Server device, control method for server device and program

Abstract

To provide a server device capable of setting load appropriate to a user using a training machine.SOLUTION: A server device includes calculation means and generating means. The calculation means calculates physical condition information about a physical condition of a training starter on the basis of vital data of the training starter who is about to start training by using a training machine. The generating means generates load information on load set to the training machine on the basis of the calculated physical condition information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a server device, a method for controlling a server device, and a program. [Background technology]

[0002] There is technology regarding how to control training equipment.

[0003] For example, Patent Document 1 describes a method for providing a user with an effective training method in unmanned training. In the training equipment control method disclosed in Patent Document 1, a server device refers to the user's training information and acquires information about the training equipment. The server device analyzes the training equipment information and controls the training equipment based on the analyzed training equipment information and the referred training information. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-097990 Summary of the Invention [Problem to be solved by the invention]

[0005] To improve the effectiveness of training using a training machine, an appropriate load must be set on the training machine. Regarding the setting of the load, for example, paragraph

[0031] of Patent Document 1 describes correcting the load based on the user's training history. However, the optimal load for a user is not determined solely by the training history.

[0006] A primary object of the present invention is to provide a server device, a server device control method, and a program that contribute to enabling a user of a training machine to set a load that is more suitable for the user. [Means for solving the problem]

[0007] According to a first aspect of the present invention, there is provided a server device comprising: a calculation means for calculating physical condition information relating to the physical condition of a training initiator who is about to start training using a training machine, based on vital data of the training initiator; and a generation means for generating load information relating to the load to be set on the training machine, based on the calculated physical condition information.

[0008] According to a second aspect of the present invention, there is provided a method for controlling a server device, comprising: a calculation step of calculating physical condition information relating to the physical condition of a training initiator who is about to start training using a training machine, based on vital data of the training initiator; and a generation step of generating load information relating to the load to be set on the training machine, based on the calculated physical condition information.

[0009] According to a third aspect of the present invention, there is provided a program for causing a computer mounted on a server device to execute a calculation process for calculating physical condition information relating to the physical condition of a training initiator who is about to start training using a training machine, based on vital data of the training initiator, and a generation process for generating load information relating to a load to be set on the training machine, based on the calculated physical condition information. [Effects of the Invention]

[0010] According to various aspects of the present invention, a server device, a server device control method, and a program are provided that contribute to enabling a user of a training machine to set a load that is more suitable for the user. Note that the effects of the present invention are not limited to those described above. The present invention may achieve other effects instead of or in addition to the effects described above. [Brief explanation of the drawings]

[0011] [Figure 1]FIG. 1 is a diagram for explaining an outline of an embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of the operation of one embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of a schematic configuration of an information processing system according to an embodiment of the present disclosure. [Figure 4] FIG. 4 is a diagram for explaining the configuration of the training machine according to the embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram illustrating an example of a display on the accepting device according to an embodiment of the present disclosure. [Figure 6] FIG. 6 is a diagram for explaining the operation of the information processing system according to the embodiment of the present disclosure. [Figure 7] FIG. 7 is a diagram illustrating an example of a display on the accepting device according to an embodiment of the present disclosure. [Figure 8] FIG. 8 is a diagram for explaining the operation of the information processing system according to the embodiment of the present disclosure. [Figure 9] FIG. 9 is a diagram illustrating an example of a processing configuration of a server device according to an embodiment of the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of a user management database according to an embodiment of the present disclosure. [Figure 11] FIG. 11 is a flowchart illustrating an example of the operation of the authentication control unit according to an embodiment of the present disclosure. [Figure 12] FIG. 12 is a diagram illustrating an example of table information according to an embodiment of the present disclosure. [Figure 13] FIG. 13 is a diagram illustrating an example of table information according to an embodiment of the present disclosure. [Figure 14] FIG. 14 is a diagram illustrating an example of a processing configuration of the receiving device according to an embodiment of the present disclosure. [Figure 15] FIG. 15 is a sequence diagram illustrating an example of the operation of the information processing system according to an embodiment of the present disclosure. [Figure 16] FIG. 16 is a diagram illustrating an example of a processing configuration of a server device according to a modified example of the embodiment of the present disclosure. [Figure 17]FIG. 17 is a diagram illustrating an example of a display on a terminal according to a modified example of the embodiment of the present disclosure. [Figure 18] FIG. 18 is a diagram illustrating an example of a hardware configuration of a server device according to the present disclosure. [Figure 19] FIG. 19 is a diagram illustrating an example of a display on a receiving device according to a modification of the present disclosure. [Figure 20] FIG. 20 is a diagram illustrating an example of a display on a receiving device according to a modification of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] First, an overview of one embodiment will be described. Note that the reference numerals in the drawings are added to each element for convenience as an example to facilitate understanding, and the description of this overview is not intended to be limiting in any way. Furthermore, unless otherwise specified, the blocks shown in each drawing represent functional units, not hardware units. Connection lines between blocks in each drawing include both bidirectional and unidirectional lines. Unidirectional arrows are used to schematically indicate the flow of main signals (data) and do not exclude bidirectionality. Note that in this specification and drawings, elements that can be similarly described may be assigned the same reference numerals to avoid redundant explanation.

[0013] A server device 100 according to one embodiment includes a calculation means 101 and a generation means 102 (see FIG. 1). The calculation means 101 calculates physical condition information relating to the physical condition of a training starter who is about to start training using a training machine, based on vital data of the training starter (step S1 in FIG. 2). The generation means 102 generates load information relating to the load to be set on the training machine, based on the calculated physical condition information (step S2).

[0014] The server device 100 calculates the physical condition information of the user about to start training. The server device 100 determines the load to be set on the training machine based on the physical condition information. That is, the server device 100 determines the load on the training machine taking into account the physical condition of the user starting training. As a result, a load that is most suitable for the user using the training machine is set.

[0015] Specific embodiments will be described in more detail below with reference to the drawings.

[0016] [First embodiment] The first embodiment will be described in more detail with reference to the drawings.

[0017] [System Configuration] 3 is a diagram illustrating an example of a schematic configuration of an information processing system (authentication system) according to an embodiment of the present disclosure. As illustrated in FIG. 3, the information processing system includes a training gym.

[0018] An operator of a training gym manages and operates the server device 10. The server device 10 is a server that manages users who use the training gym and handles tasks such as payment of usage fees.

[0019] The server device 10 may be installed in the building of a business operator that operates the training gym, or may be installed on a network (on the cloud).

[0020] The training gym is equipped with a plurality of training machines (fitness machines) 20. For example, various types of training machines 20 such as a running machine, an upright bike, and a bench press are installed in the training gym.

[0021] The server device 10 and the training machines 20 are connected to each other. Specifically, the server device 10 and the training machines 20 are connected by wired or wireless communication means and are configured to be able to communicate with each other.

[0022] Each training machine 20 is composed of a main body 21 and a reception device 22 (see FIG. 4). A user uses the main body 21 to perform training. Before starting training, the user is authenticated by the server device 10 using the reception device 22. Furthermore, when the training is finished, the user uses the reception device 22 to complete the training completion procedure.

[0023] The receiving device 22 is, for example, an information processing terminal such as a tablet or a mobile personal computer. The receiving device 22 and the main body 21 are connected by a communication means such as a USB (Universal Serial Bus). The receiving device 22 is also connected to the server device 10 via a network.

[0024] 3, a user carries a terminal 30 such as a smartphone. The user operates the terminal 30 to access the server device 10.

[0025] The configuration of the information processing system shown in Fig. 3 is an example and is not intended to be limiting. For example, the information processing system may include multiple server devices 10. Load balancing and redundancy may be achieved by using multiple server devices 10. Furthermore, the number of training machines 20 included in the training gym is not limited to "2".

[0026] [General operation] Next, the general operation of the information processing system according to the first embodiment will be described.

[0027] <User registration> In order to use the training gym, a user must register as a user (member) and create an account. The user operates the terminal 30 to access a predetermined website (for example, a member registration site) provided by the server device 10.

[0028] On the membership registration site, users register their login information (ID, password), name, gender, date of birth, address, telephone number, email address, biometric information, payment-related information, etc.

[0029] Examples of biometric information include data (features) calculated from physical characteristics unique to an individual, such as a face, fingerprint, voiceprint, veins, retina, or iris pattern. Alternatively, the biometric information may be image data such as a face image or fingerprint image. The biometric information may be any information that includes the user's physical characteristics. In this disclosure, a case where biometric information related to a person's "face" (a face image or features generated from a face image) is used will be described.

[0030] The payment-related information is information used by the training gym operator to settle facility usage fees with users. For example, the payment-related information includes credit card information and bank account information.

[0031] When the user's name and other information are acquired, the server device 10 generates a user ID for identifying the user. The server device 10 associates the generated user ID with login information, name, biometric information, payment-related information, and other information and stores them in a user management database. The user management database will be described in detail later.

[0032] By completing user registration (membership registration), a user can enter the training gym and can use each training machine 20 installed in the training gym.

[0033] <Training begins> When starting to use the training machine 20, the training starter (user) is authenticated by the server device 10 via the reception device 22. Specifically, the user moves in front of the reception device 22.

[0034] When the reception device 22 detects a user in front of it, it acquires whether the user wishes to start training or to complete the training. For example, the reception device 22 acquires the user's preference (start training or end training) using a GUI (Graphical User Interface) as shown in FIG.

[0035] When the user selects to start training, the receiving device 22 acquires biometric information of the user. For example, the receiving device 22 photographs the user and acquires face images (at least one face image). The receiving device 22 transmits an "authentication request" including the acquired biometric information and machine ID to the server device 10 (see FIG. 6).

[0036] The machine ID is an ID for identifying the training machine 20 installed in the training gym. The MAC (Media Access Control) address or IP (Internet Protocol) address of the reception device 22 can be used as the machine ID.

[0037] Upon receiving the authentication request, the server device 10 identifies the training machine 20 that the user is about to start using based on the machine ID included in the authentication request.

[0038] The server device 10 executes a matching process (authentication process) using the biometric information included in the authentication request and the biometric information stored in the user management database.

[0039] If the matching process is successful, server device 10 determines that authentication of the person to be authenticated (the user who wishes to start training) has been successful. If the matching process is unsuccessful, server device 10 determines that authentication of the person to be authenticated has failed.

[0040] If the authentication of the person to be authenticated is successful, the server device 10 calculates (estimates) vital data of the user using the biometric information (e.g., at least one or more facial images) included in the authentication request. For example, the server device 10 calculates vital data such as weight, blood pressure, heart rate, etc. The server device 10 stores the calculated vital data in the user's account.

[0041] Furthermore, the server device 10 calculates information (physical condition information) related to the physical condition of the user (authentication successful person; person to be authenticated who is determined to have been successfully authenticated). Specifically, the server device 10 quantifies the physical condition (health state) of the user using the user's vital data. For example, the server device 10 quantifies the user's physical condition into three levels: "good," "normal," and "poor." The server device 10 stores the calculated physical condition information of the user in the account.

[0042] After calculating the user's physical condition information, the server device 10 determines the load level to be set on the training machine 20 on which the user will train, based on the calculated physical condition information of the user. Specifically, if the user is in good physical condition, the server device 10 selects a load level higher than the standard load. Conversely, if the user is in poor physical condition, the server device 10 selects a load level lower than the standard load.

[0043] The server device 10 generates "load information" to be set on the training machine 20 according to the selected load level. For example, when a user uses a treadmill, the server device 10 generates information on the speed and time according to the load level as the load information. Alternatively, when a user uses a bench press, the server device 10 generates information on the weight of the weight and the number of training sessions according to the load level as the load information.

[0044] The server device 10 proposes the generated load information as a load (training menu) to be set on the training machine 20 that the user starts using.

[0045] The server device 10 transmits a response to the authentication request to the accepting device 22. If the user authentication is successful, the server device 10 transmits an affirmative response indicating this to the accepting device 22. At that time, the server device 10 transmits the affirmative response including the user ID and load information of the user to the accepting device 22.

[0046] If authentication of the user (training starter) fails, the server device 10 transmits a negative response to the accepting device 22 indicating that the authentication has failed.

[0047] The accepting device 22 performs processing according to the authentication result (authentication success, authentication failure).

[0048] If the authentication is successful, the accepting device 22 presents the acquired load information to the user. For example, the accepting device 22 connected to a running machine displays a GUI such as that shown in Fig. 7 and acquires whether the user agrees to train in accordance with the load information.

[0049] When the user agrees to the proposed load information (settings of the training machine 20), the accepting device 22 transmits the load information to the main body 21. The main body 21 operates based on the notified load setting. The user starts training with the set load.

[0050] If the user rejects the proposed load information, the reception device 22 acquires the load setting desired by the user (the load of the training machine 20). The reception device 22 transmits the load desired by the user to the main body 21.

[0051] <End of training> When the user has finished training, the person who has finished training (user) inputs this fact into the reception device 22. Specifically, the user selects "End training" on the GUI shown in FIG.

[0052] When the user finishes the training, the reception device 22 notifies the server device 10 of this fact. Specifically, the reception device 22 transmits a training completion notification to the server device 10, which includes the user ID of the user who has finished the training and load information (settings on the training machine 20) of the training performed by the user (see FIG. 8).

[0053] The server device 10 identifies the user who has completed the training based on the user ID included in the training completion notification. The server device 10 stores load information in the account of the identified user. That is, the server device 10 stores the training history in the user's account.

[0054] Next, details of each device included in the information processing system according to the first embodiment will be described.

[0055] 9 is a diagram illustrating an example of a processing configuration (processing module) of the server device 10 according to the embodiment of the present disclosure. Referring to FIG. 9, the server device 10 includes a communication control unit 201, a user management unit 202, an authentication control unit 203, a completion notification processing unit 204, and a storage unit 205.

[0056] The communication control unit 201 is a means for controlling communication with other devices. For example, the communication control unit 201 receives data (packets) from the accepting device 22. The communication control unit 201 also transmits data to the accepting device 22. The communication control unit 201 passes data received from other devices to other processing modules. The communication control unit 201 transmits data acquired from other processing modules to other devices. In this way, other processing modules transmit and receive data to and from other devices via the communication control unit 201. The communication control unit 201 has a function as a receiving unit that receives data from other devices and a function as a transmitting unit that transmits data to other devices.

[0057] The user management unit 202 is a means for controlling and managing users of the training gym.

[0058] The user management unit 202 acquires login information (ID, password), name, sex, date of birth, address, telephone number, email address, biometric information, payment-related information, etc. from users who access the membership registration site.

[0059] When a face image is acquired as biometric information, the user management unit 202 generates a feature amount from the face image.

[0060] Since existing technology can be used for the process of generating feature amounts, detailed description thereof will be omitted. For example, the user management unit 202 extracts the eyes, nose, mouth, etc. from the face image as feature points. Then, the user management unit 202 calculates the positions of each feature point and the distances between each feature point as feature amounts (generating a feature vector consisting of multiple feature amounts).

[0061] Furthermore, upon acquiring the user's name, etc., the user management unit 202 generates a user ID for identifying the user. The user ID may be any information that can uniquely identify the user. For example, the user management unit 202 may assign a unique value each time a user is registered and use this as the user ID.

[0062] When the user ID is generated, the user management unit 202 associates the generated user ID with login information, name, biometric information (features), payment-related information, etc., and stores them in the user management database (see FIG. 10). Note that the user management database shown in FIG. 10 is an example and is not intended to limit the items to be stored. For example, a "face image" may be registered in the user management database as biometric information.

[0063] The authentication control unit 203 is a means for controlling the authentication of the person to be authenticated (the user who intends to use the training machine 20).

[0064] The authentication control unit 203 has a function as an authentication unit, a function as a calculation unit, and a function as a generation unit.

[0065] The authentication control unit 203, which serves as authentication means, receives an authentication request including the biometric information of the training starter, and performs authentication processing using the biometric information included in the authentication request and the biometric information stored in the user management database. By performing the authentication processing, the authentication control unit 203 authenticates the training starter and notifies the training machine 20 of the authentication result.

[0066] The authentication control unit 203 as a calculation means calculates physical condition information relating to the physical condition of a training starter who is about to start training using the training machine 20, based on the vital data of the training starter. The authentication control unit 203 as a generation means generates load information relating to the load to be set on the training machine 20, based on the calculated physical condition information.

[0067] 11 is a flowchart showing an example of the operation of the authentication control unit 203 according to an embodiment of the present disclosure. The operation of the authentication control unit 203 when an authentication request is received will be described with reference to FIG.

[0068] When receiving an authentication request from the accepting device 22, the authentication control unit 203 identifies the training machine 20 that the user is going to use by using the machine ID included in the authentication request (step S101).

[0069] For example, the authentication control unit 203 identifies the training machine 20 by referring to table information that stores, in association with each other, the machine ID, the type (name) of the training machine 20, and details of the training machine 20 (for example, information regarding the settable load).

[0070] Thereafter, the authentication control unit 203 executes a matching process (one-to-N matching; N is a positive integer, the same applies below) using the biometric information included in the authentication request and the biometric information stored in the user management database (step S102).

[0071] Specifically, the authentication control unit 203 calculates a feature amount from the facial image included in the authentication request. The authentication control unit 203 sets the calculated feature amount as a matching target and performs a matching process with the feature amount registered in the user management database. More specifically, the authentication control unit 203 sets the calculated feature amount (feature vector) as a matching target and performs one-to-many matching with the multiple feature amounts in the user management database.

[0072] The authentication control unit 203 calculates the similarity between the feature to be matched and each of the multiple feature values on the registration side. The similarity can be calculated using chi-square distance, Euclidean distance, or the like. Note that the greater the distance, the lower the similarity, and the closer the distance, the higher the similarity.

[0073] The authentication control unit 203 determines that the matching process is successful if there is a feature among the multiple feature amounts stored in the user management database that has a similarity with the feature amount to be matched that is equal to or greater than a predetermined value. If there is no such feature amount, the authentication control unit 203 determines that the matching process is unsuccessful.

[0074] If the matching process fails (step S103, No branch), authentication control unit 203 determines that authentication of the person to be authenticated who is attempting to use training machine 20 has failed. In this case, authentication control unit 203 transmits a negative response indicating authentication failure to accepting device 22 (step S104).

[0075] If the matching process is successful (step S103, Yes branch), the authentication control unit 203 calculates the vital data of the authenticated person (step S105). The authentication control unit 203 treats the user with the feature value having the highest similarity in the matching process as the authenticated person, and calculates the vital data of the authenticated person.

[0076] Specifically, the authentication control unit 203 calculates (estimates) vital data of the successfully authenticated person using the biometric information (e.g., at least one or more facial images) of the successfully authenticated person. For example, the authentication control unit 203 uses the acquired biometric information to acquire estimated values of vital data such as the user's weight, heart rate, blood pressure, blood glucose level, and oxygen saturation level.

[0077] The vital data may be estimated using a learning model obtained by machine learning. For example, a business operator of a training gym may generate a learning model using a large amount of training data consisting of a combination of face images (image data including at least one face area) and vital data measurement results.

[0078] For example, a person's weight is related to the contours of their face, and a learning model utilizing this relationship (a learning model that can obtain weight when a face image is input) can be generated. Heart rate is also related to changes in the brightness of the face surface (brightness of the face surface resulting from blood flow), and a learning model utilizing this relationship (a learning model that can obtain heart rate when multiple face images are input) can be generated. Furthermore, facial swelling can be estimated from the physical distance between facial feature points and the amount of blood flow, and a learning model that estimates facial swelling can be generated.

[0079] The generated learning model is implemented in the server device 10.

[0080] The learning model can be generated using any algorithm such as a support vector machine, boosting, neural network, etc. Since the algorithm such as the support vector machine can be a known technique, a description thereof will be omitted.

[0081] After that, the authentication control unit 203 calculates the physical condition information of the successfully authenticated person (step S106).

[0082] For example, the authentication control unit 203 acquires the physical condition information of the successfully authenticated person by inputting the vital data of the successfully authenticated person into a learning model. Alternatively, the authentication control unit 203 may acquire the physical condition of the user by inputting the facial image (at least one facial image) of the successfully authenticated person used in the biometric authentication into a learning model.

[0083] The former learning model is obtained by machine learning using a large amount of training data in which labels (health status; for example, good, normal, bad) are assigned to vital data (weight, blood pressure, heart rate, etc.), while the latter learning model is obtained by machine learning using a large amount of training data in which labels (health status; for example, good, normal, bad) are assigned to image data (at least one or more face images).

[0084] The authentication control unit 203 acquires the physical condition information of the authenticated person using vital data and biometric information. For example, the authentication control unit 203 acquires the physical condition information of the authenticated person classified into one of three levels: "good," "normal," and "bad." It goes without saying that the user's physical condition is not limited to being expressed in three levels.

[0085] Thereafter, the authentication control unit 203 generates load information to be set on the training machine 20 proposed to the successfully authenticated person (step S107). The authentication control unit 203 generates load information according to the type of training machine 20 used by the training starter (successfully authenticated person) identified by the matching process.

[0086] Specifically, the authentication control unit 203 determines the load level to be set on the training machine 20 based on the physical condition of the person who has been successfully authenticated. For example, the authentication control unit 203 determines the load level by referring to table information that stores physical conditions and load levels in association with each other.

[0087] At this time, the authentication control unit 203 may determine the load level according to the user's attributes (e.g., age and / or gender) and physical condition. In this case, the authentication control unit 203 may determine the load level according to the user's age, gender, and physical condition by referring to table information such as that shown in Fig. 12. Fig. 12 shows an example of table information for determining the load level for a man in his 40s.

[0088] The load level is expressed, for example, in 10 levels from level 1 to level 10. Note that an increase in the level indicates an increase in the load. A system administrator or the like can generate table information for each age group and / or gender, taking into consideration the attributes (age, gender) and physical condition of the users, and register the information in the server device 10.

[0089] For example, in the table information, if the user is in good physical condition, a load level higher than the standard load (for example, level 5) is set. Also, if the user is in poor physical condition, a load level lower than the standard load is set.

[0090] Once the load level is determined, the authentication control unit 203 generates "load information" to be set on the training machine 20 used by the successfully authenticated person. For example, the authentication control unit 203 generates the load information by referring to table information that stores the load level and the load information to be set on the training machine 20 in association with each other (see FIG. 13). Note that FIG. 13 shows an example of table information for generating load information for a running machine.

[0091] For example, in the examples of Figures 12 and 13, if the load level of a man in his 40s who is about to use the treadmill is level 7, "8km / h; 40 minutes" is generated as the load information to be set on the treadmill (load information suggested to the user).

[0092] After generating the load information, authentication control unit 203 notifies training machine 20 (accepting device 22) that authentication of the person to be authenticated has been successful. Specifically, authentication control unit 203 transmits an acknowledgment indicating successful authentication to accepting device 22 (step S108). Authentication control unit 203 transmits an acknowledgment including the user ID of the person who has been successfully authenticated and the generated load information to accepting device 22.

[0093] If the authentication is successful, the authentication control unit 203 updates the following fields in the user management database before or after sending the positive response: the usage date and time field, the used machine field, the vital data field, and the physical condition information field. For example, the authentication control unit 203 stores the date and time when the authentication request was processed in the usage date and time field. The authentication control unit 203 also stores the name of the training machine 20 derived from the machine ID in the used machine field.

[0094] Although not shown in FIG. 10 etc., the user management database may store the load level used to calculate the load information.

[0095] In this way, the authentication control unit 203 calculates vital data of the training starter identified by the authentication process from among multiple users using the biometric information of the training starter. The authentication control unit 203 calculates physical condition information based on the calculated vital data. The authentication control unit 203 generates load information to be proposed to the training starter. In this case, the authentication control unit 203 may generate the load information based on the calculated physical condition information and the attributes of the identified training starter. If the authentication control unit 203 successfully authenticates the training starter, it notifies the training starter of the generated load information via the training machine 20 (reception device 22).

[0096] The end notification processing unit 204 is a means for processing the “training end notification” received from the accepting device 22 .

[0097] Upon receiving a training end notification, the end notification processor 204 searches the user management database using the user ID included in the notification as a key. The end notification processor 204 sets the load information included in the training end notification in the load information field of the user (entry) identified by the search.

[0098] When a user trains according to load information suggested by the server device 10, the suggested load information is stored as training history in the user management database. On the other hand, when a user trains according to load information determined by the user himself, the load information determined by the user himself is stored as training history in the user management database.

[0099] The storage unit 205 is a means for storing information necessary for the operation of the server device 10. The storage unit 205 stores biometric information of each of multiple users who can use the training machine 20. Furthermore, the storage unit 205 stores the biometric information of the training starter identified by the authentication process in association with vital data calculated from the biometric information included in the authentication request used in the authentication process.

[0100] [Reception device] 14 is a diagram illustrating an example of a processing configuration (processing module) of accepting device 22 according to an embodiment of the present disclosure. Referring to FIG. 14, accepting device 22 includes communication control unit 301, biometric information acquisition unit 302, determination unit 303, authentication request unit 304, end notification unit 305, and storage unit 306.

[0101] The communication control unit 301 is a means for controlling communication with other devices. For example, the communication control unit 301 receives data (packets) from the server device 10. The communication control unit 301 also transmits data to the server device 10. The communication control unit 301 passes data received from other devices to other processing modules. The communication control unit 301 transmits data acquired from other processing modules to other devices. In this way, other processing modules transmit and receive data to and from other devices via the communication control unit 301. The communication control unit 301 has a function as a receiving unit that receives data from other devices and a function as a transmitting unit that transmits data to other devices.

[0102] The biometric information acquisition unit 302 is a means for controlling a camera or the like to acquire biometric information of the person to be authenticated.

[0103] Specifically, the biometric information acquisition unit 302 periodically or at a predetermined timing captures an image of the area in front of the device. The biometric information acquisition unit 302 determines whether the acquired image data includes a human face area, and if a face area is included, treats the acquired image data as a face image.

[0104] Since existing technology can be used for the facial region detection process by the biometric information acquisition unit 302, detailed description thereof will be omitted. For example, the biometric information acquisition unit 302 may detect a facial region from an image using a learning model trained by a CNN (Convolutional Neural Network). Alternatively, the biometric information acquisition unit 302 may detect a facial region using a method such as template matching.

[0105] When acquiring a plurality of face images, the biometric information acquiring unit 302 captures the user for a predetermined period of time after image data including a face area is detected, and acquires the plurality of face images.

[0106] The biometric information acquisition unit 302 passes the acquired biometric information (at least one or more facial images) to the determination unit 303.

[0107] The determination unit 303 is a means for determining whether the user in front of the user wishes to start training or wishes to complete the training procedure.

[0108] When the determination unit 303 acquires the biometric information from the biometric information acquisition unit 302, it displays a GUI as shown in FIG. 5 and acquires the user's preference (start of training, end of training).

[0109] If the user wishes to start training, the determination unit 303 passes the user's biometric information (at least one or more facial images) to the authentication request unit 304 .

[0110] If the user wishes to complete the training, the determination unit 303 notifies the completion notification unit 305 of this.

[0111] The authentication request unit 304 is a means for requesting authentication of the person to be authenticated from the server device 10. Specifically, the authentication request unit 304 transmits an authentication request including the biometric information and machine ID of the person to be authenticated (the user who wishes to use the training machine 20) to the server device 10.

[0112] The authentication request unit 304 receives the authentication result (authentication success, authentication failure) from the server device 10.

[0113] When the authentication failure is received, the authentication request unit 304 notifies the person to be authenticated that the authentication has failed and that the person cannot use the training machine 20.

[0114] When the authentication success is received, the authentication request unit 304 stores the user ID received from the server device 10 in the storage unit 306 .

[0115] Furthermore, the authentication request unit 304 presents the load information received from the server device 10 to the user, and acquires whether the user agrees to train according to the load information. For example, the authentication request unit 304 acquires the user's intention (agree to the proposed load information, reject the proposed load information) using a GUI such as that shown in FIG.

[0116] When the user agrees to the proposed load information, the authentication request unit 304 transmits the load information (settings of the training machine 20) acquired from the server device 10 to the main unit 21.

[0117] If the user rejects the proposed load information, the authentication request unit 304 acquires the load settings desired by the user and transmits the acquired load settings to the main unit 21 as load information.

[0118] The authentication request unit 304 stores the load information transmitted to the main unit 21 in the storage unit 306 .

[0119] The end notification unit 305 is a means for notifying the server device 10 that the user has completed training.

[0120] When the determination unit 303 notifies the user that the user wishes to complete the training procedure, the completion notification unit 305 notifies the server device 10 of this fact. Specifically, the completion notification unit 305 transmits to the server device 10 a training completion notification including the user ID stored in the storage unit 306 and load information on the training performed by the user.

[0121] The end notification unit 305 may delete the user ID and load information stored in the storage unit 306 in response to sending the training end notification.

[0122] The storage unit 306 is a means for storing information necessary for the operation of the training machine 20.

[0123] [Device] Examples of the terminal 30 include a smartphone, a mobile phone, a game console, a mobile terminal device such as a tablet, a computer (personal computer, laptop computer), etc. The terminal 30 can be any equipment or device that can accept user operations and communicate with the server device 10, etc. Furthermore, the configuration of the terminal 30 is clear to those skilled in the art, so a detailed description thereof will be omitted.

[0124] [Training machine body] A description of the main body 21 of the training machine 20 will be omitted, as the configuration and operation of the main body 21 of the training machine 20 will be obvious to those skilled in the art.

[0125] [System Operation] Next, the operation of the information processing system according to the first embodiment will be described. Fig. 15 is a sequence diagram showing an example of the operation of the information processing system according to the embodiment of the present disclosure. With reference to Fig. 15, the operation of the information processing system when a user starts using the training machine 20 will be described.

[0126] The reception device 22 acquires biometric information of an authentication subject who wishes to start using the training machine 20 (step S01).

[0127] Receiving device 22 transmits an authentication request including the acquired biometric information to server device 10 (step S02).

[0128] The server device 10 executes authentication processing using the biometric information included in the authentication request and the biometric information stored in the user management database (step S03). If the authentication of the person to be authenticated is successful, the server device 10 calculates the person's vital data, physical condition information, etc., and generates load information to be proposed to the person to be authenticated.

[0129] Server device 10 transmits the authentication result (authentication success, authentication failure) to accepting device 22 (step S04).

[0130] When the authentication is successful and the person to be authenticated agrees to the proposed load information, the accepting device 22 sets the load information determined by the server device 10 in the main body 21 of the training machine 20 (step S05).

[0131] Next, a modified example of the first embodiment will be described.

[0132] <Variation 1> The server device 10 may calculate the vital data of the user after using the training machine 20. In this case, the reception device 22 transmits to the server device 10 a training end notification including the biometric information (at least one or more facial images) of the user who has completed the training end procedure.

[0133] The server device 10 calculates vital data using the facial image included in the notification. The server device 10 stores the calculated vital data in a user management database. The server device 10 stores the vital data before and after the user uses the training machine 20 in the user management database.

[0134] <Variation 2> When starting to use the training machine 20, the authentication control unit 203 may use changes in vital data from when the user previously used the same type of training machine 20 to determine the load level and generate load information.

[0135] For example, consider a case where a user starts using a treadmill. In this case, the authentication control unit 203 acquires vital data (e.g., heart rate) before and after the user's previous use of the treadmill. The authentication control unit 203 calculates the difference between the acquired vital data.

[0136] The authentication control unit 203 may reflect the calculated difference value in determining the load level. Specifically, if the difference value is smaller than a predetermined value, the authentication control unit 203 determines that the load set for the user is insufficient and sets a higher load level. On the other hand, if the difference value is larger than the predetermined value, the authentication control unit 203 determines that the load set for the user is too high and sets a lower load level.

[0137] Alternatively, the authentication control unit 203 may directly reflect the calculated difference value (for example, the difference value of the heart rate) in the load information. For example, the authentication control unit 203 may adjust the load information determined based on the user's physical condition information or the like, using the difference value.

[0138] In this way, the authentication control unit 203 as a generating means may generate load information based on changes in vital data before and after use of the training machine 20 when the training starter previously used the training machine 20. That is, the server device 10 may determine the load information (load level) of the training machine 20 used by the user based on changes in vital data before and after training.

[0139] <Variation 3> The server device 10 may reflect the user's training history in determining the load level and generating the load information.

[0140] For example, when processing an authentication request, the authentication control unit 203 refers to the training history of the same type of training machine 20 as the training machine 20 on which the user is about to start training. The authentication control unit 203 may generate load information that sets a higher load than the load information set in the previous training session.

[0141] Alternatively, the authentication control unit 203 may change the amount of load increase depending on the user's attribute information (age, sex) or physical condition. For example, the authentication control unit 203 generates load information with a large increase for a user in good physical condition. On the other hand, for a user in poor physical condition, the authentication control unit 203 generates load information with a small increase, or generates load information without increasing the load.

[0142] <Variation 4> The server device 10 may use all or part of the user's attributes, physical condition information, changes in vital data, and training history to determine the load level when processing an authentication request. For example, the authentication control unit 203 may determine the load level based on a combination of the user's attributes and training history.

[0143] <Variation 5> The server device 10 may have a function to provide information such as vital data, training history, etc. In this case, the server device 10 includes an information provision control unit 206 as shown in FIG.

[0144] The information provision control unit 206 is a means for providing information related to vital data, training history, etc. Specifically, the information provision control unit 206 provides information using vital data and training history stored in the user management database.

[0145] For example, in response to a request from a user who has logged in to their own account (for example, pressing a vital data confirmation button), the information provision control unit 206 provides information about the accumulated vital data of the user.

[0146] For example, the information provision control unit 206 may graph time-series data relating to vital data desired by the user (vital data selected by the user; for example, weight) and display it on the terminal 30. For example, the information provision control unit 206 may display a screen such as that shown in FIG. 17 on the terminal 30.

[0147] Alternatively, the information provision control unit 206 may perform statistical processing on the vital data of the user and display the results of the statistical processing on the terminal 30. For example, the information provision control unit 206 may calculate the average value, median value, mode value, variance value (standard deviation), rate of change, etc. for a predetermined period of time regarding the vital data specified by the user, and provide the results to the user.

[0148] Alternatively, the information provision control unit 206 may provide the user with the training history (history of load information) for each training machine 20.

[0149] <Variation 6> In the above embodiment, the case where the vital data and training history of the user are stored in the server device 10 has been described. However, the vital data and the like may also be stored in the terminal 30 carried by the user.

[0150] For example, instead of or in addition to storing vital data calculated from biometric information in the user management database, the authentication control unit 203 of the server device 10 may transmit the vital data to the terminal 30 carried by the user. The authentication control unit 203 may also transmit the vital data to an email address or the like registered in the user management database.

[0151] If vital data and the like are stored in the user's terminal 30, the terminal 30 may present the stored vital data and training history to the user in response to an operation by the user.

[0152] As described above, the server device 10 according to the first embodiment authenticates the training initiator using the biometric information acquired from the training machine 20 and calculates the vital data of the training initiator. The server device 10 calculates the user's physical condition information based on the calculated vital data. The server device 10 generates load information to be set on the training machine 20 based on the physical condition information. The server device 10 determines the load on the training machine 20 taking into consideration the physical condition of the training initiator, allowing the user to train with an optimal load.

[0153] Next, the hardware of each device constituting the information processing system will be described. Fig. 18 is a diagram showing an example of the hardware configuration of the server device 10.

[0154] The server device 10 can be configured by an information processing device (so-called computer), and has the configuration exemplified in Fig. 18. For example, the server device 10 includes a processor 311, a memory 312, an input / output interface 313, and a communication interface 314. The components such as the processor 311 are connected by an internal bus or the like, and are configured to be able to communicate with each other.

[0155] 18 is not intended to limit the hardware configuration of the server device 10. The server device 10 may include hardware not shown, and may not include the input / output interface 313 as necessary. Furthermore, the number of processors 311 and the like included in the server device 10 is not intended to be limited to the example shown in FIG. 18, and for example, the server device 10 may include multiple processors 311.

[0156] The processor 311 is a programmable device such as a central processing unit (CPU), a micro processing unit (MPU), or a digital signal processor (DSP). Alternatively, the processor 311 may be a device such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). The processor 311 executes various programs including an operating system (OS).

[0157] The memory 312 is a random access memory (RAM), a read only memory (ROM), a hard disk drive (HDD), a solid state drive (SSD), etc. The memory 312 stores an OS program, application programs, and various data.

[0158] The input / output interface 313 is an interface for a display device and an input device (not shown). The display device is, for example, a liquid crystal display. The input device is, for example, a device that accepts user operations such as a keyboard or a mouse.

[0159] The communication interface 314 is a circuit, module, etc. that communicates with other devices. For example, the communication interface 314 includes a network interface card (NIC).

[0160] The functions of the server device 10 are realized by various processing modules. The processing modules are realized, for example, by the processor 311 executing a program stored in the memory 312. The program can be recorded on a computer-readable storage medium. The storage medium can be a non-transitory medium such as a semiconductor memory, a hard disk, a magnetic recording medium, or an optical recording medium. That is, the present invention can also be embodied as a computer program product. The program can be downloaded via a network or updated using a storage medium storing the program. The processing modules can also be realized by semiconductor chips.

[0161] The receiving device 22 can also be configured by an information processing device, similar to the server device 10, and its basic hardware configuration is no different from that of the server device 10, so a description thereof will be omitted. The receiving device 22 may be provided with a camera or the like.

[0162] The server device 10, which is an information processing device, is equipped with a computer, and functions of the server device 10 can be realized by causing the computer to execute a program. The server device 10 also executes a control method for the server device 10 by the program.

[0163] [Variations] The configuration, operation, etc. of the information processing system described in the above embodiment are merely examples, and are not intended to limit the configuration, etc. of the system.

[0164] In the above embodiment, the reception device 22 and the main body 21 of the training machine 20 are separate from each other. However, the reception device 22 may be incorporated into the main body 21.

[0165] In the above embodiment, the case where load information is transmitted to the main body 21 of the training machine 20 has been described. However, depending on the type of training machine 20, the reception device 22 may not need to transmit the load information to the main body 21. For example, if the training machine 20 is a bench press, the reception device 22 cannot transmit the load information to the main body 21. In this case, the user can select a weight and train according to the load information proposed by the server device 10 or the load information selected by the user.

[0166] In the above embodiment, when the reception device 22 detects a user in front of it, it uses a GUI to obtain whether the user wishes to start training or to end training. However, the reception device 22 may automatically determine this decision (start training or end training). Specifically, when the reception device 22 detects a user in a situation where the user ID is not stored, it determines that training has started. When the reception device 22 detects a user in a situation where the user ID is stored, it determines that training has ended.

[0167] In the above embodiment, a registered user can use the training machine 20 without any restrictions. However, there are cases where a user's use of the training machine 20 is restricted depending on the fee plan of each member, etc. For example, there are users who cannot use the training machine 20 depending on the time of day or day of the week. In this case, the server device 10 stores the user's fee plan, etc. in the user management database. The server device 10 can authenticate the person to be authenticated using the stored fee plan. Specifically, if the training machine 20 cannot be used under the fee plan of the user identified by the matching process, the server device 10 can notify the receiving device 22 of authentication failure.

[0168] In the above embodiment, the server device 10 calculates the physical condition information of the user based on the vital data of the user. However, the server device 10 may acquire the physical condition information of the user by inputting the biometric information of the user (person to be authenticated) into a learning model.

[0169] In the above embodiment, the case where the server device 10 calculates the vital data of the user has been described. However, the accepting device 22 may calculate the vital data of the user. In this case, the accepting device 22 transmits an authentication request including the calculated vital data to the server device 10.

[0170] When acquiring vital data, the accepting device 22 may use sensors or devices corresponding to various types of vital data such as weight, body fat percentage, body temperature, pulse, blood pressure, etc. For example, the accepting device 22 may be configured to be able to communicate with a weight scale and acquire the user's weight from the weight scale.

[0171] In the above embodiment, an example has been described in which a learning model is implemented in the server device 10. However, the learning model may be implemented in an external server or the like different from the server device 10. In this case, the server device 10 transmits a face image or the like to be input into the learning model to the external server (the server on which the learning model is implemented). The server device 10 may obtain an output of the learning model (e.g., an estimated value of vital data) from the external server.

[0172] In the above embodiment, the accepting device 22 acquires whether the user agrees to train in accordance with the load information using a screen such as that shown in FIG. 7 . In this case, the accepting device 22 may display whether the load is higher or lower than the standard, taking into account the user's physical condition. Furthermore, the accepting device 22 may display the reason why the proposed load information was determined. For example, the accepting device 22 may display a screen such as that shown in FIG. 19 . In this case, the authentication control unit 203 of the server apparatus 10 may transmit an affirmative response to the accepting device 22 including the load information and the above information (whether the load is higher or lower than the standard, and the reason why the load information was determined). For example, if the authentication control unit 203 determines that the user's physical condition is "good," it notifies the accepting device 22 that the load level is higher than the standard. On the other hand, if the authentication control unit 203 determines that the user's physical condition is "poor," it notifies the accepting device 22 that the load level is lower than the standard. Furthermore, authentication control unit 203 may set information such as "because the physical condition was determined to be good" or "because the physical condition was determined to be poor" as the reason for determining the load information. Alternatively, authentication control unit 203 may notify accepting device 22 of the specific type of vital data used to determine the physical condition and its value.

[0173] The server device 10 may suggest changing the load of the training machine 20 on which the user is training, based on the vital data of the user during training. Specifically, the accepting device 22 or the main unit 21 transmits a facial image of the user during training to the server device 10 in real time. The accepting device 22 or the like is equipped with a camera device capable of capturing an image of the user (face image) during training. The authentication control unit 203 generates load information to be suggested to the user during training using vital data from the start of training. For example, the authentication control unit 203 uses time-series data of heart rate to determine whether to increase, decrease, or maintain the load. This decision is obtained by inputting the time-series data of heart rate into a learning model. When increasing or decreasing the load, the authentication control unit 203 generates load information and notifies the accepting device 22 or the like. Upon receiving the notification, the accepting device 22 or the like presents the suggestion from the server device 10 to the user, and if the user agrees to the proposed load (load information), sets the agreed load information in the main unit 21.

[0174] Furthermore, when load information during training is changed based on changes in vital data as described above, the reception device 22 may omit obtaining the user's consent (to train using the proposed load information) using the GUI shown in FIG. 7 . That is, when the training machine 20 has an "automatic load setting mode" and the user selects the automatic load setting mode, load information is proposed to the user at an appropriate time during training. Therefore, the reception device 22 does not need to obtain the user's consent to the load information (load of the training machine 20) proposed by the server device 10 before starting training. Alternatively, when the reception device 22 detects a user in front of it and displays a screen such as that shown in FIG. 5 , the reception device 22 may obtain whether the user desires the "automatic load setting mode." For example, the reception device 22 may obtain whether the user desires the automatic load setting mode based on their physical condition using a GUI such as that shown in FIG. 20 .

[0175] The receiving device 22 may acquire an evaluation (impression) of the proposed load information from a user who has completed training based on the load information proposed by the server device 10. For example, the receiving device 22 acquires the user's evaluation of the proposed load information, such as "appropriate," "not enough load," or "too much load." The receiving device 22 transmits a training completion notice including the acquired evaluation to the server device 10. The server device 10 stores the acquired evaluation in the user's account. When the same user starts training using the same training machine 20, the server device 10 may generate load information taking into account the evaluation stored in the account.

[0176] In the above embodiment, a case has been described in which a facial image is transmitted as biometric information from the accepting device 22 to the server device 10. However, a feature amount generated from the facial image may be transmitted as biometric information from the accepting device 22 to the server device 10. In this case, the server device 10 may omit the process of generating a feature amount from the facial image and may simply perform the matching process.

[0177] In the above embodiment, the case where the user management database is configured inside the server device 10 has been described, but the database may also be configured on an external database server or the like. That is, some of the functions of the server device 10 may be implemented on another server. More specifically, it is sufficient that the above-described "authentication control unit (authentication control means)" and the like are implemented on any of the devices included in the system.

[0178] The format of data transmission between the devices (server device 10, accepting device 22) is not particularly limited, but the data transmitted between these devices may be encrypted. Biometric information of users and other information is transmitted between these devices, and in order to properly protect this information, it is desirable to transmit and receive encrypted data.

[0179] In the flow charts (flowcharts, sequence diagrams) used in the above explanation, multiple steps (processes) are described in order, but the execution order of the steps executed in the embodiments is not limited to the order described. In the embodiments, the order of the illustrated steps can be changed to the extent that the content is not affected, such as by executing each process in parallel.

[0180] The above-described embodiments have been described in detail to facilitate understanding of the present disclosure, and it is not intended that all of the above-described configurations are required. Furthermore, when multiple embodiments are described, each embodiment may be used alone or in combination. For example, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of one embodiment with another configuration.

[0181] The above explanation makes clear the industrial applicability of the present invention, and the present invention is suitably applicable to an information processing system that authenticates users who use training machines 20 installed in a training gym or the like.

[0182] Some or all of the above embodiments can be described as, but are not limited to, the following supplementary notes. [Appendix 1] a calculation means for calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine, based on vital data of the training starter; a generating means for generating load information relating to a load to be set on the training machine based on the calculated physical condition information; A server device comprising: [Appendix 2] a storage means for storing biometric information of each of a plurality of users who can use the training machine; an authentication means for receiving an authentication request including biometric information of the training starter, authenticating the training starter by performing an authentication process using the biometric information included in the authentication request and the stored biometric information, and notifying the training machine of the authentication result; 2. The server device according to claim 1, further comprising: [Appendix 3] 3. The server device according to claim 2, wherein the authentication means, upon successful authentication of the training initiator, notifies the training initiator of the generated load information via the training machine. [Appendix 4] The server device described in Appendix 3, wherein the calculation means calculates vital data of the training starter using biometric information of the training starter identified from the multiple users by the authentication process, and calculates the physical condition information based on the calculated vital data. [Appendix 5] 5. The server device according to claim 1, wherein the generating means generates the load information based on the calculated physical condition information and attributes of the identified training starter. [Appendix 6] The server device according to any one of appendices 1 to 4, wherein the generating means generates the load information based on changes in the vital data before and after use of the training machine when the training starter has used the training machine in the past. [Appendix 7] 5. The server device according to claim 1, wherein the generating means generates the load information according to the type of the training machine used by the identified training starter. [Appendix 8] the storage means stores the biometric information of the training starter identified by the authentication process in association with vital data calculated from the biometric information included in the authentication request used in the authentication process; 5. The server device according to claim 2, further comprising an information provision control means for providing information using the stored vital data. [Appendix 9] a calculation step of calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine based on vital data of the training starter; a generating step of generating load information regarding a load to be set on the training machine based on the calculated physical condition information; A method for controlling a server device, comprising: [Appendix 10] a storage step of storing biometric information of each of a plurality of users who can use the training machine; an authentication process of receiving an authentication request including biometric information of the training starter, authenticating the training starter by performing an authentication process using the biometric information included in the authentication request and the stored biometric information, and notifying the training machine of the authentication result; 10. The method for controlling a server device according to claim 9, further comprising: [Appendix 11] 11. The server device control method according to claim 10, wherein the authentication step notifies the training initiator of the generated load information via the training machine if the authentication of the training initiator is successful. [Appendix 12] The control method for a server device described in Appendix 11, wherein the calculation step calculates vital data of the training starter using biometric information of the training starter identified from the multiple users by the authentication process, and calculates the physical condition information based on the calculated vital data. [Appendix 13] 13. The server device control method according to any one of claims 9 to 12, wherein the generation step generates the load information based on the calculated physical condition information and the attributes of the identified training starter. [Appendix 14] 13. The control method for a server device according to any one of claims 9 to 12, wherein the generating step generates the load information based on changes in the vital data before and after use of the training machine when the training initiator has used the training machine in the past. [Appendix 15] 13. The server device control method according to any one of appendices 9 to 12, wherein the generating step generates the load information according to the type of the training machine used by the identified training starter. [Appendix 16] the storage step stores the biometric information of the training starter identified by the authentication process in association with vital data calculated from the biometric information included in the authentication request used in the authentication process; 13. The method for controlling a server device according to any one of claims 10 to 12, further comprising an information provision control step of providing information using the stored vital data. [Appendix 17] The computer installed in the server device a calculation process for calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine, based on vital data of the training starter; a generation process for generating load information regarding a load to be set on the training machine based on the calculated physical condition information; A program to execute. [Appendix 18] a storage process for storing biometric information of each of a plurality of users who can use the training machine; an authentication process of receiving an authentication request including biometric information of the training starter, authenticating the training starter by performing an authentication process using the biometric information included in the authentication request and the stored biometric information, and notifying the training machine of the authentication result; 18. The program of claim 17, further comprising: [Appendix 19] 19. The program according to claim 18, wherein the authentication process notifies the training initiator of the generated load information via the training machine if the authentication of the training initiator is successful. [Appendix 20] The program described in Appendix 19, wherein the calculation process calculates vital data of the training starter using biometric information of the training starter identified from the multiple users by the authentication process, and calculates the physical condition information based on the calculated vital data. [Appendix 21] 21. The program according to any one of appendices 17 to 20, wherein the generation process generates the load information based on the calculated physical condition information and attributes of the identified training starter. [Appendix 22] The program according to any one of appendices 17 to 20, wherein the generation process generates the load information based on changes in the vital data before and after use of the training machine when the training starter has used the training machine in the past. [Appendix 23] 21. The program according to any one of appendices 17 to 20, wherein the generation process generates the load information according to the type of the training machine used by the identified training starter. [Appendix 24] the storage process stores the biometric information of the training starter identified by the authentication process in association with vital data calculated from the biometric information included in the authentication request used in the authentication process; 21. The program according to any one of appendices 18 to 20, further causing the program to execute an information provision control process that provides information using the stored vital data.

[0183] Furthermore, some or all of the configurations described in Supplementary Notes 2 to 8, which are dependent on Supplementary Note 1, may also be dependent on Supplementary Notes 9 and 17 in the same dependent relationship as Supplementary Notes 2 to 8. Furthermore, not limited to Supplementary Notes 1, 9, and 17, but within the scope of each of the above-mentioned embodiments, some or all of the configurations described as Supplements may also be dependent on various hardware, software, various recording means for recording software, or systems.

[0184] The disclosures of the above-cited prior art documents are incorporated herein by reference. Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments. Those skilled in the art will understand that these embodiments are merely illustrative and that various modifications are possible without departing from the scope and spirit of the present invention. In other words, the present invention naturally includes various modifications and alterations that may be made by those skilled in the art in accordance with the entire disclosure, including the claims, and the technical concepts thereof. [Explanation of symbols]

[0185] 10 Server device 20 Training Machines 21 Main Unit 22 Reception Device 30 devices 100 Server device 101 Calculation Method 102 Generation means 201 Communication control unit 202 User Management Department 203 Authentication control unit 204 End notification processing unit 205 Storage section 206 Information provision control section 301 Communication Control Unit 302 Biometric information acquisition unit 303 Judgment section 304 Authentication Request Section 305 Termination Notice Section 306 Storage section 311 processor 312 memory 313 Input / Output Interface 314 Communication Interface

Claims

1. a calculation means for calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine, based on vital data of the training starter; a generating means for generating load information relating to a load to be set on the training machine based on the calculated physical condition information; A server device comprising:

2. a storage means for storing biometric information of each of a plurality of users who can use the training machine; an authentication means for receiving an authentication request including biometric information of the training starter, authenticating the training starter by performing an authentication process using the biometric information included in the authentication request and the stored biometric information, and notifying the training machine of the authentication result; The server device according to claim 1 , further comprising:

3. 3. The server device according to claim 2, wherein said authentication means, upon successful authentication of said training initiator, notifies said training initiator of said generated load information via said training machine.

4. 4. The server device according to claim 3, wherein the calculation means calculates vital data of the training starter using biometric information of the training starter identified from the plurality of users by the authentication process, and calculates the physical condition information based on the calculated vital data.

5. The server device according to claim 1 , wherein the generating means generates the load information based on the calculated physical condition information and attributes of the identified training starter.

6. 5. The server device according to claim 1, wherein the generating means generates the load information based on changes in the vital data before and after the training starter used the training machine in the past.

7. The server device according to claim 1 , wherein the generating means generates the load information according to the type of the training machine used by the identified training starter.

8. the storage means stores the biometric information of the training starter identified by the authentication process in association with vital data calculated from the biometric information included in the authentication request used in the authentication process; The server device according to claim 2 , further comprising an information provision control unit that provides information using the stored vital data.

9. a calculation step of calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine based on vital data of the training starter; a generating step of generating load information regarding a load to be set on the training machine based on the calculated physical condition information; A method for controlling a server device, comprising:

10. The computer installed in the server device a calculation process for calculating physical condition information relating to the physical condition of a training starter who is about to start training using a training machine, based on vital data of the training starter; a generation process for generating load information regarding a load to be set on the training machine based on the calculated physical condition information; A program to execute.

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