Information processing device, information processing device control method, and information processing device control program

Abstract

To provide an information processing device related to a training support system capable of updating a training program according to the daily training situation of a user and maintaining the motivation of the user.SOLUTION: An information processing device for providing a user with a training program on running comprises: a setting unit which sets a training menu to be carried out during a predetermined period and the execution dates of the training menu as the training program.; an acquisition unit which acquires execution information indicating whether the user has performed the training menu scheduled for the execution date; a determination unit which determines whether the training menu scheduled for the execution date was performed on that day; an update unit, when the determination unit determines that the training menu for the day has not been performed, updates the training menus scheduled for the following days on the basis of predetermined conditions; and a display processing unit which displays the updated training menu on a terminal.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing device, a control method for an information processing device, and a control program for an information processing device. [Background technology]

[0002] Conventionally, there are services for helping users maintain their exercise habits. For example, Patent Literature 1 discloses a service that collects exercise information of a user and provides direct and visible feedback to the user to motivate the user to maintain a regular exercise program. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2017-073125 A Summary of the Invention [Problem to be solved by the invention]

[0004] Even if a training program for running, walking, cycling, or other exercises is provided, there may be cases where the program cannot be carried out due to bad weather or poor physical condition, or where the user is unable to find time due to work. Even on a day when a training menu is to be carried out according to the training program, the user may not be able to practice according to the provided menu depending on the user's physical condition and the amount of time available. In this way, not being able to practice according to the program may lead to a decrease in the user's motivation.

[0005] Therefore, there has been a demand for a practice support system that can update a practice program to an appropriate state for the user in accordance with the user's daily practice situation, thereby maintaining the user's motivation. [Means for solving the problem]

[0006] An information processing device according to one embodiment of the present invention that provides a user with a running training program includes a setting unit that sets, as the training program, a training menu to be performed within a specified period and the date on which the training menu will be performed, an acquisition unit that acquires implementation information regarding whether or not the user has performed the training menu set on the implementation date, a judgment unit that determines whether the training menu on the implementation date has been performed, an update unit that updates the training menu for the day after that based on specified conditions when the judgment unit determines that the practice menu for that day has not been performed, and a display processing unit that displays the updated training menu on a terminal.

[0007] A control method of an information processing device that provides a user with a running training program according to one embodiment of the present invention includes the steps of the information processing device setting, as a training program, a training menu to be performed within a specified period and a date on which the training menu will be performed, acquiring implementation information regarding whether or not the user has performed the training menu set on the implementation date, determining whether or not the training menu on the implementation date has been performed, updating the training menu for the day after that based on specified conditions if it is determined that the training menu for that day has not been performed, and displaying the updated training menu on a terminal.

[0008] A control program of an information processing device that provides a user with a running training program according to one embodiment of the present invention provides the information processing device with the following functions: a training menu to be performed within a specified period and a date on which the training menu will be performed as a training program; a function to obtain implementation information regarding whether or not the user has performed the training menu set on the implementation date; a function to determine whether or not the training menu on the implementation date has been performed; a function to update the training menu for the day after that based on specified conditions if it is determined that the training menu for that day has not been performed; and a function to display the updated training menu on the terminal. Effect of the Invention

[0009] According to one embodiment of the present invention, an information processing device, etc. can be provided for a practice support system in which a practice program is updated to an appropriate state for the user in accordance with the user's daily practice situation, thereby contributing to maintaining the user's motivation. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a practice support system according to one embodiment of the present invention. [Diagram 2] FIG. 2 is an example of a functional block diagram of a server (information processing device), a user terminal (communication terminal, and a sensor device) according to an embodiment of the present invention. [Diagram 3] FIG. 3 is an example of a training program. [Figure 4] FIG. 4(a) is an example of a first priority order table according to an embodiment of the present invention, and (b) is a schematic diagram illustrating a training program update process. [Diagram 5] FIG. 5 is a flowchart showing an example of the operation of the server according to one embodiment of the present invention. [Figure 6] FIG. 6 is a flowchart showing an example of the operation of the server according to one embodiment of the present invention. [Figure 7] 7(a) to (c) are diagrams showing an example of a display screen of a user terminal according to an embodiment of the present invention. [Figure 8] 8(a) to (c) are schematic diagrams illustrating updating of the running ability growth rate. [Figure 9] FIG. 9 is an example of the second priority order table according to an embodiment of the present invention. [Figure 10] 10(a) and (b) are schematic diagrams illustrating the update process of a practice program according to one embodiment of the present invention. [Figure 11] FIG. 11 is a diagram showing an example of a display screen of a user terminal according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the invention (also referred to as the present invention) according to the present disclosure will be described with reference to the drawings. Note that the drawings are merely examples, and the present invention is not limited to those shown in the drawings. For example, the illustrated servers (information processing devices), user terminals (communication devices), database servers, the number of sensor devices and their size ratios, data sets (tables), display screens, training programs, and flow charts are merely examples, and the present invention is not limited to these.

[0012] <System configuration> FIG. 1 is a diagram showing an example of the configuration of a practice support system according to an embodiment of the present invention. The practice support system 600 may be an information and communication system that supports practice by a user (runner). According to an embodiment of the present invention, a practice program according to the running ability of the user may be set for the user, and the practice program may be adaptively updated according to the implementation status of the practice by the user. Furthermore, according to an embodiment of the present invention, information on the growth rate of running ability according to the implementation status of the practice program may be provided to the user. Note that "practice" in this specification includes "training," "training," "discipline," etc., and may include practice independently conducted by an individual, or practice under the guidance of an expert or trainer.

[0013] The practice support system 600 may include at least a server 100, a database server 101, a user's communication terminal (user terminal) 200 (200A, 200B), and sensor devices 301 (301A, 301B), 302 (302A, 302B). In FIG. 1, two users A and B are shown, and the alphabets "A" and "B" are added to the symbols of the user terminal and the sensor device, respectively. However, the number of users may be more or less than this, and the number of user terminals and sensor devices may be the same as the number of users. In addition, hereinafter, when no particular distinction is made, the user terminal and the sensor device are simply referred to as the user terminal 200 and the sensor devices 301 and 302, respectively. In addition, the sensor device 301 may be a motion sensor, and the sensor device 302 may be a vital sensor, as will be described in detail later.

[0014] The server 100 can execute various processes related to the practice support service realized by the practice support system 600. The server 100 is connected to the user terminal 200 via a network 500. The network 500 may include a wireless network or a wired network, and may be, for example, a wireless LAN (WLAN), a wide area network (WAN), integrated service digital networks (ISDNs), wireless LANs, code division multiple access (CDMA), long term evolution (LTE), LTE-Advanced, fourth generation communication (4G), fifth generation communication (5G), sixth generation communication (6G) or later mobile communication systems, or a combination of these.

[0015] The server 100 further transmits and receives various data to and from the database server 101. The database server 101 stores (stores) various data required to realize the functions of the practice support system 600. In the figure, the server 100 and the database server 101 are shown connected via a network 500, but the server 100 and the database server 101 may be connected via a dedicated internal network. In the figure, the server 100 and the database server 101 are shown separately, but the database server 101 may function as a storage unit of the server 100, which will be described later. In FIG. 1, one server 100 and one database server 101 are shown, but this is not limited to this. That is, each function described as being provided by the server 100 may be realized by multiple servers, or there may be multiple database servers 101. In addition, the server 100 may be, for example, a distributed server system that cooperates by communicating via a network, or a so-called cloud server. That is, the server 100 is not limited to a physical server, and may also include a virtual server implemented by software.

[0016] The user terminal 200 is a communication terminal used by a user, and has an application (hereinafter, also referred to as a "practice support application") for using the practice support service installed therein. Although details will be described later, the user terminal 200 may be capable of transmitting information acquired from the motion sensor device 301 and the vital sensor 302 to the server 100 via the practice support application.

[0017] 1 shows a smartphone as the user terminal 200, the user terminal 200 may be any terminal capable of implementing the functions described in each embodiment described below. For example, the user terminal 200 may be a computer (e.g., a tablet, a desktop computer, a notebook computer), a handheld computing device (including, but not limited to, a wearable device (glasses-type device (smart glasses), watch-type device (smart watch), etc.), a smart speaker, etc.). The sensor device 302 may also have various functions of the communication device 200 described below and function as the communication device 200.

[0018] The user may wear the motion sensor device 301 and the vital sensor 302 and perform various training menus related to running. Here, the "training menu" is a combination of an exercise menu (described later) that defines the type of running, such as jogging, interval running, and build-up running, and a running distance. The motion sensor device 301 and the vital sensor 302 are wearable devices with a communication function that are worn on the user's body, acquire the user's running information and biometric information, and can transmit the acquired information to the user terminal 200. The motion sensor device 301 is worn near the waist along the user's torso, and measures sensor data for calculating an evaluation value of an index that evaluates the user's running form as running information. Depending on the type of the motion sensor device 301, it may be worn on shoes. In addition, the vital sensor 302 acquires biometric information of the user while running. The running information and biometric information may be included in the "implementation information" described later, which is related to the determination of whether the user has performed the training menu.

[0019] 1, the motion sensor device 301 and the vital sensor 302 are shown separately, but the present invention is not limited to this, and the running information and the biological information may be acquired by a single sensor device in which the motion sensor device 301 and the vital sensor 302 are integrated, or a plurality of sensor devices may be used. The running information and the biological information will be described later.

[0020] Next, the hardware configuration and functional configuration of the server 100, the user terminal 200, the motion sensor device 301, and the vital sensor 302 will be described with reference to FIG.

[0021] <Sensor device> 2 shows an example of a block diagram of the sensor devices (motion sensor device 301, vital sensor 302). Note that the motion sensor device 301 and the vital sensor 302 have the same basic configuration and function, except for the information they acquire, so they will be described using the same block diagram.

[0022] The motion sensor device 301 and the vital sensor 302 each include a control unit 310, a communication unit 320, a sensor unit 330, an operation unit 340, and a storage unit 370. The control unit 310 is composed of an arithmetic processing device such as a CPU, and acquires the output of the sensor unit 330 at a predetermined timing by executing a program stored in the storage unit 370. The control unit 310 also transmits the data acquired from the sensor unit 330 to the user terminal 200 via the communication unit 220.

[0023] In the motion sensor device 301, the sensor unit 330 detects, for example, acceleration occurring in a linear direction along three mutually orthogonal axes, angular velocity occurring in a rotational direction around the three mutually orthogonal axes, or geomagnetism. The sensor unit 330 acquires sensor data such as acceleration and angular velocity when the user runs as running information. The running information may be stored in the storage unit 370 together with information related to the time when the information was acquired.

[0024] In the vital sensor 302, the sensor unit 330 detects biological information such as the user's body temperature, blood pressure, heart rate, number of breaths per unit time, etc. The biological information may be stored in the storage unit 370 together with information related to the time when the biological information was acquired.

[0025] The communication unit 320 has a function of transmitting and receiving data to and from the user terminal 200 using a predetermined communication protocol by wireless communication such as wireless LAN (Local Area Network) or short-range wireless communication (e.g., Bluetooth (registered trademark) Low Energy: BLE) or wired communication. For example, the communication unit 320 transmits the running information and biological information stored in the storage unit 370 to the user terminal 200. Note that the communication unit 320 may send the running information and biological information stored in the storage unit 370 together to the user terminal 200 after the measurement by the motion sensor device 301 and the vital sensor 302 is completed, or may transmit the running information and biological information stored in the storage unit 370 at a predetermined timing during the measurement by the sensor unit 330.

[0026] The operation unit 340 is configured with, for example, an input button or a touch panel, and accepts operations by a user. For example, in the motion sensor device 301 and the vital sensor 302, measurement by the sensor unit 330 may be started, interrupted, stopped, etc., when a user inputs an operation to start measurement on the operation unit 340.

[0027] <User device> (1) Hardware configuration of user terminal The user terminal 200 includes a control unit 210 , a communication unit 220 , a display unit 230 , an input / output unit 240 , and a storage unit 270 .

[0028] The control unit 210 is typically a processor, and is realized by a central processing unit (CPU), a micro processing unit (MPU), a graphics processing unit (GPU), etc. The control unit 210 reads out a program stored in the storage unit 270, and executes a code or instruction included in the program, thereby executing the functions and methods described in each embodiment.

[0029] The control unit 210 controls the communication unit 220, the display unit 230, and the input / output unit 240. Specifically, the control unit 210 controls communication between the user terminal 200 and the server 100, the motion sensor device 301, and the vital sensor 302 by the communication unit 220, and transmits and receives various data between them. The control unit 210 also controls the display of data on the display unit 230. For example, the control unit 210 may display, on the display unit 230, a training menu for the day of the training program set for the user, running ability predicted to be obtained by performing the training menu, and the like. Furthermore, the control unit 210 controls the transmission of various information to an external device via the input / output unit 240. For example, the control unit 210 may transmit various information to each functional unit in response to an input operation of the user received by the input device, or transmit information from each functional unit to an output device (not shown), such as a touch panel, a monitor, or a speaker.

[0030] The storage unit 270 stores various programs and various data required for the operation of the user terminal 200. For example, the storage unit 270 may store the program of the practice support application described above. The storage unit 270 may include, for example, a flash memory or the like, and may also include a memory (such as a RAM (Random Access Memory), a ROM (Read Only Memory)) that provides a working area for the control unit 210.

[0031] The communication unit 220 is implemented as hardware such as a network adapter, communication software, or a combination of these, and transmits and receives various data to and from the server 100 via the network 500. The communication may be performed either wired or wirelessly, and any communication protocol may be used as long as the communication between the two units can be performed. The communication unit 220 transmits various data to the server 100 in accordance with an instruction from the control unit 210. The communication unit 220 also receives various data transmitted from the server 100 and transmits the data to the control unit 210. The communication unit 220 also performs the above-mentioned wireless or wired communication between the motion sensor device 301 and the vital sensor 302.

[0032] Display unit 230 is a monitor that displays data according to the display data written to the frame buffer, and may be, for example, a touch panel, a touch display, or the like.

[0033] The input / output unit 240 includes an input device for inputting various operations to the user terminal 200, and an output device for outputting processing results processed by the user terminal 200. The input device may include, for example, a touch panel, a touch display, a camera, and a microphone, and the output device may include, for example, a display, a touch panel, a speaker, etc.

[0034] (2) Functional configuration of user terminal The user terminal 200 includes a sensor data acquisition unit 211 as a function realized by the control unit 210.

[0035] The sensor data acquisition unit 211 acquires sensor data measured by a motion sensor device 301 worn by the user as running information. The sensor data acquisition unit 211 also acquires sensor data measured by a vital sensor 302 worn by the user as biological information.

[0036] The running information is used to calculate an index related to the user's running form. The index is an element indicating the quality of the user's running, and may include, for example, running speed, pitch, stride, stride height ratio, vertical movement, vertical movement height ratio, left and right movement, front and rear movement, landing time, swing time, landing time rate, swing time rate, deceleration amount, sinking amount, sinking amount height ratio, sinking time, braking time, propulsion time, landing impact, kicking acceleration, kicking time, pelvic rotation amount, stiffness, stiffness to body weight ratio, landing angle, kicking angle, left and right impact, pelvic backward tilt amount, pelvic drop amount, pelvic lift amount, pelvic rotation timing after landing, forward tilt angle, and impact peak tilt. Each index can characterize the user's running form and estimate the user's fatigue level.

[0037] Any known method may be used to calculate each index, for example, the methods described in Japanese Patent No. 6648439, Japanese Patent No. 6711433, Japanese Patent No. 7155345, Japanese Patent No. 5849092, etc.

[0038] <Server> (1) Server hardware configuration The server 100 includes a control unit 110, a communication unit 120, a display unit 130, and a storage unit 170.

[0039] The storage unit 170 is typically realized by various recording media such as a hard disk drive (HDD), a solid state drive (SSD), and a flash memory, and has a function of storing various programs and data required for the operation of the server 100. The storage unit 170 also includes a memory (RAM, ROM, etc.) that provides a working area for the control unit 110.

[0040] The control unit 110 is typically a processor, and is realized by a central processing unit (CPU), an MPU, a GPU, etc. The control unit 110 may execute the functions and methods described in each embodiment by reading a program stored in the storage unit 170 and executing codes or instructions included in the program.

[0041] The communication unit 120 is implemented as hardware such as a network adapter, communication software, or a combination of these. The communication unit 120 may transmit and receive various data to and from the user terminal 200 via the network 500 using any communication protocol.

[0042] (2) Functional configuration of the server The server 100 includes a setting unit 111, an acquisition unit 112, a determination unit 113, an update unit 114, a display processing unit 115, and a prediction unit 116 as functions realized by the control unit 110. Note that in Fig. 2, functional units that are not essential to each embodiment described hereinafter may be omitted. Furthermore, the functions or processes of each functional unit may be realized by machine learning or AI to the extent that they can be realized.

[0043] The setting unit 111 sets a training menu to be performed in a predetermined period and the date on which the training menu is to be performed as a training program related to running. Here, various exercises constituting the training program are referred to as an "exercise menu." Examples of the exercise menu include jogging, pace running, build-up running, interval running, repetition running, and LSD (Long Slow Distance).

[0044] Here, jogging means, for example, running at an intensity of about 70% or less of the maximum heart rate. Pace running means, for example, running at a constant pace that simulates a target race. Build-up running means, for example, running by gradually increasing the pace. Interval running means, for example, running by repeating anaerobic sprinting and aerobic jogging. Repetition running means, for example, running a set distance at a pace close to full power, taking a rest, and then repeating the same running again. LSD means, for example, running slowly and for a long time regardless of the pace.

[0045] The setting unit 111 may use a data set conforming to a calculation table based on VDOT proposed by Jack Daniels to set the user's training program. VDOT is a pseudo VO2max (maximum oxygen uptake) and is an index indicating the user's current running ability level, and can be estimated, for example, from a record under maximum effort in a recent race. From VDOT, the completion time for a certain distance can be predicted. For example, if VDOT is 30, the completion time for 10 km can be predicted as 1 hour, 3 minutes, and 46 seconds, and the completion time for a half marathon can be predicted as 2 hours, 21 minutes, and 4 seconds. Hereinafter, VDOT is referred to as "running ability (RL: Running Level)". Here, information required for estimating the user's running ability may be obtained from running information obtained from the sensor device 301 or input by the user. Then, the setting unit 111 estimates an AT value (Anaerobic Threshold) according to the determined running ability, and sets a pace that is a guide for the training menu.

[0046] The setting unit 111 also sets the training program based on a predetermined training theory. Here, the predetermined training theory may be based on the idea of ​​periodization, which is similar to the training phase proposed by Daniels. Periodization means dividing a training period into several periods (phases) and arranging a training menu with a running pace and running distance corresponding to each period in order to match the peak of condition and performance to the actual event such as a tournament or a match. The periodization may be composed of, for example, a preparation period, a speed training period, a running period, a race simulation period, and a recovery period, but is not limited thereto. According to the idea of ​​periodization, by implementing a training program in which the type, amount, and intensity of training in each period are adjusted, the growth rate of the user's running ability will draw a predetermined growth curve from the start of training to the actual event. The setting unit 111 may adjust the running pace and running distance of the training menu to be implemented in each period based on the user's current running ability (at the time of starting training) determined above, and set a training program specific to the user.

[0047] In one embodiment of the present invention, the training program may divide a predetermined period from the start of training to a target competition into a predetermined number of time series, and a training menu for each section may be set according to the running ability of the user in accordance with the above-mentioned concept of periodization. The predetermined period may be, for example, 20 to 24 weeks, but is not limited thereto, and may be 20 weeks or less or 24 weeks or more. The training program may be arranged such that each section is one week (7 days), and each period of the periodization is composed of at least one section or more (i.e., one week to several weeks). That is, if the predetermined period is 20 weeks, the predetermined number may be 20, and each section may be one week. However, the present invention is not limited thereto, and each section may be, for example, 5 days or 10 days.

[0048] FIG. 3 shows an example of a set training program. FIG. 3 shows an example of a training program table TB10 set according to the running ability of user A, for example, and is stored in the database server 101. Note that the figure is a schematic and shows only a part, and is not accurate. In the example of FIG. 3, the training program has training menus of 4 km jogging, 8 km jogging, and 5 km jogging arranged on Tuesday, Wednesday, and Friday, respectively, in one section (one week) constituting the preparation period. Also, in multiple sections (several weeks) constituting the speed training period, 4 km jogging, 10 km build-up running, and 12 km build-up running are arranged on Tuesday, Wednesday, and Friday, respectively. Note that in each period of the division, the training menu may be the same among multiple sections constituting one period, or may be different for each section (one week). In this way, a training menu is arranged for each section until the last day of the recovery period (the last day of the specified period).

[0049] The display processing unit 115 of the server 100 displays information on the practice menu to be performed that day on the user terminal 200 in accordance with the set practice program. The user can check the practice menu to be performed that day on the user terminal 200 via the practice assistance app. Alternatively, the practice menu to be performed that day may be notified on the user terminal 200 by a pop-up display, or may be notified via email or an existing communication app.

[0050] The acquisition unit 112 acquires implementation information regarding whether or not the user has implemented the practice menu set on the implementation date. The implementation information is information that can determine whether or not the practice menu on the implementation date has been implemented by the user, and may be information input by the user via the practice support app, or may be driving information acquired by the sensor device 301. The implementation information may be acquired by the acquisition unit 112, for example, when the user transmits to the server 100 that the user has implemented the practice via the practice support app, or when the user terminal 200 transmits the driving information acquired by the sensor device 301 to the server 100 in response to receiving the driving information.

[0051] The determination unit 113 determines whether or not the user has performed the training menu on the day of the implementation date. The determination unit 113 determines whether or not the user has performed a training menu set in advance based on the implementation information acquired by the acquisition unit 112. For example, the determination unit 113 determines whether or not the training menu for the day, for example, "jogging 4km", has been performed based on the running information by the sensor device 301 acquired as the implementation information. When the sensor device 301 is used, for example, the minimum value of the running speed or the running distance may be set in advance as a reference value, and whether or not the training menu has been performed may be determined based on the reference value. Alternatively, the determination unit 113 may determine whether or not the training menu has been performed based on information input by the user via a training support app. For example, the user terminal 200 may display a screen that allows the user to select whether or not the training menu for the day, "jogging 4km", has been performed, or a screen that allows the user to input the content of the training performed on the day, and the user's selection and input results may be transmitted to the server 100.

[0052] Alternatively, the determination unit 113 may determine that the practice menu for that day has not been performed when the implementation information is not acquired. The case where the implementation information is not acquired may be, for example, when there is no driving information acquired by the sensor device 301 on that day, or when the implementation information via the practice support app is not transmitted from the user terminal 200 to the server 100.

[0053] When the determination unit 113 determines that the practice menu for the current day has not been implemented, the update unit 114 updates the practice menu for the next day and thereafter based on a predetermined condition.

[0054] Here, the update of the practice menu will be described with reference to FIG. 4. FIG. 4(a) is an example of the first priority table stored in the database server 101. Note that the figure is a rough outline and not exact. The first priority table TB20 is a table showing multiple combinations of practice menus and implementation dates of the practice menus, and the priorities of the combinations, for each section obtained by dividing a predetermined period into a predetermined number of sections in chronological order. The predetermined period is the period during which the practice program is implemented from the start of practice to the target tournament, as described above. The section obtained by dividing the predetermined period into a predetermined number of sections in chronological order corresponds to one section described above, and may be, for example, one week. The first priority table TB20 is set in advance for each section according to the concept of division. For example, the first priority order table TB20 may be stored for each section (i.e., week), such as the first week which is the preparation period, the second week onwards which is the speed training period, the Mth week (M is a predetermined integer) onwards which is the running period, etc. FIG. 4(a) shows the first priority order table TB20 for the Nth week (Nth section).

[0055] The first priority order table TB20 stores a plurality of combinations of training menus and implementation dates of the training menus together with priorities. In the example of FIG. 4(a), the combination with the highest priority order is one in which training menus "A", "B", and "C" are implemented four times a week on Tuesday, Wednesday, Friday, and Saturday, respectively. The combination with the second highest priority order is one in which training menus "A", "B", and "C" are implemented four times a week on Tuesday, Wednesday, Friday, and Sunday, respectively. The first priority order table TB20 may be used to set the training program by the setting unit 111. That is, the setting unit 111 may extract the combination with the highest priority order from the first priority order table TB20 for each category, correct it according to the user's running ability, and set it as the training program at the start of training. Furthermore, if the training program is to consist of three training sessions per week, the combinations with the highest priority among the three sessions per week in the first priority table TB20 (in the case of FIG. 4(a), the combination with the 13th priority) may be extracted for each category, and the training program may be set.

[0056] Further explanation will be given with reference to FIG. 4(b). Now, consider a case where a user who trains with the combination M2 of the practice menu is judged to have not yet performed the practice menu "B" that should be performed on Friday of the Nth week. At this time, the update unit 114 updates the practice menu for the next day and thereafter to the combination of the practice menu that is the first to have a blank Friday practice menu when looking at the combinations of the practice menus located in the row below the combination M2 of the practice menu based on the first priority order table TB20 of FIG. 4(a). In the example of FIG. 4(a), when looking at the combinations of the practice menus located in the row below the combination M2, the combination M3 is the first combination to have a blank Friday practice menu. Therefore, in the Nth week, the practice menu for Saturday and thereafter is updated to the combination M3 as shown in FIG. 4(b).

[0057] In the first priority order table TB20, the priority order between the practice menus within the practice period is set according to the concept of periodization. Also, in order to prevent the user from being injured, the priority order is set with the intention of restricting the practice menu from being performed on consecutive days. As a result, according to one embodiment of the present invention, the practice program is updated so that the unperformed practice menu can be covered after the day when practice was not possible.

[0058] Thus, according to one embodiment of the present invention, even if the user is unable to complete the training menu for that day, the training menu for the following days is updated to cover the training menu that has not been completed, thereby preventing a decline in the user's running ability and motivation and enabling efficient training to be maintained.

[0059] The display processing unit 115 displays the information on the updated practice menu on the user terminal 200. The information on the practice menu may be any information that can inform the user that practice "B" should be performed on Friday, and the timing of displaying the information does not matter. For example, the fact that practice menu "B" should be performed on Friday may be notified at a preset time on Thursday night, or may be displayed when the user starts up the practice support app on Friday. Alternatively, the user terminal 200 may be notified that the practice menu has been changed after Friday.

[0060] <Server control flow chart> The control method of the server 100 described above will be explained using the flowchart of FIG. 5. The function of the prediction unit 116 will be described later. As described above, the setting unit 111 of the server 100 sets a training menu to be performed in a predetermined period as a training program related to running, and a date on which the training menu will be performed (step S11). The acquisition unit 112 acquires implementation information on whether or not the training menu set on the implementation date has been performed by the user (step S12). The determination unit 113 determines whether or not the training menu on the implementation date has been performed (step S13). If it is determined that the training menu on the implementation date has been performed (YES in step S13), the process ends. If it is determined that the training menu on the implementation date has not been performed (NO in step S13), the update unit 114 updates the training menu for the day after the implementation date based on a predetermined condition (step S14). In addition, the display processing unit 115 displays the updated training menu on the terminal (step S1).

[0061] Thus, according to one embodiment of the present invention, if the user has not performed training in accordance with the training program, the training program for the next day and thereafter may be updated to cover the training menu that has not been performed. In addition, the user is notified that the training program has been updated, which helps to maintain the user's motivation and allow them to continue training.

[0062] <Other embodiments> According to one embodiment of the present invention, the growth of the user's running ability may be predicted according to the implementation status of the training program. That is, the prediction unit 116 predicts the user's running ability at the end of a predetermined period according to the implementation status of the training menu during the predetermined period based on the implementation information. For example, when the intensity at which the training menu is implemented is changed by the user, the predicted growth of the running ability may be updated. Also, in the above description, a mode in which the training menu is updated from the next day onwards because the user has not implemented the training menu on the implementation day has been described. According to one embodiment of the present invention, when the period during which the set training menu has not been implemented extends over a certain section, the update of the training menu is different from the case in which the training menu on the implementation day has not been implemented. Hereinafter, these modes will be described.

[0063] <When training intensity changes> FIG. 6 is a control flow chart of the server 100 according to an embodiment of the present invention. First, the server 100 judges whether or not the user has performed the training menu on the implementation day through steps P11 to P13. Note that steps P11 to P13 are the same as steps S11 to S13 in FIG. 5, and therefore will not be described. If it is judged in step P13 that the user has performed the training menu on the implementation day (YES in step P13), the judgment unit 113 judges whether or not the intensity of the training menu has changed based on the implementation information (step P14). The intensity of the training menu is the level of the load when the training menu is performed, and for example, a table in which a training menu with a heavy load and a training menu with a light load are associated with each training menu may be stored in the database server 101.

[0064] The display processing unit 115 displays on the user terminal 200 a selection screen that allows the user to select the level of load for the training menu set for the day on the day of the change in intensity. An example of the selection screen is shown in FIG. 7(a) to (c). Note that the figures are only examples, and the displayed manner and wording are not limited to these. The selection screen may display a selection menu according to the level of load and information about running ability at the end of a predetermined period of training that is predicted when the selected level of load is performed. The "information about running ability" may be a numerical value that indicates running ability itself, or may be the growth rate of running ability from the start to the end of training. Alternatively, it may be a predicted time required to complete a target competition, or a degree of reduction in predicted time compared to the start of training, etc.

[0065] Here, the prediction of running ability by the prediction unit 116 will be described. As described above, according to the concept of periodization, by implementing a set training program, the growth rate (improvement rate) of the user's running ability draws a predetermined growth curve from the start of training to the actual event. FIG. 8 shows an example of the growth rate (growth curve) of running ability. The curve (y=f(x)) shown by the dashed line in FIG. 8(a) to (c) is an example of a growth curve. The prediction unit 116 may predict the running ability at the end of a predetermined period based on the improvement rate (growth curve) of the running ability obtained by implementing a training program for a predetermined period. That is, the prediction unit 116 may predict the training ability at the end of the training program on the assumption that the training ability will grow along the growth curve when the user implements training according to the set training program. Note that FIG. 8(a) to (c) will be described later.

[0066] Returning to FIG. 7, the selection of the load level will be described. The screen 10 in FIG. 7(a) displays the standard intensity training menu 11 set by the setting unit 111, and displays "10km pace running". Furthermore, the screen 10 displays, for example, a predicted time 12 for completing a target race, as information on the running ability predicted when the training menu 11 is performed. The screen 20 in FIG. 7(b) displays "5km interval running" as a training menu 21 with a higher load than the standard intensity training menu. Since this is a training menu with a higher load, the predicted time 22 on the screen 20 is predicted to be faster than the predicted time 12 for the standard intensity. The screen 30 in FIG. 7(c) displays "5km jogging" as a training menu 31 with a lower load than the standard intensity training menu. Since this is a training menu with a lower load, the predicted time 32 on the screen 30 is predicted to be lower than the predicted time 12 for the standard intensity. Note that updating of the predicted time will be described later. Also, as shown in the figure, arrows indicating improvement, decrease, or maintenance of the predicted time may be displayed so that the user can recognize improvement in the predicted time. The user can select a practice menu to be performed by the user from screens 10 to 30, and the selected information may be transmitted from user terminal 200 to server 100.

[0067] If the user selects a training menu of standard intensity (NO in step P14), the initially set training menu and information on running ability are provided to the user (step P15). If the user selects a training menu of intensity different from the standard intensity (high or low load) (YES in step P14), the prediction unit 116 updates the running ability predicted for the user (step P18). The updated information may be stored in the database server 101.

[0068] Here, the update of running ability due to the change in intensity will be described with reference to FIG. 8(a). The prediction unit 116 updates the running ability at the end of a predetermined period according to the improvement rate of the running ability corrected by a weighting coefficient according to the load level selected by the user. In the graph of FIG. 8(a), the dashed line graph is the growth rate (growth curve) of the running ability at the beginning of the setting, and is a growth curve when, for example, the predetermined period is 20 weeks and training is performed four times a week at standard intensity. Here, it is assumed that a high-load training menu is selected in a certain training menu in the 10th week. In this case, the prediction unit 116 may correct the growth rate from the 9th week to the 10th week using a predetermined constant corresponding to a high load and a coefficient set according to the age of the user. As a result, the growth rate from the 10th week onwards is shifted from the initial growth rate by the amount of the corrected growth rate from the 9th week to the 10th week, and becomes the curve shown by the solid line in FIG. 8(a). The prediction unit 116 predicts the running ability at the end of the training from the corrected growth rate. When a low-load training menu is selected, a similar correction may be made using a predetermined constant corresponding to a low load and a coefficient related to age.

[0069] After step P18, the process proceeds to step P19, where information regarding the initial training menu and updated running ability is provided to the user.

[0070] In this way, the user may be able to select the intensity of the training menu. This allows the user to select a training menu that can be implemented depending on the user's physical condition, time, etc., making it easier to continue training. In addition, information regarding the training ability expected to be obtained for each training intensity is provided to the user, which is expected to have the effect of maintaining the user's motivation.

[0071] <If one or more sections of the practice menu have not been completed> Next, the update of the practice program when the period during which the set practice menu has not been performed reaches one section will be described with reference to the flowchart of FIG. 6. If it is determined in step P13 that the practice menu on the day of the practice has not been performed (NO in step P13), the process proceeds to step P16, where the determination unit 113 determines whether the period during which the practice has not been performed reaches one section. That is, here, it may be determined whether the day on which the practice has not been performed continues for one week. If it is determined that the period during which the practice has not been performed reaches one section (one week) (YES in step P16), the update unit 114 updates the practice menu for the next day and thereafter based on the second priority order table (step P20). The second priority order table TB30 is a table indicating the priority order of the sections to be deleted from among a plurality of sections, and may be stored in the database server 101.

[0072] The update unit 114 updates the practice menu by deleting the practice menu of the section with the highest priority to be deleted from the section that has not been implemented based on the second priority table. FIG. 9 shows an example of the second priority table TB30. Also, FIGS. 10(a) and (b) show schematic diagrams for explaining the update of the practice program using the second priority table TB30. In the example of FIG. 10, a practice program is set for a period of 20 weeks, and the priority of the week to be deleted is shown in association with the week. Here, in the table TB40 of FIG. 10(a), it is assumed that the user has not implemented the practice in the fourth week. In this case, the update unit 114 deletes the practice menu set in the tenth week, which has the highest priority of the week to be deleted from the fourth week onwards. Then, the practice menu set in the fourth to ninth weeks before the update is set as the practice menu for the fifth to tenth weeks. Also, in table TB40, for example, if the user has not practiced in the 13th week, the update unit 114 deletes the practice menu set in the 13th week, which is the week with the highest priority of the week to be deleted after the 13th week. Similarly, in table TB40' in FIG. 10(b), it is assumed that the user has not practiced for two weeks, the 4th and 5th weeks. In this case, the update unit 114 deletes the practice menu set in the 10th week, which is the week with the highest priority of the week to be deleted after the 4th week, and deletes the practice menu set in the 7th week, which is the week with the second highest priority of the week to be deleted after the 5th week. Then, the practice menus set in the 4th, 5th, 6th, 8th, and 9th weeks before the update are set as the practice menus for the 6th to 10th weeks, respectively.

[0073] Returning to the flowchart of Fig. 6, after step P20, the prediction unit 116 updates the predicted running ability (step P18). When the training menu is not performed by the user for one section, the prediction unit 116 predicts the running ability at the end of the predetermined period by subtracting the improvement rate of the running ability obtained by performing the training menu set for the one section from the improvement rate of the running ability obtained by performing the training program for the predetermined period.

[0074] This will be explained with reference to FIG. 8(b). In FIG. 8(b), similarly to FIG. 8(a), the growth curve in the case where the predetermined period is 20 weeks and training is performed four times a week at standard intensity is shown by a broken line. Here, it is assumed that the training in the seventh week is not performed and the training menu set in the tenth week is deleted based on the second priority table TB30. In this case, the prediction unit 116 updates the growth rate by deleting the growth rate that was expected to be obtained in the tenth week. As a result, the growth rate from the seventh week onwards is reduced from the initial growth rate by the amount of the deleted growth rate, and becomes the curve shown by the solid line in FIG. 8(b).

[0075] After step P18, the process proceeds to step P21, where the updated training menu and information regarding running ability are provided to the user.

[0076] Thus, according to one embodiment of the present invention, even if the period during which training has not been performed becomes long, the training program is updated taking into account the period during which training has not been performed. Therefore, a reasonable and efficient training program is provided for the user, making it easier for the user to continue training. In addition, since the predicted value of running ability is updated taking into account the period during which training has not been performed, the user is not made to feel apathetic and is helped to maintain motivation.

[0077] <If the number of practice sessions decreases> If the unimplemented period is less than one week (NO in step P16), the update unit 114 updates the practice menu for the next day and thereafter based on the first priority order table TB20 as described above (step P17).

[0078] After step P17, the prediction unit 116 updates the running ability according to the contents of the updated practice menu (step P18). For example, if the number of practice sessions in one section is reduced by updating the practice menu, the running ability may be updated. This will be described with reference to FIG. 8(c). In FIG. 10(b), similar to FIG. 10(a), a growth curve in the case where the predetermined period is 20 weeks and four practice sessions are performed at standard intensity per week is shown by a broken line. Here, assume that the number of practice sessions in that week is reduced from the initial four sessions to three sessions because no practice session was performed on Thursday in the 12th week. In this case, the prediction unit 116 may correct the growth rate from the 11th week to the 12th week with a weighting that is preset according to the number of practice sessions for each section. As a result, the growth rate from the 12th week onwards is shifted from the initial growth rate by the amount of the corrected growth rate from the 11th week to the 12th week, and becomes the curve shown by the solid line in FIG. 10(b).

[0079] After step P18, the process may proceed to step P21, where the updated training menu and information on running ability may be provided to the user. Note that if there is no change in the number of training sessions in one section in step P17, updating of running ability may not be performed.

[0080] Although the present invention has been described based on the drawings and examples, it should be noted that a person skilled in the art can easily make various modifications and corrections based on the present disclosure. Therefore, it should be noted that these modifications and corrections are included in the scope of the present invention. For example, the functions included in each means, each step, etc. can be rearranged so as not to be logically contradictory, and multiple means, steps, etc. can be combined into one or divided. In addition, the configurations shown in the above embodiments may be appropriately combined. For example, each component described as being included in the server 100 may be realized in a distributed manner by multiple servers. In addition, the processing described as the function of the server 100 may be performed by the user terminal 200 and the sensor devices 301 and 302. Conversely, the processing performed by the user terminal 200 may be performed by the server 100 and the sensor devices 301 and 302.

[0081] For example, in the above description, it has been explained that the user can select the intensity of the training menu. In addition, according to one embodiment of the present invention, the user may be notified that rest is recommended. The screen 40 in FIG. 11 may be an example of a notification screen displayed on the user terminal 200 to prompt the user to rest. For example, the determination unit 113 may determine a deviation from the user's usual running form based on, for example, a landing impact included in the running information of the sensor device 301, and when the deviation exceeds a predetermined threshold, it may be determined that rest is required. Then, the display processing unit 115 may display the screen 40. At this time, the prediction unit 116 may update the running ability predicted at the end of the training program in response to rest (i.e., not performing training), convert it into a completion time, and display it on the screen 40. This makes it possible to provide a training program that can maintain the motivation of the user while preventing the user from getting injured.

[0082] The second priority order table TB30 may also be used when a training program is organized with weeks other than 20 weeks. For example, when setting a training program for a full marathon, the training program may be set with a training period of 20 weeks as standard, 12 weeks as shortest, and 24 weeks as longest. Here, when the training period is shorter than the standard 20 weeks, a training program may be configured by deleting the training menu of the week with high priority to be deleted with reference to the second priority order table TB30. For example, when the training period is 19 weeks, a training program that does not include the training menu of the second week with the highest priority may be set.

[0083] Although not shown in FIG. 9, the second priority order table TB30 may further store the number of weeks in which the training menu to be added is arranged and the position to insert the number of weeks in association with each other when the training period is longer than the standard 20 weeks. For example, when the training period is 21 weeks, a training program may be set in which the training menu set in the 7th week is added before the 8th week. When the training period is 22 weeks, a training program may be set in which the training menu set in the 7th week is added before the 8th week, and further the training menu set in the 16th week is added before the 15th week.

[0084] Furthermore, the user terminal 200 displays the progress up to the current day in the training program set by the user as shown in Fig. 7. For example, the progress rate of the training program may be provided to the user as the progress by the progressing ring 13 on the screen 10 of Fig. 7(a). Furthermore, the update unit 114 may update the progress rate according to the implementation status of the user's training program. Note that the progress rate may be updated, for example, as follows, but is not limited to these.

[0085] <Percentage of progress per week> The training program is evenly allocated to each week, and for example, if a 20-week training program is implemented as initially set, the progress rate may increase by 5% each week. In addition, by using the value of the growth curve function f(x) according to the shape of the above-mentioned predetermined growth curve, for example, if the progress rate from the 14th week to the 15th week is ΔRL=f(15)-f(14)=7%, the progress rate may be 7% if the 14th week training menu is implemented as set.

[0086] <Progress rate per practice menu> If the progress rate is equally allocated to each practice menu, and the progress rate for a certain week is 5%, and three practices are performed, the progress rate can be 5 x 0.75 = 3.75%. In addition, according to the weight of each week's practice menu, if the progress rate for a certain week is 5%, and a practice with a weight of 10% has not been performed, the progress rate can be 5 x 0.9 = 4.5%.

[0087] <Performance of practice menu> Considering whether or not a training menu was performed, the achievement level for each training menu is evaluated by assigning 1 if the training menu was performed and 0 if not. The achievement level may be calculated from a constant according to "the training menu was performed," "60% of the distance specified in the training menu was run," "60% or more of the distance specified in the training menu was run, and the average pace is faster than the specified pace + 10 seconds / km (however, if there is a range in the specified pace, the lower limit (slower side) pace + 10 seconds / km)." For example, when the current progress rate in a certain week is 7%, and the achievement level of a training with a weight of 30% is 90%, 7 x 0.3 x 0.9 = 1.89% may be determined as the progress rate.

[0088] Each functional unit of the server 100 or the information processing device 100 may be realized by a logic circuit (hardware) formed in an integrated circuit (IC (Integrated Circuit) chip, LSI (Large Scale Integration)) or a dedicated circuit, or may be realized by software using a CPU (Central Processing Unit). Each functional unit may be realized by one or more integrated circuits, and the functions of multiple functional units may be realized by one integrated circuit.

[0089] The programs of the embodiments of the present disclosure may be provided in a state stored in a storage medium readable by an information processing device. The storage medium can store the programs in a "non-transitory tangible medium." The programs include, for example, software programs and information processing device programs. When each functional unit of the information processing device 100 is realized by software, the information processing device 100 functions as a setting unit 111, an acquisition unit 112, a determination unit 113, an update unit 114, a display processing unit 115, and a prediction unit 116 by the processor executing a program loaded on the memory.

[0090] The storage medium may, where appropriate, include one or more semiconductor-based or other integrated circuits (ICs) (e.g., field programmable gate arrays (FPGAs), application specific ICs (ASICs), etc.), hard disk drives (HDDs), hybrid hard drives (HHDs), optical disks, optical disk drives (ODDs), magneto-optical disks, magneto-optical drives, floppy diskettes, floppy disk drives (FDDs), magnetic tapes, solid state drives (SSDs), RAM drives, secure digital cards or drives, any other suitable storage media, or any suitable combination of two or more of these. The storage medium may, where appropriate, be volatile, non-volatile, or a combination of volatile and non-volatile.

[0091] Furthermore, the program of the present disclosure may be provided to the information processing device 100 via any transmission medium (such as a communication network or broadcast waves) capable of transmitting the program.

[0092] In addition, each embodiment of the present disclosure may be realized in the form of a data signal embedded in a carrier wave in which a program is embodied by electronic transmission. The program of the present disclosure may be implemented using, for example, a script language such as JavaScript (registered trademark) or Python, C language, Go language, Swift, Koltin, Java (registered trademark), or the like.

[0093] It will be understood by those skilled in the art that the above-described embodiments are illustrative of the following aspects. [1] The information processing device disclosed herein is an information processing device that provides a user with a running training program, and includes a setting unit that sets, as the training program, a training menu to be performed within a specified period and the date on which the training menu will be performed, an acquisition unit that acquires implementation information regarding whether or not the user has performed the training menu set on the implementation date, a judgment unit that determines whether the training menu on the implementation date has been performed, an update unit that updates the training menu for the day after that based on specified conditions when the judgment unit determines that the practice menu for that day has not been performed, and a display processing unit that displays the updated training menu on a terminal. [2] The information processing device of [1] above further includes a prediction unit that predicts the user's running ability at the end of a predetermined period according to the implementation status of a practice menu during the predetermined period based on the implementation information. The prediction unit predicts the user's running ability at the end of the predetermined period when the load level for the set practice menu is changed, and the display processing unit displays on the terminal a selection screen that allows the user to select the load level for the practice menu set on the implementation day, the selection screen including information on the running ability at the end of the predetermined period predicted according to the load level. [3] In the information processing device described in [1] or [2] above, the setting unit sets a practice program based on a first priority table indicating the priority of combinations of multiple combinations of practice menus and implementation dates of the practice menus, for each division into a predetermined number of chronological periods, stored in a predetermined memory unit, and the priority of combinations, and the update unit may, if the practice menu for the day has not been implemented, update the practice menu for the next day and onwards to a practice menu based on a combination with a high priority among combinations that include unimplemented practice menus on the day and onwards, based on the first priority table. [4] In the information processing device described in [3] above, when a practice menu set for a certain category is left unimplemented for the entire category, the update unit may update the practice menu by deleting the practice menus of categories with higher priority from the category that has been left unimplemented onwards, based on a second priority table stored in a specified memory unit and indicating the priority of categories to be deleted from among a plurality of categories. [5] In the information processing device described in [2] above, the setting unit may set a training program based on a predetermined training theory, and the prediction unit may predict the user's running ability at the end of the predetermined period based on the improvement rate of running ability obtained by carrying out the training program over the predetermined period. [6] In the information processing device described in [2] above, the prediction unit may update the running ability at the end of a specified period according to the improvement rate of the running ability corrected by a weighting coefficient according to the level of load selected by the user. [7] In the information processing device described in [2] above, when a training menu is not performed by the user for a certain category, the prediction unit may update the running ability at the end of the specified period by subtracting the improvement rate of running ability that would be achieved if the training menu set for the certain category were performed from the improvement rate of running ability obtained by performing the training program for the specified period. [8] In the information processing device described in [2] above, the display processing unit may display, on the selection screen, a predicted time required to complete a predetermined distance as information relating to running ability at the end of the predetermined period. [9] In the information processing device described in [2] above, the display processing unit may display, on the selection screen, the progress status up to the day in the practice program set by the user.

[10] In the information processing device described in any of [1] to [9] above, the acquisition unit may acquire information regarding the burden on the user's body from a sensor worn by the user, and the update unit may update the subsequent practice menu to a less strenuous practice menu when the burden on the user's body satisfies a predetermined condition.

[11] The control method disclosed herein is a control method for an information processing device that provides a user with a running training program, in which the information processing device executes the following steps: setting, as a training program, a training menu to be performed within a specified period and a date on which the training menu will be performed; acquiring implementation information regarding whether or not the user has performed the training menu set on the implementation date; determining whether or not the training menu on the implementation date has been performed; if it is determined that the training menu for that day has not been performed, updating the training menu for the day after that based on specified conditions; and displaying the updated training menu on a terminal.

[12] The control program disclosed herein is a control program of an information processing device that provides a user with a running training program, and provides the information processing device with the following functions: a training menu to be performed within a specified period and a date on which the training menu will be performed as a training program; a function to obtain implementation information regarding whether or not the user has performed the training menu set on the implementation date; a function to determine whether or not the training menu on the implementation date has been performed; a function to update the training menu for the day after that based on specified conditions if it is determined that the training menu for that day has not been performed; and a function to display the updated training menu on the terminal. [Explanation of symbols]

[0094] 100 Server (information processing device) 110 Control section 111 Setting section 112 Acquisition Department 113 Judgment section 114 Update Department 115 Display processing unit 116 Prediction Department 120 Communications Department 130 Display section 170 Storage section 101 Database Server 200 User terminal (communication terminal) 210 Control section 211 Sensor data acquisition unit 220 Communications Department 230 Display section 240 Input / output section 270 Storage section 301 Sensor device (motion sensor) 302 Sensor device (vital sensor) 310 Control section 320 Communications Department 330 Sensor section 340 Operation section 350 Storage section 500 Network 600 Practice Support System

Claims

1. An information processing device that provides a running training program to a user, A setting unit that sets, as the training program, a training menu to be performed during a predetermined period and a date on which the training menu is to be performed; An acquisition unit that acquires implementation information regarding whether or not the user has implemented the practice menu set for the implementation date; A determination unit that determines whether or not the practice menu on the day of the implementation date has been implemented; an update unit that updates a practice menu for the day after the day based on a predetermined condition when the determination unit determines that the practice menu for the day has not been performed; a display processing unit that displays the updated practice menu on a terminal; An information processing device comprising:

2. a prediction unit that predicts the running ability of the user at the end of the specified period according to the implementation status of the practice menu during the specified period based on the implementation information; Further equipped with The prediction unit predicts the user's running ability at the end of the predetermined period when a load level is changed for a set training menu, The display processing unit displays, on the terminal, a selection screen that allows the user to select a level of the load for the practice menu set for the day on the implementation day, the selection screen including information about the running ability at the end of the predetermined period predicted according to the level of the load. The information processing device according to claim 1 .

3. The setting unit sets the practice program based on a first priority table indicating a plurality of combinations of the practice menus and implementation dates of the practice menus for each of the sections obtained by dividing the predetermined period into a predetermined number of time series, the combinations being stored in a predetermined storage unit, and the priorities of the combinations; the update unit, when the practice menu for the day has not been implemented, updates the practice menu for the next day and thereafter to a practice menu based on a combination with a high priority among combinations including the practice menu that has not been implemented on the day and thereafter, based on the first priority order table; The information processing device according to claim 1 .

4. when a practice menu set for a certain category is left unimplemented throughout the category, the update unit updates the practice menu by deleting practice menus of categories with higher priority from the category that has been left unimplemented onward based on a second priority table stored in a predetermined storage unit and indicating priorities of categories to be deleted from among the plurality of categories; The information processing device according to claim 3 .

5. The setting unit sets the practice program based on a predetermined training theory, The prediction unit predicts the running ability at the end of the predetermined period based on an improvement rate of the running ability obtained by the user implementing the training program for the predetermined period. The information processing device according to claim 2 .

6. the prediction unit updates the running ability at the end of the predetermined period in accordance with a rate of improvement of the running ability corrected by a weighting coefficient corresponding to the level of the load selected by the user. The information processing device according to claim 2 .

7. When the training menu is not performed by the user for a certain period, the prediction unit updates the running ability at the end of the specified period by subtracting an improvement rate of the running ability obtained by performing the training menu set for the certain period from an improvement rate of the running ability obtained by performing the training program for the specified period. The information processing device according to claim 2 .

8. the display processing unit displays, on the selection screen, a predicted time required to complete a predetermined distance as information regarding the running ability at the end of the predetermined period. The information processing device according to claim 2 .

9. The display processing unit displays, on the selection screen, a progress status up to the day in the training program set by the user. The information processing device according to claim 2 .

10. The acquisition unit acquires information regarding a burden on the user's body from a sensor worn by the user, The update unit updates the subsequent practice menu to a low-stress practice menu in response to the load on the user's body satisfying a predetermined condition. The information processing device according to claim 1 .

11. A method for controlling an information processing device that provides a running training program to a user, comprising: The information processing device includes: A step of setting, as the training program, a training menu to be performed during a predetermined period and a date on which the training menu is to be performed; acquiring implementation information regarding whether or not the user has implemented the practice menu set for the implementation date; A step of determining whether or not the practice menu for the day of the implementation date has been implemented; updating a practice menu for the day after the current day based on a predetermined condition when it is determined that the practice menu for the current day has not been performed; displaying the updated practice menu on a terminal; A method for controlling an information processing device.

12. A control program for an information processing device that provides a running training program to a user, In the information processing device, A function of setting a practice menu to be performed during a predetermined period and a date on which the practice menu is to be performed as the practice program; A function of acquiring implementation information regarding whether or not the user has implemented the practice menu set for the implementation date; A function for determining whether or not the practice menu on the day of the implementation date has been implemented; a function of updating a practice menu for the day after the day based on a predetermined condition when it is determined that the practice menu for the day has not been implemented; A function of displaying the updated practice menu on a terminal; A control program for an information processing device that realizes the above.

Images