number
KR101864987B1
KR101864987B1 KR1020170033947A KR20170033947A KR101864987B1 KR 101864987 B1 KR101864987 B1 KR 101864987B1 KR 1020170033947 A KR1020170033947 A KR 1020170033947A KR 20170033947 A KR20170033947 A KR 20170033947A KR 101864987 B1 KR101864987 B1 KR 101864987B1
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South Korea
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user
training
motion
service providing
data
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KR1020170033947A
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Korean (ko)
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우지환
우민정
주효성
양혜진
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울산대학교 산학협력단
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16—Constructional details or arrangements
    • G06F1/1613—Constructional details or arrangements for portable computers
    • G06F1/163—Wearable computers, e.g. on a belt
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services

Abstract

The present invention relates to a training service providing terminal and a service providing method thereof. According to an embodiment of the present invention, the training service providing terminal includes: an input device which receives body information from a first user; a network communication module which receives training motion data related to a first exercise selected by the first user from the outside; a training analysis module which generates reference data of the first exercise based on the body information; a wearable sensor which is worn on the body of the first user and detects movement of the first user; and a display unit which outputs the detected movement of the first user, reference data, and training motion data. The training analysis module generates an artificial neural network model by using the body information and generates reference data in accordance with the learning result of the artificial neural network model. The reference data includes at least one of the angles between the spine and thigh part of the first user, the position of the hip joint of the first user, and the angle of the knee joint between the calf and the thigh part of the first user.

Description

TECHNICAL FIELD [0001] The present invention relates to a training service providing terminal,

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

According to the National Survey of Participation in Physical Activity in National Life (2012), the reason for not participating in physical activities was found to be the lack of time, lack of interest (25.3%) and health problems (7.2%). For this reason, "self-fitness" for people who lack exercise time and place is spreading recently. Self-fitness means exercising alone at home or in the office with a variety of online content, and the population that uses self-fitness is also increasing.

However, exercise in the wrong posture can cause irritation to the body and injury to the knee and lumbar spine. For example, in the case of a squat, which is one of the self-fitness, when exercising in a wrong posture, excessive shearing force and compressive force may be generated on the knee joint and lumbar spine, resulting in injury.

Therefore, in order to reduce the risk of injury, exercise should be carried out with a proper squat depth. Here, the appropriate squat depth means the degree of being able to squat as deep as possible in the correct posture, and the appropriate squat depth is determined according to an individual's body strength and range of motion. However, beginners are easily exposed to the risk of injuries 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's appropriate squat depth.

In this regard, Korean Patent Registration No. 10-1687252 (entitled " customized personal training management system and method ") creates reference data of a plurality of professional trainers for various sports events according to the user's needs, Based on this data, trainer provides diverse data obtained according to the changing process by detailed information of the individual and exercise, and provides exercise plan and diet optimized for individual on the basis of this data. Based on the trainer and user two-way sensor data log, Discloses a personalized personal training management system and method that promptly provides various feedbacks that can be generated by smoking cigarettes, alcohol consumption, exercise posture correction, or various exercises that the user can easily overlook.

Korean Patent No. 10-1687252

SUMMARY OF THE INVENTION The present invention provides a training service providing terminal and a service providing method for solving the problems of the prior art described above.

Specifically, a training service providing terminal and a service providing method that can provide an attitude, an appropriate angle, and a depth of a motion to be trained by a user in accordance with a user's body information and a body composition index, .

It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are not intended to limit the invention to the precise form disclosed. It can be understood.

According to an aspect of the present invention, there is provided a training service providing terminal, comprising: an input device for receiving physical information from a first user; A network communication module for receiving training motion data related to a first motion selected by the first user from outside; A training analysis module that generates reference data of the first motion based on the body information; A wearable sensor that is worn on the body of the first user and detects movement of the first user; And a display for outputting the training motion data, the motion of the first user and the reference data, wherein the training analysis module generates an artificial neural network model using the body information, Wherein the reference data includes at least one of an angle formed by the spine and the thigh of the first user, a position of the hinge of the first user, and an angle of the knee joint between the thigh and the calf of the first user, Or the like.

According to another aspect of the present invention, there is provided a service providing method of a training service providing terminal, comprising: receiving physical information of a first user through an input device; Receiving training motion data relating to a first motion selected by the first user from the outside and outputting the received training motion data to a display; Generating reference data of the first motion based on the body information; Detecting movement of the first user through a wearable sensor worn on the body of the first user; And simultaneously outputting the detected motion of the first user and the reference data to the display, wherein the generating of the reference data of the first motion includes generating an artificial neural network model using the body information, Wherein the reference data includes at least one of an angle formed by the spine and the thigh of the first user, a position of the hip joint of the first user, and a position of the thigh and the calf of the first user, Of the knee joint.

According to any one of the above-mentioned tasks, a training service providing terminal and a service providing method can be provided.

Specifically, the training service providing terminal and the service providing method according to an embodiment of the present invention provide a posture, appropriate angle and depth of a motion to be trained by the user according to the user's body information and body composition index, And the efficiency of the exercise can be increased.

It should be understood, however, that the effects obtained by the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those skilled in the art to which the present invention belongs It will be possible.

1 is a block diagram schematically illustrating a training service providing terminal according to an embodiment of the present invention.
FIG. 2 shows an example of a statistical model generated using an artificial neural network model according to an embodiment of the present invention.
FIG. 3 illustrates a wearable sensor according to an embodiment of the present invention and an embodiment worn on the wearer's body.
4 is a flowchart illustrating a service providing method of a training service providing terminal according to an exemplary embodiment of the present invention.
5 is an image showing an example of an image displayed on a display of a training service providing terminal according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "electrically connected" with another part in between . Also, when an element is referred to as "including" an element, it is to be understood that the element may include other elements as well as other elements, And does not preclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof.

In this specification, the term " part " includes a unit realized by hardware, a unit realized by software, and a unit realized by using both. Further, one unit may be implemented using two or more hardware, or two or more units may be implemented by one hardware.

In this specification, some of the operations or functions described as being performed by the terminal or the device may be performed in the server connected to the terminal or the device instead. Similarly, some of the operations or functions described as being performed by the server may also be performed on a terminal or device connected to the server.

Hereinafter, a training service providing terminal 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 terminal according to an embodiment of the present invention.

Referring to FIG. 1, a training service providing terminal 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 . However, the present invention is not limited to the above-described configuration.

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

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

Accordingly, the display 500 can provide a list of body information to be input to the user, provide the keypad on the screen so that the user can input the information, and then receive the user's body information .

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

At this time, in one embodiment of the present invention, the length of the upper body is the length of the spinal root, the length of the thigh, and the length of the calf indicate the length of the rectus femoris and the gastrocnemius respectively. The lower body length is the sum of the length of the thigh and the length of the calf, the thigh is the circumference of the point where the thigh is 1/2 of the rectus femoris, and the calf circumference is the circumference of the point where the calf is 1/2.

In addition, the input device 100 may further include an electrode for analyzing body composition.

At this time, the electrode is attached to a part of the user's body, and the user's body composition index can be measured through the electric signal of the user's body. The body composition index can be, for example, any one of body fat mass, percent body fat, dietary fat, abdominal fat percentage, skeletal muscle fat, dietary fat, and skeletal muscle percentage. Since the measurement of the body composition index is the same as that of the conventional body composition analyzer, the description thereof will be omitted.

The network communication module 200 may receive training motion data regarding a motion that the user intends to train from a server or a trainer terminal.

At this time, the training motion data may be pre-stored in the server or received from the trainer terminal and stored. Alternatively, the network communication module 200 may transmit the exercise information to be trained by the user to the trainer terminal, receive the training image data for the exercise from the trainer, and provide the image to the user.

Accordingly, the network communication module 200 may include one or more modules for enabling wireless communication between a training service providing terminal and a trainer terminal according to an exemplary embodiment of the present invention. For example, the network communication module 200 may include a broadcast receiving module, a mobile communication module, a wireless Internet module, and a local communication module.

The broadcast receiving module receives broadcast signals 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 refer to a server for generating and transmitting broadcast signals and / or broadcast related information, or a server for receiving broadcast signals and / or broadcast related information generated by the broadcast management server and transmitting the generated broadcast signals and / or broadcast related information. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, a data broadcast signal, and a broadcast signal in which a data broadcast signal is combined with a TV broadcast signal or a radio broadcast signal.

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

The broadcast-related information may exist in various forms. For example, an EPG (Electronic Program Guide) of DMB (Digital Multimedia Broadcasting) or an ESG (Electronic Service Guide) of Digital Video Broadcast-Handheld (DVB-H).

For example, the broadcast receiving module may be a Digital Multimedia Broadcasting-Terrestrial (DMB-T), a Digital Multimedia Broadcasting-Satellite (DMB-S), a Media Forward Link Only (DVF-H), a Digital Video Broadcast- , Integrated Services Digital Broadcast-Terrestrial (ISDB-T), or the like. Of course, the broadcast receiving module may be configured to be suitable for other broadcasting systems as well as the digital broadcasting system described above.

The mobile communication module transmits and receives radio 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 depending on a voice call signal, a video call signal or a text / multimedia message transmission / reception.

The wireless Internet module refers to a module for wireless Internet access and may be built in or enclosed in a training service providing terminal. WLAN (Wi-Fi), Wibro (Wireless broadband), Wimax (World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access) and the like can be used as wireless Internet technologies.

The short-range communication module is a module for short-range communication. Bluetooth, Radio Frequency Identification (RFID), infrared data association (IrDA), Ultra Wideband (UWB), ZigBee, and the like can be used as a short range communication technology.

Referring again to FIG. 1, the training analysis module 300 generates reference data of a motion to be self-trained using the user's body information and body composition data input through the input device. At this time, the reference data refers to the proper training depth and angle of the exercise to be trained. In one embodiment of the present invention, the proper training depth and angle are an angle between the spine and the thigh of the first user, a position of the first user ' s hip joint, and an angle of the knee joint between the thighs of the first user and the calf It can be one.

In one embodiment of the present invention, the training analysis module 300 may generate a statistical model to calculate an appropriate training depth and angle of a first motion the user is willing to train.

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

At this time, a multiple regression analysis and an artificial neural network can be applied to the statistical model described above. Multiple regression analysis and artificial neural network are general statistical models for predicting a single output value by applying multiple input values.

However, since multiple regression analysis requires various statistical assumptions, data that do not satisfy the statistical assumptions will have poor predictive accuracy. Accordingly, the training analysis module 300 according to an embodiment of the present invention can generate the statistical model by applying the artificial neural network, and calculate the appropriate training depth and angle of the first motion.

Artificial neural networks are statistical learning algorithms for processing information in a human brain model. An artificial neural network is a model in which artificial neurons form a network like a brain information processing method, and change the synaptic bonding strength through learning and have problem solving ability.

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

FIG. 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 a link with neurons in different layers, and each link has a connection strength (W) of neurons, so that the artificial neural network can process data. The artificial neural network learns the input user's body information and body composition data and predicts the optimal training depth and angle of the first exercise, i.e., the squat, selected by the user. Here, learning means a process of changing the connection strength (W) of a neuron so that the artificial neural network can operate according to the example of learning data.

More specifically, the training analysis module 300 applies the sex, body information, and body composition data of the user as input learning data and the appropriate squat depth as output learning data to the artificial neural network. Accordingly, the relationship between the user's sex, body information, and body composition data and the appropriate squat depth is analyzed, and the appropriate squat depth is calculated by adjusting the connection strength of the neurons.

At this time, the number of neurons can be selected through an optimization process. Lavenberg-Marquardt (Marquardt, 1963) can be used to learn artificial neural networks.

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

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

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

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

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

The display 500 may be a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED) a flexible display, and a 3D display.

Some of these displays may be transparent or light transmissive so that they can be seen through. This can be referred to as a transparent display, and a typical example of the transparent display is TOLED (Transparent OLED) and the like. The rear structure of the display 500 may also be of a light transmissive structure.

In the case where a display 500 and a sensor (hereinafter, referred to as 'touch sensor') that detects the touch operation of the input device 100 described above form a mutual layer structure (hereinafter, referred to as a 'touch screen' The display 500 may be used as an input device in addition to the 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 a pressure applied to a specific portion of the display 500 or a capacitance generated in a specific portion of the display 500 into an electrical input signal. The touch sensor can be configured to detect not only the position and area to be touched but also the pressure at the time of touch.

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

4 is a flowchart illustrating a service providing method of a training service providing terminal according to an exemplary 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 training motion data on a first motion selected by the first user and outputting the training motion data on a display (S200); Calculating an appropriate angle and depth of the first movement for the first user (S300); Sensing the motion of the first user through the wearable sensor (S400); And outputting an image of the first user and an appropriate angle and depth of the calculated first motion to the display (S500).

Meanwhile, the training service providing terminal according to an embodiment of the present invention may further include a step of outputting a plurality of serviceable motions through a display 500. Therefore, in the exercise list output from the first user to the display 500, it is possible to select the first exercise to be trained. In this case, in one embodiment of the present invention, the first motion may be a squat, but is not necessarily limited thereto.

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

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

Next, in step S200, the training service providing terminal receives the training motion data related to the first motion selected by the first user and outputs the training motion data to the server through the network communication module 200, To the trainer terminal, receives the training motion data for the first motion, and outputs the training motion data for the first motion to the image through the display.

At this time, the training motion data for the first motion refers to data for describing the legitimate attitude and method for the first motion. Accordingly, the training motion data may be directly produced by the trainer and stored in the server or may be transmitted from the trainer terminal in real time when the first user's motion image of the first motion captured by the trainer is transmitted.

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

5A, the training motion data of the training first movement received through the network communication module 200 may be output as an image to the first region of the display 500. [

Next, in step S300 of calculating the appropriate squat angle and depth of the first user, the training analysis module 300 calculates a squat angle and a depth of the first user based on the body information of the first user and the measured body composition index inputted from the first user, Create a statistical model. Then, the input body information and body composition data of the first user are learned and the appropriate training depth and angle of the first motion selected by the first user, that is, the squat is calculated.

Next, in step S400 of sensing the movement of the user through the wearable sensor, the movement of the first user is sensed through the wearable sensor 400 to detect the posture of the first user, the depth and angle of the first movement, do.

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

5 (b), the training service providing terminal according to an exemplary embodiment of the present invention calculates the appropriate depth and angle of the first movement of the first user calculated through the training analysis module 300 20 may be displayed together in the second area of the display 500. Accordingly, the first user can recognize the erroneous posture and can perform the exercise according to the appropriate angle and depth of the first motion.

Meanwhile, the training service providing terminal according to an embodiment of the present invention may further include a camera module. Accordingly, the image may be the actual motion image of the user obtained through the camera module. Alternatively, the image reproduced by the user through the wearable sensor may be displayed on the display 500, but the present invention is not limited thereto.

In addition, the training service providing terminal according to an embodiment of the present invention may output any one of the precaution, the exercise time, and the exercise frequency of the first exercise selected by the first user in one area of the display.

Accordingly, it is possible to allow the first user to perceive a wrong posture while exercising himself / herself, and to adjust the number and intensity of the first exercise.

In addition, the training analysis module 300 according to an embodiment of the present invention refers to a hardware component such as software, a field programmable gate array (FPGA), or an application specific integrated circuit (ASIC), and performs predetermined roles. However, 'component' is not meant to be limited to software or hardware, and each component may be configured to be in an addressable storage medium and configured to play back one or more processors.

Thus, by way of example, an element may comprise components such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, 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 separated into additional components.

The method of providing a training service according to an embodiment of the present invention can also be implemented in the form of a recording medium including instructions executable by a computer such as a program module executed by a computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

For example, it may be a ROM (Read Only Memory), a RAM (Random Access Memory), a magnetic tape, a magnetic disk, a flash memory, an optical data storage device, or the like. In addition, the computer-readable recording medium may be distributed and executed in a computer system connected to a computer network, and may be stored and executed as a code readable in a distributed manner.

Communication media typically includes computer-readable instructions, data structures, program modules, or any information delivery media.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

100: input device
200: Network communication module
300: Training Analysis Module
400: wearable sensor
500: Display

Claims (18)

An input device for inputting body information from a first user;
A network communication module for receiving training motion data related to a first motion selected by the first user from outside;
A training analysis module that generates reference data of the first motion based on the body information;
A wearable sensor that is worn on the body of the first user and detects movement of the first user; And
A display for outputting the training motion data, the motion of the detected first user, and the reference data,
The training analysis module
Generating an artificial neural network model using the body information, generating the reference data according to a learning result of the artificial neural network model,
The reference data
An angle formed by the vertebrae of the first user, a position of the hip joint of the first user, and an angle of the knee joint formed between the thigh and the calf of the first user,
The input device includes:
A key pad, a dome switch, a touch pad (static pressure / static electricity), a jog wheel, and a jog switch, and is provided on the display in the form of the touch pad,
The network communication module includes:
Receiving the training motion data regarding a motion that the first user intends to train from a server or a trainer terminal,
A training module for training the first user to the trainer terminal, a training image data for the exercise from the trainer and providing the training image data to the user, One of the short-range communication modules,
The training motion data includes:
Stored in the server, received or stored from the trainer terminal,
Wherein the training analysis module comprises:
Wherein a three-layer artificial neural network composed of an input layer, a hidden layer, and an output layer is applied to generate a statistical model, and a proper training depth and angle of the motion are calculated.
Training service provision terminal. delete The method according to claim 1,
The trainer terminal includes a camera module,
The training motion data of the first motion
Wherein the training image is a video image of the first motion of the trainer photographed through the camera module. The method according to claim 1,
The first movement
A training service providing terminal that is a squat. The method according to claim 1,
The input device
Further comprising an electrode for acquiring a bio-signal of the first user,
And calculates a body composition index (BMI) of the user based on the obtained bio-signal. The method according to claim 1,
The training analysis module
And outputs to the display any one of a number of times of movement, a note, and a movement time of the first movement.
Training service provision terminal. The method according to claim 1,
The wearable sensor
An angular velocity sensor, and a gyro sensor. 8. The method of claim 7,
The wearable sensor
Further comprising a band portion,
Wherein the angular velocity sensor and the gyro sensor are formed in close contact with a part of the body of the first user by the band part.
Training service provision terminal. The method according to claim 1,
And a camera module for acquiring an image of the first user.
Training service provision terminal. A service providing method of a training service providing terminal according to claim 1,
Receiving body information of a first user through an input device;
Receiving training motion data relating to a first motion selected by the first user from the outside and outputting the received training motion data to a display;
Generating reference data of the first motion based on the body information;
Detecting movement of the first user through a wearable sensor worn on the body of the first user; And
And simultaneously outputting the detected motion of the first user and the reference data to the display,
Wherein generating the reference data for the first motion comprises:
Generating an artificial neural network model using the body information, generating the reference data according to a learning result of the artificial neural network model,
The reference data
An angle between the spine and the thigh of the first user, a position of the hinge of the first user, and an angle of the knee joint between the thigh and the calf of the first user.
A service providing method of a training service providing terminal. 11. The method of claim 10,
The step of receiving the training motion data regarding the first motion selected by the first user from the outside and outputting the received training motion data to the display
And receives training motion data of the first motion from an external trainer terminal.
A service providing method of a training service providing terminal. 12. The method of claim 11,
The trainer terminal includes a camera module,
The training motion data of the first motion
Wherein the training image is a video image of the first motion of the trainer photographed through the camera module. 11. The method of claim 10,
The first movement
Wherein the training service providing terminal is a squat. 11. The method of claim 10,
Receiving body information of a first user through an input device; after,
And obtaining a body composition index (BMI) of the first user.
A service providing method of a training service providing terminal. 11. The method of claim 10,
The step of simultaneously outputting the detected motion of the first user and the reference data to the display
And further outputs at least one of a number of times of exercise, a note, and a exercise time of the first exercise to the display.
A service providing method of a training service providing terminal. 11. The method of claim 10,
The wearable sensor
An angular velocity sensor and a gyro sensor.
A service providing method of a training service providing terminal. 17. The method of claim 16,
The wearable sensor
And an electrode for analyzing body composition of the first user.
A service providing method of a training service providing terminal. A computer-readable medium storing a program for executing a service providing method according to any one of claims 10 to 17.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020045742A1 (en) * 2018-08-29 2020-03-05 정광 Mobile trainer system and method for providing trainer service using same
KR20200129327A (en) * 2019-05-08 2020-11-18 아이픽셀 주식회사 Method of providing personal training service and system thereof
WO2021020667A1 (en) * 2019-07-29 2021-02-04 주식회사 네오펙트 Method and program for providing remote rehabilitation training
WO2022186508A1 (en) * 2021-03-04 2022-09-09 삼성전자주식회사 Electronic device and control method therefor
KR102454758B1 (en) * 2021-06-01 2022-10-13 박신기 Method and apparatus for providing exercise informaion
WO2023074980A1 (en) * 2021-10-26 2023-05-04 아이픽셀 주식회사 Motion recognition-based interaction method and recording medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090059497A (en) * 2007-12-06 2009-06-11 삼성전자주식회사 Module for measuring character linked to exercise, system for analyzing character linked to exercise with the module, and method for applying the module
KR101582347B1 (en) * 2015-04-08 2016-01-04 (주)프로차일드 Personal Health Training Services Method and Systems
KR20160114996A (en) * 2015-03-25 2016-10-06 한국전자통신연구원 personalized sports service providing method and apparatus thereof
KR101673212B1 (en) * 2015-01-30 2016-11-22 남부대학교산학협력단 Training system and method for proper squat exercise
KR101687252B1 (en) 2014-11-06 2016-12-16 장재윤 Management system and the method for customized personal training

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090059497A (en) * 2007-12-06 2009-06-11 삼성전자주식회사 Module for measuring character linked to exercise, system for analyzing character linked to exercise with the module, and method for applying the module
KR101687252B1 (en) 2014-11-06 2016-12-16 장재윤 Management system and the method for customized personal training
KR101673212B1 (en) * 2015-01-30 2016-11-22 남부대학교산학협력단 Training system and method for proper squat exercise
KR20160114996A (en) * 2015-03-25 2016-10-06 한국전자통신연구원 personalized sports service providing method and apparatus thereof
KR101582347B1 (en) * 2015-04-08 2016-01-04 (주)프로차일드 Personal Health Training Services Method and Systems

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020045742A1 (en) * 2018-08-29 2020-03-05 정광 Mobile trainer system and method for providing trainer service using same
KR20200129327A (en) * 2019-05-08 2020-11-18 아이픽셀 주식회사 Method of providing personal training service and system thereof
KR102266219B1 (en) * 2019-05-08 2021-06-17 아이픽셀 주식회사 Method of providing personal training service and system thereof
WO2021020667A1 (en) * 2019-07-29 2021-02-04 주식회사 네오펙트 Method and program for providing remote rehabilitation training
WO2022186508A1 (en) * 2021-03-04 2022-09-09 삼성전자주식회사 Electronic device and control method therefor
KR102454758B1 (en) * 2021-06-01 2022-10-13 박신기 Method and apparatus for providing exercise informaion
WO2023074980A1 (en) * 2021-10-26 2023-05-04 아이픽셀 주식회사 Motion recognition-based interaction method and recording medium
US11954869B2 (en) 2021-10-26 2024-04-09 Ipixel Co., Ltd. Motion recognition-based interaction method and recording medium

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