JP7344560B2 - How to control training equipment - Google Patents

Description

The present invention relates to a method for controlling training equipment.

Conventionally, methods have been devised for collecting and managing information regarding the operation of training equipment installed in a training gym. In particular, Patent Document 1 discloses a technique in which a weight training device is equipped with a sensor that senses weight and distance, calculates the number of times the weight is raised and lowered from information acquired by the sensor, and generates training status information.

Patent No. 6566591

However, even if the training situation can be managed by the technology disclosed in Patent Document 1, for example, the technique disclosed does not even disclose a method for a user to effectively train in an unmanned training gym without the support of a trainer. I can't say that.

The present invention was made in view of this background, and an object of the present invention is to provide a method for a user to effectively perform training in unmanned training.

The main invention of the present invention for solving the above problems is a training equipment control method, in which a server refers to training information of a user, acquires training equipment information, analyzes the training equipment information, and The training equipment is controlled based on the analyzed training equipment information and the referenced training information.

Other problems disclosed in the present application and methods for solving the problems will be made clear by the section of the embodiments of the invention and the drawings.

According to the present invention, physical exercise can be effectively supported.

FIG. 1 is a diagram showing an example of the overall configuration of an unmanned training system according to a first embodiment. 1 is a diagram showing an example of a functional configuration of a training device 10. FIG. 2 is a diagram showing an example of a hardware configuration of a server device 20. FIG. 2 is a diagram showing an example of a software configuration of a server device 20. FIG. 3 is a diagram showing an example of the configuration of a training information storage unit 231. FIG. 3 is a diagram showing an example of the configuration of a user information storage unit 232. FIG. 3 is a diagram showing an example of the configuration of an image data storage section 233. FIG. 3 is a diagram showing an example of the configuration of a device information storage section 234. FIG. It is a figure showing an example of the control method of the training equipment concerning a first embodiment. FIG. 3 is a diagram showing an example of training control. It is a figure which shows another example of training control. It is a figure shown as an example of the control method of the training equipment concerning a second embodiment. It is a figure shown as an example of the control method of the training equipment concerning a third embodiment.

The contents of the embodiments of the present invention will be listed and explained. The exercise support system according to the embodiment of the present invention has the following configuration.

[Item 1]
A method for controlling training equipment, the method comprising:
The server is
View user training information,
Get training equipment information,
Analyzing the training equipment information,
controlling the training equipment based on the analyzed training equipment information and the referenced training information;
How training equipment is provided.
[Item 2]
A method for controlling the training device according to item 1, comprising:
The training equipment information is
Any of information regarding the load on a predetermined part of the training equipment, information regarding the moving distance of the predetermined part, information regarding the pressure applied to the predetermined part, and information regarding the torque of a drive device provided in the training equipment. including,
How to control training equipment.
[Item 3]
A method for controlling the training device according to item 1, comprising:
Controlling the training equipment includes:
adjusting the torque of a drive device of the training equipment;
How to control training equipment.
[Item 4]
A method for controlling a training device according to claim 1, comprising:
The training information is
including a repetition maximum of the user;
How to control training equipment.
[Item 5]
A method for controlling the training device according to item 1, comprising:
further comprising obtaining a training video of the user;
How to control training equipment.

(First embodiment)
FIG. 1 is a diagram showing an example of the overall configuration of an unmanned training system according to this embodiment. As shown in the figure, in the unmanned training system 1, a server device 20 is connected to a training gym 24 via a communication network 23 such as the Internet. The training gym may be a conventional training gym, or it may be a certain space necessary for training, such as a karaoke store, a rental conference room, a vacant room of a building tenant, or an indoor/outdoor space. . The communication network 23 is, for example, the Internet or a LAN (Local Area Network), and is constructed from a public telephone line network, a private telephone line network, a mobile phone line network, Ethernet (registered trademark), a wireless communication path, and the like. The server device 20 is also connected to the training device 10 and the user terminal 11 that uses the training device. The camera 21 installed in the training gym 24, the user terminal 11, and/or the camera equipped on the display 22 can photograph the exercise of the user using the training equipment 10 from a predetermined angle, and the photographed video can be sent to the server 20 via the network 23. The server device 20 receives information about users who use the gym from each of a training gym 24 (a terminal and/or various sensors provided in the store), a camera 21 in the training gym, a training device 10, a user terminal 11, and a display 22. information necessary for exercise support, information related to the operating status of the gym, information regarding equipment, etc. can be received, and the necessary information is transmitted to each of the terminals of the training gym 24, the user terminal 11, and the display 22. can do.

As described above, the server device 20, the camera 21, and the display 22 are connected to each other via the communication network 23 so as to be able to communicate with each other.

A camera captures a user performing physical exercise using a training device from a predetermined angle, and the captured image (which may be a still image or a moving image, but in this embodiment, a moving image is used). ), it is possible to count the number of training sessions and to evaluate the user's body posture and movement during training.

The camera 21 photographs the user 1 and the training equipment 10 during training. The camera 21 may be, for example, a surveillance camera, or may be installed at a training location, such as by attaching the camera 21 to training equipment. The camera 21 can transmit captured images to the server device 20 using protocols such as TCP/IP and Bluetooth (registered trademark). The camera 21 may be configured to take pictures all the time, to start taking pictures when it detects that the user 1 has come nearby, or to start taking pictures in response to an instruction from the user 1. It's okay.

The display 22 is installed so that it can be viewed by the user 1 before and during training. It is assumed that the display 22 outputs information under the control of the server device 20 via the communication network 23. Note that by connecting a computer to the display 22 and communicating with the server device 20, information can be output to the display 22 in response to instructions from the server 20. Further, together with the display 22 or in place of the display 22, the user 1 can be made to wear an audio output device such as headphones, earphones, or a neck speaker, so that the information can be output as audio. Further, information can also be output to the user via an interface such as an HMD (Head Mounted Display) or a BMI (Brain Machine Interface). Furthermore, a camera (not shown) provided on the display 22 can also photograph the user and the training equipment 10 during training.

The user terminal 11 is a computer operated by the user or his/her supporter. The user terminal 10 is, for example, a smartphone, a tablet computer, a personal computer, or the like. The user terminal 11 may be equipped with an imaging device such as a camera, and may be configured to take images of the user's body and the training equipment 10 during exercise. The information displayed on the display 22 is also provided from the server device 20 to the user terminal 11. The user can view information regarding training by checking the user terminal 11 later.

The server device 20 is a computer that supports training. The server device 20 is, for example, a workstation, a personal computer, a virtual computer logically realized by cloud computing, or the like. The server device 20 receives various types of training equipment information from the training equipment 10 and/or moving images taken by the user terminal 10, analyzes the received information and/or moving images, and analyzes the operation of the equipment and the physical exercise. Evaluate.

FIG. 2 is a diagram showing an example of the hardware configuration of the training device 10. The training device 10 includes a calculation device 101, a memory 102, a storage device 103, a communication interface 104, an input device 105, an output device 106, a drive device 107 such as a motor, and a sensor 108 such as an acceleration sensor. The calculation device 201 is, for example, a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) that performs various calculation processes. The storage device 203 stores various data and programs, and is, for example, a hard disk drive, solid state drive, flash memory, or the like. The communication interface 204 is an interface for connecting to the communication network 30, and includes, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line, and a wireless communication device for performing wireless communication. , a USB (Universal Serial Bus) connector for serial communication, an RS232C connector, etc. The input device 205 is, for example, a keyboard, mouse, touch panel, button, microphone, or the like for inputting data. The output device 206 outputs data, such as a display, printer, or speaker. Note that the input device 205 and the output device 206 can be replaced with the user terminal 11, the display 22, or other external terminal devices. For example, when the training device 10 is a Smith machine, the drive device 107 includes a motor that drives the movement of the shaft in the vertical movable range, and adjusts the load applied in the vertical direction by a control signal transmitted from the calculation device 101. can do. Further, the sensor 108 is provided at an arbitrary location on the drive device 107 or the shaft, and can be a weight sensor, an acceleration sensor, an angular velocity sensor, a force sensor (including a strain sensor), a capacitance sensor, a torque sensor, etc. , it is possible to measure the distance in the vertical range of motion of the shaft, and to measure the load applied to the shaft. For speed and distance measurement, an acceleration sensor or a sensor (encoder) that measures the rotation angle of the motor can be used. Furthermore, by using a load sensor, it is possible to measure force in six axial directions, and it is also possible to obtain the directionality of force.

FIG. 3 is a diagram showing an example of the hardware configuration of the server device 20. As shown in FIG. The server device 20 includes a calculation device 201, a memory 202, a storage device 203, a communication interface 204, an input device 205, and an output device 206. The calculation device 201 is, for example, a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) that performs various calculation processes. The storage device 203 stores various data and programs, and is, for example, a hard disk drive, solid state drive, flash memory, or the like. The communication interface 204 is an interface for connecting to the communication network 30, and includes, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line, and a wireless communication device for performing wireless communication. , a USB (Universal Serial Bus) connector for serial communication, an RS232C connector, etc. The input device 205 is, for example, a keyboard, mouse, touch panel, button, microphone, or the like for inputting data. The output device 206 outputs data, such as a display, printer, or speaker.

FIG. 4 is a diagram showing an example of the software configuration of the server device 20. As shown in FIG. As shown in the figure, the server device 20 includes a user authentication section 210, a training information management section 211, an information acquisition section 212, an image analysis section 213, a device information analysis section 214, an evaluation section 215, a device control section 216, etc. It includes a functional unit and storage units such as a training information storage unit 231, a user information storage unit 232, an image data storage unit 233, and a device information storage unit 234.

Note that each of the above functional units is realized by the arithmetic unit 201 included in the server device 20 reading a program stored in the storage device 203 into the memory 202 and executing it; It is realized as part of the storage area provided by the memory 202 and the storage device 203.

The training information storage unit 231 stores information regarding training. The information regarding training is, for example, a description of the training. The training explanation includes how to use the training equipment and how to effectively train using the training equipment. FIG. 5 is a diagram showing a configuration example of the training information storage section 231. As shown in FIG. As shown in the figure, the training information storage section 231 stores training information. Training information is information related to training. The training information includes information for specifying a training menu (menu ID) and associated information such as training equipment, training purpose, training content, number of training sessions, and load. Training equipment includes, for example, Smith machines, treadmills, exercise bikes (registered trademarks), leg presses, etc., but is limited to equipment that allows the user to exercise repeatedly a predetermined number of times while applying a load. I can't do it. Further, the purpose of training indicates the result sought through training, such as resolving lack of exercise or increasing muscle mass. The content of the training depends on the training equipment and purpose, and examples of the Smith machine include deadlifts, squats, and bench presses. In addition, any information such as precautions regarding training can be set. It is also possible to store video data corresponding to training content. Examples of video data include videos of people demonstrating how to train, and tutorial videos showing how to use training machines. The number of training sessions and load (weight) can be determined by the user's selection or training purpose and content, and can also be determined based on RM (Repetition Maximum). RM sets the number of joint movements for a given load, and the load and number of times can also be set according to the user's physical information, athletic ability, training purpose, etc. set as the user information below. . While viewing the training menu on the display 22, the user can select the training equipment to be used and the purpose, and change or adjust the training menu as necessary. Furthermore, the load and number of times per session can be changed or adjusted based on the load actually measured by the user's training.

The user information storage unit 232 stores information regarding users (hereinafter referred to as user information). FIG. 6 is a diagram showing a configuration example of the user information storage section 232. As shown in FIG. As shown in the figure, the user information stored in the user information storage unit 232 includes user information (for example, user name, date of birth, address, gender, membership status, etc.) in association with a user ID that identifies the user. ), physical information (e.g., height, weight, body fat, muscle mass, flexibility), authentication information (e.g., password, authentication data such as face photo image), health information (e.g., body temperature, blood pressure, blood sugar level, This includes hemoglobin levels, medical history), etc. Authentication information is information that can be used to authenticate user 1. Note that the authentication information may be, for example, the feature amount of the face part of the user 1 used for face authentication, the device ID of the user terminal 10, or a combination of a user name and password. The information may be the public key of the user 1, but is not limited to these as long as it is information that can authenticate the user 1. In addition to the above-mentioned items, the user information can also include various types of information regarding the user's body that can be measured or evaluated. Furthermore, the user's training history can also be stored as user information. As the training history, information regarding the menu ID under which the user performed training using a specific device (identified by the device ID) and the load and number of times when the user actually performed repetitive exercise can be stored. In addition, information such as calorie consumption, average speed and average time of repetitive exercise can be acquired as a training history. The training history can be transmitted from the device 10 to the server device 20 in real time while the user is training, or the information can be temporarily stored in the memory of the device 10 and transmitted at predetermined intervals or when the user completes the training. You can also send information each time you do so.

The image data storage unit 233 stores images taken by the camera 21. FIG. 7 is a diagram showing an example of the configuration of the image data storage section 233. As shown in the figure, the image data storage unit 233 stores image information, and the image information includes image data in association with a camera ID that identifies the camera 21 that took the image. The image data is data for displaying an image taken by the camera 21. The image data may be in any format such as MP4, MPEG2, AVI, MOV, etc., for example.

The equipment information storage unit 234 stores information regarding the training equipment 10 (hereinafter referred to as equipment information). FIG. 8 is a diagram showing a configuration example of the device information storage section 234. As shown in the figure, the device information storage unit 234 stores device information, and the device information includes the training device ID, device detailed information (device type, name, model number, etc.), and device operation information (for example, In the case of a Smith machine, information such as the load on the motor or shaft, the distance traveled by the shaft, and the torque value of the motor obtained from the motor or sensor, the operating history of the equipment (the history of the operating information above), and the It includes the user's training history (for example, menu ID, information regarding RM, burned calories), etc. In addition, if the device 10 is equipped with a reaction force meter that measures the reaction force from the ground at a predetermined portion of the device, information regarding the reaction force obtained from the reaction force meter can also be included.

The user authentication unit 210 authenticates the user 1 viewing the display 22. The user authentication unit 210 can authenticate the user 1 using the authentication information of the user information. In this embodiment, the authentication information of the user information is the feature amount of the face part of the user 1, and the user authentication unit 210 authenticates the user 1 by extracting the feature amount from the image taken by the camera 21. Assume that Note that the user authentication unit 210 may communicate with the user terminal 10 to authenticate the user 1, or the display 22 may communicate with the user terminal 10 to authenticate the user 1. The user may be authenticated and the result may be transmitted from the display 22 to the user authentication section 210. Note that user authentication is not limited to facial recognition; it can also be performed by having the user input necessary information, or by having the user pass or stand still in the training gym or at a predetermined position near the training equipment in the training gym. It can also be performed based on detecting that the

The training information management unit 211 manages training information in the training information storage unit. The training information management section 211 stores training information in the training information storage section 231 or refers to training information stored in the training information storage section 231. Further, the training information management unit 211 specifies a menu ID corresponding to the display ID indicating the display 22 from the display information, and outputs the content of training information and video data corresponding to the specified menu ID to the display 22. The training information management unit 211 determines that the user has come near the display 22 (for example, the display 22 is equipped with a motion sensor, the motion sensor detects the user, or the display 22 communicates with the user terminal 11). function, and by detecting that the display 22 is able to communicate with the user terminal 11, it is possible to detect that the user is nearby. Training information is transmitted to the display 22 when the user takes a picture, stops at a predetermined position, or is recognized as having a predetermined size in the viewing angle of the camera equipped on the display. It is possible to output the information and accept selection and confirmation processing from the user as necessary. Before or during training, the user can view the training content and video output on the display 22 and use it as a reference for training. Note that if the display 22 is not present, the training information may be output to the user terminal 11.

For example, the training information output screen displays the purpose of the training, the training content, and a video. A plurality of moving images may be included, and a plurality of moving images may be displayed on the output screen.

Note that the training information management unit 211 may correct the content of the training information based on the user's physical information and/or health information. For example, the training information management unit 211 can change the height of the chair of the training device depending on your height, set the weight and number of weights to use, and make suggestions based on your height and weight. .

Further, the training information management unit 211 may correct the content of the training information according to the training history of the user 1. For example, the training information management unit 211 reads out the training history corresponding to the user ID indicating the user from the user information storage unit 232, and sets information (such as the weight of weights and the height of the chair) included in the read out training history. For example, it may suggest information similar to the content of the previous setting information, a weight that is heavier or lighter than the previous weight by a predetermined value, or a number of times that is larger or smaller than the previous weight by a predetermined value. This can be included in the content of the training information.

The information acquisition unit 212 acquires device information transmitted from the device 10 and/or acquires a moving image captured by the camera 21 in which a user is training using the device 10. In this embodiment, the device 10 transmits device information to the server device 20 through communication, and the information acquisition section 212 registers the device information in the device information storage section 234 in association with the device ID. Furthermore, the camera 21 transmits the captured image data to the server device 20 via communication, and the information acquisition unit 212 associates the image data transmitted from the camera 21 with the camera ID indicating the camera 21 and stores the image data. 233. Note that the information acquisition unit 212 may transmit an instruction to the camera 21 so that the camera 21 starts capturing images when the user authentication unit 210 successfully authenticates the user 1. If user authentication is performed, device information and image data can also be registered in association with the user ID. Here, if the training gym 24 is not equipped with the camera 21, the image acquisition unit 212 can also acquire an image taken by a camera equipped on the display 22 or the user terminal 11.

The image analysis unit 213 analyzes image data. The image analysis unit 213 analyzes the image data, extracts the feature amount of a specific part of the training device 10, and calculates the movement distance of the position of the part. The image analysis unit 213 can also extract the feature amount of each part of the user's body and specify the position of each part in the image. It should be noted that a general method of image analysis by the image analysis unit 213 is adopted, and a detailed explanation will be omitted here. The image analysis unit 213 may analyze the image data frame by frame or key frame by frame, or may analyze the image data at random timing.

Further, the image analysis unit 213 can also recognize the movement of the user's 1 body. In this case, the image analysis unit 213 may, for example, create a model that can recognize body movements (for example, squats, push-ups, etc.) from the video data, and use the model to recognize the movements through machine learning. I can do it. In this case, the image analysis unit 213 may be implemented, for example, by performing parallel processing using a plurality of GPUs. Other posture estimation techniques include machine learning and posture estimation techniques that use deep learning.

The device information analysis unit 214 analyzes device information. In an example of device information obtained from a Smith machine, the number of repetitions of vertical movement of the shaft by the user is counted from the load applied to the motor or shaft and the information related to the movement distance of the shaft obtained from the acceleration sensor. Determine the success or failure of RM. Furthermore, if the device information includes information on the reaction force meter of the device 10, the load and the user's repetitive motion can be estimated from the reaction force and counted up. Here, as another counting method, a method of analyzing image data may also be considered. Using the position of each part of the user analyzed by the image analysis unit 213, it is possible to count the number of times the user changes to a predetermined posture (from another posture). Further, for example, for each part analyzed by the image analysis unit 213, if the distance between the position of the part and the position included in the position reference information is within a predetermined value, the count can be increased. . Alternatively, the count may be increased when the angles of two parts with the joint parts included in the angle reference information as apexes are within a predetermined value. In addition, the image analysis unit 213 prepares in advance a posture estimation model that uses the body posture as training data and the position (relative positional relationship) of each part as input data, and uses the model to estimate the posture. The user's posture may be specified and the count may be counted up when the user reaches a predetermined posture. Alternatively, the count may be increased when the acceleration at a predetermined position of the user's body is within a predetermined value.

The image analysis unit 213 or the equipment information analysis unit 214 counts the number of training sessions and the number of sets of training sessions, multiplies these numbers by the weight of the weights, and calculates the training volume to calculate the user's workload. It can also be calculated. This training volume can be used as an index for measuring the user's fatigue level. By storing this training volume in the user storage unit 232, the user can check the training volume and its transition by displaying it on the display 22 or the like at a desired timing.

The evaluation unit 215 evaluates the user's body movements. Specifically, the evaluation unit 215 compares the training volume and RM with predetermined evaluation condition information (e.g., target value and average value), determines whether the conditions are satisfied, and evaluates the training volume and RM according to the comparison result. Display the evaluation rank and comments. In addition, the evaluation unit 215 compares the position, posture, and motion of each body part of the user identified from the image data with the reference position information, posture, and/or motion information of each body part, and It is determined whether the position, posture, and motion are within a predetermined range or exceed the reference position, posture value, and motion index, and an evaluation rank and comment are displayed according to the results. In addition, the user's actual measured values and various conditions can be compared and displayed as numerical values, visualized in graphs, etc., and the positions, postures, and movements of the user's body parts can be compared with standards. In order to easily compare the positions, postures, and movements with the positions, postures, and movements that will occur, the positions, postures, and movements that serve as a reference or reference can be displayed side by side or superimposed on the captured video.

The device control unit 216 generates an instruction signal to control the device 10 based on the analyzed device information and/or the analyzed image. For example, in the case of a Smith machine, the device information analysis unit 214 monitors the load and the number of repetitions of vertical movement by the user, and determines whether the user has cleared a predetermined RM (for example, load (60 kg) x 10 times = 10 RM). is determined, and based on the determination, the device control unit 216 adjusts the load to such a level that 10 RM can be achieved in the user's next trial if the user ends up with less RM than the predetermined RM (for example, 8 RM). For example, an instruction signal is generated to control the torque value of the drive device 107 of the device 10 to be adjusted (increased) by reducing the load of 60 kg to 48 kg. Alternatively, the device information analysis unit 214 monitors the load and the number of repetitions of vertical movement of the user, and the user does not reach a predetermined RM (for example, load (60 kg) x 10 times = 10 RM) and ends at 8 RM ( or a predetermined time has elapsed to reach 9RM), an instruction signal is generated to control the torque value of the drive device 107 of the device 10 to be adjusted (increased) in order to reduce the load so that the remaining 2RM can be completed. You can also.

FIG. 9 is a diagram illustrating an example of a method for controlling the training equipment according to the first embodiment.

First, the user authentication unit 210 of the server device 20 detects that the user has come near the training device 10 (S101). The user may be detected by various methods, for example, by installing a human sensor near the device 10 or the display 22, or by monitoring an image from the camera 21 and detecting a person from the image. Detectable.

Next, the user authentication unit 210 authenticates the user 1 (S102). Authentication of the user 1 can be performed, for example, by extracting the feature amount of the facial part from the image and comparing it with the feature amount included in the authentication information of the user information. Further, the user authentication unit 210 authenticates the user by, for example, communicating with the user terminal 11 (for example, accepting input of authentication information such as a user ID and password or a public key from the user terminal 11). You can do it like this. Alternatively, an IC card reader may be installed near the device 10 or the display 22 to perform authentication using a membership card.

When the user is authenticated, the training information management unit 211 refers to the training information stored in the training information storage unit 231 for a training menu corresponding to the device 10 that the user intends to use (S103). Further, the training information management unit 211 outputs the referenced training information to the display 21 or the like as a training menu. Here, the training history associated with the authenticated user ID is referred to from the user information stored in the user information storage unit 232, and the training menu is modified or whether the user performs the same training menu as the previous training menu. , can also provide options. For example, if the equipment 10 is a Smith machine, the training information management unit 211 can modify the weight of the weights, the number of repetitions, etc., according to user information such as height, weight, and muscle mass updated by the user. Further, the training information management unit 211 may receive an input of the purpose from the user, and read training information corresponding to the purpose and menu ID. When a user selects and executes a desired training menu, in the case of a Smith machine, the weight (load) of the weights and the number of repetitions are set.

When training begins, the information acquisition unit 212 acquires information from the device 10 and stores the information in the device information storage unit 234 (S104). For example, if the device 10 is a Smith machine, information regarding the load applied to the motor or shaft and the moving distance of the shaft obtained from the acceleration sensor is acquired. Alternatively, if the device 10 is equipped with a reaction force meter, information regarding the floor reaction force can also be acquired. The information acquisition unit 212 can continuously acquire information from the device 10 while the user is training using the device 10, or can acquire information accumulated in the device 10 all at once at regular intervals. You can also. In particular, by directly measuring the load applied to the motor or shaft without relying on reaction force, it is possible to measure isometric power in a state where the user stands still with an increased load.

Subsequently, the device information analysis unit 214 analyzes the acquired device information (S105). For example, in the example of device information obtained from a Smith machine, the device information analysis unit 214 analyzes the load applied to the motor or shaft and the information related to the movement distance of the shaft obtained from the acceleration sensor. The number of repetitions of vertical movement is counted to determine whether RM is successful or not. Alternatively, the number of repetitions can be counted by measuring force or distance using a force sensor, load sensor, or the like. Furthermore, if the device information includes information on the reaction force meter of the device 10, the load and the user's repetitive motion can be estimated from the reaction force and counted up. The device information analysis unit 214 can also determine power efficiency by calculating the distance traveled by the load per unit time. The analysis result analyzed by the device information analysis section 214 can be stored as a training history in the device information storage section 234 in association with the device ID or in the user information storage section 232 in association with the user ID. Further, the load applied to the motor or shaft and the number of repetitive motions can be output on the display 22 or the like in real time.

Subsequently, the device control unit 216 controls the device 10 based on the information analyzed by the device information analysis unit 214 (S106). For example, in the case of a Smith machine, the device information analysis unit 214 monitors the load and the number of repetitions of vertical movement by the user, and as shown in FIG. x 10 times = 10 RM), and based on the determination, the device control unit 216 determines whether the RM is cleared with less than the predetermined RM (for example, 8 RM), as shown in FIG. 10(b). , in the user's next trial, control is performed to adjust (increase) the torque value of the drive device 107 of the device 10 in order to adjust the load to such a level that 10RM can be achieved (for example, lowering the 60 kg load to 48 kg). Generate an instruction signal. Alternatively, the device information analysis unit 214 monitors the load and the number of repetitions of vertical movement of the user, and as shown in FIG. First, when it is determined that the process has ended at 8RM (or a predetermined time has passed until 9RM), the torque value of the drive device 107 of the device 10 is adjusted (increased) in order to reduce the load so that the remaining 2RM can be completed. It is also possible to generate an instruction signal to control the process. In addition, it is also possible to monitor the time it takes for the load to reach its peak in one RM, and if it is detected that it takes longer than a predetermined time, the torque value can be adjusted to reduce the load to help the user raise the shaft more easily. Furthermore, when it is detected that the force supporting the shaft has weakened due to user fatigue or the like, the torque can be adjusted so that the force supporting the shaft is added at the timing of lowering the shaft.

As described above, by controlling the equipment, it is possible to reliably complete the training menu that the user is originally supposed to accomplish, and it is possible to support the user to obtain training effects.

(Second embodiment)
FIG. 12 is a diagram illustrating an example of a method for controlling a training device according to the second embodiment. The system configuration in the second embodiment can be substantially the same as the configuration in the first embodiment, so a description thereof will be omitted.

First, the user authentication unit 210 of the server device 20 detects that the user has come near the training device 10 (S201). The user may be detected by various methods, for example, by installing a human sensor near the device 10 or the display 22, or by monitoring an image from the camera 21 and detecting a person from the image. Detectable.

Next, the user authentication unit 210 authenticates the user 1 (S202). Authentication of the user 1 can be performed, for example, by extracting the feature amount of the facial part from the image and comparing it with the feature amount included in the authentication information of the user information. Further, the user authentication unit 210 authenticates the user by, for example, communicating with the user terminal 11 (for example, accepting input of authentication information such as a user ID and password or a public key from the user terminal 11). You can do it like this. Alternatively, an IC card reader may be installed near the device 10 or the display 22 to perform authentication using a membership card.

When the user is authenticated, the training information management unit 211 refers to the training information stored in the training information storage unit 231 for the training menu corresponding to the device 10 that the user intends to use (S203). Further, the training information management unit 211 outputs the referenced training information to the display 21 or the like as a training menu. Here, the training history associated with the authenticated user ID is referred to from the user information stored in the user information storage unit 232, and the training menu is modified or whether the user performs the same training menu as the previous training menu. , can also provide options. For example, if the equipment 10 is a Smith machine, the training information management unit 211 can modify the weight of the weights, the number of repetitions, etc., according to user information such as height, weight, and muscle mass updated by the user. Further, the training information management unit 211 may receive an input of the purpose from the user, and read training information corresponding to the purpose and menu ID. When a user selects and executes a desired training menu, in the case of a Smith machine, the weight (load) of the weights and the number of repetitions are set.

When training begins, the information acquisition unit 212 acquires information from the device 10 and stores the information in the device information storage unit 234 (S204). For example, if the device 10 is a Smith machine, information regarding the load applied to the motor or shaft and the moving distance of the shaft obtained from the acceleration sensor is acquired. Alternatively, if the device 10 is equipped with a reaction force meter, information regarding the floor reaction force is acquired. The information acquisition unit 212 can continuously acquire information from the device 10 while the user is training using the device 10, or can acquire information accumulated in the device 10 all at once at regular intervals. You can also. In particular, by directly measuring the load applied to the motor or shaft without relying on reaction force, it is possible to measure isometric power in a state where the user stands still with an increased load.

The information acquisition unit 212 also acquires an image from the camera 21 and registers it in the image data storage unit 233 (S205). The camera 21 captures a moving image that includes the movement of the user's body and/or the movement of a specific part of the device 10. For example, if the device 10 is a Smith machine, the camera 21 photographs the user's training by moving the shaft up and down from a predetermined position. In order to recognize the vertical movement of the shaft in later image processing, it is desirable to photograph the user facing the front from the side. Here, if the training gym is not equipped with the camera 21, images can also be acquired from the camera if the display 22 is equipped with a camera, or the camera equipped on the user terminal 11. Furthermore, photographing can be started by the user's operation, or the sensor can detect the start of the user's operation and automatically start photographing, and the image taken by the camera can be sent to the server device 20.

The device information analysis unit 214 analyzes the acquired device information (S206). For example, in the example of equipment information obtained from a Smith machine, the equipment information analysis unit 214 can monitor the load on the motor or shaft and track changes in the load. The number of repetitions of vertical movement of the shaft by the user is counted from information regarding the moving distance of the shaft obtained from the acceleration sensor, and the success or failure of RM is determined. Furthermore, if the device information includes information on the reaction force meter of the device 10, the load and the user's repetitive motion can be estimated from the reaction force and counted up. The device information analysis unit 214 can also determine power efficiency by calculating the distance traveled by the load per unit time. The analysis result analyzed by the device information analysis section 214 can be stored as a training history in the device information storage section 234 in association with the device ID or in the user information storage section 232 in association with the user ID. Further, the load applied to the motor or shaft and the number of repetitive motions can be output on the display 22 or the like in real time.

The image analysis unit 213 analyzes the image data acquired from the camera 21 (S207). Specifically, the position of each part of the user's body or a specific part of the device 10 (in the case of a Smith machine, the position of the shaft) is specified. Here, in the case where an image can be acquired in this embodiment, the number of training sessions performed by the user can be counted based on the position of the shaft from the acquired image, without depending on the device information. Alternatively, counting can also be done based on the user's body parts. For example, when the angle of the user's knees falls within a certain angle, it is counted as one bending and stretching of the legs, and when the position of the buttocks falls within a certain distance above the floor, it is counted as one squat. You can do it. Next, the image analysis unit 213 calculates the moving distance based on the positions of the highest and lowest points of the shaft that can be recognized from the image, and calculates the load obtained from the device information and the moving distance of the shaft obtained from the image analysis. The number of repetitions of vertical movement of the shaft by the user is counted based on the information related to this, and the success or failure of RM is determined. The analysis results analyzed by the image analysis section 213 and the device information analysis section 214 are stored as training history in the device information storage section 234 in association with the device ID or in the user information storage section 232 in association with the user ID. be able to. Further, the load applied to the motor or shaft and the number of repetitive motions can be output on the display 22 or the like in real time. Power efficiency can also be determined by calculating the distance traveled by the load per unit time.

Subsequently, the device control section 216 controls the device 10 based on the information analyzed by the image analysis section 213 and the device information analysis section 214 (S208). For example, in the case of a Smith machine, the image analysis unit 213 and the device information analysis unit 214 monitor the load and the number of repetitions of the user's vertical movement, and as shown in FIG. , load (60 kg) x 10 times = 10 RM), and based on the determination, the device control unit 216 determines whether the load (60 kg) x 10 times = 10 RM) has been cleared, and based on the determination, if the device control unit 216 has cleared the RM that is less than the predetermined RM (for example, 8 RM), ), in the user's next trial, the torque value of the drive device 107 of the device 10 is adjusted (increased generates an instruction signal to control the Alternatively, the image analysis unit 213 and the device information analysis unit 214 monitor the load and the number of repetitions of vertical movement of the user, and as shown in FIG. If it is determined that the process has finished at 8RM (or a predetermined time has passed until 9RM) without reaching 10RM, the torque value of the drive device 107 of the device 10 is adjusted in order to reduce the load so that the remaining 2RM can be completed. It is also possible to generate an instruction signal for controlling the temperature to increase (increase). In addition, it is also possible to monitor the time it takes for the load to reach its peak in one RM, and if it is detected that it takes longer than a predetermined time, the torque value can be adjusted to lower the load to help the user raise the shaft more easily. Further, when it is detected that the force supporting the shaft has weakened due to user fatigue or the like, the torque can be adjusted so as to add the force supporting the shaft at the timing of lowering the shaft.

As described above, according to the present embodiment, training information of a user can be acquired using image analysis technology without installing a sensor in a device, and training support can be effectively provided. In addition, in FIG. 12, for example, the timing of acquiring device information and the timing of video acquisition may be the same or before or after the other, and similarly the timing of information analysis and image analysis may be either before or after the same. can be taken as a thing.

Although the present embodiment has been described above, the above embodiment is for facilitating understanding of the present invention, and is not for construing the present invention in a limited manner. The present invention may be modified and improved without departing from the spirit thereof, and the present invention also includes equivalents thereof.

Further, for example, in the present embodiment, the image is analyzed in the server device 20, but the invention is not limited to this, and the image may be analyzed in the camera 21 or the user terminal 10 to identify the positional relationship of each part. You can also do this.

Further, in this embodiment, it is assumed that the position of the part is a position on a two-dimensional image, but the position is not limited to this, and may be a three-dimensional position. For example, from a two-dimensional image or video, using a predetermined image recognition technology, in addition to the position of a predetermined part on a two-dimensional image, a method of specifying depth information; A method of specifying the position on a two-dimensional image of the body part and using machine learning to specify the three-dimensional position of the specified part from the position on the two-dimensional image, or using a predetermined image recognition method using multiple cameras. Examples include a method in which the position of each predetermined part on a two-dimensional image is specified using technology, and the three-dimensional position of the specified part is specified from the position on the two-dimensional image using machine learning or the like. Furthermore, in addition to the camera 21, a depth camera can be placed at the location where the training equipment is installed, and the three-dimensional position of the body part can be specified based on the image from the camera 21 and the depth map from the depth camera. . Note that it is also possible to provide a depth camera instead of the camera 21 and specify the three-dimensional position only from the depth map from the depth camera.

In addition, in this embodiment, it is assumed that the part of the user's body photographed by the camera is the part seen from the front or side of the user, but the camera is not limited to this. Taking advantage of the characteristics, the region may be viewed from above the user's head. In this case, analysis can be performed by specifying the two-dimensional positions of the center of the user's head and both shoulders when viewed from above.

Further, in the present embodiment, an image of the user's body during exercise is transmitted from the camera 21 to the server device 20, but the present invention is not limited to this, and a computer may be placed at the location where the training equipment is installed, and the A computer may extract feature amounts from the image and send the feature amounts to the server device 20, or the computer may estimate body parts based on the feature amounts and determine the absolute position of the part (in the image). It may be a position on the XY coordinates, it may be an actual distance from a reference position (for example, the ground, toes, head, center of gravity of the body, etc.), or it may be a position in any other coordinate system. ), or the relative positional relationships between a plurality of parts may be acquired, and these absolute positions and relative positional relationships may be transmitted to the server device 20.

Further, in this embodiment, the execution of a predetermined function and the storage of information are performed by the user terminal or the server device, but the present invention is not limited to this, and the execution of the function and the storage of information are performed by either one of the devices. It can also be done. Alternatively, the functional unit and the storage unit may be provided in a distributed manner in a form different from this embodiment.

Further, in this embodiment, the reference information (position reference information and angle reference information) is set in advance, but the reference information is not limited to this, and the reference information may be created from image data taken of multiple users. It's okay. In this case, for example, it is possible to receive an input as to whether the user's posture or movement is correct, and to create reference information based only on those evaluated as correct.

(Third embodiment)
FIG. 13 is a diagram showing an example of a method for controlling a training device according to the second embodiment. The system configuration in the third embodiment can be substantially the same as the configuration in the first embodiment, so a description thereof will be omitted.

The present embodiment relates to controlling the load according to the purpose and purpose of training of a user who uses the device 10 (for example, a Smith machine). Depending on the user, for example, depending on the user's muscle strength, the muscle part he or she wants to strengthen, or the purpose of the competition or exercise he or she is participating in, concentric contraction, isometric contraction, etc. may be used when moving the shaft up and down. It can be determined whether control that emphasizes muscle contraction (isometric contraction) or extensible muscle contraction (eccentric contraction) is preferable.

First, the information acquisition unit 212 of the server device 20 acquires information from the device 10 based on the user's input to the device 10, such as “extension contraction (eccentric),” “contraction contraction (concentric),” and “isometric contraction.” (Isometric)" (S301). Here, the user can perform menu settings via the input interface provided in the device 10 or the user interface of the user terminal 11. In response to a menu setting request by the user, a menu is provided for selecting "elastic contraction (eccentric)," "contraction contraction (concentric)," or "isometric contraction (isometric)." Additionally, for users who do not understand the meanings of "extensive contraction (eccentric)," "contractive contraction (concentric)," and "isometric contraction (isometric)," the training information management unit 211 of the server device 20 It is also possible to determine which muscle contraction menu is suitable for the user by asking the user questions such as the purpose of training, the parts of the muscles that have been strengthened, or the sports that the user usually engages in.

Then, in accordance with the user's menu selection, the information acquisition unit 212 of the server device selects “extension contraction (eccentric),” “contraction contraction (concentric),” or “isometric contraction (isometric).” The training request is received (S302-304). Here, it is also possible to accept the selection of a combination of each muscle contraction form.

In response to receiving the training request, the device control unit 216 of the server device 20 transmits an instruction signal to the device 10 to start training (S305).

Subsequently, the device control unit 216 controls the device 10 based on the selected menu (S306). When controlling the device 10, for example, when the device 10 is a Smith machine, the device control unit 216 controls the user's vertical movement of the shaft (not only vertical movement, etc.) based on which muscle contraction is occurring. By making the load (weight of the weight) of the Smith machine variable according to the speed of the vertical movement of the shaft or the vertical movement Power (force multiplied by distance traveled per unit time) can be adjusted. For example, if the user selects "extension contraction (eccentric)", the device control unit 216 can increase the load when the user lifts the shaft, and decrease the load when the user lowers the shaft. When combining multiple muscle contraction exercise forms, the load can be adjusted during training. Here, the vertical movement of the shaft can also be determined by analyzing an image acquired by the camera 21 or the camera provided in the user terminal 11. The image analysis unit 213 and the device information analysis unit 214 monitor the load and the number of repetitions of the user's up and down movements, and for the selected muscle contraction exercise form, the image analysis unit 213 and the device information analysis unit 214 monitor the load and the number of repetitions of the user's vertical movement, and for the selected muscle contraction exercise form, the image analysis unit 213 and the device information analysis unit 214 x10 times) can be monitored. Here, the equipment control unit 216 controls the load (weight of the weight) based on the muscle contraction movement set in advance by the user, but during training, that is, the vertical movement speed of the user's shaft or By controlling the load (weight of the weight) while monitoring the power, it is possible to perform "extension contraction (eccentric)", "contraction contraction (concentric)", or You can also switch between "isometric contractions". For example, if a certain user lifts a weight at a slow speed, the weight can be adjusted to be lighter to promote eccentric muscle contraction. In addition, it is also possible to set training menus that utilize velocity, such as VB T (Velocity Based Training).

As described above, the user can perform desired muscle contraction exercises even in an unmanned training gym where no trainer is present. Note that in this embodiment, the device control section, the image analysis section, the device information analysis section, etc. are described as being included in the server device 20, but are not limited to this, and may be included in the device 10 or other devices. You can also use it as

1 Training equipment 11 User terminal 20 Server device 21 Camera 22 Display 23 Communication network 24 Gym store 30 Administrator terminal 210 User authentication unit 211 Training information output unit 212 Information acquisition unit 213 Image analysis unit 214 Equipment information analysis unit 215 Evaluation unit 216 Equipment Control unit 231 Training information storage unit 232 User information storage unit 233 Image data storage unit 234 Equipment information storage unit

Claims (3)

A method for controlling torque of a drive device of training equipment, the method comprising:
The server is
Analyzing images of the user during training to obtain information regarding the distance traveled by a predetermined part of the training equipment;
controlling the torque based on information regarding the load on a predetermined part of the training equipment and information regarding the moving distance;
How to control training equipment. authenticating the user based on the image, and starting to capture the image upon successful authentication;
A method for controlling a training device according to claim 1. presenting a training explanation to the user when it is determined that the user is in a predetermined position based on the image;
A method for controlling training equipment according to claim 1 or 2.